• Volume 45, All articles

      Continuous Article Publishing mode

    • A novel non-customary method of image compression based on image spectrum


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      Compression of multimedia content is an important processing step and backbone of real life applications in terms of optimum resource utilization in transmission and storage. It is an established field of research with very little scope for further improvement in achieved compression through customary codingbased compression techniques. Consequently, non-customary compression methods have become an important area for future research. Based on the principle ‘Any information that can be restored can be compressed’, we propose a novel spectrum-based image compression technique to further reduce the data footprint with satisfactory quality metric for images. We first blur the image with a point spread function (PSF) determined usingfrequency content of the given image. Blurring increases the DC component in the image, which in turn gets further compressed compared with original image by DCT-based JPEG compression. To recover the image, we perform deconvolution using the known blur PSF. Results obtained show further improvement of 20 - 30% in achieved compression with respect to original JPEG compressed image with satisfactory quality of recovered image.

    • An image processing method to measure droplet impact and evaporation on a solid surface


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      We employ high-speed visualization to quantify the impact and evaporation of a droplet on a solid surface. The time-varying droplet shapes are recorded using a high-speed camera and an image processing method is developed for measurement for droplet dimensions, dynamic contact angle, and volume. The method is based on the liquid-gas and liquid-solid interface detection using Canny’s method and Otsu’s method for threshold digitalization. To obtain the dynamic contact angle, a higher-order polynomial is fitted along the pixelsnear the contact line. The droplet volume is measured assuming an axisymmetric geometry of the droplet and numerically integrating the identified pixels in the droplet. We demonstrate the detection of the complex topology of the deforming liquid-gas interface of an impacting and evaporating droplet on a solid surface. We plot the time-variation of droplet dimensions, namely, wetted diameter, maximum diameter, height; dynamic contact angle, and droplet volume. The contact angle and volume measurements are verified with known analytical values. Three case studies are considered to demonstrate the capability of the proposed method, namely, sessile evaporating droplet, bouncing droplet, and spreading viscous droplet on a solid surface

    • Detection of electricity theft using data processing and LSTM method in distribution systems


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      Electricity theft is a big problem faced by all energy distribution services and continues to rising. Therefore, studies on electricity theft detection techniques have increased in recent years. Unsuitable calibration and illegal calibration of energy meters during production may cause non-technical losses. Non-technical losses have been a major concern for the resulting security risks and the immeasurable loss of income. In most of the meter tampered locations, damaged meter terminals and/or illegal applications cannot be distinguishable duringchecking. In fact, electric distribution companies will never be able to eliminate electricity theft. But it is possible to take measure to detect, prevent and reduce it. In this paper, we developed by using deep learning methods on real daily electricity consumption data (Electricity consumption dataset of State Grid Corporation of China). Data reduction has been made by developing a new method to make the dataset more usable and to extract meaningful results. A Long Short-Term Memory (LSTM) based deep learning method has beendeveloped for the dataset to be able to recognize the actual daily electricity consumption data of 2016. In order to evaluate the performance of the proposed method, the accuracy, prediction and recall metric was used by considering the five cross-fold technique. Performance of the proposed methods were found to be better than previously reported results.

    • Influence of ethanol on the performance, combustion and emission characteristics of a stationary diesel engine run on diesel–Mesua ferrea linn oil blend


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      The addition of ethanol to a blend of vegetable oil (VO) and diesel, in general, has been found to improve the compression ignition diesel engine performance. In the present investigation, the influence of ethanol on Mesua ferrea Linn oil–diesel blend has been studied. Mesua ferrea Linn trees, abundant in the northeastern states of India, have the potential to supplement the fossil diesel. The blend studied is composed of 30% Mesua ferrea Linn oil and 70% diesel by volume (VO30). Ethanol is added 5 and 10% by volume to VO30 binary blend to form two ternary blend VO30E05 (5% ethanol and 95% VO30) and VO30E10 (10% ethanol and 90% VO30). Experiments have been carried out in a four-stroke, single cylinder, water cooled, stationary diesel engine at various engine loads. The addition of ethanol results in an increase of brake thermal efficiency up to 1.5% as compared to neat VO30. The brake specific fuel consumption of the engine increases on an average by 1.8 and 3% with the use of 5 and 10% ethanol, respectively. The use of ethanol results an increase of CO and HCemissions while a decrease of NOX emission

    • A comparison of novel optimization model and algorithm for solving PMU deployment issues in the grid


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      Phasor Measurement Unit (PMU) sensors are commonly used nowadays for sensing different line parameters of the grid for making it more efficient and reliable. However, they are costly to procure and maintain. Also, they may fail and produce measurements with errors. Towards these issues, a novel optimizationmodel and a polynomial time algorithm are developed that solve these issues with respect to minimal PMU deployment in the grid. These techniques are compared and tested on the standard IEEE 5, 14, 30, 57 and 118 bus systems. For achieving cross-validation and robustness ability in the grid, the developed optimization model and algorithm deploy about 70% and 141% less number of additional PMUs, respectively, as compared with the baseline approach. The results indicate that the developed techniques are very pragmatic and holistic since they take minimal time for allocating minimum PMU sensors while solving problems of cross-validation of PMU measurements and robustness against PMU outages.

    • Effects of Roughness on the Performance of a threaded Zigzag Demister Using RSM and k - w turbulent models


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      In this paper, the effects of channel roughness on the droplet removal efficiency and pressure drop in a zigzag mist eliminator are investigated. The fluid flow, droplet dispersion and deposition through the demister are modelled using a commercial Computational Fluid Dynamics (CFD) tool. The turbulent airflow issimulated using two different Shear-stress Transport (SST) k-w model and Reynolds Stress Model (RSM) with enhanced wall treatment. The Eddy Interaction Model (EIM) is also used to predict the trajectories of thedroplets in the gas flow. The results show that inserting roughness increases the maximum velocity of the gas flow at the bends and enhances the removal efficiency with a little cost of an increase in the pressure drop foreach bend. At the velocity inlet of 2 m/s with 6 lm droplets, the pressure drop and removal efficiency of the threaded zigzag demister with 5 threads increases by 22.7% and 16.08 %, respectively. Moreover, a higher value for the figure of merit is achieved for the threaded demister compared with the smooth unit which means that the effect of higher removal efficiency of the threaded unit is more pronounced than the effect of higher pressure drop showing the advantages of adding threads in demisters

    • Design and implementation of CDTA: a review


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      In this paper a review on design perspective of current-mode current differential trans-conductance amplifier (CDTA) is presented for the state of the art analog signal processing/generating modules design as the main objective. The CDTA circuits are classified according to the active element used for the design with allrelated parameters taken into consideration. Likelihood implementations of different analog signal processing/generating modules are covered and a comparison of their main parameters trans-conductance, bandwidth, port impedances and power consumption is given. The feasibility of implementing with a lesser area is also considered from the VLSI design viewpoint. The review concludes with CDTA structures with the best possible parameters obtained and future possibilities.

    • A unified method to the design of an improved high frequency sliding mode current controller for DC/DC boost converter in continuous current condition based on analogue implementation


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      In this study, an improved high frequency sliding mode current controller is proposed for DC/DC power converters in continuous current condition using analogue-based implementation. The sliding mode control is a variable frequency method. In this strategy, the controller frequency is a function of summation of alltime delays of different parts of control circuit. If these delays increase, the switching frequency extremely decreases, steady error of the output voltage increases; and also, the converter frequency may be less than the audible frequency. In practical applications, it is extremely important that the output voltage tracks exactly its reference signal. Moreover, the switching frequency of a power converter must be more than 20 kHz in practice. A good way for enhancement of the switching frequency and dynamical performance of the sliding mode method is to use all state variables of the controlled system in the sliding manifold. This attempt has been made for the voltage regulation and input current control of a typical Boost converter in this paper. Using sliding modetheory and Filippov’s method, the stability of the suggested controller is established. Simulations and practical implementation of the proposed system show that the developed controller is successful to control the converterat high frequencies by removing the voltage error in steady region, despite using low speed and cheap electrical devices in the control circuit

    • Nano-TiO2 particles: a photocatalytic admixture to amp up the performance efficiency of cementitious composites


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      The utilization of nanoparticle-blended cement while producing concrete or mortar is gaining immense significance nowadays, mainly on account of the improvements in the long-term durability characteristics of the composites. The feasibility of using cement blended with nano-TiO2 particles to produce lesspermeable or impermeable mortar and concrete of sufficient strength and durability requirements was investigated in the present study. The composite cement includes Ordinary Portland Cement replaced with TiO2 nanoparticles at 0%, 2%, 4%, 6%, 8% and 10% quantities by weight. The properties studied include heat of hydration, compressive strength, bond strength, water absorption, permeability and sorptivity of mortar or concrete specimens. The roughness and surface defects of coarse aggregates greatly alleviated due to the incorporation of nano-TiO2 particles in concrete specimens. The rate of heat evolution increased during early stages of hydration owing to the high fineness and additional reactive surfaces induced from the nano-TiO2 particles blended in cementitious composite. Additionally, with reference to strength and durability characteristics, the nano-TiO2-blended composites performed relatively better than the control samples. The role of blended nano-TiO2 cement composites in reducing the interconnected matrix porosity of concrete is discussed briefly, providing evidences from scanning electron microscope (SEM) observations

    • A simple and low cost measurement technology for solar PV modules


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      The appropriate measurement of solar power output plays a critical role in the performance analysis of any solar power plant or a photovoltaic array. The performance under standard test conditions (STC), as mentioned by the manufacturers, is seldom attained as measurements of a PV module/array are done in outdoor terms. To evaluate the efficiency of performance, a photovoltaic module/array accurately, an on-line characterization of such photovoltaic (PV) set-ups at non-standard test conditions (NSTC) is always necessary. In thebackdrop of the absence of reliable and competitively priced PV module characterization systems, a smart, digital and portable test set-up seem to be highly significant, and such a model has been developed and analyzedin this work. This system uses supercapacitors as the load to the PV module under test. At present, such characterizations are carried out using imported devices, which cost around INR 200-300 thousand. The system so developed will cost around INR 30 thousand and is aimed at import substitutions of such measurement devices. This is very important with regard to field installations testing and will also be of extreme help to researchers in the laboratories, who require all cannot use extensive testing and costly imported instruments.Proper attention has been paid in this work to determine the suitability of the method concerning I-V plotting time and accuracy. Thus it becomes imperative that the quality of the new PV metrology be verified experimentally and duly validated to instill confidence among the users. A detailed investigation regarding the qualityof measurements has been carried out, taking into consideration the effect of a wide range of climatic variations. It has been found that these values are consistently in good agreement with the results obtained at the standardElectronics Regional Test Laboratory (ERTL Govt. Of India) test set-up. Statistical analysis of the PV measurements is ensured by regression analysis (RA) of the respective electrical parameters and the standard deviation (SD) of fill factor (FF) values. Experimental evaluation of quality parameters like Fill-Factor (FF) hasyielded satisfactory ranges of 70% to 79% for FF. Elaborate regression analysis (RA) of principal PV parameters has yielded consistently high values exceeding 99%. At this time, when India is planning to install large-scale PV plants, there is a significant need to measure the electrical parameters of PV modules of different technologies and, after that, choose the appropriate one for optimum performance in a specific region.

    • Mechanical, thermal, and water absorption behaviour of jute/carbon reinforced hybrid composites


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      The demand for fiber-reinforced composite materials is increasing in structural applications due to their crucial characteristics such as stiffness, strength, and durability and processing benefits at low cost. In this study, jute/carbon hybrid composite laminates were investigated for the effect of fabric hybridization andstacking sequence on tensile, impact, microhardness, water absorption, and thermal behavior of the material. The hand layup process was used to fabricate the composite laminates with four different stacking sequences. The X-ray diffraction (XRD), Fourier-Transform Infrared spectroscopy (FT-IR), Thermogravimetric analysis (TGA), and Scanning Electron Microscope (SEM) were used to characterize the structural morphology and thermal stability of the fabricated composites. The experimental results exposed that the hybridization process enhanced the properties of jute reinforced composites. FT-IR and XRD analysis revealed that the alkalization process removed the binding constituents like lignin and hemicelluloses from raw jute fiber, which resulted in a higher crystallinity index. The TGA analysis proved that the hybrid composites are thermally stable at a higher temperature. The hybrid composite with Jute/Carbon/Carbon/Jute stacking patterns has the highest tensile strength of 234.68 MPa compred to other stacking sequences. The hybrid composite with Carbon/Jute/Jute/ Carbon fabric stacking sequence exhibited enhanced impact strength of 108.45 kJ/m2 and better moisture resistance. The incorporation of jute with carbon declined the tensile strength and impact strength by 22% and 14%, respectively, compared to carbon-reinforced composites. The surface micrographs of the fractured samples exhibit the interfacial bonding of fiber/matrix, matrix crack, fiber fracture, and fiber pullouts

    • Direct approximation of fractional order systems as a reduced integer/ fractional-order model by genetic algorithm


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      In this paper, a new method is proposed for the reduced-order model approximation of commensurate/incommensurate fractional order (FO) systems. For integer order approximation, the model order is determined via Hankel singular values of the original system; while the order of FO approximations is determined via optimization. Unknown parameters of the reduced model are obtained by minimizing a fitness function via the genetic algorithm (GA). This fitness function is the weighted sum of differences of Integral Square Error (ISE), steady-state errors, maximum overshoots, and ISE of the magnitude of the frequency response of the FO system and the reduced-order model. Therefore, both time and frequency domain characteristics of the system considered in obtaining the reduced-order model. The stability criteria of the reducedordersystems were obtained in various cases and added to the cost function as constraints. Three fractional order systems were approximated by the proposed method and their properties were compared with famous approximation methods to show the out-performance of the proposed method

    • Retraction Note to: Writer identification using graphemes


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    • Karhunen Loeve Transform with adaptive dictionary learning for coherent and random noise attenuation in seismic data


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      Seismic reflection data are used by geologists to identify the best site for oil and gas explorations. The raw seismic image cannot be directly used for explorations because the noises may hinder the primary reflections and result in misinterpretations. In the proposed research work, the denoising method with adaptive dictionary learning is attempted to attenuate the coherent and random noises which affect the seismic reflections. In this method, Karhunen Loeve Transform(KLT) is combined with K-means Singular Value Decomposition (KSVD) to improve the Signal to Noise Ratio (SNR) of the seismic data. The combination of fixed transform using KLT and learning-based dictionary using KSVD remove the redundant data while retaining the necessary data for further interpretations. KLT is applied on the whole seismic image to decorrelate the coefficients and retain the primary reflections. The horizontal events in the seismic image are preserved as they represent the eigen images with large energy. The KSVD is applied to the KLT resultant data, which denoises the patch of data while simultaneously updating the dictionary. The noise is eliminated using local sparsity of the image where mutually overlapping small image blocks are learned to yield the self-adaptive redundant dictionary. It is then used to obtain the sparse representation of the image blocks by eliminating noise. The algorithm is tested for both synthetic and field seismic images, and the results indicate a better reduction of random and coherent noise with the acceptableexecution time compared to other denoising algorithms used. The KLT combined with KSVD method decorrelate the seismic data from noise by preserving the primary reflections and discarding the redundant noise.

    • Wide-range energy-efficient buffer-based voltage level-up converters for multi-supply voltage systems


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      The voltage level converters (LCs) are required to attain optimized power consumption by interfacing two or more supply voltage domains in Systems-on-Chip (SoC) applications. The voltage level-up conversion can be easily and effectively achieved by the use of buffer structures. Hence this article proposes two buffer-based LCs, namely transmission gate buffer level converter (TGBLC) and stacked PMOS buffer level converter (SPBLC), based on voltage stepping technique. The energy-efficient transmission gate (TG) and stacked PMOS (SP) structures are proposed to define voltage steps in the buffer and ensure a wider voltage conversion range with high speed. The LCs are implemented in 0.18 lm technology and their performance metrics are verified using a Spectre circuit simulator. The simulation results show that TGBLC and SPBLC can convert a low input voltage of 600 and 550 mV to 1.8 V, respectively. For the target input voltage of 0.8 V with frequency of 1 MHz, the TGBLC and SPBLC exhibit an improved delay of 7.3 and 7.1 ns with an energy consumption of 9.66 and 6.66 pJ per transition, respectively. It is noted from the experimental results that theproposed LCs are suitable for applications where simplicity and energy efficiency/low power with a wider conversion range is preferred.

    • Modelling and multiresponse optimization for minimizing burr height, thrust force and surface roughness in drilling of ferritic stainless steel


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      Although there have been many studies on the drillability of various grades of stainless steel, there is no scientific research on the drilling of ferritic stainless steel. Also, the burr at hole exit means the need for secondary machining operation and indirectly increases the production cost. Thus, this study focused on the modeling and minimizing burr height (Bh), thrust force (Fz) and surface roughness (Ra) during drilling of AISI 430 ferritic stainless steel with uncoated carbide drill under dry condition. Bh, Fz and Ra based on different cutting speed and feed rates were measured during drilling tests, and then cutting parameters were optimized by applying Taguchi based grey relational analysis. Moreover, the mathematical models were created by employing the response surface method to predict the machining outputs. The thrust force and the surface roughnessdecreased while the burr height increased with the increase in cutting speed. Uniform burr formation with drill cap was observed for all machining parameters under dry environment. The effect levels of feed rate and cutting speed on burr height were determined as 54.82% and 44.67%, respectively. These result shows that cutting speed is as important as the feed rate during the drilling of the ferritic stainless steel. In the current study, the best suitable levels of feed rate and cutting speed were detected as 0.12 mm/rev and 45 m/min for minimizing Bh, Fzand Ra. The coefficients of determination obtained by RSM indicated a relationship in high level between the cutting parameters and machining outputs.

    • Design and investigation of low-complexity Anurupyena Vedic multiplier for machine learning applications


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      The current world of computers is based on machine leaning and profound learning towards artificial intelligence. In recent investigations, parallelisms are used to solve difficult problems. For the implementation of the FPGA, new architectures have been built using design techniques VLSI and parallelcomputing technologies. Research on reconfigurable computing, machine learning and signal processing should be constantly monitored in the development of artificial intelligence. Energy-restricted computer devices shouldbe continuously developed to support algorithms in the machine learning process. In machine learning algorithms, multipliers and adders play a significant role. In ALU, Convolutionary Neural Network (CNN) and Deep Neural Networks (DNN), the multiplier is an energy-consuming factor of signal processing. In this project, for the DNN, the high-speed Vedic multiplier has been introduced. The versions of the parallel–parallel (PP), serial–parallel (SP) and two-speed (TS) multipliers are compared to the standard 64-, 32- and 16-bit models. Theresults are obtained for an Intel Cyclone V 5CSEMA5U23C6 FPGA, using the Intel Quartus 17.0 software suite.

    • Implementation of a novel and versatile initial rotor position estimation method on surface-mounted permanent magnet synchronous motor prototype at zero speed


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      This paper presents a novel initial rotor position estimation method for a surface-mounted permanent magnet synchronous motor (SPMSM) using its inherent magnetic features. Here, the initial rotor position has been estimated utilising the variation in phase inductances arising out of the unavoidable but verysmall saliency occurring either out of magnetic saturation of the machine or the magnet shape. Detailed investigations have been carried out to enumerate the actual magnitude of the inductances of the SPMSM with distributed armature winding and the dynamic saturation status with armature current variation. Here, 3-phase balanced voltage of higher frequency (150 Hz) is applied to the motor terminals for a short period of time (for 300 ms) and the corresponding phase currents are indirectly used to determine the rotor position. Innovativesignal processing steps have been used to distinguish small differences in the 3-phase currents caused by the small differences in the phase inductances. The position is determined from the relative values of different phase currents using a novel approach. This still leads to two diametrically opposite (electrical phase) solutions for the instantaneous rotor position. To eliminate this ambiguity, two alternative methods (for pole identification) have been proposed. Extensive co-simulations of finite-element method (FEM)-based electromagnetic simulation andsystem simulation (for logic implementation) have been conducted. The estimation methods have been validated experimentally on a laboratory-developed prototype SPMSM that was designed and fabricated by the authors.The experimental results are found to be in excellent agreement with the FEM-based simulation results. The complete initial position estimation method takes less than 1 s of real time, which is typically less than the prechargingtime of standard commercial inverters.

    • Detection of situational information from Twitter during disaster using deep learning models


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      Twitter is an excellent resource for communicating between the victims and organizations during a disaster. People share opinions, sympathies, situational information, etc., in the form of tweets during a disaster. Detecting the situational tweets is a challenging task, which is very helpful to both humanitarian organizations and victims. There is a chance that both situational and non-situational information may be present in a tweet. Most of the existing works focused on identifying single-information-type tweets like situational information,actionable information, useful information, etc. Detecting the mixture of situational and non-situational information tweets remains a challenging task. Although existing works designed an SVM classifier using low-level lexical and syntactic features for classifying situational and non-situational tweets, their method does not work well for a mixture of situational and non-situational information tweets. This paper addresses the problem of detecting the situational tweets using different deep learning architectures such as Convolutional Neural Network(CNN), Long Short-Term Memory (LSTM), Bi-directional Long Short-Term Memory (BLSTM) and Bidirectional Long Short-Term Memory with attention (BLSTM attention). Moreover, deep learning models are applied to Hindi language tweets besides English language tweets for identifying the situational informationduring a disaster. Some of the tweets are posted in the Hindi language, where the information is not available in the English language in countries like India during the disaster. Experiments are performed on various disaster datasets such as Hagupit cyclone, Hyderabad bomb blast, Sandhy shooting, Nepal Earthquake and Harda rail accident in both in-domain and cross-domain. The results of deep learning models demonstrate that it outperforms the existing traditional approach, such as the SVM classifier with low-level lexical and syntactic featuresfor detecting the situational tweets during the disaster. Additionally, to our best knowledge, this is the first attempt in applying the deep learning models to identify the Hindi language situational tweets during the disaster.

    • RNN based question answer generation and ranking for financial documents using financial NER


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      Organizations, governments and many entities deal with an expanse of voluminous financial documents and this necessitates a need for a financial expert system which, given a financial document, extracts finance-related questions and answers from it. This expert system helps us to adequately summarize the document in the form of a question-answer report. This paper introduces the novel idea of generating finance-related questions and answers from financial documents by introducing a custom Financial Named Entity Recognizer,which can identify financial entities in a document with an accuracy of 92%. We have introduced a method ofgenerating finance-based questions using a sample document to obtain a set of generalized questions that we canfeed to any similar financial document. We also record the expected answer type during the question generationphase, which helps to develop a robust mechanism to verify that we always generate the correct answers duringthe answer extraction stage

    • Cost-efficiency measurement for two-stage DEA network using game approach: an application to electrical network in Iran


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      This study proposes a two-stage game–data envelopment analysis (DEA) approach for cost-efficiency (CE) measurement using centralized and Stackelberg game models. Each decision-making unit (DMU) is proposed to make up two-stage network structures (or processes), where all the first-stage outputs are the only second-stage inputs. The main contribution of this study is the development of cooperative and non-cooperative models for CE measurement and implies a unique CE decomposition. We apply centralized and Stackelbergapproaches for cooperative and non-cooperative assumption between two stages. We proposed a simplified version of the two-stage DEA network CE model. Applying the proposed model for CE calculation reduces boththe number of constraints and variables, resulting in a sharp reduction in computational requirements. The applicability of the presented model is demonstrated in the context of studying the output of the electrical network in Iran. The results of the case study show that in a two-stage network, the proposed DEA model can provide accurate estimates of CE. This paper aids the two-stage network structures to control the costs by weak DMUs management. To the authors’ knowledge, this paper is the first research on the CE in a network by the DEA approach so that the relationships between the internal stages of the network are considered.

    • E-learning based on the adaptive learning model: case study in Serbia


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      Today’s education faces many challenges related to learning and teaching efficiency, effectiveness, and costs. Contemporary research shows that the learning environment with the ability to adapt to individual needs, requirements, and competencies of students, facilitates the learning process and leads to improved learning outcomes and achievements. Nevertheless, learning management systems (LMS) that are often used in e-learning typically provide a limited level of adaptivity. The goal of this paper is to introduce an adaptivee-learning model which enables personalized learning experience and more intelligent decision making. It consists of the students’ model, the adaptation module, the expert system for data analysis and decision making, the repository of learning objects, and database of educational methods. The designed model provides adaptivity through a learning management system, considering individual characteristics of the student, such as their learning styles and prior knowledge. It is capable to adapt course content, structure, and assessment based on the specific student’s needs and performance. The model is implemented within the widely used open-source LMS, which makes it more usable and easier to deploy. The process of applying the proposed model is illustrated with a higher education case study that shows how the recommended method is applied for a successful transition to an adaptive form of learning. The model has been tested through experiment during which a group of students attended traditional non-adaptive e-learning course, and the other group attended the adaptive e-learning course.The results of data analysis showed that students who learned from an adaptive course achieved better performancein various aspects. The proposed adaptive model can enhance educational processes in terms ofimproving learning performance, personalized application of teaching/learning methods, as well as continuousimprovement cycle.

    • A robust WKNN-TLS-ESPRIT algorithm for identification of electromechanical oscillation modes utilizing WAMS


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      This paper proposes a robust WKNN-TLS-ESPRIT algorithm that takes into account the effect of the unavailability of phasor measurement unit (PMU) data for identifying the low-frequency oscillatory modes in power systems. The main contribution of the proposed work is to create an enhanced autocorrelation matrixusing a weighted K nearest neighbours (WKNN)-based predictive model to deal with such issues. In the present work, a Bayesian approach is utilized to determine the empirical number of neighbourhood parameters. The improved autocorrelation matrix is then used by total least square estimation of signal parameters via rotational invariance technique (TLS-ESPRIT) algorithm to provide a robust estimate of the modes. Robustness of the proposed method over the other methods is validated with a simulated test signal with missing data through Monte Carlo simulations at different SNRs. The effectiveness of the proposed approach is further verified on real data derived from PMU located in Western Electricity Coordinating Council grid.

    • Experimental investigation on electric discharge drilling of titanium alloy (Ti–6Al–4V) with a gas-aided rotary tool


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      In this study, the authors tried to make holes in a titanium-based superalloy by a completely new machining method called electro-discharge drilling (EDD) using a gas-aided multi-hole rotating tool. Successful machining of the titanium work samples is extremely challenging due to its extreme hardness and stiffness. Oneof the key challenges facing the EDD operation is the elimination of spark-eroded matters from the electrodes gap. Arcing happens when the trash is collected in the working passage, which adversely affects the performance of the EDD. In this study, an effort has been made to explore an active flushing mechanism that can improve the flushing activity during the EDD process. Computational fluid dynamics analysis suggested that successful internal flushing by multi-hole rotating tools might result in the efficient removal of the molten material from theelectrodes gap. In addition, in this study, a comparative assessment of the EDD with the gas-aided multi-hole rotary electrode and the EDD with the stationary solid tool was carried out taking into account significant EDD responses. Besides, it was observed from the investigation that increased material removal rate and reduced EWR as well as surface roughness were acquired in the EDD with a gas-aided multi-hole rotating electrode in comparison with the EDD with a conventional stationary solid electrode. Basic analysis of surface morphologyindicates that the development of recast layers and surface cracks is not very likely to occur on specimens machined with a gas-aided multi-hole rotating electrode in comparison with a workpiece machined with a conventional stationary solid electrode. The results indicate that the use of pressured argon gas in EDD with a gas-assisted multi-hole rotating electrode has a beneficial effect on the execution of the procedure

    • NN-based analytic approach to symbol level recognition for degraded Bengali printed documents


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      Analysis of degraded printed documents has been a research topic for last several years. In this article the contribution lies in segmentation of word images into symbols and recognition of the symbols of degraded printed document images of Bengali, the 7th most popular language in the world. A novel approach to symbol level segmentation based on a Multilayer Perceptron (MLP) network is proposed. A database of segmenting and non-segmenting image columns is developed from the ISIDDI page level database and segmentation is treated as a two-class classification problem. The MLP weights are learnt based on this database using the back propagation algorithm. We have introduced certain new metrics, based on which the F-score of the proposed segmentation algorithm is determined. Our method utilizes information that is relevant for charactersegmentation, ignoring other highly variable information contained in a printed text document, thus allowing for efficient transfer learning between datasets and alleviating the need for labelled training data. Other than Bengali, we have tested on English, Tamil and Devnagari scripts. For the classification purpose we haveidentified 336 symbols, and the corresponding training and test sets have been developed. The ISIDDI database is used for this purpose. Two classifiers, one CNN based and the other LSTM based, have been developed for this 336-class problem. The classification accuracies obtained on the test set by the CNN classifier and the LSTM classifier are 86.05% and 88.11%, respectively. The proposed classifiers outperform the existing classifiers for the ISIDDI database.

    • Asymmetric nose-fairing for wing–body interference flow


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      In the context of the wing–fuselage junction flow the purpose of a nose-fairing is to prevent the oncoming boundary-layer flow separation, which in turn eliminates the horseshoe vortex formation at the junction. A simple procedure is proposed here to arrive at an asymmetric fairing shape for a non-zero wing incidence angle. Even though it is a simple method to decide on fairing shape and size, the fairing designed by this method for a wing at 4ͦ incidence is shown to satisfy the purpose of the nose-fairing. The wind tunnel experimental results clearly show that the designed fairing improves the flow quality at the wing–body intersectionby preventing flow separation and vortex formation. Relatively lower momentum deficit in the boundarylayer (behind the wing trailing edge) hints at drag-reduction for the faired configuration.

    • A compact printed ultra-wideband filtenna with low dispersion for WiMAX and WLAN interference cancellation


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      A printed monopole filtenna fed by a co-planar waveguide with U-shaped split slot on patch and circular split ring resonator pairs at the other side of feed is proposed in this letter. The compact filtenna of dimension 0.32k 9 0.215k (k denotes wavelength corresponding to 2.68 GHz) is capable of providing largebandwidth from 2.68 to 8.72 GHz with dual frequency notch bands over 3.28–3.84 and 4.95–6.02 GHz, primarily to eliminate the WiMAX and WLAN interferences. The dual notched antenna performances are evaluatedby simulation and experimental measurement and compared to those of recently reported ultra-wideband (UWB) notched antennas. The proposed filtenna provides bidirectional E-plane and omni-directional H-plane radiation patterns with gain variation of 2–4.5 dBi and average radiation efficiency of 78% in its pass band. Also the filtenna offers minimal dispersion characteristic as stable group delay response, and linear variation of transfer function (S21) is achieved in its pass bandwidth

    • Heat and mass transfer analysis on multiport mini channel shelf heat exchanger for freeze-drying application


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      An experimental study on heat transfer characteristics of shelf heat exchangers, which are used in small-scale freeze dryers, is presented in this paper. The proposed heat exchanger consists of the multiport minichannel flow paths, and a comparison with a conventional serpentine is carried out based on uniformity of the product temperature achieved. The experimental results indicate that the mini-channel shelf has better temperature uniformity than the latter. Skimmed milk is used as the test fluid. In the freezing and drying process, the product temperature variation is minimal in the mini-channel heat exchanger, with a variation of 12.5 % and 25%, respectively, and the heat transfer coefficient is found to be from 140 to 267 Wm-2 K-1. The moisture content in the product reduces to 50 % in 2 hours, and the drying rate is higher at 0.032 kg hr-1 after 1 hour of the drying process. The redesign of the heat exchanger will be an essential tool to improve the performance with uniform temperature distribution on the product and to improve the product quality.

    • A numerical study on the effect of aspect-ratio and density ratio on the dynamics of freely falling plate in the flutter-to-tumble transition regime


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      The motion of a freely falling thin aluminium plate in water is studied using two-dimensional numerical simulations. The fluid-solid interface is treated using the diffuse interface immersed boundary method. Periodic side-to-side fluttering motion at the small dimensionless moment of inertia (I*) becomeschaotic in the intermediate range which finally settles for pure tumbling at high I*). Even the stable flutter trajectories exhibit significant sensitivity to incremental deviation in fluid forces brought in by inaccurate time marching. The maximum instantaneous inclination angle of the plate increases with I*) during flutter with the uniform multilevel distribution. At larger I*) , such distribution collapses to nearly a single level indicating the ability of the plate to autorotate under the influence of turning moment created by the neighbouring fluid. The plate is observed to retain the initial orientation during its flight in the tumbling regime. The range of I*) for chaotic motion is found to extend with the increase in initial inclination angle. Tests on the effect of initial conditions on the trajectories of the plate indicate while the chaotic regime is mostly affected by initial orientation and velocity of release, flutter and tumble motions converge for a variety of initial states. The chaotic motion transforms into a flutter or tumbles depending on the solid-to-fluid density ratio for a fixed geometry of the plate. However, with a fixed solid-to-fluid density ratio, aspect-ratio of the plate does not alter the stable trajectories appreciably.

    • Influences of gear design parameters on dynamic tooth loads and time-varying mesh stiffness of involute spur gears


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      Gears are one of the most significant machine elements in power transmission due to the many advantages such as high load capacity, long life, and reliability. Due to the increasing power and speed values,the characteristics expected from the transmission elements are also increasing. Significant changes occur in thedynamic behavior of the gears at high speed due to the resonance. For this reason, determining the resonance frequencies is becoming an important issue for designers. This paper presents a method for determining the resonance regions of the gear system under different design parameters. The main purpose of this study is to examine the effects of different gear design parameters on spur gear dynamics. For this aim, the effects of these parameters on the mesh stiffness and contact ratio are examined, and the interaction of mesh stiffness, contact ratio, and dynamic response is presented. Different mesh stiffness calculation methods used to calculate timevarying mesh stiffness and a parametric gear dynamic model are proposed. To solve the equations of motions, a computer program is developed in MATLAB software. Five different design parameters, which are teeth number, pressure angle, reduction ratio, profile shifting factor, addendum factor, and damping ratio, are taken into consideration. The dynamic factor variation is calculated for 1600 rpm a constant pinion speed for each parameter for a single mesh period. Furthermore, the dynamic factor is calculated for the pinion speed between 400–30000 rpm and the frequency response and the resonance regions of the gear system are defined. As a resultof the study, the profile shifting and the addendum factor are the most effective two parameters on the gear dynamics. Also, the contact ratio and mesh stiffness have a great effect on the dynamic response of the system. The methods decreasing dynamic load factors are also discussed at the end of the study.

    • Bi-level multi-objective model for existing link capacity expansion problem across urban transportation network considering travel time reliability: presenting dynamic particle swarm algorithm


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      Urban transportation network design and traffic control problems fall within the scope of infrastructural engineering sciences which become increasingly more important in ever-growing societies of today. In highly populated old cities where establishing new links are facing many human-related, social, economic, andpolitical problems, a workaround for addressing traffic problems is to expand the capacity of existing links, so as to not only control the traffic, but also reduce the urban environmental pollutions caused by vehicles stuck in traffic and decrease the time wasted in traffic to accelerate routines of the society. In the present research, an urban transportation network design model is presented with the aim of enhancing travel time reliability by expanding the capacity of existing network links at minimum possible cost. A significant assumption taken inthe present study is that demands in normal condition and peak traffic hours are treated separately, so as to prevent possible problems by congestion management. In the present study, the uncertainty associated with demand for travel, travel time, and the flow passing through different links are taken into consideration. Travel time reliability calculations are carried out assuming that the demand for travel and travel time follow lognormal distributions. In order to solve this bi-level model, particle swarm optimization algorithm was used. Incorporationof the inertial coefficients dynamics, personal learning, and communal learning into the algorithm contributes to the convergence of this algorithm for solving the bi-level model

    • Performance analysis of current lightweight stream ciphers for constrained environments


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      Maintaining an adequate balance between security and other performance metrics like memory requirement, throughput and energy requirement in a resource-constrained environment is a major challenge. The National Institute of Standards and Technology (NIST), in its latest lightweight cryptography report,suggested the suitability of symmetric ciphers in constrained devices. In this paper we have performed statistical security analyses of six state-of-the-art stream ciphers, namely Lizard, Fruit, Plantlet, Sprout, Grain v1 and Espresso, with the help of randomness test, structural test, autocorrelation test and avalanche test. We have also carried out the performance analysis of these ciphers in detail after porting the optimized code of the ciphers to a low-cost microcontroller, namely ATmega 328P. The selection of the device is based on its acceptability in the Internet of Things (IoT)-based network. The statistical security, performance metrics and comparative analysis suggest the suitability of the selected ciphers for providing security in constrained environments

    • Branch-and-bound algorithms for scheduling in an m-machine no-wait flowshop


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      In this paper, we develop branch-and-bound algorithms for objectives such as sum of weighted flowtime, weighted tardiness and weighted earliness of jobs, for an m-machine no-wait (continuous) flowshop. We believe that there has been no prior work on exact algorithms for this problem setup with a variety of objective functions. For the interest of space, we confine our discussion to a subset of certain combination of these objectives and the extension to other objective combinations is quite straight-forward. We explore the active nodes of a branch-and-bound tree by deriving an assignment-matrix based lower bound, that ensures oneto-one correspondence of a job with its due date and weight. This idea is based on our earlier paper on general m-machine permutation flowshop (Madhushini et al. in J Oper Res Soc 60(7):991–1004, 2009) and here weexploit the intricate features of a no-wait flowshop to develop efficient lower bounds. Finally, we conclude our paper with the numerical evaluation of our branch-and-bound algorithms.

    • An automated approach to retrieve lecture videos using context based semantic features and deep learning


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      Video digitization is one of the emerging technologies holding significant importance over years in applications like video recording and video compression. There are different techniques available in the literaturefor the effective retrieval of videos. This research work presents a video retrieval scheme based on a deep learning strategy. Initially, the video archive is subjected to the keyframe extraction, for extracting useful keyframes from the video. The features extracted from the keyframes are stored in the feature database. The features are clustered using the Fuzzy C Means (FCM) algorithm. These clustered features have been provided to the deep learner for finding the optimal centroid for the incoming user query. For experimentation, theresearch has considered videos from different categories, and both the text query and the video query have been used for the retrieval. The experimental results demonstrate the efficiency of the proposed deep learning strategyin video retrieval and its achievement of improved values of 0.9620, 0.9682, and 0.9652 respectively for recall, precision, and F-measure

    • Experimental investigation of magnetic-field-assisted electric discharge machining by silicon-based dielectric of Inconel 706 superalloy


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      Inconel 706 is a nickel–iron-based superalloy having higher mechanical strength along with easiness of fabrication, which makes it suitable for gas turbine disk applications. The current study investigates the hybrid magnetic-field-assisted powder mixed electric discharge machining (MFAPMEDM) process to improveperformance in machining Inconel 706. For conducting experiments, an in-house set-up was designed and fabricated. Experiments were conducted according to the Taguchi L9 OA and ANOVA to examine the effect of the peak current (Ip) and pulse duration (P-on/P-off) on the material removal rate (MRR) and surface roughness (Ra) of the machined samples. The quality of the machined surface is assessed using a field emission scanning electron microscope (FESEM), which has revealed the presence of micro-holes, melted debris and microglobuleson the machined specimen surface. The Ra is significantly affected by Ip (49.63%) and P-off (37.12%).Further, Ip has more than 78% contribution to the MRR. Furthermore, a mathematical model has been established to develop the relation between input and output factors

    • An integrated feedforward-feedback control structure utilizing a simplified global gravitational search algorithm to control nonlinear systems


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      This paper presents an integrated feedforward-feedback control structure to control nonlinear dynamical systems. This intelligent control system exploits a modified recurrent wavelet neural network (MRWNN) in the feedforward (FF) and the feedback (FB) loops of the control structure. Specifically, the MRWNN is proposed to boost the approximation performance of a previously reported network by employing two amendments to the original structure. To optimize the parameters of both the FF and the FB controllers, an enhanced version of the gravitational search algorithm (GSA) is developed to improve the searching capability of the original algorithm. In particular, two modifications were adopted, including the removal of two control parameters related to the gravitational constant in the original algorithm and the utilization of the global bestsolution to constitute the next generation of agents. Hence, the proposed algorithm is called the simplified global gravitational search algorithm (SGGSA), which has demonstrated better optimization performance compared to those of other techniques, including the original GSA. By conducting several evaluation tests using different nonlinear time-variant dynamical systems, the effectiveness of the proposed control structure was confirmed in terms of control precision and robustness against external disturbances. In addition, the MRWNN has exhibited a superior control performance compared with other related controllers

    • Experimental investigation to evaluate total energy release rate for unidirectional glass/epoxy composite under Mixed mode-I/II load


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      In this paper, the total energy release rates for unidirectional glass/epoxy composites were evaluated using Compact Tension Shear (CTS) and Four-Point Bend (FPB) Mixed mode (I/II) fracture specimens. Unidirectional glass fibre laminates were considered for the experimental work. Specimen plates of required thickness were fabricated using hand lay-up technique. The experimental study was conducted for seven loading angles varying from 0° to 90° with an increment of 15° for CTS specimen and 6 crack positions varying from 0 to 1 with an increment of 0.2 for FPB specimen. Load vs. displacement data are plotted to evaluate the peak loads for both the CTS and FPB Mixed mode (I/II) fracture specimens of various loading angles and crack positions, which are utilized to estimate the total energy release rate. It is found that the total energy release rate depends on the loading angle and crack positions for CTS and FPB Mixed mode (I/II) fracture specimens. For a particular load, the total energy release rate is highly dominating in FPB compared with the CTS fracturespecimen. Hence, the FPB Mixed mode (I/II) fracture specimen can be preferred over CTS Mixed mode (I/II) fracture specimen to evaluate the total energy release rate.

    • Machinability study of Ti-6Al-4V alloy using solid lubricant


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      Cutting tool suffers rapidly during machining titanium-based alloys due to low thermal conductivity. Thus most of the heat is concentrated on the tool rather than chip during machining. To overcome this problem, a suitable cutting parameter, tool geometry, and sustainable methods are necessary. This paper presents the effect of MoS2 solid lubricant (SL), cutting speed, and nose radius during turning of Ti-6Al-4V alloy using the TiAlN coated carbide tool. The experiments are performed at different cutting speeds, nose radius, and flowrates of solid lubricant to study tool wear, surface roughness, and chip morphology. The results show that the use of solid lubricant reduces the tool wear (37%), and the surface roughness (65%) compared to the dry cutting.Similarly, the effects of nose radius and cutting speed have also been studied for both conditions

    • Optimization of the growth of GaN epitaxial layers in an indigenously developed MOVPE system


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      Growth of GaN epitaxial layers is optimized in an indigenously developed nitride metal organic vapour phase epitaxy (MOVPE) system. The motivation of present work is to develop a simple MOVPE reactor which is though affordable but can deliver GaN epilayers of desired quality. The design and fabrication methodology of nitride MOVPE system is briefly discussed. MOVPE growth of GaN epilayers is carried out through a two-step growth process where influence of the growth parameters of low temperature buffer layer on the crystalline properties of high temperature GaN epilayer is discussed in detail. Optimum values of the growthtemperature, annealing duration and thickness of GaN buffer layer are achieved. High resolution X-ray diffraction measurements (HRXRD) confirmed that the crystalline quality of GaN epitaxial layers is reasonable. A good surface morphology of the optimized sample is strongly corroborated by the results obtained from photoluminescence (PL) and HRXRD techniques. Usefulness of a systematic Williamson-Hall analysis in the optimization of growth of GaN epitaxial layers is demonstrated where a high value of lateral coherence length ofGaN buffer layer is found to be a key parameter. Such an optimization process leads to the good crystalline quality of GaN epitaxial layers with low dislocation density. It is found that the high temperature GaN epilayers grown on the optimized GaN buffer layer are compressively stressed which is also revealed by the PL measurements

    • Large-scale testing and finite-element simulation of twin square anchor plates embedded at shallow depth in layered soil media


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      The motivation and scope of the present work are to investigate the interaction phenomenon of two closely spaced square plate anchors through physical modelling and validating it with the help of finite-element modelling. In the present study, different sizes of plate anchors are considered for studying their uplift behaviour when they are laid as single as well as in a group of two symmetrical anchors. A large-scale model testing facility has been developed and fabricated in order to perform the physical modelling. In physical modelling, poorly graded, dry Quartzanium sand is utilized as the foundation material. PLAXIS3D, a finite-element software for geotechnical engineering, has been used to validate the experimental results obtained from the large-scale model testing facility. The effects of embedment depth and size of the anchor plate as well as layering in soil media are the parameters considered in order to determine the interaction factors with respect to the uplift capacity and displacement of anchors.

    • Design, analysis, parameter evaluation and testing of a laboratoryfabricated brush-less DC motor prototype


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      This paper presents detailed steps and procedures for the design of a 4-pole, 0.75-hp, 1500-r.p.m. surface-mounted permanent magnet brush-less DC (SPM-BLDC) motor. The motor has been fabricated at the works of a local manufacturer. The parameters of the machine have been analytically evaluated and subsequently compared to the experimentally determined values. Its practical performance on load has been experimentally evaluated in the laboratory and verified against analytical predictions too. Low-cost M45 electrical steel laminations, as used for commercial induction motors (IMs), have been used from considerations of cost and availability. This also enables direct comparison of important parameters (e.g. torque density, power density and efficiency) between the fabricated prototype and commercially available fractional-hp 3-phase and 1-phase IMs of similar rating. This study is significant since electrical motor manufacturers need not change their stator stamping production line for BLDC motor vis-a-vis IM in case of mass production. Such an approach is hardlyreported in the available technical literature. Analytical methods adopted include both conventional hand calculations and finite-element analysis using commercially available software package(s). Excellent agreementsbetween analytical and experimental values uphold the correctness of the design process, precision of fabrication and accuracy of experimental investigations

    • Computing prosody to detect the Arud meter in Punjabi Ghazal


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      Ghazal is a very popular poetic form of Punjabi poetry. Every verse of a Ghazal follows the same rhythmical pattern. Punjabi Ghazal is written in Hindi meter and Arud meter. In this research, we deal with Arud meter. Arud is the science of versification being followed in Arabic, Turkish, Persian, Urdu, Hindi and Punjabias well as some other languages of South Asia. It is a complex set of rules and has a steep learning curve for a novice. In this work, we devised an algorithm to detect the Arud meter in the Punjabi verse and developed a web-based application as well. This web application will not only facilitate the professional poets but also help the students to analyse the poetry in the context of prosody rules. Computing prosody of any poetry depends on recitation instead of written transcription. In the first phase of orthography, we analyse the text phonetically and phonologically to transform it according to the recitation by adding (as in gemination), removing (as in weightless nasalization and aspiration), modifying (as in tonal sounds) and grafting (to assimilate the sounds of neighbouring words) the letters. In the second phase of verse scansion, the verse is passed through a pipeline process of syllabification and step by step weight assignments, figuring out short, flexible and long syllables, ending up in one or more rhythmical patterns. All of these rhythmical patterns are compared one by one tostandard and most famous 37 Arud meters. The Cartesian product type matching between verse patterns and Arud meters is solved using nested iterations, regular expressions and finite state automata. The meter that matches with verse pattern is declared as the Arud meter of the verse. This automatic process is more efficient than the manual process and yields satisfactory results.

    • Distributed directional cooperative MAC (DD-CoopMAC) protocol for improving VBR throughput in IEEE 802.11ad WLAN


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      The IEEE 802.11ad-based wireless local area network (WLAN) has emerged out as a promising network technology that is capable of operating on millimetre wave spectrum. This network is being used in many applications and can be extended to serve many different streams of the networking industry. However,the network still has some glitches with respect to throughput, overhead, etc., which need to be handled to make it more reliable and efficient. In this paper, distributed directional cooperative medium access control (DDCoopMAC)protocol for improving variable bit rate (VBR) throughput in IEEE 802.11ad WLAN is proposed. In this protocol, information about network stations is intelligently collected; based on this, the relay stations are selected for transmission. Simulation results illustrate that this protocol aids in enhancing the throughput and reducing the related overhead. Also, simulation results show that the proposed DD-CoopMAC has given high throughput and less MAC delay compared with D-CoopMAC and IEEE 802.11ad.

    • A compact SIW bandpass filter using DMS-DGS structures for Ku-band applications


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      This paper presents a design of compact SIW (substrate integrated waveguide) bandpass filter for application in Ku-band Transmit up-convert frequency (i.e., 13.7–14.1 GHz) used for satellite communications. Based on Defected Microstrip Structure-Defected Ground Structure combination (DMS-DGS), this SIW filterstructure is designed to improve passband and stopband performance. By merging circular ring slot (CRS) with interdigital DGS, better passband characteristics with sharp stopband attenuation are obtained. To validate thedesign, the filter is fabricated using Rogers substrate. The size measures 23.8 mm 9 10 mm and operates at a center frequency of 13.9 GHz. Measured results of the filter agree well with the simulated results. Also, designed BPF filter has advantage of low insertion loss, better return loss, compact size and high stopband rejection

    • Devanagari Handwritten Character Recognition using fine-tuned Deep Convolutional Neural Network on trivial dataset


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      In order to rapidly build an automatic and precise system for image recognition and categorization, deep learning is a vital technology. Handwritten character classification also gaining more attention due to its major contribution in automation and specially to develop applications for helping visually impaired people. Here, the proposed work highlighting on fine-tuning approach and analysis of state-of-the-art Deep Convolutional Neural Network (DCNN) designed for Devanagari Handwritten characters classification. A new Devanagari handwritten characters dataset is generated which is publicly available. Datasets consist of total 5800 isolated images of 58 unique character classes: 12 vowels, 36 consonants and 10 numerals. In addition to this database, a two-stage VGG16 deep learning model is implemented to recognize those characters using two advanced adaptive gradient methods. A two-stage approach of deep learning is developed to enhance overall success of the proposed Devanagari Handwritten Character Recognition System (DHCRS). The first modelachieves 94.84% testing accuracy with training loss of 0.18 on new dataset. Moreover, the second fine-tuned model requires very fewer trainable parameters and notably less training time to achieve state-of-the-art performanceon a very small dataset. It achieves 96.55% testing accuracy with training loss of 0.12. We also tested the proposed model on four different benchmark datasets of isolated characters as well as digits of Indic scripts. For all the datasets tested, we achieved the promising results

    • A strong intuitionistic fuzzy feature association map-based feature selection technique for high-dimensional data


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      In this work, a graph-based approach has been adopted for feature selection in case of highdimensional data. Feature selection intends to identify an optimal feature subset to solve the given learning problem. In an optimal feature subset, only relevant features are selected as ‘‘members’’ and features that haveredundancy are considered as ‘‘non-members’’. This concept of ‘‘membership’’ and ‘‘non-membership’’ of a feature to an optimal feature subset has been represented by a strong intuitionistic fuzzy graph. The algorithm proposed in this work at first maps the feature set of the data as the vertex set of a strong intuitionistic fuzzy graph. Then the association between features represented as an edge-set is decided by the degree of hesitation between the features. Based on the feature association, the Strong Intuitionistic Fuzzy Feature Association Map (SIFFAM) is developed for the datasets. Then a sub-graph of SIFFAM is derived to identify features with maximal non-redundancy and relevance. Finally, the SIFFAM based feature selection algorithm is applied on very high dimensional datasets having features of the order of thousand. Empirically, the proposed approach SIFFAM based feature selection algorithm is found to be competitive with several benchmark feature selection algorithms in the context of high-dimensional data

    • Optimal two-stage parachute and retro motor sizing for launch vehicle stage recovery


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      A deceleration system consisting of staged parachute clusters and retro thrusters is optimized for the recovery of the first stage of a launch vehicle on sea. Optimal mass as well as reduction in speed by each parachute cluster and the retro thrusters is essential to minimize the inherent payload loss due to inclusion of additional systems. Three disciplines are involved in the study, namely parachute design, grain design and Three Degrees of Freedom (3-DOF) trajectory simulations. Parachute components are sized and their masses are estimated using a parachute design code. It computes the number of parachutes in the cluster, their sizes and opening loads for multiple reefing stages. Solid motor grain design is carried out, using high burn rate propellant, to provide highthrust to decelerate the launch vehicle stage to a near-zero descent rate at touchdown. A Multiobjective Multidisciplinary Design Optimization (M2DO) problem has been formulated to minimize the mass of the decelerationsystem and minimize the touchdown speed of the recovered stage, subject to constraints on Maximum Expected Operating Pressure (MEOP), feasibility, etc. The optimization is carried out and the Pareto optimal front is obtained using an in-house multi-objective optimization algorithm, Attractor Anchored Multi-objectiveEvolutionary Algorithm (A2-MOEA). A total of twenty-five design variables are considered including initial conditions for each deceleration stage, size of parachute cluster components for both drogue and main parachutes,and the size and shape of the solid motor grain for retro rockets. It is seen that the two objectives are conflicting.The Pareto optimal designs are discussed and the variation of design variables is presented

    • Experimental investigations on cryo-machining of Hastelloy C-276 with tool wear characteristics


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      The super alloy exhibits great strength and fatigue behaviour when nickel (Ni) is present in major quantities. Moreover, it possesses good corrosive resistant behaviour at high temperatures. However, these alloys are very difficult to machine under normal machining conditions due to their great strength and low heat dissolution. In this work, machining was performed on Hastelloy C276 under various machining conditions (speed, feed and depth) and environments (dry and cryogenic). Liquid nitrogen was used as a coolant in themachining region. The machinability of Hastelloy C276 was investigated with machining forces, temperature, surface roughness and hardness under different cutting conditions. Turning experiments that resulted from passing LN2 drastically reduced temperature by up to 40%. Machining forces were minimal under cryogenic machining due to its effective lubrication property. Surface finish of the machined area improved by about 26% under cryogenic conditions. Both dry and cryogenic machining improved the hardness of the work material. Thehigh cooling efficiency of LN2 improved hardness of the machined surface was about 8-15%. Chip width and side-flow of chip material were reduced under cryogenic cooling. Moreover, adhesion and abrasion wear wereobserved minimally in cryogenic machining compared to dry machining. But no significant difference was observed in notch wear for both types of machining. Machinability of Hastelloy C276 significantly improved when LN2 used as a cutting fluid.

    • An improved RNS-to-binary converter for 7-modulus set {2n-5–1, 2n-3–1, 2n-2+1, 2n-1–1, 2n-1+1, 22, 2n+1} for n even


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      In this paper a residue-to-binary converter for the 7-modulus set {2n-5–1, 2n-3–1, 2n-2+1, 2n-1–1,2n-1+1, 22, 22+1} for n even is presented, which is an improved version of a reverse converter presented recently. The proposed converter needs less hardware resources ranging from 52.9% to 66.9%, conversion time of 68–70.7% and power dissipation of 47–63% of those needed for an earlier described converter for the same considered dynamic ranges.

    • Machinability of Ti-5Al-2.5Sn for electro-discharge machining: an experimental investigation


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      Present work attempts to investigate machinability of Ti-5Al-2.5Sn for Electro-Discharge Machining (EDM). Extent of machinability is determined through material removal efficiency, tool wear rate, and surface integrity of the EDMed specimen of Ti-5Al-2.5Sn. Detailed analysis of surface morphology followed by study of surface topographical features including surface roughness, crack density, thickness of the recast layer, foreign material migration, metallurgical phase, residual stress, and micro-indentation hardness are carried out. Disappointing morphology is noticed for EDMed work surface at higher values ofpeak current as well as pulse-on time values. It is experienced that occurrence of surface cracks depends on recast layer thickness. As compared to ‘as received’ workpiece exhibiting compressive residual stresses, tensile stresses are found induced after performing EDM operation. Similar phenomenon is experienced incase of tool electrode. EDM operation improves microhardness of the machined surface. For Ti-5Al-2.5Sn,such improvement is nearly three times than that of ‘as received’ work material. During EDM operation on Ti-5Al-2.5Sn, titanium carbide is formed over tool as well as work surface. Formation of such hard carbidesmay degrade machining efficiency

    • An application of evaporation-rate-based water cycle algorithm for coordination of over-current relays in microgrid


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      Relay coordination is reliable and crucial to guarantee that healthy feeders are properly isolated from the defective areas in a microgrid network. An appropriate protection scheme must be properly planned during the design of the microgrid to ensure safety for the power components in the event of a failure. Theimplementation of distributed generators in the microgrid changes the total network’s Load-Flow and often impacts the magnitude and direction of the fault current. Using the nature-inspired novel evaporation-rate-based water cycle algorithm (ERWCA), the enhancement in microgrid protection is accomplished in this work by optimizing the relay settings, reducing their operation time and time dial setting of each relay. The approach proposed is validated with the IEC microgrid benchmark system and the findings are contrasted with currenttechniques. It is found that the proposed strategy produces substantial improvement for the microgrid in the application of over-current relays and greatly reduces the relays’ overall net operating time.

    • A novel optimization algorithm on surface roughness of WEDM on titanium hybrid composite


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      Titanium based alloys and composites have excellent strength and stability in high thermal condition,excellent resistance to creep, wear and corrosion, light weight and bio-compatible properties and are extensively used in defence, aerospace, spacecrafts, marine, automobile, sports and bio-medical applications.This paper presents an investigation based on a novel optimization algorithm called desirable grey relational analysis (DGRA) where experimental analysis is done on wire electro-discharge machining (WEDM) of a developed novel titanium hybrid composite having enhanced corrosion resistance, wear resistance, improved tribological and biocompatible properties than pure titanium, fabricated by laser engineered net shaping (LENS) process varying peak current (Ip) and pulse duration (PD) as main input process parameters. A mathematicalmodel is proposed based on 2 factors 4 levels design of experiments on output response like surface roughness (SR) and satisfactory results are obtained and authenticated by the confirmatory test. Deionized water is used as dielectric medium. Diffused zinc-coated brass wire is used as tool electrode. SR enhances with the enhancement of Ip but reduces with PD. The process model is prepared and the optimum process parameters are hence determined. The best SR obtained experimentally is 1.31 lm (Ip, 3A, PD, 4 ls). One optimized solution isobtained where Ip is 4.666 A, PD is 17.092 ls, SR is 1.742 lm, standard error (StdErr) of Design is 0.049 and Desirability is 0.900. The novelty lies in the combination of desirability function and grey relational analysiswhere experimental SR measured at optimized condition gets improved by 2.78% by desirability approach and further improves to 7.29% when predicted with DGRA

    • Effect of individual phase properties and volume fractions on the strain partitioning, deformation localization and tensile properties of DP steels


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      Deformation band localization modes, uniform tensile strength, and uniform elongation of Ferrite-Martensite Dual-Phase (DP) steels are analyzed by finite element (FE) study. Treating the microstructure inhomogeneity as the sole cause of imperfection, failure initiation is predicted as the natural fallout of plasticinstability caused by load drop because of localized plastic strain in the Representative Volume Element (RVE) during straining. Strain partitioning between two phases (ferrite matrix and martensite island) are investigated onRVEs, and it reveals that the increase of martensite yield stress decreases the plastic deformation and increases the stress state in martensite. Whereas, a decrease in martensite island volume fraction (Vm) results in the reduction of plastic deformation and stress state in the island. Studies are then carried out to investigate the effects of the ferrite-martensite flow properties and martensite volume fraction on the macroscopic tensile deformation behavior and band localization of DP steels. Micromechanical based FE simulation resultsemphasize that an increase in initial yield strength and volume fraction of martensite increases the ultimate tensile stress (UTS) with the decrease in uniform elongation. Similarly, as the hardening rate of ferrite increases,it increases the ultimate tensile stress (UTS) and uniform elongation. Additionally, deformation band localization modes alter from inclined to perpendicular to the loading axis with an increase in martensite volume fraction and initial yield strength of martensite. The knowledge of this work can be used to design DP steels with desired mechanical properties.

    • Analysis of three-dimensional ponded drainage of a multi-layered soil underlain by an impervious barrier


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      A general analytical model is proposed for predicting three-dimensional seepage into ditch drains through a soil column comprising of three distinct vertical anisotropic soil layers and underlain by an impervious barrier, the drains being fed by a distributed ponding head introduced at the surface of the soil column. The problem is solved for three different situations resulting from three different locations of the water table in the ditches, namely, when the water level lies in the first layer, when it lies in the second layer and finally when it falls in the third layer. The derived solutions are validated by comparing with analytical solutions of others for a few drainage scenarios; in addition, a few numerical checks on them have also been carried out by making use of the Processing MODFLOW environment. From the study, it is seen that ponded drainage of a multi-layered soil is mostly three-dimensional in nature, particularly in locations close to the drains and that the directional conductivities of the layers play a pivotal role in deciding the hydraulics of flow associated with such a system. Further, it has also come out of the study that by suitably altering the ponding distribution at the surface of the soil, the uniformity of water movement in a multi-layered drainage system can be considerably improved mainly if the directional conductivities of the bottom layers are relatively lower than those of the top layer. As soils innature are mostly stratified and as no analytical solution to the three-dimensional ponded ditch drainage problem currently exists for a layered soil, the proposed solutions are expected to be important additions to the alreadyexisting repertoire of drainage solutions on the subject, particularly when looked in the context of reclamation of water-logged and saline soils in layered field situations.

    • Assessment of voltage changeability with reactive power source allotment for real time network


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      In this research work investigation of reactive power necessity at standard voltage level is practiced. The 39-bus test network modeled in mipower application is a part of Rajasthan power system, attached with North Regional National Grid synchronized at 765 kV voltage level. State power utilities are unable to obtain the profoundness in providing, static or dynamic compensation at multiple voltage available within the grid. Reactive power drawl from the network end is judged and analysed by placing imaginary generator at availablevoltage level. In Rajasthan power system voltage level arrays from 765 kV to 33 kV and the utilities are puzzled in managing var penetration due to poor estimation. As a result, higher loading levels and abrupt line trippingraises losses and reduces system reliability. The simulation case studies presented herby from the database of financial year 2018-19 will be envisaged by the utilities after evaluation is over. Presently State Load DispatchCenters deliver instruction to substations to utilize any compensation device available without prior calculation. But this paper underlines a way to access the effects on voltage profile, losses etc. in power system structure afterplanned var support at optimum voltage level. Case studies over real time network is detailed, to check the observability for a load of 370 MW. The impact of practices followed is observed for the designed network.

    • A novel image compression model by adaptive vector quantization: modified rider optimization algorithm


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      In recent days over the internet, the uploading of enormous new images is being made every day, and they necessitate large storage to accumulate the image data. For the earlier few decades, more analysts have evolved skillful image compression schemes to enhance the compression rates and the image quality. In this work, Vector Quantization is used, which uses the Linde–Buzo–Gray algorithm. As a novel intention, the codebooks are optimized by an improved optimization algorithm. In this approach, the database image is firstlyseparated into a set of blocks, i.e., pixels, and these sets of blocks are referred to as vectors. Then a suitable codeword is selected for each vector such that is the closest representation of that input vector. The encoder generates a codebook by mapping the vectors on the basis of these code words, and the compression of the vectors takes place. The encoder then sends a compressed stream of these vectors by pointing out their indices from the codebook to the decoder through a channel. The decoder then decodes the index to find out thecompressed vector and places it on the image. For attaining a better image compression effect, the codebook is optimized using the Best Fitness Updated Rider Optimization Algorithm. The optimization of codebooks is doneso that the summation of the compression ratio and the error difference between the original and decompressed images has to be minimized. Moreover, the proposed model is scruntized with other existing algorithms, and the experimental outcomes are validated.

    • Selection of teak sawdust polypropylene composite’s composition for outdoor applications using TOPSIS analysis


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      Selection of a material for their end use in engineering applications depends on the properties of materials. In this paper, physical and mechanical properties of teak sawdust-polypropylene composite are evaluated and most suitable composition for outdoor applications have been determined by using TOPSIStechnique of optimization. Virgin and recycled polypropylene are mixed with teak sawdust to fabricate the composite with and without maleated polypropylene (MAPP) using compression molding method. TOPSIS technique of optimization involves prioritizing the performance indicators. Important properties such as tensile strength, flexural strength, impact strength, hardness, melt flow index, water absorption and thickness of swell are selected for the study. The composition 50% recycled polypropylene, 45% wood sawdust and 5% MAPP byweight is found to be most suitable for outdoor applications

    • Characterization of laminar flame using high speed camera and spectrometer


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      In order to improve flame stabilization in small scale combustors, there have been many research works going on non-premixed as well as on premixed flame. The present experimental study characterizes colour and shape of the premixed and non-premixed flames through a laminar co-flow burner. Various flamebehaviors are observed and their stabilization limits are investigated at different fuel–air ratios. The spectroscopic approach becomes suitable method for the measurement of chemiluminescensce for both premixed and diffusion flames. Thus, we can predict the behavior of a combustion process. We observe also the intensity variation of chemiluminescence species, OH*, CH*, and C2* for different fuel-air flow combinations. Apart from that, we have an analysis of colour variance of the premixed flame for different flame locations

    • Fluid structure interaction studies of human airways


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      Study of flow characteristics of human airways using Fluid-Structure Interaction (FSI) analysis is very important in the context of prognosis, diagnostic and treatment of respiratory diseases. The present study is focused on effect of elasticity on the respiratory wall during inhalation. Airflow in Computed Tomography (CT) scan model with rigid and compliant airway walls is studied. FSI technique is used to simulate the airflow in the model. The comparison for the two different respiratory models (rigid and compliant) shows that FSI technique brings out more realistic results as compared to Computational Fluid Dynamics (CFD) analysis. It is found that respiratory wall elasticity affects the different flow parameters (pressure, wall shear stress, etc.) at different location of the model. Wall shear stress (WSS) and airway pressure were decreased due toflexibility effect of the airway wall. This will help medical practitioners to correlate the clinical assessment with this FSI results.

    • Permutation flowshop scheduling to obtain the optimal solution/a lower bound with the makespan objective


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      This paper focuses on developing the optimal solution or a lower bound for N-job, M-machine Permutation Flowshop Scheduling (PFS) problem in a manufacturing system with the objective of minimizing the makespan using Lagrangian Relaxation (LR) technique. Even though LR technique is considered, in general,as a good method to obtain a lower bound, research in this direction with respect to our problem under study appears scarce. We address this gap by developing two MILP based Lagrangian Relaxation models, namely, Lagrangian Relaxation Method 1 (called Proposed Lagrangian Lower Bound Program (PLLBP)) and Alternate Lagrangian Relaxation Method 1 (called ALR) to find the optimal solution or a lower bound on the makespan. Basically, we develop these LR methods to overcome the possible limitation of the general LR procedureinvolving the sub-gradient approach. Benchmark PFS problem instances are used to evaluate the performance of these methods. It is observed that the PLLBP outperforms the ALR, and it provides better lower bounds than thelower bounds (in most instances) reported in the literature. Even though the PLLBP is superior in terms of solution quality, it has a limitation in that it cannot execute problem instances beyond 500 jobs due to the associated computational effort.

    • Magneto-thermal convection in lid-driven cavity


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      The fluid flow and convective heat transfer occurring in a lid-driven cavity which is filled with electricity conductive fluid and subjected to external magnetic field, is analyzed comprehensively. The variations in inclination angle of magnetic field and its strength are addressed during the investigation. The cavity is heatedby a linearly varying heat source applied on the left wall. Different regimes of heat transfer are considered by varying pertinent flow-parameters namely Reynolds number (Re), Richardson number (Ri) and Hartmann number (Ha). The effects of magnetic field and the wall motion are studied extensively. The study is carried out using a well-validated in-house CFD code based on finite volume method and SIMPLE algorithm. The obtained results reveal strong influence of Ri and Ha on the heat transfer characterization

    • Analysis of electromagnetic and loss effects of sub-harmonics on transformers by Finite Element Method


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      Power transformers are generally designed to be used in conditions where voltage and current are sinusoidal. However, nonlinear loads are increasing in modern power systems with the developing technology. Therefore, line voltages and currents often have harmonically distorted or non-sinusoidal waveforms. In this article, a model has been developed. The mathematically developed model has been proven experimentally and numerically. In this paper, different sub-harmonic content parametric analysis of the loss of transformer under no-load conditions with voltage excitation was performed. For this purpose, the Finite Element Method (FEM) based modeling of the core and windings of the transformer has been developed. An efficient method based on harmonic field model of transformer windings and FEM based modeling of transformer core is used. ANSYS@MAXWELL program, which realizes a solution based on FEM, is used for this. From the results of the analysis, it was seen that the effect of harmonic voltages on the loss of the transformer core is negligible. However, these tensions have been shown to increase winding losses in the unloaded state. This case reveals the importance of harmonics to be taken into account in calculating the losses of power transformers

    • A hybrid computing approach to improve convergence time for scalable network


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      Border Gateway Protocol (BGP) is a widely used routing protocol in the new era for the intercommunication between the multiple autonomous systems and it has been largely on the internet in all categories of the scalable network. In the event of failure, the BGP as an inter-domain routing protocol shows slowconvergence, which results in high considerable delay in several internet/web applications. The minimum route advertisement interval (MRAI) timers are mostly used by network operators to reduce the issues occurring at the time of increasing convergence time. Many researchers have been working on variation in MRAI timer and effect of it on scalability and network convergence. The increasing size of a network leads to an increase in the value of MRAI timers. Hence, keeping the value of MRAI timers optimum results in reducing the issue of slow convergence for the scalable network. The proposed system (FAPSO) reduces the problem of convergence time by incorporating fuzzy logic into Particle Swarm Optimization (PSO) algorithm for the scalable network. Incomparison with the static value of MRAI timer i.e., 30 s, FAPSO is a suitable algorithm that gives the optimal value of convergence time for the scalable network

    • Thermal magneto-hydrodynamics in a ventilated porous enclosure


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      The present study examines mixed convection in a ventilated cavity saturated with porous substance and heated at the right-bottom and top-left corners under the influence of uniform magnetic field applied externally. The analysis is carried out numerically using in-house CFD code. Five different heating configurationsare analyzed. The effects of pertinent parameters such as Reynolds number (Re = 1–1000), Richardson number (Ri = 0.1–100), Darcy number (Da = 10-7–10-3), Hartmann number (Ha = 1–100), angle of magnetic field (c = 0–180°) and porosity (e = 0.1–1.0), on the flow and temperature fields are examined for the search of the appropriate configuration yielding optimum heat transfer rate. Furthermore, heat transfer characterization at different heating configurations and parametric combinations is assessed

    • Flow reversal prediction of a single-phase square natural circulation loop using symbolic time series analysis


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      In the field of thermal engineering, one of the biggest concerns is the cooling of heat producing systems. For this purpose, today’s world is encouraging to use such cooling systems which are free from any active components (passive systems) for its high reliability and compact size. For this reason, to establishcooling by transferring heat from one place (source) to another (sink) passive system like natural circulation loop (NCL) is highly used. Fluid flow dynamics of the NCL is changing with the increase in heater power which is used as the source for the simulation. We found steady flow dynamics for the comparatively low power of heat, and with the rise in the power first, we saw the oscillatory flow dynamics and then found flow reversal characteristics. This paper presents a novel strategy for the early prediction of flow reversal phenomenon in NCLusing symbolic analysis of time series data. This time series data is found from the numerical simulation, and for the proper study, we are considering data after the initial transient part is overcome. Total time series data is transformed into a symbol string by partitioning into a finite number of specified symbolised groups. The state probability vector is calculated based on the number of occurrences of each symbol group. Present work is a single-phase study, and according to our geometry, we can provide a maximum 800 W heater power to stay in the single-phase. Therefore, for the early prediction of flow reversal in NCL, state probability vector evaluated at 800 W heater power which is the most undesirable state (chaotic data), and this is considered as the reference vector. The difference of the reference state vector from the current state vector is used as a parameter for early detection of flow reversal. It can be observed from the results that this difference changes significantly when the system is sufficiently away from the flow reversal.

    • Identification and early prediction of lean blowout in premixed flames


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      Lean premixed combustion is a state-of-the-art technology to meet the stringent emission norms, especially to reduce the NOx emission. In the present study, we focus on the transition to lean blowout of premixed flames. The main objective of the study is to explore some important measures for prediction of leanblowout as the existing methods are not always suitable in early detection of blowout in case of premixed flames. We further consider different cases through which lean condition can be attained. For such cases, we first discussthe flame dynamics prior to blowout. Among different statistical measures, mean, median, root mean square and coefficient of variance of heat release rate fluctuations are found to be useful in blowout prediction. On the otherhand, skewness and excess of kurtosis do not show any predictive quality. We also observe that the flickering frequency defined in a specific manner also shows a significant variation near lean blowout. Further, the meanfrequency evaluated using Hilbert transform is found to show indication of LBO well before its occurrence. Therefore, the frequency analysis along with statistical analysis of the heat release rate oscillations is found to be very relevant in the context of blowout prediction and can be applied in the practical combustors.

    • Pressure dependence of dryout in a heat-generating porous debris bed


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      The primary objective of this work is to numerically study the effect of system pressure on the occurrence of dryout phenomena in heap-shaped, heat-generating porous debris beds. This is achieved using a multiphase computational fluid dynamics (CFD) model that is implemented in the framework of the commercial CFD platform ANSYS FLUENT. The model is extensively validated with available experimental data on two different aspects: pressure drop in two-phase flow through porous media and prediction of dryout in typicalporous debris beds. A wide range of system pressure, relevant to severe accident conditions, is considered in this analysis in order to obtain a thorough understanding of its impact on multiphase flow and dryout occurrence inporous debris beds. This analysis is performed for different subcoolings of flooding water, which gives additional knowledge on the effects of coolant subcooling on dryout occurrence. Results indicate that dryout in debris beds occurs at progressively higher power densities as the system pressure is raised. Similar effects are observed with increase in liquid subcooling as well.

    • Evolution of nanoliter size fluid droplet on micropatterned surface


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      Static shape of liquid droplets on textured surface draws significant attention from the standpoint of several engineering applications, ranging from heat transfer to bio-printing. This paper discusses the equilibrium behavior of a nanoliter size droplet dispensed on a micropatterned surface. For a given combination of intrinsic wettability of the surface, liquid surface tension and the geometric morphology of the textured surface, the liquid droplet prefers to be on Cassie-Baxter, Wenzel or an intermediate, hybrid state. Here we have carried out anenergy-based simulation of nanoliter size droplets on micropatterned surface, using an open-source surface evolver fluid interface tool SE-FIT. A simplified periodic geometry of rectangular (straight or tapered) micropillarsof specified dimensions is chosen for the micropatterned surface. For a given solid surface texture, we found that droplet prefers to transit from Wenzel to Cassie state beyond a threshold intrinsic sessile contact angle (which the liquid would have subtended on a microscopically smooth surface of the same solid material). This critical transition contact angle is plotted against the roughness parameter. Present study helps in designing the wettability-engineered surfaces for specific engineering applications.

    • Time dependent response of impact induced functionally graded conical shell considering porosity


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      Time dependent low-velocity single and multiple impact response of functionally graded (FG) untwisted and pretwisted conical shells are analysed considering porosity factor. A modified Hertzian contact law which accounts for permanent indentation is considered for the low velocity impact problem. An eightnodedisoparametric shell element is used for the finite element formulation while Newmark’s time integration algorithm is used to solve the time dependent equations. The effects of porosity considering even and uneven porosity factor, initial velocity of impactor (VOI), mass of the impactor and twist angle of FG conical shell on the transient impact response of the conical shell are examined and analyzed. The contact force and indentation increase with increase of VOI and mass of the impactor while the contact duration decreases for both theoccasions. Twist angle has a significant effect on contact force but has marginal effect on contact duration. Contact force for perfect (porosity free) FG conical shells is higher than that of porous FG conical shells. Lower contact force is observed for higher porosity factor. Even porous FG conical shell predicts lower contact force and higher shell displacement than that of an uneven porous FG conical for a given porosity factor

    • A finite element prediction of first ply failure and delamination in composite conoidal shells using geometric nonlinearity


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      A review of the existing literature shows that there is only one research report available on failure of laminated composite conoidal shells using geometrically nonlinear strains. Thus, this paper aims for a detailed study on first ply failure and delamination predictions of laminated composite conoidal shell using von-Karman nonlinearity and first order shear deformation theory. The nonlinear equations are solved by Newton–Raphson iterative method. The failure loads of the shell are furnished for two different boundary conditions and stackingorders of cross and angle-ply laminations. The failure locations on the shell surface and failure modes/tendencies are also reported. This study finds that the SSCC boundary and 0°/90°/0° lamination should be selected by practicing engineers to achieve the maximum load carrying capacity of the conoid out of the two edge conditions considered here. Factor of safety values applicable on the failure loads are also suggested keeping due weightage to serviceability criterion.

    • Modeling serrated flow of SS 316L under dynamic strain aging effect


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      The serrated behavior of the stress-strain curves also known as PLC effect due to dynamic strain aging of SS 316L is investigated here from room temperature to 550°C. Tensile tests were conducted for strain rates 10-5-10-2/s. Serrations of type D, type A and type A?B were observed at different loading conditions. Amaterial model was fitted to the experimental data to simulate the serrated flow in the stress strain diagrams. For this an approach similar to a previous study done with an Al-Mg alloy was followed. However, few changes in the analysis steps were performed to accommodate temperature dependency, a feature not addressed in the earlier work. In addition, the fitment technique was improvised so that the material model could be fit through a substantially smaller set of experimental data, thus improving the speed of the fitting process. Finally, comparisons were done between the experimental data and the results from the simulations. Critical strains from the simulations were found to be of the same order of magnitude of the experimental critical strains and theserrations could also be found in the simulated stress-strain diagrams similar in some aspects to the experimental serrations.

    • Special Issue: First International Conference on Mechanical Engineering (INCOM-2018)


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      This special issue contains selected papers from among those presented at the ‘‘First International Conference on Mechanical Engineering (INCOM)’’, 2018 held from 4 to 6 January, 2018 at Jadavpur University, Kolkata. The conferencewas organized by the Department of Mechanical Engineering, Jadavpur University. Around 200 papers were presented at the conference in wide ranging areas of mechanical engineering. Based on a preliminary scrutiny, some papers, mostly based on fundamental areas of mechanical engineering, wereshortlisted for consideration of publication in the special issue of Sadhana. The authors of the shortlisted papers were invited to submit extended versions of their works presented at the conference. The submitted papers were reviewedfollowing the review protocol of Sadhana. After multiple rounds of review, eleven papers were finally selected. These papers, apart from being of high quality that meets the standards of the journal, represent different areas like solidmechanics and materials, fluid-structure interaction, heat transfer, combustion and dynamic analysis of mechanical systems.

    • A static risk assessment model for underwater shield tunnel construction


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      The shield method is widely used in underwater tunnel construction. However, the shield construction process faces many uncertain risk factors that increase the level of safety risk during shield tunnel construction. Therefore, risk assessment has become a necessary task in the early stages of tunnel construction.In this study, a new risk assessment model for underwater shield tunnel construction is proposed that combines a normal cloud model with an entropy weight method. The model contains 20 assessment indexes and gives therange of each index corresponding to different risk levels, which comprehensively reflects the influencing factors of risk. By using a normal cloud model, the fuzziness and randomness of risk assessment data are taken into account effectively, and the reliability of assessment results is increased. Based on an entropy weight method, the rules and characteristics of the evaluation data in the model are considered, and the weight coefficient of the evaluation index is determined to avoid the subjectivity of the expert weight method. The risk assessment model is applied using the Xiangjiang shield tunnel as an example. The results show that the overall construction risk level of the Xiangjiang tunnel is level II, which is consistent with the site risk situation and shows that the modelcan objectively and accurately evaluate the construction risk level of an underwater shield tunnel

    • Improvements of IS 1343-2012 Shear Design Provisions Using a New Traditional Shear Database of Prestressed Concrete Members with Stirrups


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      Various national codes of practice play a crucial role in the development of the country’s infrastructure and should be developed based on principles of mechanics and experimental verification. Continuous monitoring of infrastructure and updating of relevant codes of practice at regular intervals is essential towithstand the ever-increasing demand of the country’s infrastructure. In the present study, the shear design provisions of prestressed concrete (PC) in IS 1343-2012 have been reviewed. The assumptions used in the formulations of the existing shear design equations in IS 1343-2012 have been discussed. The present study reveals that the IS 1343-2012 shear design provisions, which are based on old test data, are too conservative and are unable to distinguish the two major modes of traditional shear failure, namely web-shear and flexure-shear.Modifications for the existing IS 1343-2012 shear design equations have been proposed to improve the shear strength estimation of PC members and also to distinguish between the web-shear and flexure-shear failure modes. A detailed comparison of existing IS 1343-2012 shear design provisions with the proposed modified shear strength equations has also been made with the help of a traditional shear database on PC members with stirrups.

    • Experimental study and analysis of a thermoacoustically driven thermoacoustic refrigerator


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      Experimental investigations are performed on a half-wavelength standing wave type thermoacoustically driven thermoacoustic refrigerator also known as TADTAR. Present TADTAR device conceived to be a quarter wavelength standing wave type thermoacoustic engine (TAE) coupled to a quarter wavelength standing wave thermoacoustic refrigerator (TAR). A TAE generates acoustic work using heat, and this produced acoustic work is directly fed to TAR where a useful cooling effect is developed. The study here aims to projectthe enhancement in the performance of a TADTAR system by using better geometric choices and operating conditions. In the present work, by keeping the engine part unaltered, parametric variations on the refrigerator side are performed. Two geometric parameters namely resonator length and TAR stack position and one operating parameter, working gas, have been varied at three distinct choices. The performance of TADTAR is examined for three output parameters of TADTAR namely frequency of oscillations, pressure amplitude, andtemperature difference across TAR stack. The present study should be useful for assisting select these parameters for starting the designing of a TADTAR. It also helps in concluding in a more generalized way the dependence of the above-said output of TADTAR on the varying parameters. This paper shows that longerresonator and He-Ar mixture as working gas among the choices is better for a TADTAR system for achieving better performance. It also highlights the potential existence of a unique position for a stack length for a TADTAR to attain maximum performance in terms of the temperature difference across the TAR stack. Thepresent paper reports the maximum temperature difference of 16.3 K across the TAR stack

    • Graph based event measurement for analyzing distributed anomalies in sensor networks


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      Wireless Sensor Network (WSN) has emerged drastically with numerous practical applications of considerable Engineering importance where privacy and security are of dominant influence. This paves the way for this investigation and present interest in the development of novel and innovative intrusion detectionapproach. This work anticipated a novel Intrusion detection framework by modeling sensor connectivity with a targeted graph and uses statistical graph properties by modeling intrusion detection. In anticipated graph-based detection, data capturing magnitude is modeled with the Gaussian model, and the corresponding correntropy is estimated by graph matrix with adaptive sensor measurements. Anticipated detection approach is modeled basedon the Laplacian Matrix, and closed-form expressions are attained for statistical analysis. At last, temporal network analysis are characterized by evaluating sensor distance among measurement distributions in consecutive time. The results depict that the anticipated detection framework offers superior detection recital than compared to existing frameworks.

    • On the solutions of the two preys and one predator type model approached by the fixed point theory


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      The purpose of this paper is to discuss a special type of functional equation that describes the relationship between the predator animals and their two choices of prey with their corresponding probabilities. Our aim is to find the existence and uniqueness results of the proposed functional equation using the Banachfixed point theorem. Finally, we give an illustrative example that supports our main results

    • Deep convolutional network for urbansound classification


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      The efficiency of Convolutional Neural Networks in classifying terse audio snippets of Urban-Sounds is evaluated. A deep neural model contains two convolutional layers coupled with Maxpooling plus three fully interconnected (dense) layers. The deep neural model is being trained upon low level description of various urban sound clips with deltas. The efficiency of the neural network is examined on urban recordings and compared with different contemporary approaches. The model obtained 76% validation accuracy that is better than other conventional models which relied only on Mel Frequency Cepstral Coefficients

    • 1-out-of-2: post-quantum oblivious transfer protocols based on multivariate public key cryptography


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      Oblivious transfer (OT) is a fundamental cryptographic primitive. It is developed for the efficient and feasible implementation of most advanced cryptographic tasks. Today, most of the existing OT protocols’ security is based on number-theoretic assumptions. However, many number-theoretical problems are solvable by a quantum computer in polynomial time. Therefore, OT protocols with post-quantum cryptography approach are required. Multivariate cryptographic constructions are one of the potential candidates for post-quantum cryptographyas they are speedy and require only modest computational resources. This paper presents constructions of OT protocols utilizing multivariate public key cryptography (MPKC). Security of our schemes is achieved under the hardness of multivariate quadratic (MQ) problem. To the best of our knowledge, our designs are the first MPKC-based post-quantum OT protocols.

    • Development and performance analysis of solar photovoltaic–thermal (PVT) systems


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      The photovoltaic–thermal (PVT) systems have been established for providing both electricity and heat using the existing photovoltaic (PV) system set-up. The PVT systems capture panel heat for some useful purpose. It is based on deploying a polymer sheet at the back of the PV panel to accommodate cooling water between the PV panel and the sheet to maximize the contact area between cooling water and panel. The present work compares the performance of a normal PV panel to that of the novel PVT panel. The PVT system isfabricated and experiments are conducted to evaluate electrical and thermal efficiencies. An improvement of 2.17% is observed in the electrical efficiency of the PVT panel in comparison with the normal PV panel. A brief cost analysis along with payback period calculations of the PVT panel is also included.

    • A time-interleaved pipelined ADC with ultra high speed sampling


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      Based on a standard 0.18lm BiCMOS process, a 12 bit 2GSps ADC is achieved using timeinterleaved pipelined architecture in this work. The DC offset caused by the mismatch of ADC channels is removed due to the application of digital calibration technology, which improves the performance of the ADC.The power supply voltage is 1.8 V and the power consumption is 100 mW for each lane. The measurement results indicated that the circuit in this paper can be used in multi-channel time-domain interleaved pipelined ADC architecture to achieve a 2GSps ultra high speed ADC.

    • Numerical and experimental study on dynamic characteristics of honeycomb core sandwich panel from equivalent 2D model


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      Numerical and experimental investigation on free and forced vibration of honeycomb core sandwich structure using the equivalent two-dimensional (2D) model is presented. Initially, a three-dimensional (3D) honeycomb core sandwich structure is converted to a 2D panel with equivalent properties obtained based on the honeycomb plate theory. Following this, the 2D panel is modelled using a layered structural shell element to obtain the vibration response using commercial element software. An experiment on harmonic analysis is carriedout on the honeycomb core sandwich structure. The results obtained based on numerical results of free- and forced-vibration responses match well with experimental results. Further, from the forced-vibration response ofboth experimental and numerical results, it is noticed that the second mode is not observed. This can be attributed to the excitation location corresponding to the nodal point of the second mode and this is verified with the mode shape obtained based on numerical and experimental analysis.

    • Power- and time-optimized MMSE-based joint beam-forming with relay selection for future generation MIMO networks using Modified Cuckoo-Search Optimization algorithm


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      Multiple Input Multiple Output (MIMO) networks operating in millimeter wave frequency band bring promising solutions for the increased demand of future generation networks in terms of data rate, signal quality, power optimization and computational complexity. A joint beam-forming (JBF) system working concurrently on source–relay–destination nodes leads to faithful delivery of signals by mitigating the effect of interferences. The traditional JBF designs in MIMO networks yield power wastage due to undesirable participationof intermediate relay nodes for message forwarding. The computational delay in beam-forming (BF) matrix update is tedious in traditional systems. This paper proposes a novel design of power-optimized JBF that facilitates optimum relay selection for solving power wastage issues. The selected relays co-operate in BF with the power constraint, and all other relays are powered down and enter into sleeping mode. Modified Cuckoo-Search Optimization (MCSO) algorithm is used for relay selection and minimum mean square error algorithm is used for BF matrix calculation. The proposed JBF is able to maximize Achievable Sum Rate (ASR) for optimum value of transmission power. The maximum power efficiency is achieved for distant communication with the aid of selected relays contributing to maximizing the ASR value. The proposed work minimizes the sum of meansquare error and concurrently computes optimum time slot for BF matrix update, and hence computational delay is reduced. Thus a hybrid optimization for power and time in JBF design is achieved with relay selection and it can be widely used in future generation networks for high-quality and interference-free communication

    • A TDOA-based multiple source localization using delay density maps


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      The higher computational efficiency of the time difference of arrival (TDOA) based sound source localization makes it a preferred choice over steered response power (SRP) methods in real-time applications. However, unlike SRP, its implementation for multiple source localization (MSL) is not straight forward. Itincludes challenges as accurate feature extraction in unfavourable acoustic conditions, association ambiguity involved in mapping the feature extractions to the corresponding sources and complexity involved in solving the hyperbolic delay equation to estimate the source coordinates. Moreover, the dominating source and early reverberation make the detection of delay associated with the submissive sources further perplexing. Hence, this paper proposes a proficient three-step method for localizing multiple sources from delay estimates. In step 1, the search space region is partitioned into cubic subvolumes, and the delay bound associated with each one is computed. Hereafter, these subvolumes are grouped differently, such that whose associated TDOA bounds are enclosed by a specific delay interval, are clustered together. In step 2, initially, the delay segments and later each subvolume contained by the corresponding delay segment are traced for passing through estimated delay hyperbola. These traced volumes are updated by the weight to measure the likelihood of a source in it. The resultant generates the delay density map in the search space. In the final step, localization enhancement is carried out in the selected volumes using conventional SRP (C-SRP). The validation of the proposed approach isdone by carrying out the experiments under different acoustic conditions on the synthesized data and, recordings from SMARD & Audio Visual 16.3 Corpus

    • Novel realizations of digitally controlled low power current controlled current conveyor for tuning filter outputs with constant power consumption


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      This paper presents a dual output resistance tunable current controlled current conveyor (DORTCCCII). In the existing current conveyor the change in bias current is required to alter the design parameter Rx which is the intrinsic resistance of input X terminal. This variation changes the internal dc bias conditions such as saturation margins as well as total power consumption of the block. A resistance trimming block is added at X terminal which is controlled by some programmable bits. The usage of programmable bits helps to achieve the desired response without changing bias current, dc operating point and total power consumption. The port relationships of the DO-RTCCCII block are checked and the circuit and design parameters of current follower, voltage follower are analyzed. The operation of filter circuit is also included to illustrate usefulness ofthe proposal. The circuit has been designed and simulated using 28 nm CMOS bulk technology model parameters on Cadence Virtuoso/AMS environment (eldo simulator) using 0.75 V supply voltage and results have been verified with post layout netlist.

    • Multi-objective optimisation of damper placement for improved seismic response in dynamically similar adjacent buildings


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      Multi-objective optimisation of damper placement in dynamically similar adjacent buildings is considered with identical viscoelastic dampers used for vibration control. An exhaustive search is used to describe the solution space in terms of various quantities of interest such as maximum top floor displacement, maximumfloor acceleration, base shear and inter-storey drift. With the help of examples, it is pointed out that the Pareto fronts in these problems contain a very small number of solutions. The effectiveness of two commonly used multiobjectiveevolutionary algorithms, viz. NSGA-II and MOPSO, is evaluated for a specific example.

    • Optimal feature subset selection using hybrid binary Jaya optimization algorithm for text classification


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      Feature selection is an important task in the high-dimensional problem of text classification. Nowadays most of the feature selection methods use the significance of optimization algorithm to select an optimal subset of feature from the high-dimensional feature space. Optimal feature subset reduces the computation cost and increases the text classifier accuracy. In this paper, we have proposed a new hybrid feature selection method based on normalized difference measure and binary Jaya optimization algorithm (NDM-BJO)to obtain the appropriate subset of optimal features from the text corpus. We have used the error rate as a minimizing objective function to measure the fitness of a solution. The nominated optimal feature subsets are evaluated using Naive Bayes and Support Vector Machine classifier with various popular benchmark text corpus datasets. The observed results have confirmed that the proposed work NDM-BJO shows auspicious improvements compared with existing work.

    • Statistical analysis and optimization of process parameters in development of metal matrix composite using industrial waste


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      Bauxite residue (BR) is the hazardous waste produced during extraction of alumina by processing of bauxite ore. BR has an adverse effect on humans and the environment due to its disposable problem. To minimize the environmental impact, BR must be effectively utilized. One such way is to use BR as a reinforcing for metal matrix composite. In this study, Taguchi’s mixed fractional factorial experimentation (L18) approach is employed in the development of Al6063/BR composite through advanced stir casting process. The processparameters considered are stirring speed (rpm), reinforcement particle size (lm), reinforcement weight fraction (wt%) by weight of the matrix phase, pouring temperature (°C), and preheat temperature (°C). Later, ANOVA results indicate that particle percentage (wt%) is the major contributor in the development of porosity content. Moreover, the interaction of process parameters was also found to have an impact on porosity content. The outcome of the study reveals that the stirring intensity at 350 rpm, particle size at 80 lm, particle percentage at 2 wt%, pouring temperature at 730 °C, and preheat reinforcement temperature at 450 °C are the optimal conditions for fabricating defect free Al6063/BR composite

    • Elevated temperature molten salt corrosion study of SS304L austenitic boiler steel


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      The aim of this study is to investigate the high-temperature corrosion behavior of 304L stainless steel in the environment of various molten salt mixtures in the temperature range of 550–850°C. Weight change measurement has been done and characterization of corroded specimen was carried out using XRD, SEM/EDStechniques. Findings indicate that high chloride concentration salts affect the corrosion resistance adversely. The protective behavior of Cr2O3 layer deteriorated and its passivation is hindered at higher temperature owing to thechlorination-oxidation process. Fe2O3 and (Fe, Cr)xOy were found to be the major phases in the corrosion product. The salts were found to significantly affect the corrosion of 304L stainless steel in the following order: K2SO4 + 60% NaCl>Na2SO4 + 50% NaCl>40% K2SO4 + 40% Na2SO4 + 10% KCl + 10%NaCl>Na2SO4 + 60% V2O5 >Air.

    • General particle concentration model and experimental validation for cleanrooms


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      Numerous research reports have demonstrated that the supply air volumes of cleanrooms areusuallyover-designed to satisfy air cleanliness classes, which may lead to enormous energy waste. In this study, five well-recognised international mathematical models for calculating cleanroom particle concentration wereanalysed, which are all based on uniform particle distribution in the cleanroom, indoor particle conservation, and mass airflow balance, and an improved and more general model has been established for calculating the minimum air change rates according to the expected air cleanliness class. Following the introduction of nondimensional concentration correction factors, based on the least-squares method, the average relative error between the model-predicted and measured particle concentration is approximately 13.5%. Based on the improved model with correction factor, the test results demonstrate that the particle concentration depends mainly on the air change rate, particle emission rate and return airflow patterns, among others. When the air change rate per hour and ratio of particle concentrations between the return airflow and room average were varied from 40 h-1 to 120 h-1 and 0.7–1.3, respectively, the concentration consequently decreased by approximately 65% and 46%. The particle deposition caused by gravity can be neglected for small particles

    • Fragmented handwritten digit recognition using grading scheme and fuzzy rules


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      The handwritten digit recognition issue turns into one of the well-known issues in machine learning and computer vision applications. Numerous machine learning methods have been utilized to resolve the handwritten digit recognition problem. However, sometimes the digit is not completely present in the image dueto issues related to scanning or environmental conditions (light, illumination, dirt, etc.). Although different efficient methodologies of handwritten digit recognition are proposed, there is not much work done on fragmented handwritten digit recognition. The objective of the proposed research work is to handle this circumstance to assemble a consistent digit recognition system that can precisely handle three types (English, Bangla, and Devanagari) of fragmented handwritten digit images. To solve the confusion, a technique is created to classify handwritten digits based on geometrical functions that are utilized to calculate handwritten digit features to assess if a digit belongs to a specific class. A grading scheme and a set of specified fuzzy rules determine the performance of classification. Experiments have been directed on the three familiar datasets, i.e., MNIST database (English), NumtaDB (Bangla) and Deva numeral database (Devanagari). Since fragmented digit delivers a lesser amount of information, the work also attempts to create a tentative size threshold above which outcomes become erratic and whether such thresholds are standardized or vary depending on other factors. Since the fragmented handwritten digital image does not have a public database, a method is formed to produce repeatable fragmented handwritten digital images from the entire image. Experimental outcomes validate that the proposed approach is effective in recognizing fragmented handwritten digits to an acceptable degree of fragmentation.

    • Heterogeneous classifier ensemble for sentiment analysis of Bengali and Hindi tweets


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      Sentiment analysis is an essential step for analysing social media texts such as tweets and other posts on the various micro-blogging sites. The basic step of sentiment analysis is sentiment polarity detection, which identifies whether an input piece of social media text is positive, negative or neutral. In this paper, wepresent an approach that combines heterogeneous classifiers in an ensemble for sentiment polarity detection in Bengali and Hindi tweets. Our proposed method constructs an ensemble of three different base classifiers where the feature set for each base classifier is different from each other. We have also incorporated an external knowledge base called sentiment lexicon to augment tweet words with sentiment polarity information retrieved from the sentiment lexicon. Experimental results show the effectiveness of our proposed heterogeneous ensemble model for sentiment polarity detection for both Bengali and Hindi languages. It has been shown that our system outperforms other existing Bengali and Hindi sentiment classification systems to which it is compared.

    • Skin friction estimation on a surface under shock-boundary layer interaction


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      This article presents correlations for indirect measurement of skin friction inside a laminar separation bubble induced by hypersonic shock-boundary layer interaction (SBLI) on a flat plate. The correlations, based on parameters that are known to influence the SBLI region, were developed using exhaustive numericaland analytical studies. Experiments were conducted in a hypersonic shock tunnel at Mach 8.6 (±0.22) to measure surface heat-flux and pressure in the zone of SBLI on a flat plate, which were then used to supplement and validate the correlations. The data predicted by the correlations agreed reasonably well with that of exact solutions. The case studies contained non-reacting air, behaving as a perfect gas on a flat surface.

    • Design of a fuzzy robust-adaptive control law for active suspension systems


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      This paper outlines a new approach in control of active vibration systems to make the system robust to parametric uncertainties, unmodeled dynamic effects and external disturbances. Namely, it is aimed to ensure robustness of the system towards all kind of disturbances such as road surface inputs and unexpected system parameter changes. So, a new robust-adaptive controller is designed as a vibration isolator and then applied on a full car active suspension system to improve the ride comfort of a vehicle in the presence of structured parameteruncertainties and unstructured unknown parameters or unmodeled dynamics. For this purpose, new parametric uncertainty upper bound adaptation algorithm is developed to isolate any platform from vibrations. Using adaptive laws, the controller can operate properly under changing conditions. The robustness of controller is also ensured by robust control law. This new approach represents a groundbreaking solution to eliminate any disturbance on a vehicle. Stability of the system is guaranteed by using Lyapunov theory, thus uniform boundedness error convergence is achieved. Afterwards, fuzzy logic controller is used to achieve the optimum values of controller gains. Also, comparative numerical solution using a fuzzy logic controlled suspension is performed on the same full-car model, both in time and frequency domain since classical FLC is an effective control method for active suspensions. At the end, it has been verified that the designed fuzzy robust-adaptive controller improves ride comfort more successfully than fuzzy logic one.

    • Determination of thermal performance of hydronic radiant panel heaters for different fluid flow rates, fluid inlet temperatures and room temperatures


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      An experimental study of a commercially manufactured ceiling type hydronic radiant heating system has been performed in a test room, under controlled temperature conditions. One of the goals was to investigate how the radiant heater, under various operating conditions, affects the temperature distribution inside an occupied room. Another goal was to study the thermal performance of the radiant heating panel for different fluid inlet temperatures, fluid mass flow rates and test room temperatures. In addition, the temperature distributionon top of a surface placed below the heater, representing an actual application, was investigated. From the relevant literature, it was concluded that insufficient knowledge exists about these characteristics. The working fluid was water, and fluid inlet temperatures between 45°C and 85°C and mass flow rates of 97 kg/h and 174 kg/h were analyzed. The results showed that an almost linear increase in heat output arises, with the increase in the inlet water temperature. For lower inlet temperatures the heat output is moderately higher for a mass flowrate of m_ = 97 kg/h. The fraction of radiation heat transfer to the total heat transfer increases with decreasing water inlet temperature. It was also observed that, a relatively uniform temperature distribution could be obtained on the plate below the radiant panel. Furthermore, lower vertical temperature differences can be obtained inside the test room, for low water inlet temperature conditions. The obtained results of this study, could give information to manufacturers and building engineers, on the appropriate use and regulation of hydronic radiant systems.

    • A new fast and efficient 2-D median filter architecture


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      Existing architectures for the median filter are based on sorting algorithm where comparators are used in serial. This paper proposes a new high-speed architecture of two dimensional (2-D) median filter where compare and select modules are used in parallel to sort the incoming numbers. The hardware implementation results show that the proposed architecture (PA) operates at 26% and 34% higher frequency in Virtex 4 and Virtex 7 FPGA device, respectively, in comparison with the architectures reported. The PA is synthesized using the RTL Compiler of Cadence along with Faraday 180 nm standard cell library. The maximum operating frequency of the PA is 1.06 GHz with a total gate count of 917. The complete chip layout has been done using the SoC encounter tool. The area of the final chip is 0.13928 mm2 with a power consumption of 0.168 mW analysed using prime-power

    • Statistical machine translation based on weighted syntax–semantics


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      In this paper, we propose an alternate technique to improve the performance of the statistical machine translation (SMT) system. Here, the phrases are re-weighted in light of linguistic knowledge as both syntactic and semantic information. Syntactic knowledge helps to increase fluency whereas semantic similarity helps to incorporate semantic meaning, which is required for adequacy of translated sentences. The scores of the phrases from the phrase-table are re-balanced by expanding and diminishing the weights of the correct phrasesand the incorrect phrases, respectively. Additional knowledge in phrase-table helps in improving overall performance of translation quality. In this work, our proposed methodology achieves an impressive accuracy improvement in terms of BLEU, NIST and RIBES in different domain data. We achieve 58.54 BLEU points,0.7759 RIBES points and 9.684 NIST points for product domain catalog.

    • Articulatory-feature-based methods for performance improvement of Multilingual Phone Recognition Systems using Indian languages


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      In this work, the performance of Multilingual Phone Recognition System (Multi-PRS) is improved using articulatory features (AFs). Four Indian languages – Kannada, Telugu, Bengali and Odia – are used for developing Multi-PRS. The transcription is derived using international phonetic alphabets (IPAs). Multi-PRS istrained using hidden Markov models and the state-of-the-art Deep Neural Networks (DNNs). AFs for five AF groups – place, manner, roundness, frontness and height – are predicted from Mel-frequency cepstral coefficients (MFCCs) using DNNs. The oracle AFs, which are derived from the ground truth IPA transcriptions, are used to set the best performance realizable by the predicted AFs. The performances of predicted and oracle AFs are compared. In addition to the AFs, the phone posteriors are explored to further boost the performance ofMulti-PRS. Multi-task learning is explored to improve the prediction accuracy of AFs and thereby reduce the Phone Error Rates (PERs) of Multi-PRSs. Fusion of AFs is done using two approaches: i) lattice re-scoring approach and ii) AFs as tandem features. We show that oracle AFs by feature fusion with MFCCs offer aremarkably low target of PER of 10.4%, which is 24.7% absolute reduction compared with baseline Multi-PRS with MFCCs alone. The best performing system using predicted AFs has shown 3.2% reduction in absolute PER(9.1% reduction in relative PER) compared with baseline Multi-PRS. The best performance is obtained using the tandem approach for fusion of various AFs and phone posteriors

    • Self-heating of rolled ZnCuTi sheets


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      Self-heating effect for thermomechanical forming processes turns out to be dramatically significant for material with a very low melting point, such as zinc alloys. Zinc low melting point temperature (419.54°C) accentuates metallurgical effects when it is formed in cold or warm manufacturing processes. During deformation, self-heating can therefore induce a relative softening in the behavior law (that could improve formability) which competes with the conventional plastic hardening of the material. Hence, the correct identificationof zinc material behavior has to account for both softening and hardening phenomena. This paper studies the effect of plastic work energy in the material identified by means of tensile tests by combining digital image correlation and infrared thermography technique.

    • On the static deformation of FG sandwich beams curved in elevation using a new higher order beam theory


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      This article presents the static analysis of FG sandwich beams curved in elevation. Navier-type semi-analytical solutions are obtained based on polynomial type fifth order shear and normal deformation theory. The beam has FG skins and isotropic core. Material properties of FG skins are graded in z-directionaccording to the power-law distribution. The present theory accounts for a fifth-order distribution of axial displacement and fourth-order distribution of transverse displacement. The present theory considers the effect of thickness stretching and gives a realistic variation of transverse shear stress through the thickness of the beam. The governing equations are obtained within the framework of the principle of virtual work. Semi-analytical static solutions for the simply supported FG sandwich beams curved in elevation are obtained using Navier’stechnique. The beam is subjected to uniformly distributed load. The non-dimensional numerical values for displacements and stresses are obtained for various power-law index and thickness of the core. The present results are found in good agreement with previously published results

    • Experimental investigations of sol-gel process parameters for wear reduction on thermal barrier coated AA2024 aluminum alloys with the use of Taguchi-based optimization


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      The present sol-gel processes present a surface modification technique for improving the sliding wear resistance characteristics of metallic materials of 2024-T351 aluminum alloy. With the help of dip-coating methods, seven weight% yttria stabilized zirconia (7YSZ) as a top-coat is applied over the air plasma sprayedbond-coated materials, CoNiCrAlY, on aluminum alloys. Thereafter, coating thickness is measured using an optical microscope. Further, sliding wear tests are performed on Pin-On-Disc Friction and Wear test rig as per L16 orthogonal arrays of Taguchi method. Investigations revealed temperature as the most influencing parameter for uncoated samples while temperature and applied load, both for coated samples. In comparison to base metallic alloys, sol-gel derived YSZ coating on the AA2024 surface exhibited better wear resistance, resultedinto the reduction of wear rate.

    • Satellite image based flood classification in urban areas using B-convolutional networks


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      Spatial features with spectral properties enhance the quality of satellite image while mapping complex land cover. These features are integrated with the proposed classification approach for improving classification results. The ultimate objective of this investigation is to provide high-level features to the convolutionalneural network (CNN) for mapping flooded regions (before and after) using remote sensing data. Here, boundary-based segmentation is done to recognize the dimensions and scales of objects. Modeling a fully trained Convolutional network is feasible for training a huge amount of data in remote sensing studies. Finetuned CNN is utilized with slight modification for attaining classified Landsat images. Classification outcomes and confusion matrix are manipulated using B-CNN are compared with classifiers like SVM, random forest (RF)to compute B-CNN efficiency

    • Solution and stability analysis of non-homogeneous difference equation followed by real life application in fuzzy environment


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      The study fuzzy difference equation becomes very important as huge numbers of real-life problems in the field of engineering; ecology social science, etc. can be mathematically represented in the form of difference equation where impreciseness is inherently involved. In this paper, we have focused on the solution techniques of non-homogeneous fuzzy linear difference equation with different cases involving fuzzy initial conditions, fuzzy forcing function and fuzzy coefficient. The idea of fuzzy equilibrium point is introduced and its stability analysis has been performed. The whole theoretical work is followed by real-life applications which show the impact of fuzzy concepts in mathematical modelling for better understanding the behaviour of the system in an elegant manner.

    • Resolution-independent fully differential SCI-based SAR ADC architecture using six unit capacitors


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      A resolution-independent successive approximation register (SAR) analog to digital converter (ADC) architecture based on a switched capacitor integrator is presented. Digital to analog converter (DAC) architecture uses charge sharing and integration principle for reference generation, using only six unit capacitorsfor a fully differential version. A 10-bit, 1.8-V and 0.9-MS/s SAR ADC is designed in 180-nm CMOS process. ADC architecture is area efficient when compared with SAR ADC with a binary weighted capacitor array DAC. The architecture is largely parasitic insensitive, also programmable resolution is possible with no hardwareoverhead.

    • A cost-causal marginal participation method using min-max fairness for transmission services cost allocation


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      We consider the problem of fair allocation of the cost of a transmission system among load and generation entities using the marginal participation approach. We show that a cost-causal approach involving capacity-based line cost rate and a min-max fair economic slack bus selection for price-taking entities leads to arigorously fair and more accurate implementation of marginal participation method. In the existing methods the counter-flows are masked, which is a compromise with fairness and linearity. However, if the counter-flows areincentivized then it can lead to pay-offs to some entities. The proposed approach solves the problem of pay-offs without masking the counter-flows. This is achieved by separation of the total transmission services cost into usage, reliability and residual capacity components. The allocation of the first two components is based on the min-max fairness policy, and the residual capacity costs are allocated on a pro-rata basis. Simulation results on multiple IEEE test systems, Indian utility power systems and extensive comparative evaluations for the contemporary methods demonstrate the claims made.

    • Effects of N2-mixed shielding gas on the ferrite number and microstructure of 304L multi-pass GTAW joint


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      Ferrite number (FN) is a crucial parameter for austenite steel welding product, since it has significant influences on the crack sensitivity and ductility at cryogenic temperature. Normally, the FN is measured using a Feritscope or predicted according to WRC-1992 and the results generally match. This investigation detected the FN of 304L stainless steel multi-pass GTAW joint protected by mixed shielding gas with different N2 additions; the measured FN did not match with the FN predicted through WRC-1992 as the N2 content wasmore than 1%. The microstructure showed that a fully austenitized zone formed at the inter-bead of the joint shielded with Ar–1.0%N2 and Ar–1.5%N2, which resulted in the inaccuracy of the FN predicted through WRC-1992. The formation mechanism of the fully austenitized zone was proposed based on the nitrogen solubility and equilibrium phase transformation map. It is suggested that traditional prediction diagrams cannot give an accurate prediction of the FN during the multi-pass process shielded with N2 addition.

    • Design of optimal high-frequency CMOS VCOs for automotive application


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      In this paper, a design methodology of Voltage-Controlled Oscillator (VCO) for long-range automotive RAdio Detection And Ranging (RADAR) is proposed and simulation analysis is carried out over Virtuoso SpectreRF software on Cadence tool. The frequency ranges of the mm-wave CMOS current-starved ring and LC VCOs for 45-nm CMOS technology are 24 and 76 GHz, respectively. The ring VCO at 25 GHz oscillation frequency demonstrates 2.06% tuning range, phase noise -71.61 dBc/Hz at 1-MHz offset, 3.43 mW power dissipation and layout area of 20 x 20 mm2 whereas cross-coupled LC VCO achieves an oscillationfrequency of 76.25 GHz for frequency tuning range of 0.65%, a phase noise of -92.44 dBc/Hz at 1-MHz offset, 8.59 mW power dissipation and 320 x 320 mm2 layout area. The proposed design of efficient VCOs shows an excellent performance for long-range automotive RADAR.

    • Operator based finite element modelling of viscoelastic cracked propeller shaft: a comparative study


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      The present study focuses on to explore the dynamic analysis of a viscoelastic propeller-shaft system with transverse breathing crack supported by journal bearings. Finite element modelling of the shaft continuum is done considering the Euler-Bernoulli beam theory. Operator based constitutive relationship isapplied to incorporate material damping of the rotor and higher-order equations of motion are established.Accurate time-dependent functions are used to formulate cracked element stiffness matrix and augmented to the overall stiffness matrix of the entire system. Eigen analysis is performed after converting the higher-order equation into the first-order form. A Comparative study is demonstrated based on different dynamic parameters like whirl frequency, modal damping factor and stability limit of spin speed. Further, the variation of stabilitylimit of spin speed and natural frequency is also studied based on the parameters such as crack depth and its location along different section of the propeller shaft.

    • Target detection method in short coherent integration time for sky wave over-the-horizon radar

      HUAN LUO

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      In order to reduce the Doppler spread effect caused by ionospheric disturbance, sky wave over-thehorizon radar often detects ships in a short coherent integration time (CIT). In short CIT, an effective means to detect ships is clutter suppression. Through the analysis of the real data, it is found that the sea clutter has a strong correlation when the sea state is relatively stable, whether in long CIT or short CIT. To avoid estimating clutter subspace dimension and clutter cancellation times of the available methods, an adaptive clutter suppressionmethod based on sea clutter correlation is proposed. This method does not need to estimate the parameters of the clutter, even when the Doppler frequency of the ship target is close to the sea clutter, the target can be detected. Theoretical analysis and real data processing indicate that the proposed method can detect ship target effectively.

    • Assessment of reactivity of energy efficient high volume fly ash based geopolymers through various approaches


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      Geopolymer belongs to the family of aluminosilicate polymers. The production of geopolymer generally involves the combination of silicon and aluminium atoms in a hydroxide-promoted activation, followed by a condensation reaction to form an aluminosilicate gel which gives the final hardened binder. Reactivity of geopolymer system is influenced by nature of alkaline activator, ratio of silicon to aluminium, curing time, pH and degree of polycondensation. Fly ash and ground granulated blast furnace slag have been utilized for the synthesis of geopolymers at ambient condition which does not require energy. The investigationaims at assessing the reactivity of geopolymer through various approaches such as degree of reactivity (by means of insoluble residue), infra-red spectroscopy and free alkali content involving various activators and admixtures. The results show that potassium based geopolymer with higher level of alkalinity shows morereactivity. Energy required for the production of geopolymer pastes with sodium silicate as activator ranges from 3.65 to 4.37 MJ/kg, with potassium silicate as activator ranges from 2.24 to 4.45 MJ/kg as against 4.79 MJ/kg for ordinary Portland cement paste. For geopolymer pastes using high volume fly ash 4% less carbon foot print is possible compared to ordinary Portland cement paste.

    • CASCM2: Capability-Aware Supply Chain Management Model for QoS-driven offload-participator selection in Fog environments


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      Computational offloading happens to be a prominent solution for leveraging the performance of handheld devices. It raises the feasibility of executing computation-intensive and latency-conscious tasks with the help of task migration to proximate cloud servers. However, longer Wide Area Network latencies of cloud and greater mobile data consumption paved the way to adopting opportunistic offloading instead of remote offloading. This proposed work uses an edge-based solution of Fog computing to handle such tasks and toprovide the users with a high Quality of Experience. This paper presents a Capability-Aware Supply Chain Management Model (CASCM2) as an extension of traditional Supply Chain Management (SCM) model. CASCM2 dynamically selects a crowd of competent mobile devices within a Foglet that is in proximity to theusers and offloads the complex computational tasks to them. The proposed model aims at optimizing two parameters, such as communication overhead and conductance cost, as they possess a remarkable impact on offloading delay-sensitive tasks. Hence an overall objective optimization is achieved using a dual Lagrangian decomposition method, which subdivides and solves the optimization of parameters in parallel. Experimental analysis of the participator selection is performed for a single period as well as multiple periods. The performanceresults yield a considerable contribution that alleviates the issues in delay-sensitive applications deployed in the Fog framework.

    • On the distribution-free continuous-review production-inventory model with service level constraint


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      In this article, we study a continuous-review production-inventory model that assembles lost sales and backorders with service level constraint. The study under consideration assumes that the distribution of demand during the lead-time is known partially. The objective of this paper is twofold. Firstly, the distributionfree procedure is applied to obtain a closed-form solution of optimal production quantity, re-order level and lead-time in the random framework. Secondly, considering demand as a fuzzy random variable, the procedure isextended to the fuzzy random framework in which an algorithm is proposed to find the optimal global solution. Two numerical examples are provided to illustrate the methods. Furthermore, sensitivity analysis is performed to present some managerial inferences

    • Photo sensitizing and electrochemical performance analysis of mixed natural dye and nanostructured ZnO based DSSC


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      The paper highlights the enactment of the natural dyes, like purple cabbage, spinach, turmeric and their mixture as a photo-sensitizer, with nanostructured zinc oxide (ZnO) as a photo-anode, based dye-sensitized solar cell (DSSC). The field emission scanning electron microscopic image of ZnO, prepared by chemical bath deposition process, proclaims two different types of morphology, nano-wire and nano-plate shape. The photo sensitizing properties of the natural dyes and their mixed part are explored through FTIR spectra and UV-vis light absorbance characteristics. The FTIR spectra explore the presence of different anchoring chemical groups which confirm the strong anchoring bond with ZnO and enhancement of electron mobility. The diffused reflectance spectra (DRS) of dye-loaded ZnO films incisive the absorption of dye on the mesoporous ZnOsurface. The relative energy band positions of individual and mixed dye, yield stable execution of the cell that has been performed through the cyclic voltammeter. The driving force energy requirement for effortless transport of electron from the mixed dye to the conduction band of ZnO is revealed lowers (0.34 eV) as compared to individual dyes. Electrochemical impedance spectroscopy (EIS) analysis has been executed to find the charge transfer resistance, total bulk resistance, recombination loss through Nyquist plots and Bode plots.These characteristics pretense as the mixed dye has an eminent rate of electron transportation and lower recombination loss with longer electron lifetime. The photon to electrical power conversion efficiencies of purple cabbage, spinach, turmeric and their mix dyes are explored as 0.1015%, 0.1312%, 0.3045%, and 0.602%,respectively under same simulated light condition. The mixed dye reveals the stable performance of the cell withthe highest conversion efficiency due to the absorption of an extensive range of the solar spectrum and wellsuited electrochemical responses.

    • Simultaneous two-sample learning to address binary class imbalance problem in low-resource scenarios


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      Binary class imbalance problem refers to the scenario where the number of training samples in one class is much lower compared with the number of samples in the other class. This imbalance hinders the applicability of conventional machine learning algorithms to classify accurately. Moreover, many real world training datasets often fall in the category where data is not only imbalanced but also low-resourced. In this paper we introduce a novel technique to handle the class imbalance problem, even in low-resource scenarios. Inour approach, instead of, as is common, learning using one sample at a time, two samples are simultaneously considered to train the classifier. The simultaneous two-sample learning seems to help the classifier learn both intra- and inter-class properties. Experiments conducted on a large number of benchmarked datasets demonstrate the enhanced performance of our technique over the existing state of the art techniques

    • Solving the shortest path problem in an imprecise and random environment


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      This paper considers a shortest path problem in an imprecise and random environment. The edges in the network represent the approximate time required to cover the distance from one vertex to another vertex while the traffic conditions change randomly for each edge. The approximate time has been defined by using trapezoidal fuzzy number whereas the traffic conditions has been defined in linguistic term. Such type of network problem can be called as Fuzzy Stochastic Shortest Path Problem (FSSPP) in imprecise and random environment. In order to solve the model, a method has been proposed based on the Dijkstra’s algorithm and some numerous example have been solved to present its effectiveness

    • Surface pressure and viscous forces on inclined elliptic cylinders in steady flow


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      Surface pressure characteristics of elliptic cylinders of various thicknesses and orientations are investigated in steady flow regime. A stabilized finite-element method has been used to discretize the conservation equations of incompressible fluid flow in two dimensions. The Reynolds number, Re, is based on the major axis of cylinder and free-stream speed. Results have been presented for Re<=40 and 0° <=a<=90°, where a is the angle of attack. Cylinder aspect ratios AR considered are 0.2 (thin), 0.5 and 0.8 (thick). It is found that adecrease in AR does not significantly alter the location of minimum surface pressure for a = 90°, but the value of minimum pressure decreases sharply, resulting in severe adverse pressure gradient. In contrast, for a = 0°, thelocation travels towards the base and the minimum pressure increases, leading to delayed flow separation. In general, the magnitude of forward stagnation pressure at low Re is smaller than the maximum pressure for AR°0:5. The maximum pressure occurs at the forward stagnation point as the Re and AR increase. However, in most cases, the locations of forward stagnation and maximum pressure points differ even when the pressure coefficients are very close to each other. The forward stagnation and maximum pressure coefficients of an elliptic cylinder decrease monotonically with increasing a. The drag of a circular cylinder in most cases exceeds the ones obtained for elliptic cylinders. With increasing AR, the drag increases approximately linearly for smalla, lift decreases approximately linearly and moment decreases non-linearly. For a thick cylinder, while the effect of Re on lift and moment is insignificant, the drag shows a strong dependence. Roughly a = 20° for Re = 40 flow represents a critical angle of attack below which a cylinder of AR<=0:5 acts like a streamlined body and above, like a bluff body.

    • An analytical investigation of pressure-driven flow and heat transfer of a Sisko fluid flowing through parallel plates with viscous dissipation


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      Pressure driven flow of a Sisko fluid through rectangular parallel plates, having different wall temperatures is investigated considering the effect of viscous dissipation. The nonlinear momentum and energy conservation equations are solved employing homotopy perturbation method (HPM) and analytical solutions for the velocity, flow rate and temperature distributions are obtained. The analytical solution of pressure-driven flow and heat transfer characteristics of Sisko fluids flowing through parallel plates, taking into account viscousdissipation effect, has not been addressed earlier. For a special case of a typical Sisko fluid, the HPM solution exhibits an excellent agreement with the exact solution. Effects of various parameters such as Sisko fluid parameter, non-Newtonian index and Brinkman numbers on the variation of velocity and temperature are discussed. Further, temperature distribution in flow of Sisko fluids through parallel plates with both the plates maintained at same temperature is also obtained by a suitable substitution in the expression for temperaturedistribution. It is observed that the velocity decreases significantly with an increase in Sisko fluid parameter. Temperature of the fluid decreases with an increase in Sisko fluid parameter and displays an increasing trend with an increase in Brinkman number. Results of the present study are useful for designing thermal systems handling polymer flows. For the typical case of two plates having same temperature, the maximum temperature is observed to occur at the centre, which is attributed to the effect of viscous dissipation acting as an internal source. The theoretical framework developed and analytical solution provided for the problem under consideration may be taken as benchmark result for validation of future work

    • Research on optimal values of contrast revealing coefficient in road tunnel lighting


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      Based on the perceived contrast method in road tunnel lighting, Commission Internationale de l¢Eclairage (CIE) defined the contrast revealing coefficient qc. The research report CIE 189-2010 recommended that contrast revealing coefficient qc was one of the indicators of tunnel lighting quality evaluation system. Many studies suggested that the value of qc was 0.6 under counter-beam lighting in tunnel lighting threshold zone. The value of contrast revealing coefficient was 0.2 under symmetric lighting. However, no studies have recommended the optimal value of contrast revealing coefficient under different lighting systems. The optimal value of contrast revealing coefficient was closely related to visual efficacy and driving safety in road tunnel lighting. Based on the range values of contrast revealing coefficient and visual efficacy experiment, this paper aimed to study the optimal values of contrast revealing coefficient under different lighting systems. The research results were as follows: the optimal value of contrast revealing coefficient qc was 0.20 under symmetric lighting and theoptimal value of qc was 0.85 under counter-beam lighting. The optimal value of contrast revealing coefficient was 0.17 under pro-beam lighting.

    • Distributed synthesized association mining for big transactional data


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      Data is increasing rapidly day by day along with the transactional database. Dividing this data and storing it in a distributed manner is an effective way for storage and retrieval. Mining such distributed data with minimum dependence between sub-problems is a crucial task. Finding frequent itemsets and corresponding association rules is a big challenge while considering the aggregation in a distributed environment. To overcome these challenges, we propose a distributed frequent itemset generation and association rule mining algorithm using MapReduce programming model. The proposed scheme generates frequent itemset and mine association rules using a synthesized distributed technique. The rules are mined in a distributed manner, and then weights are assigned to subsets of data and association rules. A proper mixture of association rules that are generated in distributed manner is done using a weighted approach. This paper presents a novel MapReduce-based synthesisapproach, which can work well over a distributed storage of large amount of data.

    • Automatic categorization of web text documents using fuzzy inference rule


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      The digital world is flooded with a huge number of documents belonging to multifarious categories. Most of these documents are uncategorized, which is a hindrance to efficient retrieval. In the case of news texts (one of the largest and most common sources of text information), it is often observed that a text does not belong to one particular category and has contents from multiple domains. This demands a text categorization system to segregate it into its respective domains for efficient information retrieval. The main challenge lies in handlingthe overlap of vocabulary among different domains at the time of categorization, which we have tackled using an approach based on fuzzy logic. In the present work a fuzzy rule inference system is presented, which works with newly proposed statistical features for segregating documents that belong to more than one or an undefined category. The generated model was defuzzified using five different techniques for determining the category of a document and the highest accuracy of 98.63% for the Centroid method was obtained. Experimentation was alsocarried out on standard English datasets (Reuters-21578 R8 and 20 Newsgroups). We obtain better results than those of reported works, thereby pointing to the language independence of our system

    • Investigations on microstructural and microhardness developments in sintered iron–coal fly ash composites


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      The present work is aimed to explore the microstructural and mechanical characteristics of coal-fly ash reinforced iron metal-matrix composites (IMMCs), synthesized through powder metallurgy technique. Coalfly ash wt%, compacting load and sintering temperature were considered as the input variables, whereas sintered density and microhardness of the composites were taken as the output responses. Flowability and compressibility of the starting materials were demonstrated using Hausner ratio and Carr’s index. Decorous morphological,crystallographic and elemental characteristics of the starting materials and IMMCs were deliberated using Scanning electron microscopy, X-ray diffraction and Energy-dispersiveX-ray spectroscopy investigations respectively. A significant improvement in the microhardness of IMMCs by 50% and drop in density by 35% were found at 15 wt% as compared to 0 wt% reinforcement. The substantial increase in the microhardness eventually resulted in an increase in their specific microhardness by a factor of two. Significant improvements inthe microhardness of IMMCs at 15 wt % of reinforcement, compacted at 10 ton and sintered at 1150°C were found to be prompted by the strengthening mechanisms like load transfer, Hall–Petch effect and Taylor strengthening. The analytically calculated microhardness in the light of strengthening mechanisms was found smaller than the corresponding experimental values as a function of wt % of reinforcement. Further, statistical analysis of the obtained results was carried out using response surface methodology

    • Moth Monarch Optimization-Based Deep Belief Network in Deception Detection System


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      Deception is the action of causing a person to believe something, which is known to be lying with the provision of evidence to support such false beliefs with certain intensions. Identification of the deceptive characteristics manually is a challenging problem for the researchers. Thus, an automatic deception detector is necessary to be developed in order to ensure higher accuracy. Accordingly, this paper proposes a novel deception detector method called Moth Monarch optimization-based Deep Belief Neural Network (MMODBN). The proposed MMO-DBN classifier undergoes the phases of feature extraction and classification. Initially, the input speech signals are pre-processed to remove the noise present in the signal and subjected to feature extraction to extract the significant features, such as Mel Frequency Cepstral Coefficients (MFCC), Spectral Kurtosis, Spectral Spread, Spectral Centroid, minimum blood pressure, maximum blood pressure,respiration rate, and Tonal Power Ratio. Then, these extracted features are subjected to classification using Deep Belief Neural Network (DBN), which is trained with the proposed Moth Monarch optimization (MMO) algorithmthat is the integration of Monarch Butterfly Optimization (MBO) and Moth Search (MS) algorithm. The performance of the proposed MMO-DBN is analyzed using the metrics, namely accuracy, sensitivity, and specificity. The proposed method obtained the higher accuracy, sensitivity, and specificity of 0.984, 0.9836, and0.9375, respectively that shows the superiority of the proposed MMO-DBN in deception detection.

    • Efficient deep learning techniques for the detection of phishing websites


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      Phishing is a fraudulent practice and a form of cyber-attack designed and executed with the sole purpose of gathering sensitive information by masquerading the genuine websites. Phishers fool users by replicating the original and genuine contents to reveal personal information such as security number, credit card number, password, etc. There are many anti-phishing techniques such as blacklist- or whitelist-, heuristicfeature-and visual-similarity-based methods proposed as of today. Modern browsers adapt to reduce the chances of users getting trapped into a vicious agenda, but still users fall as prey to phishers and end up revealing their secret information. In a previous work, the authors proposed a machine learning approach based on heuristic features for phishing website detection and achieved an accuracy of 99.5% using 18 features. In this paper, we have proposed novel phishing URL detection models using (a) Deep Neural Network (DNN), (b) Long Short-Term Memory (LSTM) and (c) Convolution Neural Network (CNN) using only 10 features of our earlier work.The proposed technique achieves an accuracy of 99.52% for DNN, 99.57% for LSTM and 99.43% for CNN. The proposed techniques utilize only one third-party service feature, thus making it more robust to failure and increases the speed of phishing detection.

    • Experimental study on mechanical properties of Ni/TiO2 FGM processed by pressureless sintering technique


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      In the present work, an experimental investigation and characterization of Functionally Graded Materials (FGMs) is carried out. The Nickel (Ni) and Titanium dioxide (TiO2) materials are taken as principal materials and the powder metallurgy technique is used for the preparation of specimens. The Nickel powder has a particle size of 20 lm with more than 99% purity and Titanium dioxide powder having 35 lm particle size with more than 99% purity is used for this study. The FGM specimens are prepared with five layers, with pureNickel on one side and pure Titanium dioxide on opposite side of the specimen; and the three intermediate layers comprising of mixture of Nickel and Titanium dioxide. The five layered FGM samples are prepared with one inch diameter round die and the compacted samples are heated up to 1200°C in an inert gas (argon) atmosphere. The microscopic result shows that the microstructure of Ni/TiO2 FGM has varied layer-by-layer and the interface between the layers are observed. As a part of mechanical characterization, both green and sinteredFGM sample densities are measured for each layer of the sample. The Rockwell hardness test method is used to find the hardness of the each layer in the samples. Linear shrinkage of the specimen is calculated with the help ofgreen sample dimensions. The Compression test is conducted on the sintered specimens by using universal testing machine; stress-strain behaviour and maximum stress reported.

    • Cylindrical air spaced high gain dielectric resonator antenna for ultra-wideband applications


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      A new geometry of ultra-wideband (UWB) hollow dielectric resonator antenna (DRA) has been designed, simulated, and fabricated. The antenna consists of a rectangular dielectric resonator and excited by a transformer type microstrip feedline. A hollow cylindrical-shaped structure is extracted from a rectangular DR to improve the gain and impedance bandwidth of the antenna. The present work shows that the shifting within the UWB range along with the gain enhancement is observed by increased diameter of the hollow structure and the use of defective ground structure in the ground plane. The antenna provides four different radiating modes, namely TE11d at 3.8 GHz, TE22d at 6.4 GHz, TE231Z at 8.8 GHz, and TE33d at 10 GHz that support to give widen impedance bandwidth. The simulated and measured results are in good agreement as an impedance bandwidth of 104.09% (3.28 to 10.4 GHz) and 103.86% along with a peak gain of 7.2 dB.

    • Fault-tolerant topology with lifetime optimization for underwater wireless sensor networks


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      Recently, underwater wireless sensor networks were proposed to explore underwater environment for scientific, commercial and military purposes. However, the limited energy of nodes is a challenge for underwater wireless sensor networks. To prolong the lifetime of battery-limited underwater wireless sensor networks, in this paper, a fault-tolerant topology that can effectively extend the network lifetime is proposed. Initially, the influence of node residual energy and load on node lifetime is analysed. Later the lifetime model ofunderwater wireless sensor networks is established, and the value range of node load adjustment coefficient satisfying network lifetime is obtained. Finally, the scale-free fault-tolerant evolution model with network lifetime optimization is built based on node residual energy and load case. In addition, simulation experiments are performed to validate performances of the new topology generated by the evolution model built. The results show that the new topology structure can balance the energy consumption of the nodes and prolong the network lifetime effectively, and has good fault tolerance

    • Molecular-dynamics-based characterization and comparison of the radiation damage properties of three polytypes of cubic BC3


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      Boron (B10)-based materials such as boron carbide (B4C) are used in control rods of the nuclear reactors because of their high neutron capture cross section and resistance to thermal and chemical degradation. There is an interest to consider other materials that may serve this purpose. In particular, boron-doped diamonds are prospective candidates as they are known to have excellent mechanical strength. In this work, molecular dynamics (MD) simulations are used to characterize and compare the basic radiation damage properties ofboron-doped diamond with the stoichiometric formula BC3. Only cubic structures of BC3 were considered since the experimentally synthesized structure (as per existing literature) was cubic. The basic radiation damage properties compared include threshold displacement energy, primary damage and defect cluster analysis. In addition, the propensity of the material to amorphize under radiation (RIA – radiation-induced amorphization) was also analysed. It was found that the three materials had very similar threshold displacement energies andhence responded to radiation damage in an identical manner. Furthermore, it was seen that none of them were as favourable as the commonly used B4C, as all of them amorphized at lower doses. Consequently, it is concludedthat BC3, while having excellent mechanical properties, may not have good radiation resistance.

    • An improved ant-based algorithm based on heaps merging and fuzzy c-means for clustering cancer gene expression data


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      The microarray technology enables the analysis of the gene expression data and the understanding of the important biological processes in an efficient way. We have developed an efficient clustering scheme for microarray gene expression data based on correlation-based feature selection, ant-based clustering, fuzzyc-means algorithm and a novel heaps merging heuristic. The algorithm utilizes the feature selection algorithm to overcome the high-dimensionality problem encountered in bioinformatics domain. Based on extensive empiricalanalysis on microarray data, clustering quality of the ant-based clustering algorithm is enhanced with the use of fuzzy c-means algorithm and heaps merging heuristic. The performance of the proposed clustering scheme iscompared with k-means, PAM algorithm, CLARA, self-organizing map,hierarchical clustering, divisive analysis clustering, self-organizing tree algorithm, hybrid hierarchical clustering, consensus clustering, AntClass algorithm and fuzzy c-means clustering algorithms. The experimental results indicate that the proposed clustering scheme yields better performance in clustering cancer gene expression data.

    • Application of temporal moments to interpret solute transport with time-dependent dispersion


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      Temporal moments of solute transport through porous media are calculated to analyze the time average spatial distribution of solute plume. Simulation of spatially and temporally distributed breakthrough curves (BTCs) is computationally rigorous and lacking the explanation about overall plume evolution within porous media. However, temporal moment provides an attractive and simple solution to study the plume behavior. In this study, temporal moments are presented to interpret solute plume behavior in heterogeneous porous media such as hydraulically coupled stratified porous media with different time-dependent dispersion models. Governing equations of solute transport have been solved numerically using Crank-Nicolson scheme,and further solute concentration data has been utilized to calculate moments of solute concentration using numerical integration. The effect of various parameters such as mass-transfer coefficient, pore-water velocity, time-dependent dispersion coefficients, and porosity of mobile region on the transport of solute has been studied through sensitivity analyses. Temporal moment analysis revealed that the mass recovery, mean residence time,and variance are sensitive to the estimated parameters. Numerical results suggested that the asymptotic timedependentdispersion function with mobile–immobile model represents the plume spreading through heterogeneous porous media in a more realistic manner

    • Investigation of electromagnetic torque production in induction motor during charging operation


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      Integrated battery chargers (IBCs) provide the flexibility of reusing the electric drive-train components of the electric vehicle (EV) for the charging operation. The purpose of the paper is to reuse its traction inverter and motor windings as rectifier and grid interfacing filter, respectively for charging and keeping rotorstandstill without using any external brake. Various winding configurations are developed by splitting the threephase induction motor (IM) winding into two parts at zero electrical degree to keep the rotor standstill. The different stator winding connections are proposed for IM which restricts the formation of rotating magnetic field (RMF). Cases are categorized into two parts, in the first part, RMF is cancelled to zero and in the other part, RMF is converted into pulsating magnetic field (PMF). Mathematical investigation for torque production in bothcases is provided to prove that the proposed winding connections are incapable of developing electromagnetic torque in machine. Mathematical findings are validated by experimentation on split three-phase IM (STP-IM). This analysis is useful in identifying the nature of torque developed in motor during charging operation of EV.

    • The effect of slot dimensions and its vertical and horizontal position on the scour around bridge abutments with vertical walls


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      Scouring is one of the major threats to the stability of bridge abutments constructed over rivers. The present study investigated the usefulness of abutment slots in reducing the scour depth around bridge abutmentswith vertical walls, experimentally. Nine experiments with no slot and hundred experiments with slots were conducted in clear water conditions. Four subcritical flow conditions (Froude number less than 1) were investigated. For each flow condition, 25 different slot models having different sizes, and vertical and horizontal positions were considered. The results indicated that the slots having heights equivalent to half of the flow depth are more effective in reducing scouring if they are located closer to the bed. Increasing the slot height improvesthe performance. The best performance is achieved when the slot begins from the water surface and extends below the bed (equal to the scour depth in the model without the slot). Further, the results showed that the greater the distance of the slot is from the abutment nose and closer it is to the channel wall, the more effective the slot would be. Therefore, the most effective slot model is the model in which the slot height equals the distance from the water surface to below the bed, and when it is attached to the channel wall. For different slot models, in different flow conditions, the percentage of reduction of scour depth varies from 20 to 100%.

    • Investigation of process parameters in electroless copper plating on polystyrene


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      There is a requirement of imparting conductivity to the surface of polystyrene for making various lightweight millimeter wave components. Researchers have worked on the plating of ABS material but there is very less work carried out on Polystyrene. This work has been carried out to make the surface of polystyreneconductive by electroless plating of copper on polystyrene followed by electroplating of copper. The acceleration process was added for increasing the acceptability of copper ions on etched surface. Test samples have successfully qualified rigorous grind saw test for checking adhesiveness of the plating layer. The samples were studied using a scanning electron microscope for the analysis of the morphology of the plated layer. Regression analysis of the different parameters was done for establishing the interrelation between the parameters. The results show that the achieved electroless plating on polystyrene is compact and continuous

    • The distribution and percentiles of channel capacity for multiple arrays


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      We show that channel capacity of N-transmitter M-receiver antenna systems is approximately normal for both Raleigh fading and Ricean environments whether or not antennas are correlated. We give the distribution and percentiles of capacity as a power-series in (MN)-1/2 when M or M/N is fixed, both for the case of fixed total power transmitted and also for the case, where total power transmitted increases with N.

    • An intruder defense model for the detection of power grid disturbances in wireless network


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      Cyber security has to gain a high level of awareness in the Network and Computer pasture due to the large spread of information transmission technology. A powerful False Data Injection (FDI) Intruder monitors the network activities and injects the malicious data thereby causing failure in the power system. To overcome this defense, the ‘‘Conviction based Intruder Defense Model’’ is proposed to identify and isolate it from the network by providing secure transmission. This scheme operates in three phases. In the first phase, thedata are analyzed with the library files to identify the conviction values. Based on the conviction values the resulting factors are analyzed with different iterations and the suspicious drafts are identified and classified using Fuzzy Intrusion Detection System (FIDS) divider. In the second phase, three algorithms are used to organize the drafts categorized. In the third phase, abnormal nodes are isolated from the network. Experimental results show higher accuracy and detection rates with low false positives.

    • Experimental investigation on the filtration characteristics of a commercial diesel filter operated with raw and processed karanjadiesel blends


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      With soaring fuel prices, engine emissions, and demand for energy security, the development of alternative fuels from renewable resources has become significant. The current work explores the filtration performance of a commercial diesel filter operated with diesel blends of raw and processed karanja oils. Threeprocesses viz. esterification, transesterification, and degumming were performed with karanja oil, and their diesel blends (20% v/v) were tested in a continuous run filtration system. The fuel filter plays a significant role in removing the contaminants/impurities from the fuel. Hence, the pressure difference across the fuel filter was monitored at the flow rates (0.03 m3/h and 0.075 m3/h) and fuel temperatures (30°C and 70°C). Besides, the effects of weight gain and surface morphology on the filter characteristics were observed during the study.Further, the head loss factors of fuel filter under varying operating conditions were deduced from the experimental measurements. The results of different processed oil blends were compared with fossil diesel to find the suitable blend. By considering the fossil diesel as the reference case, the average pressure difference for the degummed blends was significantly lower compared to other tested blends, which highlights the importance of the degumming process. Furthermore, the tested images of filter revealed the presence of minor components such as sludge or gums on the filter surface for the fuel without the degumming process.

    • Estimation of scour depth around cross-vane structures using a novel non-tuned high-accuracy machine learning approach


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      Due to the vital role of rivers and canals, the protection of their banks and beds is critically important. There are various methods for protecting beds and banks of rivers and canals in which ‘‘cross-vane structures’’ is one of them. In this paper, the scour hole depth at the downstream of cross-vane structures withdifferent shapes (i.e., J, I, U, and W) is simulated utilizing a modern artificial intelligence method entitled ‘‘Outlier Robust Extreme Learning Machine (ORELM)’’. The observational data are divided into two groups: training (70%) and test (30%). After that, the most optimal activation function for simulating the scour depth at the downstream of cross-vane structures is selected. Then, using the input parameters including the ratio of the structure length to the channel width (b/B), the densimetric Froude number (Fd), the ratio of the differencebetween the downstream and upstream depths to the structure height (Dy/hst) and the structure shape factor f eleven different ORELM models are developed for estimating the scour depth. Subsequently, the suitable modeland also the most effective input parameters are identified through the conduction of an uncertainty analysis. The suitable model simulates the scour values by the dimensionless parameters b/B, Fd, Dy/hst. For this model, thevalues of the correlation coefficient (R), Variance accounted for (VAF) and the Nash-Sutcliffe efficiency (NSC) for the suitable model in the test mode are obtained 0.956, 91.378 and 0.908, respectively. Also, the dimensionlessparameters b/B, Dy/hst. are detected as the most effective input parameters. Furthermore, the results of the suitable model are compared with the extreme learning machine model and it is concluded that the ORELM model is more accurate. Moreover, an uncertainty analysis exhibits that the ORELM model has an overestimated performance. Besides, a partial derivative sensitivity analysis (PDSA) model is performed for the suitable model.

    • Fracture and fatigue study of pervious concrete with 15–20% void ratio


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      Pervious concrete has been increasingly used all over the world to reduce the amount of rain water runoff and improve the water quality near light-traffic-volume pavements and parking lots, but its use in India is a relatively unexplored territory. The use of pervious concrete in high-load roads (HLR) requires a balancebetween the permeability and strength, as increasing the permeability by increasing porosity ends up in reducing the strength. Hence, there is a perceived need for pervious concrete mixture with optimum mechanical and hydraulic properties for use in HLR. In the present study, an attempt was made to determine that combination of aggregate size, water:cement (w/c) ratio and amount of supplementary cementitious material that would provide the best possible hydraulic and mechanical properties. The cement used was 53-grade Ordinary Portland Cement. Results were measured as flexural strength, compressive strength (both measures of mechanical properties), void ratio, porosity and permeability (as three measures of hydraulic properties). The mix with highest compressive strength and void ratio ranging between 15% and 20% was considered optimum and tested for fracture–fatigue. The results indicated that high-strength pervious concrete (i.e., compressive strength 32–45 MPa and flexural strength 3.9–5.29 MPa at 28 days of curing) can be achieved even with void ratio (%) of more than 15%).

    • Development of semi-active mass damper with impulsive reaction


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      A new semi-active mass damper, included active joint to control Lock/Unlock between the mass of damper and structure, is proposed to avoid ‘‘de-tuning effect’’ in this study. A ten-floor shear building with Tuned Mass Damper (TMD) and Semi-Active Mass Damper (SAMD) under excitation of 26 earthquake records is simulated by numerical analysis to compare the shock absorption effects. Analysis results show that: (1) Shock absorption of roof displacement and root mean square (RMS) roof displacement is 9.9%, 15.8% and 67.9%, 70.9%for structure with TMD and SAMD under excitation of Kobe 1995 earthquake respectively. Shock absorption of roof displacement and RMS roof displacement 52.7%, 62.1% and 55.7%, 66.3% for structure with TMD and SAMD under excitation of Sumatra 2007 earthquake respectively. (2) Structural response of building with SAMD controlled is very low sensitivity to frequency ratio. SAMD control effect is better than that of TMD on near fault earthquakes and suitable for far-field earthquakes. Otherwise, SAMD is almost without ‘‘de-tuning effect’’. (3) Shock absorption ratio of the roof displacement responses and RMS displacement responses for structure with SAMD under excitation of far-field earthquake is above 38%and 62%, respectively. The frequency ratio of SAMDcontrolled should be limited to less than 4.0 to avoid enlarging the maximum acceleration responses. The practicability of this proposed SAMD has been verified by numerical analysis

    • Sub-threshold start-up circuit with dynamic body-biasing for boost converters in thermoelectric energy harvesting


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      A 260 mV start-up charge pump and oscillator applying dynamic bulk-biasing (DBB) for step-up converters in thermal energy harvesting is presented and validated through SPICE simulation. This DBB employs a dynamic substrate control circuit (DSCC) directly controlled by the pump clock. It can dynamicallyreduce sub-threshold leakages during off-state and increase conduction during on-state. This is necessary for thermoelectric harvesters with output voltages of <= 300 mV. Performance of this DBB start-up circuit is compared to those of conventional reverse and forward bulk-biasing charge pumps. According to simulated results using the TSMC180 nm CMOS model, DBB reduces kick-start voltage to 225 mV. This proposed circuit has a 1.44x–52x better overall figure-of-merit (FOM) compared with conventional circuits at a supply voltageof 260 mV. It can generate 50 lW of maximum power with an unregulated output of 2.5 V within 171 ls from cold start-up. This overall improvement in speed, power and pumping efficiency facilitates battery-less solutions in biomedical applications for wearable/implanted micro-devices

    • Testing and debugging: an empirical evaluation of integrated approaches


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      Software development is a continuous process. Among all phases of software development, testing and debugging are the most essential phases. The main intention of testing is to detect maximum faults as soon as possible. After a fault is detected, it must be removed through appropriate debugging approach. Both phases are performed one after another and require different information. Hence, it is arduous to merge them. In fault detection, such test cases are required that are able to detect all the faults with less effort whereas in faultlocalization such test cases are required that are able to reproduce faults and locate them with accuracy. For enhancing the performance of testing, the integration of these two phases with consideration of multi-objective selection of test cases is to be conducted before regression testing. In the current work, an approach for multiobjective test case selection based on statement and diversified mutant coverage has been proposed and compared with existing approaches. For empirical study, SPEA-2, NSGA-2 and VEGA algorithms have been used and experiments were conducted on three applications of the Defects4j database. Outcomes of the study specify that the proposed approach has the ability to detect more faults compared to existing approaches. It is also able to locate all faults that have been detected with fault localization score better or comparable to existing approaches.

    • Comparative analysis of new improved force split-teeth Linear Switched Reluctance Motor for high speed transit systems


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      Linear Motors forms an integral part of propulsion systems used in linear motor propelled highspeed transport systems. Generally, motors such as linear induction and linear synchronous are preferred worldwide for these applications. In spite of showing the immense capabilities, linear switched reluctance motor(LSRM) is still under research for applications in high-speed systems. This paper focuses on a LSRM with enhanced propulsion force for the application in high-speed transportation systems. It has a linear structure with moving translator for direct force transmission and two-teeth in each stator pole to attain better force performance.In the proposed motor, translator teeth count is more as compared to the stator teeth count. A 6/16 LSRM with three- phase split-teeth stator has been proposed. The performance of the proposed 6/16 LSRM has beencompared with 6/4 and 6/8 three-phase conventional motors to highlight the improvements in the proposed motor. The paper also modifies the proposed 6/16 LSRM into 12/32 configuration to analyse its force ripple reduction capability. The performance of the 6/16 is compared with the 12/32 LSRM. All the motors aremodelled and analysed in 3D with the help of finite-element analysis (FEA). The paper optimizes the 6/16 LSRM using parameter based cumulative deterministic optimization algorithm (PBCDOA) to maximize its propulsion force. The FEA based analysis shows better force performance for the proposed motor.

    • A Comparative analysis for identification and classification of text segmentation challenges in Takri Script


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      Takri is an Indian regional class of scripts, used in hilly areas of north-west India which include Jammu and Kashmir (J & K), Himachal Pradesh (H.P.), Punjab and Uttarakhand. This script has immense variations; almost 13 identified in the whole region of North-west India. It has been observed that no work for text identification and recognition of Takri script has been done so far. Therefore, our work focuses on identifying and classifying the various challenges in the script based on comparative analysis of existing text segmentation approaches, as correct segmentation of text leads to more accurate machine recognition. As there were no metal fonts available for the script, it is required to collect the machine-printed form of data for solving the text identification problem in Takri script. The paper surveys for different text segmentation approaches andbased on the structural properties of the script, shows an implementation of these on Takri data in three steps-Gurmukhi segmentation technique, Connected Component segmentation approach, and Gurmukhi touching characters segmentation approach. Results are analyzed for Segmentation Accuracy and Challenges are identified along with their statistical analysis. Further, the challenges identified as half- forms, numerous types of touching characters, overlapping bounding boxes, are classified. The effectiveness of these challenges was evaluated using Naı¨ve-Bayesian machine learning algorithm. The results showed 80% accuracy in text identification and classification of Takri script.

    • Process parameters selection in manufacturing of sharp conical parts based on Taguchi design of experiments


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      Among the sheet metal forming processes, hydrodynamics deep drawing and hydromechanical deep drawing process are two main types of the deep drawing process that can fabricate complicated parts. In the hydroforming process, the blank is formed to the desired shape by applying a considerably high hydraulicpressure. In this article, the selection of the process parameters will be investigated during the manufacturing of a pure copper sharp conical part by finite element analysis and experimental tests. Two finite element models aredeveloped for hydrodynamics deep drawing and hydromechanical deep drawing processes. After verification of the FE model by experimental results, the effect of process parameters includes the applied pressure, friction coefficient, die radius and blank holder force on thinning of the blank are investigated. The thinning ratio of blank is calculated in different zones of the conical part under different working conditions determined according to the Taguchi design of experiment methods. Signal to noise ratio analysis has been carried out and the influence of process parameters on the thinning ratio is determined at different zones of the conical part. The results show that the friction coefficient has an important role in the thinning of the conical nose while at the lateral surface of the cone, the die radius is the most effective parameter on the thinning ratio. The results showthat by implementing statistical tools (Taguchi method and signal to noise ratio analysis), it is possible to select the proper process parameters conditions and fabricate defect-free parts. In addition, a non-linear regression equation is developed for prediction of thinning ratio in the hydrodynamics deep drawing and hydromechanical deep drawing processes.

    • NavIC performance over the service region: availability and solution quality


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      Navigation with Indian Constellation (NavIC) is designed and deployed by Indian Space Research Organization (ISRO) as an indigenous, regional navigational system to provide precise PVT information over the Indian region and surrounding areas. This paper presents a detailed analysis of NavIC visibility under open sky and constrained condition over the service region using an in-house developed simulation tool, the effects of NavIC satellite geometry on single-point solution accuracy and NavIC single and dual frequency solutionperformances. The results show the potential of NavIC as an alternative navigation system for India and the neighbouring countries in south and south-east Asia, and over an economically important area containing majorsea-routes. Even in constrained-visibility conditions, NavIC with its typical constellation design can offer seamless navigation solution over a large region of the globe; the unique S-Band NavIC signal supports enhanced accuracy for stand-alone operation. The results would be beneficial for understanding the potential of NavIC for the user community.

    • A methodology for designing cutting drum of surface miner to achieve production of desired chip size


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      The size of coal chips, produced during coal cutting operations, is of prime importance from the viewpoint of feed size desired by power plants. Proper chip size in cutting can eliminate primary crushing and in-turn save energy. Achieving a designated size of chip is intimately linked with the drum design inter alia thewrap angle, line spacing of picks and pick size. Operating parameters namely cutting speed and drum speed also influence the output. Considering the increased need to produce a sized product for cost-effective mining, adesign methodology was developed to achieve a required chip size for surface miners with a middle drum configuration. Various pick, drum and operational parameters were taken into account for the development ofdrum design, namely drum width, drum diameter, pick size, clearance angle, rake angle, cutting angle, lacing pattern, angle of wrap, depth of cut, indented depth of cut and pick spacing. Limiting factors for drum design such as the number of picks, pick temperature, strength of pick, depth of cut and dust generation were discussed. A new drum configuration for achieving 100 mm chip size was validated which showed close agreement with the output produced using 2200SM model surface miner

    • Multi-objective optimization in geometric design of tapered roller bearings based on fatigue, wear and thermal considerations through genetic algorithms


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      To improve the fatigue, wear and thermal based failures of Tapered Roller Bearings (TRBs) a multi-objective optimization technique has been proposed. Objective functions considered are: the dynamic capacity (Cd) that is related to fatigue life, the elasto-hydrodynamic minimum film thickness (hmin) that isassociated to the wear life, and the maximum bearing temperature (Tmax) that is related to the lubricant life. This paper presents a non-linear constrained optimization problem of three objectives with eleven design variables and twenty-eight constraints. The said objectives have been optimized individually (i.e., the single-objective optimization) and concurrently (i.e., the multi-objective optimization) through a multi-objective evolutionary procedure, titled as the Elitist Non-dominated Sorting Genetic Algorithm. A set of standard TRBs have beenselected for the optimization. Pareto-optimal fronts (POFs) and Pareto-optimal surfaces (POSs) are obtained for one representative standard TRB. Out of many solutions on the POFs/POSs only the knee-point solution hasbeen shown in a tabular form. Life comparison factors have been calculated based on both the optimized and standard TRBs, and results indicate that the optimized TRBs got enhanced lives than standard bearings. To get the graphical impression of optimized TRBs, a skeleton of radial dimensions of all seven optimized bearings based on various combinations of objectives has been shown for one of the representative standard TRB. In few cases the multi-objective optimization has better convergence as compared to single objective optimization due to its inherent diversity by the principle of dominance. The sensitivity investigation has also been conducted to observe the sensitivity of three objectives with design variables. From the sensitivity analysis data, toleranceshave been provided for design variables. These tolerances could be used by the manufacturing industry while producing TRBs

    • PAM: process authentication mechanism for protecting system services against malicious code attacks


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      The kernel of the modern operating system fails to ensure the authenticity of a running process while servicing a system call. Verifying the origin and integrity of a system call is an important security issue in terms of ensuring the proper functioning of an end-system. The conventional process identification parameterssuch as process identifier, process names and the executable flow exercised by the operating system are not reliable. As a result, a stealthy malware may mimic other processes to carry out many computer crimes, thus compromising the end-system. In this paper, we present a novel idea in which system call invocations made by a malicious application are verified during runtime in Windows operating system. To ensure the authenticity of a process while servicing a system call, we propose a behavior-based mechanism, namely, the process authenticationmechanism (PAM), for combating malicious code attacks that verifies the identity of each suspected process before being serviced by the kernel. The simulation and performance evaluation results confirm that our mechanism can effectively block all malicious samples that directly invoke system services in the kernel mode. PAM incurs no more than two percent overhead and helps to strengthen the overall system security.

    • Sentiment classification with GST tweet data on LSTM based on polarity-popularity model


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      One of the biggest issues of Indian economy in 2017 was the implementation of Goods and Services Tax (GST), and the social networks witnessed a lot of opinion contrasts and conflicts regarding this new taxation system. Inspired by such a large-scale tax reformation, we developed an experimental approach to analyze the reactions of public sentiment on Twitter based on popular words either directly or indirectly related to GST. We collected a number of almost 200 k tweets solely about GST from June 2017 to December 2017 in two phases.In order to assure the relevance of our crawled tweets with respect to GST, we prepared a topic-sentiment relevance model. Furthermore, we employed several state-of-the-art lexicons for identifying sentiment words and assigned polarity ratings to each of the tweets. On the other hand, in order to extract the relevant words that are linked with GST implicitly, we propose a new polarity-popularity framework and such popular words were also rated with sentiments. Next, we trained an LSTM model using both types of rated words for predictingsentiment on GST tweets and obtained an overall accuracy of 84.51%. It was observed that the performance of the system has been started improving while incorporating the knowledge of indirectly related GST words during training.

    • Volumetric shrinkage estimation of benchmark parts developed by rapid tooling mold insert


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      This paper estimates the volumetric shrinkage for thermoplastic Polypropylene (PP) injection molded components made using digital Acrylonitrile butadiene styrene (ABS) mold. The parameters affecting volumetric shrinkage for the digital ABS mold are mold temperature and injection temperature, cooling time,hold pressure and injecting speed. Therefore, twelve standard benchmark CAD model were selected with different geometric attributes. Subsequently, simulation analysis was performed on all CAD model using MoldflowÒ (MFA) simulation software. Additionally, regression analysis is applied to identify the effect ofinjection molding parameters on the volumetric shrinkage of part made using rapid tooling mold insert of digital ABS material. It is found that maximum volumetric shrinkage (18.75%) is observed for square pyramid frustum,conical frustum, and solid torus. On the contrary, hollow rectangular prism shows minimum shrinkage effect having 12.61% of volumetric shrinkage. This study predicted that shrinkage is the main concern for these three geometric features (i.e., square pyramid frustum, conical frustum, and solid torus) and must be looked for its minimization. The results are experimentally validated, with 3D scanner integrated with COMET plus and Inspect plus softwares. Since shrinkage estimation for digital ABS mold using Rapid Tooling technique has notbeen attempted before, therefore, this study provides guidance for the optimum parameter selection and assigning suitable shrinkage compensation values for digital ABS mold made using direct rapid tooling

    • Development of an experimental set-up to measure sound absorption coefficients of porous materials


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      This paper discusses the practical aspects of data acquisition and signal processing techniques involved while developing an impedance tube. Microphones, data acquisition systems, set of speakers were carefully selected, calibrated, and assembled as one unit. The raw time signal is acquired through a Virtual Instrument (VI) developed in LabVIEW, and the mathematical equations involved in the process are implemented in MATLAB R 2017a. Important considerations involved in these processes have been thoroughly discussed in the paper. The final results contained outliers that were removed by the application of digital filters. The results obtained from the application of different types of digital filters are shown, discussed, and the best combination of filters has been selected. This combination results in a robust and efficient method with an improved low-frequency response (<250 Hz) which, in a standard commercial impedance tube, was achieved by altering the microphone spacing. The validation was performed by conducting experiments on a blank tube, melamine foam, glass wool, and comparison were made with the result obtained on the set-up of a leading manufacturer, and with the ones reported in works of literature. They show a good match between them which completes the validation.

    • The effects of sharpened tools on tool flank wear–surface roughness and optimization of cutting parameters in milling Vanadis 4E powder metallurgic tool steel


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      Vanadis 4E is a powder metallurgic tool steel that provides an excellent combination of wear resistance and ductility for high-performance tools, and it is more machinable than AISI D2 tool steel. This study applied grooving on Vanadis 4E powder metallurgic tool steel with the dimensions of 80 9 105 9 35 mm, andduring the milling process, investigated the effects of cutting parameters on surface roughness and tool flank wear. Using the Taguchi L9 (34) array, 9 experiments were carried out. In the experiments, uniform carbide end mills with diameters of 12 mm were used as new and sharpened (first usage, first sharpening, second sharpening), and the experiments were performed with three cutting depths (1, 1.5 and 2 mm), three cutting speeds (60, 80 and 100 m/min) and three feed rates (0.02, 0.04 and 0.06 mm/tooth). During the experiments, temperature measurements were made with a thermal camera from the cutting area, and surface roughness and tool wear measurements were made after every one experiment. The cutting parameters were optimized by using theobtained roughness and flank wear values, and the results were analyzed by signal-to-noise ratios, analysis of variance (ANOVA), three-dimensional graphs and thermal images. After optimization, three confirmation experiments were conducted by using the optimum parameters, and the values that were estimated with the Taguchi method and the results of the verification experiments were compared.

    • Evaluation of dynamic SIF during crack propagation in layered plates having property variation along the crack front


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      The present study emphasizes understanding the crack propagation in layered structures under dynamic loading conditions when the property jumps occur across the crack front. Layered plates were made by joining polymethylmethacrylate (PMMA) and epoxy sheets using an epoxy-based adhesive (Araldite). Single edge notched (SEN) specimens were subjected to dynamic loading using a modified Hopkinson bar setup. An array of strain gauges installed on surfaces of specimen was used to record the strain history in the layers during crack propagation from which the dynamic stress intensity factor (SIF) during crack propagation was evaluated. Photographs of the propagating crack front were also simultaneously captured using a high-speed imagingcamera to obtain the crack tip location history in each layer

    • Powder-mixed electro-discharge machining performance of Inconel 718: effect of concentration of multi-walled carbon nanotube added to the dielectric media


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      The present work reports an experimental investigation on Powder-Mixed Electro-Discharge Machining (PMEDM) of Inconel 718 superalloy using Multi-Walled Carbon Nanotubes (MWCNTs) dispersed in kerosene, as dielectric media. Effects of variation of peak discharge current along with concentration of carbon nanotubes in the dielectric fluid are studied in purview of machining performance indicators including material removal efficiency, tool wear rate, and surface integrity of the machined part. The obtained results are compared to that of conventional EDM which utilizes kerosene as dielectric media. Morphology and topography, these two aspects of machined surface integrity are deliberated. The following surface morphological features: uneven fusion structure, globules of debris, molten metal deposition, surface cracks, pockmarks, and recast layer are identified. Topographical study includes surface roughness, severity of surface cracking, recast layer thickness, transfer of foreign elements, surface metallurgical characteristics, residual stress, and microindentationhardness. It is observed that application of MWCNT mixed dielectric media substantially improves EDM performance of Inconel 718 over conventional EDM. This is due to excellent thermo-physical properties of carbon nanotubes.

    • Improved air-gap flux in axial flux induction machine through shaping of radial slot opening


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      Axial flux machines (AFM) have inherent non-uniform flux density distribution in radial direction leading to improper utilisation of iron part. The objective of this paper is to shape the edges of tooth lamination along radial direction to achieve uniformity in radial flux density distribution using multi-slice analytical approach. The machine considered is an axial flux induction machine (AFIM) with single stator and single rotor. The machine’s core and tooth are laminated perpendicular to each other and the approach makes use of multiple2-D non-linear lumped parameter flux models along the radial direction representing each tooth lamination. For a given magneto-motive force, the laminations provide many parallel paths. Effective air gap length which is afunction of tooth opening is adjusted to level air-gap flux density. The process results in further improvement in net flux per pole. The results of performance enhancement are validated through analytical equations, quasi 3-DFEA, 3-D FEA and a 3 kVA laboratory prototype machine.

    • Metric issues for systems in state space


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      A metric structure is imposed on state space such that solutions to 1st order state variable model of a linear system are geodesics subject to restrictions on the system and input matrices. For linear time invariant systems, a 2nd order state variable model of an extended system to a given 1st order model is derived. The metric is tailored to systems under consideration.

    • Classification of Chronic Obstructive Pulmonary Disease (COPD) Using Electromyography


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      Chronic lung disease, in which the airway gets obstructed, is known as Chronic Obstructive Pulmonary Disease (COPD). According to WHO, COPD kills more than 3 million people every year. Spirometry is used to diagnose COPD; has many limitations. There is a need for physiologically accurate and easy to perform diagnosis technology. Researchers confirmed the activity of sternomastoid muscle in COPD with research limitations of; sample size, few time-domain features, lack of onset detection and the non-stationary nature ofElectromyographical signals (EMG). In this, paper COPD diagnosis is made by analyzing Sternomastoid muscle of respiration in time, frequency and time-frequency domain. The slope-based onset detection algorithm andconduction velocity lead to an improvement in COPD detection accuracy to 98.61%. The feature selection algorithm is developed for the selection of the most significant features. A single frequency Continuous Wavelet Transform (CWT) analysis at 7, 8 and 10 Hz of frequency is used to extract features and to classify COPD in its grades, leading to the classification accuracy of 85.89%. Non-invasive, easy to use COPD diagnosis and classification technique is developed.

    • Design of low-power CMOS transceiver front end for 2.4-GHz WPAN applications


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      This paper describes the design of low-power direct conversion transceiver front end for WPAN (Wireless Personal Area Network) applications using TSMC 0.13 lm CMOS technology. Subharmonic mixers are proposed to mitigate the drawbacks of DC offset problem in direct conversion receiver and injection locking problem in direct conversion transmitter. The receiver front end comprises a low-noise amplifier (LNA), balun and subharmonic mixer. The direct conversion transmitter front end adopts a subharmonic passive mixer, differential to single-ended converter, driver and power amplifier. The post-layout simulation results produce voltage gain of 29 dB, noise figure of 5.84 dB, IIP3 of - 12 dBm and 1.79 mW consumption power for receiver front end at a supply voltage of 0.8 V. The transmitter front end achieves conversion gain of 15 dB, 0 dBmoutput 1-dB compression point (OP1dB) and 4.27 mW power consumption.

    • Experimental and FE analysis for the buckling behavior of hat-stiffened panels under edge compressive loading


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      In this paper, experimental studies on two laminated composite hat-stiffened panels with equally spaced stiffeners have been carried out with application of axial compression load on the panel for the determination of the pre-buckling and post buckling behavior. A non-linear buckling analysis on the hat-stiffenedpanel has also been performed under compression load with application of finite element tool ABAQUS. From strain analysis at different locations, the local buckling of skin has been observed before the buckling of the panel, and a visual damage has been found near the skin-stiffener and debonding skin-stiffener of the panel during failure of the hat-stiffened panel. The compression load-axial displacement curve of the experiments has correlated well with simulated finite element model result for determination of the buckling behavior of thepanel up to the failure load. The out of plane displacement pattern shows that the compressive failure initiated at the edges of the panel and gone to skin-stiffener bonding, and finally failure of the panel occurred due to debonding between skin-stiffener.

    • Investigation of mechanical properties and hot corrosion behavior of friction welded AISI 304 and AISI 1021 steels


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      In the current study, friction welding of two different steels, namely low alloy steel and austenitic stainless steel was done. For conducting welding, an in-house experimental set-up was designed and fabricated. The steels were friction welded by using various axial pressures at a uniform circular speed. Influence of axialpressure on the joint strength of the friction welded specimens such as tension, impact toughness, torsion strength and microhardness were evaluated. Moreover, the weldments were also tested for high temperature corrosion resistance. The corrosion testing of the welded joints was carried out in a molten salt environment of Na2SO4 + V2O5 60% at 650°C. Weight change data were used to establish the kinetics of corrosion. Based upon this data, the weldments showing best corrosion resistance was identified. Subsequently to understand the composition of oxide scale, the specimen was evaluated using SEM/EDS and X-ray diffraction techniques.

    • Photodegradation of Methylene Blue (MB) using Cerium-doped Zinc Oxide nanoparticles


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      Cerium-doped Zinc Oxide nanoparticles were prepared with co-precipitation method. X-Ray diffraction (XRD) analysis shows sharp peaks conforming the crystalline nature of prepared particles. Crystallite size was found from XRD peaks. A Field Emission Scanning Electron Microscope (FESEM) was used to see the particles and hexagonal shape. Spectroscopic properties were studied using a Fourier Transform-Infra Red (FTIR) spectrometer and Raman spectrometer. Optical properties were studied using a Diffuse Reflectance Ultraviolet Visible (DRS UV–VIS), spectrophotometer. Band gap of doped particles reduces as doping concentration increases. Reduced band gap of Cerium doped particles makes them a good catalyst. There are many organic dyes which are used as coloring agents by industries like textile, printing, etc. These industries releaseharm full pollutants into water bodies, which effect human and aquatic life. Prepared Cerium-doped ZnO nanoparticles have proved to photodegrade Methylene Blue. Undoped ZnO nanoparticles decolorized the solution in 210 min with 81.93% efficiency. Ce (0.03 wt%) doped ZnO nanoparticles decolorized the solution in 120 min with 92.62% efficiency.

    • Develop a flux cored wire for submerged arc welding of Ni-Mo low alloy steel


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      Ni-Mo low alloy steel exhibits an admirable amalgamation of high strength and toughness at subzero temperature and show resistance to brittle fracture with good weldability. This steel has been established to fulfill the needs of specific applications, such as the construction of ships and submarines. To develop acompanionable wire for welding of Ni-Mo low alloy steel, the amount of the alloying elements in a wire is increased to toughen of weld metal, the wire itself has high strength so that the wire is hardened at the wire drawing, making the wire production difficult. In order to avoid the problems related to the solid wires, various flux cored wires have been developed. In this work, the effect of flux basicity index and heat input on chemical composition, oxygen-nitrogen analysis, mechanical properties and microstructure of Ni-Mo low alloy steel welded by SAW welding using flux cored wires are presented along with the effect of flux cored wire and basicity index on deposition rate

    • A study on critical order of joints with clearances and its effect on kinematic performance of multiloop planar mechanisms


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      Simulation and study of joint clearances has usually focused on appropriate simulation strategies and their validation against experiments. The effect of joint clearances on the output of a mechanism has been usually evaluated qualitatively. The relative importance of different joints in a mechanism in producing deviation from the output of an ideal mechanism has not been studied. This work identifies the appropriate statistical measure for quantifying this deviation and uses it to rank the joints of one degree of freedom multi-loop planar mechanisms. The inversions of six-bar mechanism have been studied through ADAMS simulations involving different clearance sizes and speed of crank. A trend in clearance location ranking has been identified which canprobably be extended to planar mechanisms of higher complexity.

    • A novel Tag Score (T_S) model with improved K-means for clustering tweets


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      Clustering of tweets is useful for analyzing the attitudes of people towards a particular product. The companies can use this analysis to modify their products to meet the needs of people. Recently, K-means clustering is widely used to cluster the tweets with bag of words as a feature set. The key factors contributing to the quality of clusters and performance of clustering are dimensionality reduction and initial selection of centroids. This paper addresses these issues using a newly proposed Tag Score (T_S) model with improved K-means in which semantically similar features from bag of words are grouped into tags, scores are modified based on sentiment polarity values and the initial centroids are selected with the help of sentiment scores. The performance of the proposed T_S model with improved K-means is compared with T_S model with random K-means and conventional word vectors with random K-means by considering three labeled datasets and three unlabeled datasets. The results show that the proposed method produces significant results in approximately 70% of the cases in terms of purity, F-measure, intra-cluster distance and inter-cluster distance.

    • Optimization of machining parameters during cryogenic turning of AISI D3 steel


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      This research paper depicts the process of used liquid nitrogen at the interface of TiN coated carbide cutting tool insert (rake face) and AISI D3 workpiece. Design of experiments (DoE) was planned according to Taguchi L9 (OA) orthogonal array. The experimental results during machining such as cutting force, machining time and temperature were optimized by Taguchi S/N ratio and analysed by ANOVA. The contribution of machining parameters of (i) speed, (ii) feed and (iii) depth of cut for each response were evaluated. Feed had thehighest effect on the percentage of contribution of 57.21% and 52.21% for cutting force and machining time, respectively. Speed had the highest effect on the contribution as 79.57% for the temperature at the interface ofinsert and workpiece. The predicted values at the optimum level of machining parameters for cutting force, machining time and temperature were 44.49 N, 37.09 sec. and 24.99°C, respectively. Regression models were made. The R-Sq values were 96.59, 89.34 and 96.09% for cutting force, machining time and temperature, respectively. The ratio of an average thickness of generated chip and feed was considered as the chip compression ratio. It was observed that the generated chips during cryogenic turning were thin, discontinuous, long snarled and most of the material had side flow on either side.

    • Chronological-brain storm optimization based support vector neural network for sentiment classification using map reduce framework


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      Sentiment classification plays a dominant role in day-to-day life including the political events, production areas, and commercial activities. The need for the accurate and instant classification of the user emotions is a hectic task to be solved. The traditional methods fail to address the classification of dynamic dataand huge volumes of documents. Moreover, to assure the classification accuracy and deal with huge volumes of data, the proposed method employs the MapReduce Framework. The proposed sentiment analysis involves twoprocesses, such as feature extraction and classification that is performed in the MapReduce framework using the mapper and reducer functions. The feature vector is based on the sentence-specific features, SentiWordNetbasedfeatures, and statistical features corresponding to the individual reviews that are classified as positive and negative reviews using the proposed Chronological-Brain Storm Optimization based Support Vector Neural Network (CBSO-SVNN). The analysis is progressed using four datasets obtained from the movie reviewdatabase that confirms that the proposed method outperformed the existing methods in terms of the accuracy, sensitivity, and specificity. The accuracy, specificity, and sensitivity of the proposed method are 0.8714, 0.9027,and 0.8714, respectively.

    • Design variables optimization effects on acceleration and contact force of the double sliders-crank mechanism having multiple revolute clearance joints by use of the Taguchi method based on a grey relational analysis


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      This study developed a mechanism with two sliders for a planer machine, in order to enhance productivity. First, the effects of the clearance size and seven imperfect revolute joints on the dynamic characteristics of the proposed mechanism were analyzed by finite element analysis in ANSYS software. In order to improve the dynamic behavior, an optimal design was carried out via the Taguchi method with grey relational analysis. The simulation results demonstrated that the clearance size has a slight effect on the velocity andgreatly affects the accelerations of the two sliders and contact forces in the seven revolute clearance joints. The values of velocity, acceleration of the two sliders and contact force increased when the clearance size increased,as compared with an ideal joint. It was found that the optimal design parameters for both the acceleration of the first slider and the contact force in the first revolute clearance joint (RCJ) are an input velocity at 500 rpm, a length of bearing at 15 mm, a journal radius at 9.7 mm, the material’s structural steel with a Young’s modulus of 69 GPa and a clearance at 0.1 mm. The optimal results of acceleration and contact force are 186.45 (m/s2) and 106.854 (N) respectively, with a 3.92% error for acceleration and 9.99% for contact force compared with the simulation results.

    • Design and implementation of a current controlled grid connected inverter for thermoelectric generator sources


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      This paper presents the digital implementation of a current controlled grid connected inverter for Thermoelectric Generator (TEG) sources. Considering the electrical characteristics of a TEG source, several important aspects that a designer has to consider in selecting the rating of power converters for the gridconnected operation of TEG source are discussed. The closed loop control of a TEG fed grid connected voltage source inverter (VSI) requires line current control to regulate the power pumped into the grid. Considering the inverter, current sensor and line inductor models, a simplified method is espoused to determine the parameters of the digital current controller. An Altera Cyclone II FPGA board is used to implement the current control strategy in VSI fed with TEG power source. The proposed design approach is validated using simulations and experiments and verified with the time domain specifications

    • Design investigation for continual torque operative performance of PMSM for vehicle


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      The increasing trend of population and its one of the requirements, on road vehicles are increasing. In addition, rural to urban development and subsequent deforestation leads to ozone depletion, climate change, loss of biodiversity and finally global warming encourages to research to give the substitute for IC Enginevehicles by developing electric vehicles. Present 20–35% of world economy is driven by IC Engine vehicles and now upcoming challenge is to develop equivalent and better technical solutions to sustenance environment with green vehicles. The existing developed electric vehicles has limitation to work under controlled environment and suitable for good road conditions. However, the requirement is to develop the continual torque operative motor which can be suitable for Indian road, Indian weather conditions and which can overcome the IC Engines. This is preliminary design investigation of motor for operative torque performance considering the different design parameters for stator slot configurations, slots/pole ratios, rotor configurations, combination of different types of magnetic materials, stack length, back iron, and dimensions of the effective magnet. The design simulation is done in RMxprt as per the important required characteristics of the electric vehicles (EVs).

    • Low power dynamic voltage scaling and CCGDI based Radix-4 MBW multiplier using parallel HA and FA based counters for on-chip filter applications


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      In this paper, a new design of low power, high performance Radix-4 MBW multiplier unit has been described. The low power performance has been achieved by dynamic voltage scaling. Based on CCGDI technique which reduces the switching activity and output capacitance, the proposed multiplier unit has been designed by utilizing three different low power methodologies i.e., reduction in output capacitance and switching activity along with biasing voltage reduction. In order to reduce the number of transistor and delay, here GDI based parallel adders are used in the Wallace tree counters. The multiplier has been implemented with constant threshold voltage PTM 45 nm devices technology and simulated in standard CAD tool simulator for 4, 8 and 16 bit operand multiplications. The proposed design consumes 238.98 lw average power and it has a propagation delay of 2.458 ns for 16 9 16 bit multiplications at speed 100 MBps which is 47% better in terms of power-delay-product than counter based GDI Wallace tree multiplier structure

    • Pricing and market segmentation in an uncertain supply chain


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      This paper addresses a new location-allocation-pricing problem in designing a three-level uncertain supply chain network with stochastic price-sensitive demands. Using the market segmentation problems, a supply-chain network is developed with two distribution channels that consist of Brick & Mortar and onlinemarkets, when some demand leakages occur from the market with a higher price. Due to the lack of physical observation of products in online markets, a return policy is used. So, demand behavior is analyzed in terms of the pricing and return policy. The problem established location, allocation, order quantities, pricing and refundprice decisions to optimize the total profit of the chain. Furthermore, it is formulated as a mixed-integer nonlinearprogramming (MINLP) model and solved by a Lagrangian relaxation algorithm. The numerical study andcomputational results indicate the efficiency and effectiveness of the proposed algorithm

    • Theoretical and experimental study on one dimensional fracture grouting in soil medium


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      In this study, a theoretical model of one dimensional fracture grouting in soil is proposed based on fluid mechanics and force analysis during grout fracturing process. Solutions for grout pressure, and the length and width of the fracture are obtained, and the influence of the yield strength on the fracturing behavior isanalyzed. Results show that, the grouting distance decreases and the fracture height increases as the yield strength of grout increases. A laboratory test was carried out in this study to validate the proposed theoretical model. The dimension of the solidified grout was measured after excavation. For higher yield strength, the grout front has a blunt shape, which means the pushing effect plays a more important role than the fracturing effect and the fracturing process was controlled by different mechanisms for different yield strength during theexperiment. Comparison between the theoretical and the experimental results shows that the proposed model can effectively describe the fracture grouting process.

    • An efficient miniature air suction system for chemical sensors for micro air vehicle application


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      This paper describes the design of a miniature air suction system to house a chemical sensor. It has been designed to improve the aerodynamic chemical sensing efficiency and to have a low weight since it is meant to be mounted on a micro air vehicle. The design is done around a readily available miniature axial flow fan by computational methods. A converging-diverging shape for the air suction system with the sensor disc having a central hole and mounted at the throat is proposed as good design concept. The systematic approach hasled to a light weight system with high aerodynamic efficiency even under extreme flow conditions that may be caused by MAV manoeuvre or cross winds.

    • Development of a task-oriented, auction-based task allocation framework for a heterogeneous multirobot system


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      A multirobot system has cooperative team of robots designed to enhance efficiency of its operations. One of the critically investigated problems of multirobot system is the multirobot task allocation (MRTA) issue. The main objective of MRTA is to assign tasks to the most suitable robot based on its functions and capability as well as availability. In this paper, a task-oriented, auction-based task allocation framework is presented and tested through simulations and real-world experiments. The developed framework consists of anovel heuristic-based task allocation algorithm and communication module. It is implemented in a multirobot system, allowing tasks to be dynamically assigned to the robots as they achieve given tasks. The implemented framework shows robustness in its flexibility to the task and environment requirements such as resource and energy requirements and size of the environment. The framework involved a task allocation algorithm, which consists of bid generation and bid selection process, and a TCP/IP-based client-server communication module.The results from both simulations and real-world experiments matched, producing optimum results in task allocation.

    • On pulse-width pulse-frequency modulator control strategy: An adaptation-based describing function representation


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      This research describes an adaptation-based control strategy to deal with the pulse-width pulsefrequency modulator. The subject behind the research is to control the above-referenced modulators the hard limiter block via closed-loop describing function representation. In a word, this modulator has a set ofparameters, which are all in need of adjusting, accurately, in order to guarantee its high performance, in the entire areas of overall systems under control. The investigated results indicate that parameter’s adjustment of the aforementioned pulse-width pulse-frequency modulator can be recognized as the state-of-the-art outcomes via adaptation rules

    • Statistical modeling of rubberized concrete beams confined by FRP using RSM technique


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      The use of rubber in concrete has been practiced in the engineering community for several years. However, the poor mechanical properties of rubberized concrete are a serious hurdle. This innovative research provides a closer look at improving the flexural strength of rubberized concrete beams with high rubber content using confinement technique. FRP jackets with different confinement thickness were used to recover the strength loss of rubberized concrete beams. In this paper, 66 rubberized concrete (RuC) beams having 0–50% rubbercontent were tested under four-point loading. RuC beams suffered up to 167% reduction in flexural strength.However, the FRP jackets were highly effective to improve the flexural strength of RuC beams. The statistical models were developed to predict the flexural strength of FRP confined rubberized concrete beams using response surface methodology (RSM). In this regard, the effect of two principle variables; unconfined strength and number of FRP layers on the flexural strength of FRP confined rubberized concrete beams was investigated. The models were found significant because the predicted and adjusted R2 was less than 0.2 (a limit proposed by Design Expert software). The predicted and experimental results for FRP confined rubberized concrete beams were found in good agreement. The developed statistical models provide insights into the sensitivity of parameters affecting the flexural strength. The proposed models can improve the reliability of the experiments and reduces the design and analysis time

    • Super-twisting sliding mode control approach for tumor growth by immunotherapy


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      Cancer is the second leading cause of death after heart disease in the world and the third leading cause of death after heart disease and accidents in Iran. In general, cancer is a disorder of the rate of proliferation and cell differentiation that can occur in any tissue of the body and at any age and by invading healthy tissues may exacerbate the disease and eventually cause death. In a word, one of the most commonly used treatments for cancer is the use of chemotherapy. The drugs of the aforementioned chemotherapy are transported throughthe blood to cancer cells and all parts of the body. In addition to cancer cells, these drugs also have a detrimental effect on healthy cells, which can be seen as side effects. It is to note that they are temporary and can stop at the end of treatment. The subject behind this research is to propose super-twisting sliding mode control approach without chattering for mathematical model of cancer by immunotherapy with the aim of stabilizing the closedloop system, as long as determining the optimal drug dose is taken into consideration as the innovation of this study to conclude which controller has the better performance in the presence of uncertainties and disturbances

    • A novel symmetric switched capacitor multilevel inverter using nonisolated power supplies with reduced number of components


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      In this paper, a novel 15 level symmetric switched capacitor multilevel inverter (SCMLI) structure is proposed first. The structure is developed by using 3 non-isolated DC power sources. The capacitors utilized in the structure can be charged to the summation of all the power supplies by turning ON the minimum number of switching devices. After that a generalized structure of the proposed SCMLI is developed. The voltage and current stresses for different switches of the proposed general structure are discussed. The selection procedure ofswitched capacitors for the proposed 15 level inverter is presented for resistive and resistive-inductive load conditions. A detailed comparison study of the proposed structure with other recently developed structuresshows that the proposed structure requires reduced number of components and the number of switches in the conducting path as compared to other SCMLI structures for generating an output voltage level. Further, the overall cost of the proposed and suggested topologies has been compared based on a cost function (CF). It has been observed that the proposed structure is more cost effective as compared to others. An extensive experimental study conducted on a 15 level SCMLI laboratory prototype proves the effectiveness and merits of theproposed structure.

    • A standalone PV operated DC milk chiller for Indian climate zones


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      This work illustrates the design of a standalone solar power system used to power a milk chiller with 200 W DC compressors using the PVsyst software for different climatic zones in India. The design includes determination of minimum number of PV panels and batteries and also the means of obtaining annual solarfraction values for five different climatic zones of India using the software. Simulations were performed considering two different operational modalities. The first modality considered a milk chiller with an inbuilt ice bank tank for cool thermal energy storage. The ice formed during sunshine hours take care of the cooling of the milk throughout. The second modality considered a milk chiller coupled with a battery backup to get charged during sunshine hours and to run the compressor throughout. The first modality was found to be advantageous interms of PV panel requirement, battery backup as well as better solar fraction. Hence the same was experimentally studied for Chennai’s climate condition to confirm the maintenance of milk temperature. The power supply from the PV panel was simulated using a regulated power supply. While doing so, considering the maximum power point, the power supply was varied every hour as predicted by the PVsyst software. From the experiment, it was found that the required number of PV panels got reduced from 4 to 2 panels when consideringthe maximum power point for a typical summer day. The custom built milk chiller was able to chill down the milk from 37°C to 4°C within 2 hours on all days using cold energy from the ice bank tank.

    • Particle swarm optimization and feature selection for intrusion detection system


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      The network traffic in the intrusion detection system (IDS) has unpredictable behaviour due to the high computational power. The complexity of the system increases; thus, it is required to investigate the enormous number of features. However, the features that are inappropriate and (or) have some noisy dataseverely affect the performance of the IDSs. In this study, we have performed feature selection (FS) through a random forest algorithm for reducing irrelevant attributes. It makes the underlying task of intrusion detection effective and efficient. Later, a comparative study is carried through applying different classifiers, e.g., k Nearest Neighbour (k-NN), Support Vector Machine (SVM), Logistic Regression (LR), decision tree (DT) and Naive Bayes (NB) for measuring the different IDS metrics. The particle swarm optimization (PSO) algorithm wasapplied on the selective features of the NSL-KDD dataset, which cut down the false alarm rate and enhanced the detection rate and the accuracy of the IDS as compared with the mentioned state-of-the-art classifiers. This studyincludes the accuracy, precision, false-positive rate and the detection rate as performance metrics for the IDSs. The experimental results show low computational complexity, 99.32% efficiency and 99.26% detection rate onthe selected features (=10) out of a complete set (= 41).

    • High slew rate and low output resistance class-AB flipped voltage follower cell with increased current driving capability


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      The paper proposes a class-AB flipped voltage follower (FVF) cell, in which the bulk-driven transistor is used as an input transistor with a replica-biased scheme to eliminate the DC level shift while a cascoding transistor is used to reduce the output resistance. The proposed FVF cell has several advantages suchas low output resistance, approximately unity voltage gain, high symmetrical slew rate, high current sourcing capability, high current sinking capability and wide bandwidth. The proposed FVF cell has been simulated inCadence Virtuoso Analog Design Environment using BSIM3v3 180 nm CMOS technology with a power supply voltage of 1.2 V.

    • Convective transport around two rotating tandem circular cylinders at low Reynolds numbers


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      The convective transport around two rotating circular cylinders kept in a tandem configuration to an unconfined flow of an incompressible fluid (Prandtl number, Pr = 0.717) is investigated through two-dimensional numerical simulation. The flow Reynolds number is considered constant at Re = 100. Four different gapspacings between the tandem cylinders such as 0.2, 0.7, 1.5 and 3.0 are chosen for simulation. The cylinders are rotating about their centroidal axes for a range of dimensionless speed (0<=W<=2.75). The rotation to the objects causes the unsteady periodic flow around them to become stabilized and at some critical rotational speed, the vortex shedding stops completely resulting in a steady flow pattern. The critical speed of rotation at which the vortex shedding completely stops is a function of the cylinder spacing. Overall, it is observed that increasing the gap increases the critical rotation rate. The thermal fields are also strongly stabilized as a result of the cylinder rotation. The rotating cylinders actually create a zone in their proximity which acts like a buffer to the convective transport. The conduction mode of heat transfer predominates in these regions causing the heat transfer rate to assume a decaying pattern with increasing the rotational speed at all cylinder spacings.

    • Grey-fuzzy method-based parametric analysis of abrasive water jet machining on GFRP composites


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      Abrasive water jet machining (AWJM) is an advanced non-traditional material removal process which can machine almost all types of thin hard-to-cut materials. The quality of its machining operation can be effectively enhanced while selecting the appropriate settings of its different input parameters through the application of optimization techniques. This paper aims in obtaining the optimal combination of four AWJM control parameters, such as water jet pressure, stand-off distance, abrasive mass flow rate and traverse speed while machining of glass fiber reinforced polymer (GFRP) composites. Grey relational analysis combined withfuzzy logic is employed here for attaining the most favored values of the process outputs (responses), i.e material removal rate, surface roughness, kerf width and kerf angle. The effects of varying AWJM process parameters on the measured responses are further studied through the developed interaction plots, while thecontributions of those process parameters are identified through analysis of variance technique. The response surface plots would further help in determining the attainable values of the corresponding process parameters to realize the desired quality of the considered responses

    • Control of the inverted pendulum system: a Smith fractional-order predictive model representation


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      The inverted pendulum system in the presence of uncertainties and external disturbances with delay is considered as one of the most applicable nonlinear systems to be used in real environments and industrial domains, extensively. The subject behind the research is to design a state-of-the-art fractional-order slidingmode control approach to stabilize the inverted pendulum angle. Subsequently, a consideration of uncertainties and external disturbances in the pendulum dynamic’s parameters such as pendulum length and chariot’s massaims us to find an efficient technique to decrease chattering and correspondingly increase system’s performance as well. In addition, the Smith predictive model representation along with the control approach is realized as asolution of eliminating time delay. In a word, the realization of sliding mode control to deal with uncertainties and external disturbances in line with an application of fractional-order sliding surfaces for decreasing chattering under the aforementioned Smith predictive model representation to eliminate delay is taken into real consideration as remarkable novelty of research proposed. Finally, the effectiveness of the approach analyzed here is verified in the form of numerical simulations through MATLAB software, tangibly

    • SDN-based DDoS Attack Mitigation Scheme using Convolution Recursively Enhanced Self Organizing Maps


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      In a cloud computing environment, the Distributed Denial of Service (DDoS) attack is considered as the crucial issue that needs to be addressed in ensuring the availability of resources that emerge due to the compromisation of hosts. The process of detecting and preventing DDoS attacks is determined to be predominant when the potential benefits of decoupling data plane from the control plane are facilitated through the Software Defined Networking (SDN) in the cloud environment. The incorporation of SDN in DDoS mitigationalso enhances the probability of investigating the data traffic flow using the reactive process of updating forwarding rules, analyzing the network with a global view and centralized control in monitoring for better DDoS mitigation enforcement. In this paper, a Convolution Recursively Enhanced Self Organizing Map and Software Defined Networking-based Mitigation Scheme (CRESOM-SDNMS) is proposed for ensuring the better rate of detection during the process of preventing DDoS attacks in clouds. This proposed CRESOMSDNMSfacilitates a predominant option in resolving the issue of vector quantization with enhanced topology preservation and the superior initialization mechanism during the process of SOM-based categorization of flooded data traffic flows into genuine and malicious. The simulation experiments and results of the proposedCRESOM-SDNMS confirmed a superior classification accuracy of around 21% when compared to the existing systems with minimized False Positive rate of 19% compared to the benchmarked DDoS mitigation schemes of the literature.

    • High-speed, low-power and low-offset fully differential double-tail dynamic comparator using charge sharing technique


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      To meet the demand for low-voltage/low-power and high speed analog-to-digital convertors, a new fully differential double-tail dynamic comparator is proposed. To reduce the power dissipation and speed up the comparison process, charge sharing technique has been used in the latch stage of the proposed dynamiccomparator. In addition, differential pair and double-tail dynamic comparator topologies are combined to minimize the offset voltage. The proposed dynamic comparator has worst case delay of 0.219 ns, power dissipation of 156.3 lW and offset voltage of 0.184 mV with 1r deviation of 7.65 mV. The proposed dynamiccomparator has been simulated in 0.18 lm CMOS technology with supply voltages of ± 0.75 V using Cadence virtuoso analog design environment

    • Microstructure evolution of interface between magnesium ammonium phosphate cement and Portland cement under sulphate corrosion environment


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      This paper reports the test results on the bonding strength between magnesium ammonium phosphate cement and Portland cement. The bonded specimens were prepared by immersion in Na2SO4 solution. Following immersion, the surfaces and positions of fractures on the specimens were examined. SEM and an optical microscope were used to analyse changes of the interfacial microzone following different immersion periods. Microstructure changes of the magnesium ammonium phosphate cement-based interfacial microzone within the bonded mortar specimens were studied and compared with those immersed in normal conditions. The bonded mortar specimens were found to have weaker bonding strength than that of the mortar specimens in normal conditions. Under normal conditions, slight crystal morphology changes of the interfacial microzonewere observed and the crystal structure appeared compact, while more noticeable changes occurred within mortar specimens immersed in Na2SO4 solution, with the crystal structures within them being more loose. Thebonding behaviour of the magnesium ammonium phosphate cement includes mechanical bonding, mutual diffusion, and chemical bonding. Structural diagrams of the interfacial transition zone (ITZ) in different environments are also presented. Further investigations are needed to determine the performance of the bonding interface microzone of Portland cements and magnesium ammonium phosphate cements within repair materials in order to enhance the performance of cement-based composite materials for concrete repair.

    • A decision support system for the selection of an additive manufacturing process using a new hybrid MCDM technique


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      Recently, Additive Manufacturing (AM) has been widely used in many applications. For a particular AM component, the choice of available AM processes is critical to the component’s quality, mechanical properties, and other important factors. In that context, this article presents an efficient decision support system for the selection of an appropriate AM process. A novel hybrid Multi-Criteria Decision Making (MCDM) technique has been proposed to select an appropriate AM process from available AM processes. The Best WorstMethod (BWM) is used to determine optimal weights of criteria and the Proximity Indexed Value (PIV) method is employed to rank the available AM processes. For benchmarking the abilities of an AM process, a conceptual model of spur gear was fabricated by four available AM processes viz., Vat Photopolymerization (VatPP), Material Extrusion (ME), Powder Bed Fusion (PBF), and Material Jetting (MJ). Additionally, Dimensional accuracy (A), surface roughness (R), tensile strength (S), percentage elongation (%E), heat deflection temperature(HDT), process cost (PC) and build time (BT) has been considered as most significant criteria. Further, sensitivity analysis has been performed to validate the reliability of the results. The results suggested that the Material Jetting (MJ) process produces dimensionally accurate and quality parts among available alternatives AM processes. The ranking obtained using the PIV method is consistent and reliable

    • FuRL: fuzzy RBM learning framework to detect and mitigate network anomalies in Information Centric Network


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      Information Centric Network (ICN) is a promising next-generation internet architecture in which the network focuses on retrieving the content by employing open in-network caching scheme to provide an efficient content distribution to users. However, such open in-network caching is vulnerable to networkanomalies. In particular, cache pollution attack disrupts the smooth working of in-network caching by flooding unpopular contents. Hence, the in-network caching malfunctions and legitimate consumer requests are dropped. To address this problem, a secure framework based on Fuzzy Restricted Boltzmann Machine has been proposed to detect the anomalies and defend against such pollution attacks in ICN. Further, a reward-based cache replacement (ReBac) algorithm that is capable of avoiding cache pollution attack has also been proposed. Theexperimental results obtained while testing the proposed framework show better detection rate compared with the state-of-art solution and the proposed framework shows better cache rate

    • Robust control of single-machine infinite bus system: a novel approach


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      This work proposes a novel robust controller in Linear Matrix Inequality framework for a singlemachine infinite bus system. The mathematical equations defining the system are highly nonlinear. The novelty of the paper is the linear control law, which is obtained without linearizing the system. Along with thenonlinearity here, another two contingencies are also taken into account—(i) uncertainties in terms of parameter variations and losses and (ii) time delay in the feedback control law. The proposed controller is expected to accommodate the parameter uncertainties and the time delay. Simulation results support the analytical findings

    • A secure authentication framework for WSN-based safety monitoring in coal mines


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      Underground coal mines are considered as one of the most dangerous workspaces as many hazardous factors regularly cause accidents. It may be avoided by real-time monitoring of environmental parameters (gas, temperature, the width of walls, etc.) of underground tunnels. Nowadays, wireless sensor network (WSN) is widely used for safety monitoring of coal mines. However, any kind of interception, modification and interruption of transmission of environmental parameters can mislead the professionals that might lead to amajor accident. Therefore, security is an essential issue for WSN-based safety monitoring. Sensors in WSN have limited computational power and storage capacity, which creates a challenge to design authentication and keyagreement (AKA) scheme with low computational cost. To address these issues, As this scheme is light-weight and provides mutual authentication (MA), sensor anonymity (SA) and user anonymity (UA), we have considered this scheme for a case study. We first propose the cryptanalysis of this scheme, in which we prove that this scheme fails to resist sensor node compromise (SNC), stolen smart card (SSC) and user impersonation (UI) attacks. To counteract these attacks and to provide efficient authentication scheme, we propose a lightweight AKA scheme for WSN-based safety monitoring in coal mines. We simulated the scheme on AVISPA tool. We used the random oracle model (ROM) to perform formal security analysis and also performed informal security analysis. These analyses demonstrate that the proposed scheme is secure and invulnerable to various known attacks. We compared the proposed scheme to other related schemes regarding security features and computational cost. Our scheme requires comparable computational cost and is more secure than related schemes.

    • Printed circular ultra-wideband antenna with triple sharp frequency notches for surface penetrating radar application


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      A printed ultra-wideband antenna of compact size (0.36 lL 9 0.31 lL) that delivers bandwidth (S11 <= -10 dB) of 2.64–9.36 GHz (112%), with triple notches at 3.28–3.84, 5.08–5.44 and 5.62–6.06 GHz to reject contemporaneous wireless interventions such as WiMAX and WLAN is reported in this article. Theproposed antenna performance is established by both simulation and experimental measurement. The antenna affords gain variation from 2 to 5 dBi, radiation efficiency of 80% on an average, linear transfer function andnon-varying group delay response in its pass bandwidth while significant deviations are observed in the three notch bands. Bi-directional E-plane and non-directional H-plane patterns are testified in the antenna pass band.Antenna bandwidth is also measured in proximity of soil, wood and glass by keeping metal plate at bottom where an unaltered bandwidth response is observed that justify its capability to work for surface penetratingapplication.

    • A smart bi-objective two-stage algorithm for optimal transmission switching without islanding


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      In a deregulated environment, optimal transmission switching (OTS) plays an important role in coordination among power generating companies (GENCOs) and transmission company (TRANSCO) by minimizing operating costs. This paper solves ac OTS (ACOTS) in two different stages sequentially with acoptimal power flow (ACOPF) and transmission switching through ac power flows (TS-ACPF) for optimal power generation and efficient power transmission, respectively. The mutual dependency along with the coordination among these optimal problems are treated intelligently by adopting a metaheuristic based two-stage algorithm with a multi-objective approach to achieve an effective solution through maximum utilization of power in the existing system or for future expansion planning. Production cost optimization problem is taken care of in thefirst stage while transmission loss is optimized in the second stage with successive iterations of the proposed algorithm. MATLAB simulations to optimize both transmission loss and production cost for both the IEEE-30 bus system and the Indian Utility 62-bus real system are experimented. Results are provided to validate the proposed technique which satisfies several cases of load variations, N - 1 standards and other combinations of stressed security constraint conditions. The detailed investigation of the results prove the effectiveness of theproposed intelligent two-stage method over the existing methods in terms of automatic and cost-effective biobjective solution relying on the flexibility of switching strategy and security by avoidance of islanding without any manual interaction in between

    • Computational method for generalized fractional Benjamin–Bona– Mahony–Burgers equations arising from the propagation of water waves


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      In this research, by utilizing the concept of the mixed Caputo fractional derivative and left-sided mixed Riemann–Liouville fractional integral, we approximate the solution of generalized fractional Benjamin–Bona–Mahony–Burgers equations (GF-BBMBEs). In addition, using Genocchi polynomial properties, we obtaina new formula to approximate the functions by Genocchi polynomials. In the process of computation, we discuss a method of obtaining the operational matrix of integration and pseudo-operational matrices of the fractional order of derivative. Also, an algorithm of obtaining the mixed fractional integral operational matrix is presented. Using the collocation method and matrices introduced, the proposed equations are converted to a system of nonlinear algebraic equations with unknown Genocchi coefficients. In addition, we discuss the upper bound ofthe error for the proposed method. Finally, we examine several problems to demonstrate the validity and applicability of the proposed method.

    • Experimental investigation of drying kinetics of apple with hot air, microwave and ultrasonic power


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      The experiments were performed for various conditions at 40–60 °C air temperature, 0.5–1.5 m/sair velocity, 120–600 W microwave and 50–200 W ultrasonic power so as to investigate the effects of drying airtemperature, air velocity, microwave and ultrasonic power on the drying characteristics of apple slices. In thestudy, the combined use of hot air, microwave and ultrasonic energy for apple slices was determined as the mosteffective and fastest drying method. Besides, according to the experimental results applied to the modelsselected from the literature, the model that best described the drying characteristics of the apple under themicrowave and ultrasonic effect was that of Midilli et al and the correlation coefficient R2 was calculated to bebetween 0.9969 and 0.9999.

    • Probabilistic planning for participation of virtual power plants in the presence of the thermal power plants in energy and reserve markets


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      Renewable energy-based on virtual power plants (VPPs) has recently attracted considerable attention for participating in energy and reserve markets due to the disadvantages of thermal power plants (TPPs). The present paper aims to maximize the VPP profitability in distribution networks including thermalpower plants, at minimum load cost, using a mathematical model for implementing the VPP and evaluating its role in the energy and reserve markets. The proposed model includes a series of probabilistic scenarios used to consider the uncertainty of wind/solar generation. Therefore in the first step, the lower bound of the problem, i.e., minimizing demand cost for all the units, should be calculated. It determines the status of VPP units based on the best-case scenarios. Afterward, the problem is cut to calculate the upper bound of the problem which is maximizing the profit of the VPP. The problem is evaluated in two cases: one is the presence of VPP only in the energy market and the other is the simultaneous presence of the VPP in the reserve and energy markets. Thecomputation ends with the convergence of lower and upper bounds of the problem. Since the proposed method uses a piece-wise model of thermal units and the problem has nonlinear equations, Mixed Integer Programming(MIP) used to calculate the contribution of units by utilizing GAMS software. Finally, the VPP profitability calculated for the day-ahead energy and reserve market after determining the method for the participation of power plants in supply at the minimum cost. The proposed method was then applied to a sample system consisting of three thermal plants, three wind farms, two solar farms, and two energy storage systems, considering several situations to examine the impact of the resources and also the resulting profitability in the energy and reserve market. The final step was the analysis of the results.

    • A polynomial-division based correction model for camera calibration: a large comparative study


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      These days, algorithms which enable correction of an image aberration such us barrel or pillow distortion can be found in a large number of scientific papers. Some sorts of algorithms have universal character, others can be used only with a certain type of optical systems. This paper compares several types of methodswhich were designed to remove an image distortion. The methods which are based on so called Polynomial Division Model (PDM) are only considered. On the grounds of extensive experimental results, a method which uses the polynomial division model was proposed. The method brought significantly better results in the correction process. It does not matter if the images are loaded with a pillow or a barrel distortion. The image correction calculation procedure is from a general point of view, very time demanding. The calculation with use of the PDM is fast, and does not need a large number of members of the correction polynomial. This rule is also valid for an image which is loaded with large distortion e.g., for Fish-Eye object-lenses - a newly proposed PDM preserves all good features of previous algorithms which are based on the PDM and extends them. All the results which are recorded in the experimental section show that the PDM is superior and more effective in comparison to other tested methods.

    • Numerical modelling of trapezoidal weir flow with RANS, LES and DES models


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      The characteristics of the trapezoidal weir flow are measured using a one-dimensional laser Doppler anemometer for two different flow conditions. The governing equations of the flow are solved using Standard k–e, Realizable k–e, Modified k–x and Reynolds Stress Model based on the Reynolds-Averaged Navier–Stokes Equations and by Large Eddy and Detached Eddy Simulations. ANSYS-Fluent package program is used for the numerical analysis of flow with the same experimental conditions. The free surface of the trapezoidal weir flowis computed by the volume of fluid method. The effect of the selected grid structure on the numerical results is examined by Grid Convergence Index. Moreover, two-dimensional (2D) and three-dimensional (3D) analyses ofthe trapezoidal weir flow are included to estimate the effects of side walls. Experimental results of the velocity field and free surface profiles are compared to the numerical results of 2D and 3D simulations for the validationpurposes. From the comparisons it is concluded that the Reynolds Stress Model estimates the flow field more accurately compared with those of the other models used in the present study. Furthermore, the flow characteristics such as turbulence kinetic energy, energy spectrum and pressure distributions for different flow rates are presented. Lastly, the discharge coefficients for different flow–weir configurations are compared experimentally and numerically.

    • Design of an improved automatic fiber cut localization with OTDR using GIS mapping


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      Optical fiber line, considered to be highly effective for signal transmission, sometimes suffer from fiber cut resulting in signal loss. It is highly desired that the exact cut location is found by use of fiber length so that entire fiber cable need not be replaced. An optoelectronic instrument OTDR (Optical Time-DomainReflectometer) is used to find the position of the cut along the fiber length. There is the need to find the physical location on the GIS map which can provide the exact location where the replacement of fiber or maintenance activity has to be carried out. This paper proposes Vincenty’s formula to be used for fiber cut localization using GIS mapping which assumes the Earth to be oblate spheroid instead of exact sphere. This method will be highly accurate than any other method for exact localization of fiber cut.

    • Assessment of interaction mechanism and bearing capacity of strip footings located on slope face


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      Construction of residential and commercial buildings on the slope face is very commonly noted in the North-eastern and other mountainous terrains of India. Closely spaced buildings and the foundation elements located on such slope faces interact with each other, thereby influencing the stability of the slopes, which, in turn, affects the failure mechanism and bearing capacity estimation of such foundation systems. Several literatures are available highlighting the response of foundation located on the slope crest, while those elucidatingthe response of foundation located directly on the slope face are scanty. Among them, there are extremely few literatures available showcasing the interaction of footings located on slope face. Hence, considering the practical importance of the issue, this paper reports a numerical two-dimensional finite element-based study that is conducted to determine the failure mechanism and bearing capacity of interfering strip footings located on the face of a slope. The study aptly demonstrates that the response of interfering footings is governed by the soiltype, footing width, slope inclination, and the relative elevation between the footings. It is observed that upon increasing the footing width by two times, the bearing capacity of interfering footing increases by 33%, even though the interfering mechanism remains the same. It was also noted that with each successive increase in the slope inclination by 5°, the interfering bearing capacity gets reduced by 37 %. Under any parametric circumstances,maximum interference between the strip footings is noted when their relative height of separation (in terms of footing width) remains close to 2, while the interference is found to be completely disappearing when the relative height of separation is 8 or more. This finding should aid in the decision making about the proper choice of inclusion of interference effect during the analysis and design of foundations on slope face

    • A novel integration of smart vehicles and secure clouds for supervising vehicle accidents on roads/highways


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      Precluding death percentage from road accidents has always been challenging task for technologists and scientists of this earth. As per the recent reports of world health organization approximately 1.5 million people including children and women are getting sudden and sad demise from road accidents. Approximately25% of these deaths are because of non-availability of in-time medical aid and the existing automobile automatic communication technology is feeling helplessness. Although, the existing technologies of this earth and theirintegrations can help to the persons who are trapped in accidents and getting sudden demise. It is the social responsibility of scientists and researchers to work in the direction of developing easily accessible technologies which can provide immediate help on urgent basis to the persons struggling for life on the place of accident. This research work uses secure cloud (SeC) based online cameras called virtual eyes and internet of things (IoT) for developing a flawless and intelligent road traffic accident death prevention system called Intelligent RoadTransportation Management and Control System (IRTMCS). The proposed IRTMCS is reliable, economically feasible and innocuous. The implementation and installation of the proposed system in existing vehicles can save the life of millions of people every year. In this research paper, the author has presented an innovative SeCBVE (Secure Cloud Based Virtual Eye) based IRTMCS (Intelligent Road Transportation Management and Control System) for preventing the deaths of individuals including women and children in road accidents. The implementation of the proposed approach brings us to a juncture where death percentage of persons in road accidents is decreased by 25% and approximately the life of approximately 400,000 (Four Hundred Thousand) persons including women and children can be saved every year by using the proposed system. The proposed approach uses secure cloud (SeC) based online cameras called virtual eye and internet of things (IoT) for implementing an unblemished and smart road traffic accident death prevention system. The proposed SeCBVE based IRTMCS is capable to help the investigators in finding the cause of accident and it will help the judicial system in tracing the culprit on the basis of stored video images. It can be concluded from the results and discussions sections that the proposed SeCBVE based IRTMCS gives promising performance in terms of efficiency, consistency and fault tolerance and it includes all the necessary features which are required for accountable, reliable and flawless road traffic accident death prevention systems (RTADPS). The implementation and installation of the proposed system in existing vehicles can save the life of millions of people everyyear.

    • Experimental investigation of local scouring around the bridge piers located at a 90° convergent river bend


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      Placing the bridge piers in the river with a convergent bend can make the flow and erosion pattern complicated around the bridge piers. In this research, the maximum depth and volume of scour hole around piers were investigated in convergent bends of a river. The experimental model with a 90° convergent bend was made with a central curvature radius of 170 cm. The piers with the cylindrical and cubic shapes with different dimensions were prepared and installed at different positions of 90° convergent bend to investigate the scouring condition under three flow discharges in Clear-water mode. On the other hand, natural sand with uniform grain size of d50 = 1 mm was used as the bed materials. The results revealed that depth and volume of the scour holearound piers increase with increasing angle, so that the maximum depth and volume of the scour hole occurred at the angle 75°. Furthermore, the depth and volume of the scour hole around cylindrical piers were lower than cubic piers in all cases. Also, the scour hole shape was asymmetric relative to central axis of the channel and was mainly the extension of the hole towards the inner bend.

    • Effect of ethanolamine and nano-TiO2 on the properties of ferrocement composites under different exposure environments


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      The main aim of this study was to investigate the effect of 1%, 3% and 5% content of ethanolamine (EA) and nano-TiO2 (NT) on the corrosion resistance properties of ferrocement composites exposed under tap water, saline water and sulphuric acidic solution environments. The corrosion behaviour composites wereassessed through potentiodynamic polarization technique. Besides, the effect of EA and NT on the fresh, hardened, microstructural and mineralogical properties of cementitious composites were evaluated by conducting setting time, compressive strength, SEM, EDX and XRD studies. The corrosion resistance properties of ferrocement composites were found to be improved with the addition of both EA and NT. The corrosion inhibition efficiency of EA was observed to be increasing up to 3% but decreased at 5% dose, whereas it wasincreasing with increasing the content of NT in all the three exposure environments. The EA and NT were found to be acting as retarder and accelerator, respectively. The addition of EA led to decrease the 28-days compressive strength of mortar, however the addition of NT showed an opposite effects. Similar impacts on the 180-days compressive strengths mortars exposed under tap water, saline water and acidic solution were also observed. The SEM and XRD analyses revealed that EA caused adverse impacts on the microstructure and hydration products of OPC, though NT enhanced the microstructure and the quantities of desirable hydration products.

    • Design optimization of cubic Bezier horn for ultrasonic machining


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      In ultrasonic machining (USM), higher amplitude is required for higher material removal rate (MRR). The objective of this research is to develop a new horn design for high displacement amplitude for getting maximum MRR within a working condition. The profile of the horn has been optimized and designed. Inthis analysis, optimization procedure and finite-element method have been used for the design of horn of USM. In this, the variation of stress components along the length of the horn has been studied. In the middle, maximum stress is found due to a change in cross-section but it is within the endurance limit of the horn material. The cubic Bezier horn as compared with traditional horn is up to 19% more amplified. Finally, an optimized cubic Bezier profile for the horn has been designed, which has maximum displacement amplitude for higher MRR andsafe working stresses for the horn material.

    • The Rupee Odyssey


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      In this paper, the most significant contribution has been a change in the focus of research on exchange rate volatility from a traditional emphasis on events in India to a more comparative approach that examines the experiences of many countries simultaneously. The focus is on using Generalized Auto Regressive Conditional Heteroskedasticity (GARCH) to understand the behavior of British Pound, United States Dollar, Euro and Japanese Yen versus Indian Rupee.

    • Single and multiple odor source localization using hybrid nature-inspired algorithm


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      In this paper, optimization-based approach has been adopted to localize the odor source in an unknown environment. Two scenarios taken into consideration, first single odor source (SOS) with a point source emission at a constant rate and four multiple odor sources (MOS) with point source emissions and different release rates constant in time. In context to SOS, four environments that have distinct dimensional layout have been generated with slight variation in wind velocity and diffusion constant. In case of MOS, there are five environments with same layout but different contributing factors such as wind velocity, placement ofodor sources and emission rates which are considered to demonstrate its impact on success rate of algorithms. A recent optimization technique called hybrid teaching learning particle swarm optimization (HTLPSO) has been adopted and implemented in all the arenas, namely SOS and MOS, where mobile robots AKA virtual agents (VAs) are working in collaboration. There are group of VAs deployed in this operation ranging from {3–15}. To investigate the effectiveness of the algorithm, results of HTLPSO are compared with classical particle swarmoptimization (PSO) and teaching learning-based optimization (TLBO). It is observed that HTLPSO outperforms TLBO and PSO in arenas with larger dimensions while utilizing few iterations in comparison with other algorithms in case of SOS. HTLPSO also performs best in case of MOS, surviving the effect of wind velocity and change in emission rates. Only when odor sources are placed differently and scattered, TLBO gives the best result. Another highlight of HTLPSO is convergence with high accuracy even with less number of VAs.

    • Study on connecting tube dynamics for transient pressure measurement


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      The present study evaluates the dynamic response of connecting tubes for transient pressure measurement. A systematic study is conducted to quantify the amplitude and phase distortion of connecting tubes of diameter 1, 2 and 3 mm with different lengths (10–50 cm). The experimental measurements andtheoretical predictions have been carried out with both air and water as the working medium to cover a wide range of frequencies. The study highlights the underdamped nature of all the systems studied. The natural frequency of the system increases with an increase in the tube diameter and a decrease in tube length. The difference in natural frequency obtained from the experimental results and theoretical prediction is less for the smaller tube diameter (d = 1 mm) and more pronounced for the larger tube diameter. Larger tube diameters arerecommended to avoid amplitude and phase distortion errors, especially in the low-frequency range. However, resonance effects are more pronounced for larger tube diameters. The phase response of larger tube diametersremains close to zero over a large range of frequency (0–0.8 times the natural frequency); hence, this range is more suitable for applications where phase information is more important than amplitude. This study is useful for compensating the amplitude and phase distortion error encountered in transient pressure measurements

    • Hybrid controller for precision positioning application


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      In this paper, a precision positioning hybrid controller for long travel distance with submicron/nanometer resolution and accuracy is designed and developed. A hybrid control algorithm is designed to combine the coarse positioning system and a precision positioning system. The coarse positioning system consists of a linear stepper motor and coarse positioning controller, which is designed by microstepping with proportional-integral (PI) current feedback (MSPICF) control. In the precision positioning system, a piezoelectric actuator (PZA) is used. The mathematical model of the PZA has been represented by 2nd order massspringsystem with the Dahl hysteresis model and the model parameters are estimated by an autoregressive with exogenous terms (ARX) model identification technique using the input–output experimental data. The precision positioning controller designed by feedforward (FF) control which is the inverse of the mathematical model of the PZA and feedback (FB) control. The coarse, precision and hybrid controller is implemented using a low-cost DsPIC30F4012 microcontroller. Experiments have been performed to evaluate the performance of the controller

    • On mechanical and thermal properties of cryo-milled primary recycled ABS


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      The virgin thermoplastics have numerous applications in fused deposition modelling (FDM) process. Commercially, different thermoplastics are recycled through extrusion (without any reinforcement as primary (1°) recycled materials) for enhancing their reusability and sustainability. However, hitherto very littlehas been reported on mechanical and thermal properties of cryogenic (cryo) milled 1° recycled ABS (to be used on FDM-based 3D printer). In the present research article the cryo ball milling of 1° recycled ABS thermoplastichas been reported to explore the influence of cryo environment (-196 °C) on mechanical, thermal and surface properties of the ABS-based feed stock filament (prepared through screw extrusion) for further use on commercial FDM set-up (without any hardware/software change). The process parameters of cryo-milling (like frequency of vibration, milling time and grinding media weight) have been selected for investigations using Taguchi-based design of experiment (DOE). The study results show significant improvement in peak strength (PS) of the cryo-milled ABS in comparison with non-cryo-milled ABS without any degradation of thermal properties (mainly heat capacity). As regards the process parameters of cryo-milling, 30-Hz frequency, 15-min milling time and 32-g media weight are the best settings for maximum PS. The maximum value of PS observed was 61.32 MPa. The optical photomicrographs supported with 3D rendered images were captured to support the surface characteristics and porosity level in the wires (to be used as feed stock filament for FDM) prepared with cryo-milled ABS (powder samples).

    • PRIB-MAC: a preamble-based receiver initiated MAC protocol for broadcast in wireless sensor networks


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      Synchronizing data communication between nodes with energy efficiency by adapting different duty cycling mechanisms is the most important task of Medium Access Control (MAC) protocol in wireless sensor networks (WSNs). Most of the low-duty-cycle MAC protocols address the issue of unicast efficiently,ignoring the broadcast performance, which presents significant challenges due to the duty cycling. In this paper, we propose an asynchronous low-duty-cycle MAC protocol for broadcasts in WSN that incorporates the advantages of existing sender-initiated and receiver-initiated MAC protocols. The Preamble-Based Receiver-Initiated Broadcast MAC (PRIB-MAC) protocol is built on RI-MAC unicast MAC protocol by adding a preamble to support broadcasting. It is found that the duration of the preamble depends on the time difference in the wake-up schedule of the nodes and with an optimized wake-up schedule, the preamble duration of just 2% of the slot duration can give 100% node coverage in very less time compared with ADB: an efficient multi-hop broadcast protocol based on asynchronous duty cycling in WSNs.

    • Evaluation of artificial neural network in data reduction for a natural convection conjugate heat transfer problem in an inverse approach: experiments combined with CFD solutions


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      In this work, natural convection fin experiments are performed with mild steel as the fin and an aluminium plate as base. The dimension of the mild steel fin is 250 mm 9 150 mm 9 6 mm and the aluminium base plate is 250 mm 9 150 mm 9 8 mm. A heater is provided on one side of the aluminium base plate and themild steel fin emerges on the other side of the plate. The heater provides required heat flux to the fin base; several steady-state natural convection experiments are performed for different heat fluxes and correspondingtemperature distributions are recorded using thermocouples at different locations of the fin. In addition, a numerical model is developed that contains the dimensions of the fin set-up along with extended domain to capture the information of the fluid. Air is treated as a working fluid that enters the extended domain and absorbs heat from the heated fin. The temperature and the velocity of the fluid in the extended domain are obtained by solving the Navier–Stokes equation. The numerical model is now treated as a forward model that provides the temperature distribution of the fin for a given heat flux. An inverse problem is proposed to determine the heat flux that leads to the temperature distributions during experiments. The temperature distributions of the experiments and forward model are compared to identify the unknown heat flux. In order to reduce computational cost of the inverse problem the forward model is then replaced with artificial neural network (ANN) as data reduction, which is developed using several computational fluid dynamics solutions, and the inverse estimation is accomplished. The results indicate that a quick solution can be obtained using ANN with a limited number of experiments.

    • Mehar approach for solving dual-hesitant fuzzy transportation problem with restrictions


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      Recently, a new type of transportation problems (named as dual-hesitant fuzzy transportation problem) as well as an approach to find the optimal solution of dual-hesitant fuzzy transportation problems have been proposed in the literature. In this paper, some dual-hesitant fuzzy transportation problems are considered toshow that the existing approach is inappropriate as (i) The existing approach fails to find the optimal solution of dual-hesitant fuzzy transportation problems. (ii) On applying the existing approach different optimal transportation costs are obtained corresponding to alternative optimal solutions. Also, to resolve the inappropriateness of the existing approach, a new expression (named as Mehar score function) is proposed to transform a dualhesitant fuzzy set into a real number. Furthermore, a new approach (named as Mehar approach), based upon the proposed Mehar score function, is proposed to find the optimal solution of dual-hesitant fuzzy transportation problems

    • Optimizing warehouse network reliability under intentional disruption by increasing network ambiguity: a multi objective optimization model


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      In today’s world, intentional disruptions in networks are expanding and the impacts are seen in many parts of the world. An effective approach for reducing the impact of such disruptions is to confuse invaders. Increasing ambiguity in the network is one of the effective ways which may confuse the invaders. Toattain this goal, dummy facilities are added to the network. Dummy facilities are the facilities which are exactly the same as the real ones thus making it hard for the invader to make the distinction. In this paper, a new multiobjectivemathematical model is presented to suitably design a network consisting of real and dummy warehouses. One objective is to minimize the total cost and the other is set to maximize reliability. An index for assessing network reliability is also introduced and used. The model is solved using AUGMECON and NSGAII.Results demonstrate that establishing dummy facilities in the network will increase reliability while no significant cost is imposed.

    • VLSI implementation of high throughput parallel pipeline median finder for IoT applications


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      This paper proposes a high-throughput median finding architecture where the sorting of an incoming pixel is executed by a high-speed Compare and Select (CS) module. In this work, four clock pulses are required to populate the 4 X 4 window as four pixels are read at a time from the incoming grey image. This median finding process is carried out by parallel and pipeline median architecture. The proposed median finding process requires two read operations to take eight input pixels and generates four output pixels with a latency of seven clock cycles. The proposed architecture has been implemented on Xilinx Virtex–VII FPGA. The proposedarchitecture is synthesized using the SoC Encounter along with Faraday 90 nm standard cell library. The maximum operating frequency is 950.57 MHz, the total gate count is 4540, area is 0:40543 mm² and the dissipated power is 0.92617 mW. The high-throughput, high-speed and low-power-dissipation nature of the proposed architecture make it suitable for computationally extensive Internet of Things (IoT) applications.

    • Analysis of super lift Luo converter with discrete time controller


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      An observer based analysis is carried out to improve the dynamic responses of the super lift Luo converter with positive output voltage along with a digital controller. The dynamics of the closed-loop system is investigated using discrete time modeling technique which includes the dynamic compensation in the form ofprediction observer controller for obtaining output voltage regulation. The implementation which includes the digital state feedback and a load estimator is very simple and well-suited for the digitally controlled PWM converters. A suitable feedback matrix and a load estimator are selected to eliminate the error and to estimate the unmeasurable state variables. Thus we can obtain zero output voltage error, stability, robustness and stiff voltage regulation at the output. The feasibility and functionality of the discrete system are verified using simulation andexperimental prototype of digitally controlled PWM superlift Luo converter.

    • Deep Gaussian processes for music mood estimation and retrieval with locally aggregated acoustic Fisher vector


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      Due to the subjective nature of music mood, it is challenging to computationally model the affective content of the music. In this work, we propose novel features known as locally aggregated acoustic Fisher vectors based on the Fisher kernel paradigm. To preserve the temporal context, onset-detected variable-lengthsegments of the audio songs are obtained, for which a variational Bayesian approach is used to learn the universal background Gaussian mixture model (GMM) representation of the standard acoustic features. The local Fisher vectors obtained with the soft assignment of GMM are aggregated to obtain a better performance relative to the global Fisher vector. A deep Gaussian process (DGP) regression model inspired by the deep learning architectures is proposed to learn the mapping between the proposed Fisher vector features and the mood dimensions of valence and arousal. Since the exact inference on DGP is intractable, the pseudo-data approximation is used to reduce the training complexity and the Monte Carlo sampling technique is used to solve the intractability problem during training. A detailed derivation of a 3-layer DGP is presented that can be easily generalized to an L-layer DGP. The proposed work is evaluated on the PMEmo dataset containing valence and arousal annotations of Western popular music and achieves an improvement in R² of 25% for arousal and 52% for valence for music mood estimation and an improvement in the Gamma statistic of 68% for music mood retrieval relative to the baseline single-layer Gaussian process.

    • Synergy of hybrid textile reinforced concrete under impact loading


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      The article presents a novel hybrid concrete composite which is produced by combining glass and basalt textiles for achieving enhanced impact resistance compared to their independently reinforced counterparts. A full factorial analysis was performed to determine the synergy of two types of textiles and theircombination on the impact strength and energy absorption. The two levels of key factors were considered for analysis such as the type of textile and impact energy level, and variance. The influencing parameters showed statistical significance with more than a 90% confidence level concerning impact resistance and energyabsorption. The combination of two textiles showed the highest impact resistance irrespective of the energy levels, compared to the use of single textiles. The findings demonstrated that the energy absorption of hybrid textile reinforced concrete is not significantly enhanced with the increasing level of impact energy. At the high levels of impact energy, in comparison to the hybrid textile reinforced concrete slabs and basalt textile reinforced concrete, more energy is absorbed by the glass textile reinforced concrete slabs. Thus, in hybrid textile reinforced concrete, it is indicated by the failure pattern that combining basalt and glass textile influences the degree of local failure. Therefore, this research emphasizes on the synergy to customize and optimize textile reinforced concrete with superior impact resistance and energy absorption for the protection of structures in theevent of impact loading.

    • Detection and characterization of CO gas using LTCC micro-hotplates


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      In the present work, a tin oxide (SnO₂)-based gas sensor has been fabricated on Low Temperature Co-fired Ceramic (LTCC) substrate by screen printing method for detection of the silent killer gas (carbon monoxide). The tin oxide paste has been prepared for deposition on inter-digitated electrodes patterned on LTCC substrate. The developed gas sensor module has been fired at different temperatures (625, 820 and 860°C) and the effect of firing temperature has been studied. The developed sensor is small in size with low power consumption, better sensitivity and repeatability.

    • Improved performance in multi-objective optimization using external archive


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      We show that the use of an external archive, purely for storage purposes, can bring substantial benefits in multi-objective optimization. We first present a new scheme for archive management. We then combine it with the NSGA-II algorithm for solving multi-objective optimization problems and demonstrate significant improvement in performance. Furthermore, we show that the additional computational effort in handling the external archive is insignificant in problems for which objective functions are expensive to evaluate.

    • Analysis, fabrication and detailed comparative study of surface and interior rotor PMSM prototypes of identical nominal ratings and stators


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      This paper presents an in-depth analysis, performance evaluation and comparative study of two 5-kW, 8-pole, 750-rpm laboratory prototypes of a permanent magnet synchronous motor (PMSM) of identical nominal ratings with surface and interior permanent magnet (PM) rotor structures having same stator and armature winding (fractional slot distributed winding). The key electrical (such as rated voltage, current, power, speed, number of poles, etc.) and mechanical variables (such as overall volume, air-gap length, rotor diameter, shaft dimensions and magnetic material) of the fabricated prototypes have also been kept same to pin-point thedirect influence of the two different rotor configurations (surface and interior PMSM) on the parameters, performance and operation of these PMSMs. For the two machines, a detailed comparison of air-gap flux density distribution, THD in induced voltage, torque ripple, losses, efficiency, torque–speed characteristics, field weakening capability, steady-state parameters at different operating conditions, etc. has been conducted. The salient observations from this comparative study have been duly highlighted. This paper also includes an indepthcomparison of volume and cost of PM used in the two types of PMSMs. The short-time performance figures of the said motors have also been presented. The possibility of demagnetisation of PMs, during a sudden fault, has also been investigated for both PMSMs. Challenges of making of both rotors have been discussed. The theoretically determined parameters and analytically evaluated performance figures have been verified through standard FEM packages and then validated experimentally on the prototypes.

    • A soft computing methodology to analyze sustainable risks in surgical cotton manufacturing companies


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      A well-organized sustainable risk management in an organization often generates environmental and economic advantages. Addressing ‘‘sustainability and risk’’ simultaneously, an organization is more capable of enduring challenges that produce environmental and operational stability in management. In an industrialorganization, these primary areas of concern involve social responsibility and a focus on occupants’ health and well-being; both areas address environmental and climate change, with an end result of increasing competitiveness and profitability. The key challenge lies in exploring sustainable risks associated with the industry so that they are addressed strategically. This research work is one such attempt to find sustainable risks in the manufacturing sector. This research is the outcome of a case study conducted in three leading surgical cotton manufacturing companies in the southern part of India. A hybrid multi criteria decision making based fuzzydecision making trial and evaluation laboratory and analytic network process with preference ranking organization method for enrichment evaluations (FDANP with PROMETHEE) methodologies is used to derive the results. The final outcome of this paper presents the identified critical sustainable risks from the case study, andalso serves as a model for risk managers in manufacturing sectors. By identifying sustainable risks at an early stage, a company may avert the occurrence of undesirable incidents while, at the same time, may enhance their production capacity.

    • Effect of horizontal vibrations on mass flow rate and segregation during hopper discharge: discrete element method approach


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      Vibration is often utilized as a means of initiating and/or controlling flow from hopper in industries dealing with powder/granular materials such as packing, conveying, etc. The effect of horizontal vibration on gravity flow of granular material from conical hopper is modeled using the discrete element method. Material considered in this study includes glass beads of diameter ranging between 0.7 mm and 2.0 mm. The flow dynamics and segregation of material are analyzed for different mixtures characterized based on mass percentageof smaller particles (fines) and multi-component mixtures (binary and ternary) at different vibration parameters. The study includes the influence of vibration frequency, acceleration amplitude, fines percentage, diameter ratio and mixture components on segregation and mass flow rate during vibratory hopper discharge.The extent of segregation is calculated by means of mass fraction of fines inside hopper for different operating conditions. The numerical results indicate that the increase in vibration acceleration at a fixed frequency results into increased mass flow rate and there exists acceleration amplitude beyond which segregation is predominant. Mixture components play significant role in segregation behaviour and binary mixture suffers more segregation as compared to ternary mixture. The spatial distribution of the velocity profile indicates that different mixturesbehave differently at a particular vibration conditions. The phenomena like sieving or percolation are also observed based on the analysis of top view simulation snap shots.

    • Accelerated Single-Linkage algorithm using triangle inequality


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      Single-Linkage algorithm is a distance-based Hierarchical clustering method that can find arbitrary shaped clusters but is most unsuitable for large datasets because of its high time complexity. The paper proposes an efficient accelerated technique for the algorithm with a merging threshold. It is a two-stage algorithm with the first one as an incremental pre-clustering step that uses the triangle inequality method to eliminate the unnecessary distance computations. The incremental approach makes it suitable for partial clustering of streaming dataalong with the collection. The second step using the property of the Single-Linkage algorithm itself takes a clustering decision without comparing all the patterns. This method shows how the neighbourhood between the input patterns can be used as a tool to accelerate the algorithm without hampering the cluster quality. Experiments are conducted with various standard and large real datasets and the result confirms its effectiveness for large datasets.

    • Optimization of machining parameters in sinking electrical discharge machine of caldie plastic mold tool steel


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      The aim of this study was to investigate the machinability of caldie cold work tool steel using the electro erosion technique. In the experimental study, graphite and copper were used as the electrode materials. Three levels for discharge current (6, 12 and 25 A) and three levels for pulse duration (50, 100 and 200 ls) wereused as machining parameters. The experimental model was designed according to the Taguchi L18 orthogonal array. Signal/noise ratios, graphs and regression analysis were used to evaluate the results of the experiments. Using the Taguchi technique, the optimum machining parameters were determined with process outputs for surface roughness, material removal rate and electrode wear rate. The optimum levels were found to be A1B1C1 for surface roughness and electrode wear rate and A2B3C3 for material removal rate. The effect of control factorson experimental outputs was calculated by performing ANOVA. According to the ANOVA results, discharge current was the most effective parameter on machinability. When the experimental data were compared statisticallywith the Taguchi optimization and regression model data, the results of the designed models were shown to be successful.

    • Modeling multiple damage mechanisms via a multi-fiber multi-layer representative volume element (M²RVE)


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      This paper is aimed at incorporating all possible micro-scale damage mechanisms, namely, fiber failure, matrix cracking, fiber-matrix debonding and delamination in multi-fiber multi-layer representative volume element (M²RVE) subjected to multi-axial loading. Different loading conditions have been selected toinduce a particular or combined damage mechanism/s to study the damage evolution. The predicted constitutive material responses for tensile and in-plane shear loading by M²RVE are in reasonably good agreement with theexperimental results. M²RVE then used for capturing all the microscale damage mechanisms even for complex multi-axial loading. The stress–strain responses have been effectively captured for different combinations of dominant damage mechanisms.

    • Development of a Markov chain based tool for studying effectiveness of Vendor Managed Inventory and result analysis from a pilot study


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      Vendor Managed Inventory is looked upon as a reliable method for inventory management. There is still a scope for improving the process. In this work, we presented a report on the pilot setting and its testing for Vendor Managed Inventory in an auto parts manufacturing company in Northern India. The pilot study was conducted by switching supplies of six components of an assembly from conventional to VMI mode. The switch was carried out in January 2018 and a time series plotting of five performance indicators nine months prior to and nine months after the switch was done and analysed. Further, transition probabilities of inventory performance index were estimated based upon the correlations with four most influential performance indicators. Sixteen state switching scenarios were modelled and Markov chain analysis of Inventory Performance Index fortwo of them was carried out to test the VMI performance.

    • Order reduction mechanism for large-scale continuous-time systems using substructure preservation with dominant mode


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      This work is about a balanced truncation type order reduction method which is developed for stable and unstable large-scale continuous-time systems. In this method, a quantitative measure criterion for choosing the dominant eigenvalues helps in determining the steady-state and transient information of thedynamical system. These dominant eigenvalues are used to form a new substructure matrix that retains the dominant modes (or may desirable mode) of the original system. Retaining the dominant eigenvalues in the reduced mode assures stability and results in greater accuracy as the retained eigenvalues provides a physical link to the real system. In the quest to preserve the dominant eigenvalue of the real system, the proposed technique uses Sylvester equation for system transformation. Having obtained transformed model, the reducedmodel has been achieved by truncating the non-dominant eigenvalues using the singular perturbation approximation method. The efficiency and accuracy of the proposed method has been demonstrated by the benchmark test systems which were from the state-of-the-art models.

    • Predictive safety assessment for storage tanks of water cyber physical systems using machine learning


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      Cyber physical systems (CPS) are critical to the infrastructure of a country. In addition to being vulnerable to hardware and software failures, and physical attacks, they are now becoming vulnerable to cyber attacks because of their use of off the shelf servers and industrial network protocols. Availability on World WideWeb, for monitoring and reporting, has further aggravated their risk of being attacked. Once an attacker breaches the network security, he can affect the operations of the system, which may even lead to a catastrophe. Variousmachine learning, mathematical and formal models try to detect the departure of the system from its expected behaviour. However, little or no work predicts how long the system would take to become unsafe. We here propose a machine learning predictive safety assessment approach that quickly calculates the time to being unsafe (TTBU) of a water-based CPS. We validate our results on a complete replicate of the physical and control components of a real modern water treatment facility. Our approach is fast, scalable and robust to noise. The model can be easily updated to match the changing behaviour of the system and environment.

    • A methodology for optimal deployment and effectiveness evaluation of air defence resources using game theory


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      Planning for the deployment of air defence (AD) assets in areas of operation to achieve maximum protection coverage against enemy air threats is an important problem in military science.Athree-stage approach to address the problem is proposed: a static methodology to deploy AD resources to maximize the coverage and performance of radar systems under various terrain conditions is studied, followed by the second stage that considers the dynamics of enemy air attacks and Electronic Warfare (EW) conflict that ensues between the attackerand defender modeled using game theory. In the final stage the conflict scenarios modelled using game theory are represented as AD wargames and experimented on a battlefield simulation test-bed called Air Warfare Simulation System (AWSS) to assess the AD effectiveness in operations. The first stage uses a coverage-based optimization, and the second stage is modelled using game theory. The strategies of the attacker (enemy aircraft) and defender (sensors-radars grid and weapons-missiles grid) in the EW operations as Electronic Counter Measures and Electronic Counter-Counter Measures in a game-theoretic setting are illustrated using several scenarios.

    • Design and evaluation of low-cost network architecture for persistent WiFi connectivity in trains


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      With the exponential growth in the number of mobile devices, providing Internet access via WiFi in trains is rapidly becoming a necessity. Cellular network is predominantly used for the backhaul connection to the train. However, the railway companies of developing countries may not go for cellular-network-based solutionsmainly for two reasons: (1) high deployment cost of a cellular network and (2) lack of sufficient coverage of existing cellular networks of telecom companies along the railway tracks. In this paper, we propose a Software Defined Networking (SDN)-based architecture to provide Internet connectivity inside trains. The backhaulconnection to the train, in the proposed architecture, is provided via WiFi. Deployment of such an architecture is more cost-efficient than that of a dedicated cellular network of the same capacity, or that of the existing cellularnetworks of telecom companies, since there are no running tariffs and the spectrum is free. Moreover, this architecture can be used to provide connectivity in the coverage holes of the existing networks of the telecom companies. Through simulation, we show that the architecture can provide high throughput and packet delivery ratio while maintaining per packet delay within reasonable limits inside a train.

    • A mixed fractional Vasicek model and pricing Bermuda option on zero-coupon bonds


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      This paper considers the problem of pricing of Bermuda options on zero-coupon bond in which the dynamics of the interest rate model follows the mixed fractional Vasicek model. The strong convergence of the Euler discretization scheme for the mixed fractional Vasicek model is analysed. Specifically, we find an approximate formula for zero-coupon bond price. Numerical experiments are provided and compared for Bermuda-style call and put options with the Monte Carlo simulation approach.

    • Evaluation of the physico-mechanical properties of activated-carbon enhanced recycled polyethylene/polypropylene 3D printing filament


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      In this study, recycled polymer feedstocks (high-density polyethylene, HDPE and polypropylene, PP) were added with different percentages of activated carbon (AC) made from coconut fiber waste – 0, 2, 4, 6, and 8%. The melting temperatures of the recycled HDPE and HDPE/PP filaments were 113 and 170°C, respectively. The addition of AC improved the thermal stability of the recycled filaments up to 28% while decreased the crystallinity of the filament produced, resulting in a more uniform surface with less crazing. Incompatibility of the recycled HDPE and AC was observed. However, the presence of PP greatly enhanced the compatibility of AC with the HDPE polymer. With the addition of 8% AC to the recycled HDPE/PP, the elongation at break of the recycled HDPE/PP filament reached 54.2%, about 10 times higher than that without AC, which could be due to the passive local interfacial bonding of AC with the methyl group of the PP matrix. The improved elongation at break would in turn aid in 3D printing of products with better elasticity.

    • Green corrosion inhibitor: A comparative study


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      A comparative study of the inhibitory effect of various parts of the plant Mimusaps Elangi (ME) extract (leaves, fruits, barks, seeds) on the corrosion of mild steel in 1 N HCl medium was investigated using weight loss method, potentiodynamic polarization and electrochemical impedance spectroscopy techniques. Thepolarization studies revealed that the plants extract act as mixed type inhibitor. It was found from the weight loss method that the inhibition efficiency of ME extracts increase in concentration dependents manner which was also supported by the results of electrochemical techniques. On comparison, maximum inhibition efficiency was found in ME leaves extracts with 98.50% at 20 ppm concentration. The SEM morphology of the adsorbed protective film on the mild steel surface has confirmed the high performance of inhibitive effect of the plant extract. Surface coverage values were tested graphically for suitable adsorption. Temperature studies revealed decrease in inhibition efficiency with increase temperature which suggests physisorption mechanism.

    • Optimal design of spindle-tool system for improving the dynamic stability in end-milling process


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      This paper presents an optimum design approach of a spindle-tool system to improvise the dynamic stability of end-milling. Initially, the tool-tip frequency response function is obtained by analyzing the spindletool assembly with the finite element model. The chatter-free regions are maximized using an optimizationmethodology by considering the spindle and tool parameters as design variables. A simulated experimental dynamic data consisting of the average stable depth of cut is obtained for different combinations of design variables by the method of design of experiments (DOE) and analysis of variance technique is applied to find the influence of design parameters on the outputs. Based on the obtained results, the data is generalized with the help of a neural network model that works as an estimator of the average stable depths for the optimization module. The average stable depth of cut over a range of operating speeds is maximized by selecting optimal tool and spindle parameters.

    • Microstructure and mechanical properties of low power pulsed Nd:YAG laser welded S700MC steel


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      Thermomechanically controlled processed steels have gained attention increasingly by many industries. In this research S700MC steel is successfully welded using low power pulsed Nd:YAG laser and the microstructure and mechanical properties are investigated. It is shown that the average power and overlapping factor both affect the weld geometry. Full penetration with double-sided welding achieved on 2 mm thick plates autogenously. Optical metallographic methods and SEM/EDS were used to evaluate the resulting microstructures.The evaluations revealed that the weld metal microstructure contains different morphologies of ferrite such as acicular, allotriomorphic and Widmansta¨tten as well as bainaite and martensite structure in the weld zone. Also, no noticeable heat affected zone was detected near the fusion zone of the weldments. In addition tomicrostructures investigation, micro hardness and tensile tests were performed to evaluate mechanical properties. Hardness measurement results exhibit higher hardness values in weld zone than that of in the base metal. The tensile test revealed a ductile fracture behavior which happened in the base metal, due to proper weld zone microstructure. The strength and elongation of the prepared joints were 774 ± 14 MPa and 26.5 ± 2.5%, respectively.

    • Design, analysis, fabrication, control and comparative study of two different-shaped plate levitation prototypes


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      This paper presents a comparative study on the design, modelling, electromagnetic analysis based on finite-element software, fabrication and experiment on rectangular flat (148 g) and C-shaped (148 g) levitationprototypes based on steel plates. No mechanical restrainer has been used in the transverse direction for the levitation. This aspect of the work is an improvement over existing work reported in the published literature. The entire set-up has been designed, fabricated, analytically investigated and experimentally evaluated and verified. The finite-element model (FEM) has been derived using standard commercial package(s). The analytical model has been obtained using specific permeance concepts following Robert Pohl’s method. Excellent correlationbetween the predicted and experimental results is a highlight of the work. The stability against transverse mechanical perturbation has also been investigated. Control system design and implementation is successfully done.

    • ANN-based optimization framework for performance enhancement of Restricted Access Window mechanism in dense IoT networks


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      IEEE 802.11ah, marketed as Wi-Fi HaLow, operates at Sub 1 GHz spectrum to provide broad coverage, high throughput, energy efficiency and scalability. This makes IEEE 802.11ah a promising candidate for the Internet of Things (IoT). One of the major enhancements in the MAC layer is the Restricted AccessWindow (RAW) mechanism, which focuses on mitigating the channel contention in dense networks. The RAW mechanism reduces the channel contention among the group of devices by restricting their channel access to the allocated RAW slots. Since the standard does not specify the optimal RAW configuration parameters, choosing the number of RAW slots has significant impact on the performance of the RAW mechanism. In this paper, we develop an optimization framework by exploiting the Multilayer Perceptron Artificial Neural Network (MLPANN)to find the optimal number of RAW slots that can maximize the performance of the RAW mechanism in terms of throughput, delay and energy consumption. We train the ANN using the network size, Modulation and Coding Schemes, duration of the RAW period and the optimal number of RAW slots found using the analyticalmodel presented in this paper. Further, we evaluate the performance of the RAW mechanism by choosing the optimal number of RAW slots provided by the ANN-based optimization framework. Results show that the proposed scheme significantly enhances the performance of the RAW mechanism. Finally, the analytical results are corroborated using extensive simulations done in ns-3.

    • Intermittent demand forecasting: a guideline for method selection


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      Intermittent demand shows irregular pattern that differentiates it from all other demand types. It is hard to forecasting intermittent demand due to irregular occurrences and demand size variability. Due to this reason, researchers developed ad hoc intermittent demand forecasting methods. Since intermittent demand has peculiar characteristics, it is grouped into categories for better management. In this paper, specialized methods with a focus of method selection for each intermittent demand category are considered. This work simplifies theintermittent demand forecasting and provides guidance to market players by leading the way to method selection based on demand categorization. By doing so, the paper will serve as a useful tool for practitioners to manageintermittent demand more easily.

    • A comparative study of sand-blasted and electro-discharge-machined surfaces of steel substrates


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      Sand blasting is a common process to prepare steel surfaces prior to thermal spray coating application to obtain better coating adhesion. Die-sinking electro-discharge machining (EDM) is a non-conventional machining process that also produces rough surfaces. In this study, steel (EN 31) surfaces are prepared by both methods to obtain the same average roughness (Ra) of 3, 5 and 7μm. The prepared surfaces are studied and compared to investigate whether the rough EDMed surface is suitable for applying thermally sprayed Ni–5Al coating on it or not. XRD and scanning electron microscopy analysis of the samples are carried out. Nanohardness behaviour of the samples is also studied. Failure in obtaining well-adhered D-gun-sprayed Ni–5Al coating on EDMed surface is due to the presence of hard cementite and austenite phases on the surface. It isconcluded that for thermal spraying, adhesion of coating material on substrate cannot be achieved without proper metallurgical compatibility. Also, for thermally sprayed Ni–5Al coating application on steel substrate, grit blasting method is the suitable process for substrate preparation.

    • Effect of transverse reinforcement corrosion on compressive strength reduction of stirrup-confined concrete: an experimental study


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      Stirrups of reinforced concrete members are very prone to corrosion compared with longitudinal reinforcements, resulting from their small concrete covers, which lead to concrete cracking and spalling. Due to the adverse effects of corrosion, this article aims to investigate the amount of reduction in the capacity ofreinforced concrete specimens in different corrosion degrees. For this purpose, an experimental investigation is carried out on 22 reinforced and non-reinforced rectangular prism specimens, of which 12 reinforced specimens are corroded. The test variables contain the corrosion percentage, and the stirrup diameter and spacing. Eventually, all specimens are tested for compressive strength for 90 days. The experimental results show that the reduction of compressive strength depends on the corrosion percentage and stirrup diameter. According to thisconclusion, a new formulation is proposed to express the relationship between compressive strength reduction and its effects.

    • Component blending for bitumen production for Indian refineries


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      This investigation pertains to the bitumen production using component blending. During the manufacture of blended bitumen, the proportion of the constituents, the temperature during blending, and the duration of blending are selected to meet the penetration at 25°C and the absolute viscosity at 60°C as per theIndian specifications. The choices of the blend parameters become challenging when the constituents from multiple crudes are blended to produce different paving grades. Two constituent and three constituent blends for four different grades of bitumen were prepared in a laboratory blending facility from four different crudesources. A design of experiments framework was used to develop prediction models for penetration and viscosity. Simulations were carried out to suggest blending schemes to manufacture all the viscosity grades from different crude sources. Correspondence between the viscosity grade and high-temperature performance grade was observed for blend parameters for the crude sources investigated in this study.

    • In-situ stress partition and its implication on coalbed methane occurrence in the basin–mountain transition zone: a case study of the Pingdingshan coalfield, China


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      The basin–mountain transition zone presents complex geologic structures and non-uniformly distributed in-situ stress. Studying the spatial distribution laws of in-situ stress and their influences on coalbed methane (CBM) occurrence in coal seams plays a significant role in CBM extraction and prevention of coalminedisasters. Based on the actual measured in-situ stress data, CBM content and gas pressure data in the Pingdingshan coalfield, located in the basin–mountain transition zone in the south of the late Palaeozoic basins in the North China block, this research investigated the distribution characteristics of geologic structures andpartition of in-situ stress as well as the effects of in-situ stresses on CBM occurrence in the research area using evolution theories of geologic structure and a statistical analysis method. The research results show that geologicstructure and in-situ stress distribution in the research area have obvious partition characteristics. The research area is divided into three tectonic zonations. In-situ stress distribution is controlled by tectonic types and tectonic stress field evolution of different tectonic zonations, which are divided into high tectonic stress zonation,tectonic stress zonation and vertical stress zonation from east to west. Also, the research results reveal the characteristics of each stress zonation and the relationship between CBM occurrence and in-situ stress in thisresearch area.

    • Univariate data-driven models for glucose level prediction of CGM sensor dataset for T1DM management


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      The advent of machine learning has made a remarkable impact in the field of healthcare. Diabetes mellitus is a metabolism abnormality that is posing severe threat, exercising substantial pressure on human health worldwide. Diabetes mellitus is a public health problem around the world. In 1980, 108 million adultsworldwide had diabetes. By 2040 the number is expected to reach 642 million adults. Hence extensive research in interdisciplinary field that uses skills from various fields such as statistics machine learning, artificial intelligence,visualization, etc. is carried out for better management of diabetes. In this paper, the focus is to use time series forecasting algorithms. Data-driven models in time series machine learning are used to derive meaningful and appropriate information from large volumes of blood glucose level and related data for precise forecasting of upcoming blood glucose level fluctuations. Not only can the patient and physician be informed beforehand, to avert complications, but also it aids in predicting response to certain medications with ease. In this case, univariate data-driven models from time series machine learning algorithms are implemented on 2 different continuous glucose monitoring sensor datasets: Libre Pro dataset of 10 patients and Ohio T1DM dataset of 6 patients. A comparison of performance evaluation metrics of the different time series machine learning algorithmsis drawn based on root mean squared error (RMSE), mean average percentage error (MAPE) and Theil’s U, which are statistical analyses, and Clarke’s error grid, which is clinical analysis for prediction horizon from 15 to 45 min. Using Holt’s Linear AAN Algorithm on Libre Pro dataset with alpha and beta of 0.99 provided the least error among exponential smoothing algorithms with RMSE of 7.98 mg/dl for 15 min, 19.47 mg/dl for 30 min and 28.40 mg/dl for 45 min prediction horizon. Theil’s U coefficient was 0.12 for 15 min, 0.39 for 30 min and 0.72 for 45 min prediction horizon. Autoregressive Integrated Moving Average (ARIMA) Algorithmgave the best performance evaluation results with RMSE of 7.07 mg/dl for 15 min with a MAPE of 3.98. The performance results were on par when these algorithms were tested on Ohio T1DM dataset. ARIMA Algorithm gave the best performance evaluation results with RMSE of 13.14 mg/dl for 15 min with a MAPE of8.213. The difference in the error coefficient for Ohio dataset was due to missing data.

    • Performance evaluation of mechanically pressed Magnesium/Teflon/ Viton (MTV) decoy flare pellets


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      Infra-red decoy flares constituting of Magnesium, Teflon and Viton or MTV, is the most widely acceptable off-board counter measures among majority of the defence forces across the world. These flares are essentially pyrotechnic compositions operating in the range of 3–5lm wavelength owing to the selective emission of the combustion products (MgO, MgF₂ and oxides of carbon namely CO and CO₂). However, literature on manufacturing techniques and performance characteristics of standard configurations flare pellets developed and supplied by few firms globally is somewhat restricted. Hence, this study is an attempt to evaluate the performance of mechanically pressed 50 mm diameter cylindrical MTV pellets. While varying the process parameters viz. charge mass and applied load for pelleting, the cross-sectional area of the pellets and dwell timeof applied load have been maintained constant. With increase in applied load, elastic/brittle fracture of the particles occur which increases surface area of contacts between particles. The optimum density was achieved at 8 tons of load. Similarly, the improvement in density with increase in charge mass was observed till L/D ratio of unity was achieved. SEM images confirmed the increase in contact surfaces and reduction in size of particles owing to elastic/brittle fracture. With increase in applied load, the available surface area decreased and there wasa conspicuous increase in burn time. With increase in charge mass, the quantity of pyrotechnic mixture available for burning increased leading to increase in burn time.

    • Reduction of false positives in the screening CAD tool for microcalcification detection


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      Breast cancer is one of the leading causes of cancer deaths among women worldwide. Early diagnosis of breast cancer can help in reducing the mortality rate. The major challenge in the early diagnosis of breast cancer is the fewer number of radiologists available per million population in developing countries. Thetotal number of radiologists is less than 30 in many third world countries. Since majority of the screening mammograms are normal or do not show any cancer signs, there is need of a screening computer-aided diagnosis (CAD) tool that can detect normal mammograms correctly and thereby reduce the burden on radiologists. Thus, a screening CAD is developed that is able to detect microcalcification clusters in mammogram with 100% sensitivity on the subset of DDSM, INbreast and PGIMER-IITKGP databases at lower false positives ascompared with state of the art methods. The synthetic minority over-sampling technique and the majority class under-sampling based on data distribution are used to improve the classifiers performance by reducing the false positives. An approach based on principal component analysis is proposed to further reduce the false positives by removing the vascular calcifications that are not of any clinical significance and may increase the false positives.

    • Performance analysis of a vortex chamber under non-reacting and reacting conditions


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      A series of non-reacting and reacting flow experiments are performed in a vortex combustion coldwall (VCCW) chamber using gaseous oxygen and gaseous hydrogen as propellants. Oxidizer is injected tangentially at the aft end of a combustion chamber from four ports. Hydrogen is injected axially from the top centre of the chamber. The oxidizer to fuel mixture ratios considered for the experimental studies are in the range of 4.2–6.0 for non-reacting case, and 6.38 for reacting flow experiments. Numerical simulations under non-reacting conditions are conducted to understand the flow behaviour in the chamber at a mixture ratio of 4.2 considering the same propellants used in the experiment. Results from non-reacting flow cases indicated that the chamber pressure increased by 0.8 bar with an increase in the mixture ratio from 4.2 to 6.0. The chamber pressure developed under the reacting flow conditions is found to be higher by around 1.3 bar compared with the non-reacting flow condition. The oxidizer concentration is found to be higher along the inner chamber wall, thus limiting the wall surface temperature to 360 K in the reacting conditions.

    • Writer identification using graphemes


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      This paper is presenting a handwriting strokes and grapheme-based offline writer identification framework. This framework works by firstly measuring the hand pressures during script writing using identical grapheme and writing strokes and then generates the pressure descriptors which are rotation as well as scaleinvariant. The descriptors are used to present different hand pressure distribution accuracies which are defined according to approximation-coefficients of the grapheme zone, perpendicular lines average over the handwritten script skeleton, stroke-width, and handwritten script skeleton grapheme. Discrete-Cosine Transform and Principal- Component-Analysis methods are used to evaluate the descriptors execution accuracy. The performance of the proposed method is assessed with the help of one-versus-all strategy and the k-fold validation is done with the help of Structural Support Vector Machine (S-SVM). Whereas heuristic enhancement calculation based simulated annealing is used to identify the S-SVM hyper parameters. The performance assessment of the handwriting strokes and grapheme based offline writer identification framework with single character gives the encouraging results. Also the combination of the characters enhances the accuracy as well as overall performance of personality identification up to 99.99%.

    • Position-sensorless direct torque control of grid-connected DFIG with reduced current sensors


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      Direct torque control (DTC) of a grid-connected doubly fed induction generator (DFIG) necessitates at least 2 stator current sensors, 2 rotor current sensors and a rotor position sensor. This letter presents a position-sensorless DTC scheme of DFIG without rotor current sensors. The elimination of two rotor currentsensors and position sensors improves hardware reliability by reducing the redundancy of physical components to be used. In the proposed scheme, the rotor flux vector magnitude and torque are estimated using measurable stator quantities. The effectiveness of proposed position-sensorless DTC scheme is validated using MATLAB/ Simulink for a 2-MW DFIG-based wind energy conversion system (WECS).

    • A real-time fast defogging system to clear the vision of driver in foggy highway using minimum filter and gamma correction


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      Fog is the most hindrance and unavoidable problem faced by drivers while driving. Due to foggy condition and poor visibility, especially in early morning and late-night, drivers are unable to see distant object on the road. As a result, possibility of road accident increases. In this article, a fast-real-time vision-baseddefogging system is proposed to clear the vision of highway during driving in the foggy environmental condition. The proposed system can remove the haziness of the driver’s vision and can present a clear view of the road within a very short span of time. Processing of each frame is comprised of four steps: calculation ofatmospheric light using minimum filter, transmission map, scene radiance and finally gamma correction is applied for removing the haziness with perfect contrast adjustment. In order to reduce time complexity, instead of estimating atmospheric light for each frame, it is calculated at an interval of 5000 frames. Many real-timeheuristic tests have been conducted during day as well at night on the highway and test analysis reveals that, after defogging, the distance of visibility increases by more than 65% during heavy fog. Besides, there is a massive increase in visibility during low foggy condition also.

    • Effect of cryogenic temperature and frequency on copper coils


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      There is increasing interest in development of magnetic energy storage with conduction cooling. In contrast with the liquid- and gas-cooled coils, the conduction-cooled coils are expected to have significant amount of thermally conducting structures. These thermal structures are usually made of copper, which is also a good electrical conductor. Thus, it is expected that the support structures would modify the resistances and inductances seen by the front-end converters connected to these coils. The paper, thus, presents detailed analysisand experimental results investigating the impact of temperature and frequency variations on conduction-cooled coils. The frequency variations are considered because the front-end converters are likely to produce high frequencycurrents in the coil. The results indicate that there is a significant reduction in the inductance of the coil when temperature is reduced and remarkable change is also observed when operating frequency is increased. The increase in frequency is known to increase the resistance, but significant increase in resistance isalso observed at low temperature when frequency is increased. The results indicate that beyond a certain frequency, the frequency effects dominate the observed resistance values of the coils.

    • DVSMS: dynamic value stream mapping solution by applying IIoT


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      The purpose of any business is to delight the customer as a primary stakeholder, thereby enhancing the growth and profitability. Understanding customer needs and building them on end to end value chain not only will result in serving customers on time, but also improve the effectiveness of the processes to retain competitiveness. Value stream mapping remains a popular visualization tool in the hands of the Lean Manager who seeks to produce more with less. However, value stream mapping (VSM) tends to be static and skill dependent. With the advent of Industrial Internet of Things (IIoT), there could be a paradigm shift on how VSMcould be leveraged for maximizing results. IIoT makes it possible to convert the VSM as a dynamic one, enhancing with several additional parameters measured simultaneously in real time, making the relationship between cause and effect more visible. Literally, with the addition of IIoT, we could digitally re-live themoments from the past to identify the connections between the cause and effect more specifically with better accuracy. In this paper, we attempt to clarify how IIoT could enhance the VSM as a strategic differentiator for making better decisions. In a sensor-based efficiency monitoring system, the VSM becomes dynamic; thereby all the parameters including the bottleneck operations could be continuously monitored and acted upon to attain the future state eliminating the dependency on the expertise of the people.

    • Measuring congestion by anchor points in DEA


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      One of the most important issues in microeconomics is congestion. In general, an increase in inputs will result in an increase in outputs. However, in some cases, it does not happen. Hence, in these situations congestion occurs. The existence of the congestion reduces efficiency of Decision Making Units (DMUs), so determination of congestion is highly regarded. Some studies suggested methods to determine the congestion via solving conventional Data Envelopment Analysis (DEA) models, in which first an inefficient unit was depicted on the BCC frontier. However, sometimes, some optimal projections are obtained, where some previous models encounter problems. In this paper, according to S-shape form of the production function and with respect to the geometric features of anchor points, we have developed an algorithm by the connection between the anchor points and congestion definition. In this algorithm, with no need for efficiency value and projecting the inefficient DMUs on BCC efficiency frontier, only by determining the anchor point with the largest output and comparing inefficient units with it, with an easier calculation, and solving conventional DEA models, congested DMUs and their status of congestion are obtained and their values are calculated. At the end, the proposed algorithm is illustrated by some examples and the results are compared to those of the existing methods.

    • Development of a long pulsed RF test stand and its applications for performance studies of 1 MW CW klystron


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      Research and development activities of high power microwave sources for powering RF cavities of Indian Spallation Neutron Source and Accelerator Driven Subcritical Systems are underway at RRCAT. Front end accelerating structures such as Radio Frequency Quadrupoles and Drift Tube Linac demand pulsed RFpower up to 1 MW. A 1 MW pulsed RF system based on TH 2089 klystron amplifier at 352.2 MHz with pulse width capability up to 1.5 ms has been developed and tested. A compact 100 kV, 20 A converter type modulatorwith pulse width capability up to 1.6 ms has been used to energize the klystron of RF test stand. The performance of the klystron in pulsed mode operation has been studied and presented. The variation in the RF output power was measured and it is within ±0.75%. The phase variation of RF output power within the pulse and the pulse to pulse is less than ±2.5°.

    • Impact penetration and perforation performance of square sandwich panels with EPS foam core


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      This paper addresses the impact penetration and perforation behaviour of sandwich panels having a low density core expanded polystyrene foam (EPS) bonded to two aluminum (6061-T6) face-sheets. The effects of foam and plate thicknesses on the impact energy absorption of sandwich panels were also investigated. The dynamic response of panels was analyzed using the explicit finite element method. The foam core material was modeled as a crushable foam material with ductile damage, and the metal face-sheets as Johnson-Cook (JC)material. The cohesive response of the adhesive interface was considered using cohesive zone model. The analyses showed that the impact energy, face-sheet and foam core thickness affected significantly failure modes, contact force levels and histories. The low-speed impact tests of the sandwich panels with different face-sheet and foam core thicknesses showed similar contact force histories, energy absorption ability and deformation modes to those of finite element analyses.

    • A depth-based Indian Sign Language recognition using Microsoft Kinect


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      Recognition of sign language by a system has become important to bridge the communication gap between the abled and the Hearing and Speech Impaired people. This paper introduces an efficient algorithm for translating the input hand gesture in Indian Sign Language (ISL) into meaningful English text and speech. The system captures hand gestures through Microsoft Kinect (preferred as the system performance is unaffected by the surrounding light conditions and object colour). The dataset used consists of depth and RGB images (taken using Kinect Xbox 360) with 140 unique gestures of the ISL taken from 21 subjects, which includes single handedsigns, double-handed signs and finger spelling (signs for alphabets and numbers), totaling to 4600 images. To recognize the hand posture, the hand region is accurately segmented and hand features are extracted using Speeded Up Robust Features, Histogram of Oriented Gradients and Local Binary Patterns. The systemensembles the three feature classifiers trained using Support Vector Machine to improve the average recognition accuracy up to 71.85%. The system then translates the sequence of hand gestures recognized into the bestapproximate meaningful English sentences. We achieved 100% accuracy for the signs representing 9, A, F, G, H, N and P.

    • DHCPv6Auth: a mechanism to improve DHCPv6 authentication and privacy


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      Internet Protocol version 6 (IPv6) deployment continues to gain ground due to the increasing demand for IP addresses generated by the number of Internet facing devices, and it is compounded by the exhaustion of allocatable IPv4 addresses. Dynamic Host Configuration Protocol version 6 (DHCPv6) is used toallocate IPv6 addresses and distribute network configuration information to IPv6 hosts in a link-local network. However, DHCPv6 messages in transit expose identifiable information of the DHCPv6 client that could be usedby malicious users to track their victims. Additionally, the lack of an authentication mechanism leaves IPv6 hosts vulnerable to rogue DHCPv6 server attacks. This paper introduces DHCPv6 Authentication (DHCPv6Auth) mechanism to prevent rogue DHCPv6 server attacks and protect the privacy of IPv6 hosts.DHCPv6Auth uses the Ed25519 digital signature algorithm for authentication and could be used in conjunction with Anonymity Profile mechanisms for privacy protection. The DHCPv6Auth mechanism was compared withother mechanisms in terms of processing time, prevention of rogue DHCPv6 server attack, and protection of users’ privacy. The results show that it requires less processing time and traffic overhead than other authenticationmechanisms; is able to prevent rogue DHCPv6 server attacks; and provides better privacy protection for the IPv6 host than other authentication mechanisms to which it was compared.

    • A novel extractive text summarization system with self-organizing map clustering and entity recognition


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      Extractive text summarization yields the sensitive parts of the document by neglecting the irrelevant and redundant information. In this paper, we propose a new strategy for extractive single-document summarization in Malayalam. Initially, entity recognition is done, followed by relevance analysis is made based onsome context-aware features. The scored sentences are then clustered using self-organizing maps (SOM) and from these clusters, relevant sentences are extracted out based on the proposed algorithm. Both theoretical and practical evaluations are done to analyze the implemented system. In theoretical evaluation, gradient calculations of relevance equations are used to know that which of these sentence scoring features are contributing more. The relevance equation is optimized with the help of Lagrange’s multiplier. The complexity analysis of the proposed algorithms is also performed. In practical evaluation, the system compared with online and offline summarizers upon metrics like precision, recall, and F-measure. The system is tested through a non-clustering approach also in order to analyze the impact of clustering used in our work. Some existing strategies likequestion game evaluation, sentence rank evaluation, and keyword association are also done to evaluate the different parameters like the relevance of sentences, important entity words, etc.

    • Characterization of various FinFET based 6T SRAM cell configurations in light of radiation effect


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      The microelectronics circuits used in the aerospace applications work in an extremely radiated environment, causing a large possibility of a single event upset (SEU). Static random access memory (SRAM) is the most susceptible of these circuits as it occupies a significant area of the recent System-on-Chip (SoC) andalso frequently store important data. Therefore, retaining data integrity with regards to SEUs has become a primary requirement of SRAM bit-cell design. Use of FinFET devices in the SRAM cell can offer higher resistance against radiation compared to the CMOS counterparts. In this work, using TCAD simulations, wehave analysed effect of SEU on three different FinFET based 6T bit-cell configurations, in which number of fins in the access and pull-down transistors are different. We have analysed the effect of SEU at an angle of 90° and60°.

    • Effect of coatings on rolling contact fatigue and tribological parameters of rolling/sliding contacts under dry/lubricated conditions: a review


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      The application of coating gets exceptional importance since it improves the tribological properties of the contacting surfaces. Different input parameters like coating deposition processes, coating material properties and its thickness, use of lubricant and its additives, surface roughness and temperature affect thetribological properties and the rolling contact fatigue (RCF) life of coated rolling and sliding contact elements. In this paper, an attempt has been made to review for the clear understanding of the effect of these input parameters on the RCF life and tribological performance of coated rolling and sliding contact elements. It hasbeen observed that coating deposition process must be chosen based on technical and economic aspects. Among the different techniques, thermal spraying technique is cost effective, and it also provides better bonding strength, which improves the RCF life in comparison with other techniques. Similarly, the effect of other input parameters has been reviewed and possible combination of the input parameters that help improve the performance of coated contacting elements summarized. Furthermore, the current status of research and the scopeof future work to be carried out, in this area, have been outlined.

    • An algorithmic approach to rank the disambiguous entities in Twitter streams for effective semantic search operations


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      The most challenging task in any modern reasoning system is that it has been completely relied on automatic knowledge acquisition from the unstructured text and filtering out the structured information from it has turned out to be the most crucial task of Information Retrieval systems. In this paper, we have proposed asystem that can recognize the potential named entities from the Twitter streams and link them to the appropriate real world knowledge entities. Besides, it has performed many semantic functions such as entity disambiguation, contextual similarity, type induction, and semantic labeling, to augment the semantic score of the entity and provide the rich entity feature space to quantitatively enhance entity retrieval accuracy. Nevertheless, we have leveraged a model to alleviate the entity imbalance present over the collected Twitter Streams and effectivelyutilized the contextual relatedness between the candidate entity sets. Eventually, we have proposed a probabilistic approach to deal with topic modeling and effectively disambiguate the entities by clustering the entities into its appropriate entity domain. The proposed Latent Dirichlet Allocation (LDA) model has been categorically distinguished the topics for clustering between the candidate entities and fix the exact true mentions occurred in the Knowledge Base such as DBpedia. We have also demonstrated the performance and accuracy rate of the proposed system and evaluated the results with the collected Twitter Streams for the month of August, 2016. The empirical results have shown that it has outperformed the existing state-of-the-art systems and proved that the proposed system given here has gradual accuracy rate against the conventional systems.

    • Investigation of tribological and compressive behaviors of Al/SiO₂ nanocomposites after T6 heat treatment


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      The aim of this paper is to present experimental results of tribological and compression properties of aluminum nanocomposites after T6 heat treatment. This heat treatment contained three stages: solutionizing at 500°C for 5 h, quenching in water, and ageing 180°C for 9 h. The method of nanocomposite production was the stir casting process. The SiO₂ nanoparticles in 0.5 and 1% wt were added to the aluminum melt as the reinforcement agent. The microstructural evaluation was conducted by the optical microscopy (OM) and the field emission scanning electron microscopy (FESEM) methods. The results of the wear test revealed that the specific wear rate of specimens comprising SiO₂ nanoparticles was lower than that of specimens without nanoparticles. Thus, the formation of the holes, wear debris and cracks decreased obviously for nanocomposite surfaces during wear testing. Moreover, the wear rate reduced obviously for nanocomposites fabricated by thepre-heating process compared to others. It was noticeable that the ball-milling process was an effective method to decrease the friction coefficient value to 0.15 for nanocomposites. Such observations were due to higher hardness and lower micro-porosity content. The elastic modulus for various nanocomposites improved by 8–19% compared to the aluminum alloy. In addition, when the content of SiO₂nanoparticles increased from 0.5 to 1% wt, the ultimate compressive strength decreased about 11–13% due to the presence of more microporosities.

    • Corrosion behavior of reinforcing bar in magnesium phosphate cement based on polarization curve


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      Apart from focusing on the analysis of the characteristics of reinforcing bars during corrosion, such as open circuit potential and polarization, the study also engages in the investigation of their corrosion in magnesium phosphate cement (MPC). For a more comprehensive understanding of the rusting performances, a comparison was made by an electrochemical workstation between the reinforcing bars in the MPC system and in the ordinary cement. Meanwhile, under an optical microscope, an observation was conducted on the corrosion morphology in MPC at different ages of concrete while during MPC hydration, an exploration based on pHchanges and polarization curve theory was carried out to learn about the mechanism of the resistance of the reinforcing bars in MPC to corrosion. Despite their extremely slow rate, corrosion behaviors were practically found in the reinforcing bars in MPC. Both the changes in pH and the formation of ammonium phosphate metal complex in the weak base were considered in the study to be the control factors for the resistance of reinforcing bars in MPC to corrosion.

    • Comparative analytical and experimental study of fabricated identical surface and interior permanent magnet BLDC motor prototypes


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      This paper presents a novel and exhaustive investigation involving in-depth analysis, performance evaluation and comparative study of two 0.75 hp, 4-pole, 1500 rpm laboratory prototypes of Brushless DC (BLDC) motors of identical nominal ratings with surface and interior permanent magnet rotor structures havingthe same stator and winding (integral slot distributed winding). Both the motors were designed and developed in the lab. The major electrical variables (such as rated power, speed, voltage, current, number of poles, etc.) and the stator (such as core material, stator lamination, stack length, winding pattern and wire gauge) of the fabricated prototypes have also been kept identical to pin-point the direct influence of the two different rotor configurations (viz., surface vs interior permanent magnet) on the parameters, performance and operation ofthese BLDC motors. Additionally, to ensure unbiased basis for appropriate comparison, the overall volumes of magnets/pole in both the motors have also been kept similar. A detailed comparison of different quantities likeair-gap flux density distribution, THD in induced voltage, torque ripple, losses and efficiency, torque–speed characteristics with field-weakening capability, steady state parameters at different operating conditions, etc. has been conducted for the said motors and the salient points duly highlighted. The vulnerability of the permanent magnets to demagnetisation based on armature reaction, particularly during a sudden fault, has also been investigated in both the cases. The theoretically determined parameters and analytically evaluated performancefigures have been verified through standard FEM packages, and later validated experimentally on the fabricated prototypes. Very good mutual agreement has been observed between predicted and experimental values.

    • An analysis of the conditions during the autonomous start-up of a water ram


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      The article presents the results of experimental studies investigating the conditions during the filling and start-up of a water ram based on changes in pressure in the working zone and the pressure zone. The test stand is described, and measurements are conducted in three configurations: (a) when the system is filled with water (with the delivery pipe empty); (b) when the water ram is manually activated (with the delivery pipe empty) and (c) when the water ram is activated after a manually induced break in water supply (with the delivery pipe filled with water). The results of the study indicate that the operation of the ram pump will be automatically resumed in every configuration, provided that the delivery pipe is filled with water to the appropriate height. The aim of this study was to describe new applications for a water ram, in particular under varied supply conditions.

    • Determining the error levels in the calibration procedure when viewed through a transparent cylinder for engine flow diagnostics


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      Particle image velocimetry (PIV) has been widely used to investigate the flow fields in many areas. Images captured using PIV, however, are aberrated when viewed through a transparent cylinder such as in engines, and therefore, need to be compensated for distortions. The calibration procedure is an important step inflow diagnostics for the reconstruction of displacement vectors from image plane to physical space coordinates, also incorporating the distortion compensation. In engine flow diagnostics, the calibration procedure based on global pixel size, however, is commonly used; hence local pixel size variations are ignored, even with significant distortions. In the present work, an analysis is performed to quantify the error levels in the calibration procedure by acquiring the calibration images with and without the cylindrical liner at different measurement planes. Additionally, calibration is also performed utilizing the non-linear mapping functions to account for local pixel size variations, along with error determination. It is found that the error in the calibration procedure based on global pixel size is significant, hence highlights the importance of calibration based on mapping functions inengine flow diagnostics.

    • Selection of coating material for magnesium alloy using Fuzzy AHP-TOPSIS


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      Magnesium alloys are inherently negative electrochemical potential and are very reactive compared to other engineering metals. They are prone to galvanic corrosion and micro cracks. Various coating materials or Alternatives and the required criteria and sub-criteria for the selection of Alternatives for AZ31B magnesium alloy substrate are identified by means of literature review. Criteria weight and the rank of the alternatives are usually vague and hence uncertainty prevails. The best Alternative from several potential ‘‘Candidates’’, subjectto several criteria and sub-criteria, needs to get decided. In such cases, multi criteria decision making (MCDM) techniques help in determining the MOST suitable coating material. This paper concentrates on the selection ofcoating material for the magnesium alloy substrate. The problem is subjective, uncertain and equivocal in nature. Hence in this study, fuzzy analytic hierarchy process (AHP) is applied to obtain the weights of criteria and technique for order performance by similarity to ideal solutions (TOPSIS) is utilised for ranking theAlternatives.

    • Classification of pitting fault levels in a worm gearbox using vibration visualization and ANN


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      Mechanical power transmission systems are an indispensable part of the industrial process. The most complex equipment of these processes is the gear systems. Among the gear systems the worm gearboxes are used in various applications, especially those that need high transmission ratios in one reduction stage.However, worm wheel manifests defects easily because it is made of soft material, in comparison with the worm. The stress on each tooth surface may increase because of overload, shock load, cyclic load change, gear misalignment, etc. This often causes pitting faults in worm gearboxes. This paper focuses on the detection of localized pitting damages in a worm gearbox by a vibration visualization method and artificial neural networks (ANNs). For this purpose, the vibration signals are converted into an image to display and detect pitting defects on the worm wheel tooth surface. In addition, statistical parameters of vibration signals in the time andfrequency domains are used as an input to ANN for multi-class recognition. Later, the results obtained from ANN are compared for both axial and radial vibration. It is found that the ANN can classify with high accuracy for any sample of the vibration data obtained from the radial direction according to fault severity levels.

    • Water distribution system design using multi-objective particle swarm optimisation


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      Application of the multi-objective particle swarm optimisation (MOPSO) algorithm to design of water distribution systems is described. An earlier MOPSO algorithm is augmented with (a) local search, (b) a modified strategy for assigning the leader and (c) a modified mutation scheme. For one of the benchmark problems described in the literature, the effect of each of these features on the algorithm performance is demonstrated. The augmented MOPSO algorithm (called MOPSO?) is applied to five benchmark problems, and in each case, non-dominated solutions not reported earlier are found. In addition, for the purpose of comparing Pareto fronts (sets of non-dominated solutions) obtained by different algorithms, a new criterion is suggested, and its usefulness is pointed out with an example. Finally, some suggestions regarding future research directionsare made.

    • CALAM: model-based compilation and linguistic statistical analysis of Urdu corpus


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      In this paper, we introduce an efficient framework for the compilation of an Urdu corpus along with ground truth and transcription in Unicode format. A novel scheme of the annotation based on four-level XML has been incorporated for the corpus CALAM. In addition to compilation and bench marking test, the frameworkgenerates the word frequency distribution according to category sapient useful for linguistic evaluation. This paper presents the statistical analysis with corpus data based on transcript text and frequency of occurrences. The observation of statistical analysis is conducted using vital statistics like rank of words, the frequency of words, ligatures length (number of ligatures with combination of two to seven characters), entropy and perplexity of the corpus. Besides rudimental statistics coverage, some additional statistical features are also evaluated like Zipf’s linguistic rule and measurement of dispersion in corpus information. The experimental results obtained from statistical observation are presented for asserting viability and usability of the corpus data as a standard platformfor linguistic research on the Urdu language.

    • Mechanistic-empirical design of fibre reinforced concrete (FRC) pavements using inelastic analysis


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      Use of fibre reinforced concrete (FRC) for pavements is advocated since the higher crack resistance could lead to lower slab thickness and higher joint spacing. The post-cracking capacity of FRC allows pavements to be designed and analysed considering the response beyond the elastic regime. The current paperpresents possible failure patterns in FRC pavement slabs, which are governed by the slab dimensions, loading type and boundary conditions, and the appropriateness of inelastic design methodologies for these failurepatterns. Subsequently, a mechanistic-empirical design methodology developed for FRC pavements, based on yield line analysis incorporating fatigue in the moment calculation, is discussed. The proposed design methodology gives specific checks for the different failure patterns and the consequent design strategy to be adopted. The method incorporates material parameters, such as the first crack and post crack flexural strengths, and fatigue correction factors for the evaluation of the moment carrying capacity. Cumulative fatigue damageanalysis is also done as a serviceability check. The final design solution satisfies both the inelastic moment capacity requirement and fatigue life required without excessive damage accumulation.

    • Failure modes of end-plate connections with outer flange stiffeners: an experimental and numerical study


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      This paper presents the experimental and numerical results of six full-scale beam-to-column connections with bolted end plates in two groups. The effects of vertical and horizontal stiffeners on the static behaviour of the semi-rigid beam-to-column bolted connections were investigated. In addition, the aim of this research was to analyse the influence of end-plate connections that utilize the IPE profile with stiffeners welded on the behaviour of steel connections, to provide the necessary data for improving Eurocode 3, efficient use of residue IPE profiles and back to the consumption cycle. Furthermore, finite-element and experimental models ofsemi-rigid vertical and horizontal stiffened bolted connections were tested and compared. The main parameters observed are the evolution of the resistance, the stiffness, the rotation capacity, the ductility of a joint, failure mode and the energy dissipation.

    • Synthesis of magnesium aluminate spinel nanocrystallites by co-precipitation as function of pH and temperature


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      Magnesium aluminate (MgAl₂O₄) spinel nanocrystallites are prepared through nitrate route with liquor ammonia as a precipitant by co-precipitation process. By varying the solution pH (8–10) and bath temperature (10–40°C), the precipitated gel materials are obtained. Yield of each batch is determined by firing at 1000°C with 2 hours (h) soaking. The yield is maximum at 30°C and pH 9.2. Chemical analysis indicates near stoichiometric spinel at pH 9.2. Below pH 9.2, Al₂O₃:MgO molar ratio shifts to alumina side; beyond pH 9.2, it is towards magnesia side. Stoichiometric spinel-forming precursor material is characterized by various techniques. X-ray diffraction (XRD) analysis indicates spinel formation at 600°C and its crystallinity increases with rise of temperature. Hydroxyl group and absorbed water in gel substrate disappear with variation of temperatureas observed by Fourier transform infrared (FTIR). Only one exothermic response of the precursor of spinel formation is demonstrated through differential scanning calorimetry (DSC). Studies reveal formation of near stoichiometric magnesium aluminate spinel powder having average crystalline size in the range 15–38 nm. HR transmission electron microscopy studies also confirm this nano-size crystallite formation.

    • Dynamic tail re-assignment model for optimal line-of-flight breakages


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      The literature in aircraft routing focuses on cyclic rotation with the planned maintenance being assigned to the aircraft at the end of every rotation. The rotations are a set of flights provided with sufficient Maintenance Opportunity (MO) such that the planned maintenance could be carried out for the aircraft. In thisresearch, a novel mathematical model has been introduced to the operational aircraft route assignment which considers both planned and ad hoc maintenances of the aircraft. A line-of-flight is defined as the set of geographic and time feasible flights being assigned to the hypothetical aircraft without any actual operationalconstraints. The model is formulated for the scenario where commercial planning department independently makes the line-of-flights and the maintenances have to be incorporated in those line-of-flights with minimal perturbations. In addition to the exact solution, the problem has also been solved using two heuristic solutionapproaches for the tailored module which is called the Tail Re-assignment, a problem dealt with by many airlines. The Tail Re-assignment problem can be considered as an optimization as well as feasibility problem. The objective of this research is to provide a quick solution that is feasible and near-optimal which can help in the managerial decisions in the tactical horizon. The model is tested with eight schedules with flights varying from 45 to 314, and additionally with multiple maintenance hubs and planning horizon of 20 days. The solution has all the hard constraints satisfied with the total number of onward flight rule breakages difference being minimal. The computation result shows that heuristic solutions solve the schedule for a medium-sized airline in quick time with less than 2% deviation from the exact solution.

    • Construction of lightweight authentication scheme for networkapplicants using smart cards


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      The accelerated growth of internet technologies has offered various services to users, although the access to data comes with a greater encumbrance as data are transferred via a public channel. To ensure authorised and secure data access, various authenticated key agreement protocols have been designed and analysed in recent years. Most of the existing protocols face the efficiency issue. A scheme could be made efficient using lightweight cryptographic operations such as hash functions, XOR operation, etc. However, to control the leakage of password, a biometric-based authentication approach can be adopted. Keeping the focus on these points, the proposed scheme is designed. It has attributes of secure communication, mutual authentication and efficient computation, as well as user anonymity. The security proof is proclaimed using the widely recognised random oracle model, which indicates that the proposed scheme is provably secure under any probabilistic polynomial-time adversary. Moreover, the proposed scheme achieves all desirable security attributes of authentication protocols, which is justified using informal security analysis. The simulation of the proposed scheme is done using the automated validation of internet security protocols and applications tool,which shows that the proposed scheme is safe. Furthermore, the proposed scheme is found to be computationally efficient when compared with the related schemes.

    • Influence of textile properties on dynamic mechanical behavior of epoxy composite reinforced with woven sisal fabrics


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      Due to low cost and environmentally friendly characteristics, natural fibers gain much attention over synthetic fiber. The aim of the present work is to characterize the textile properties of three different types of sisal fabric and study dynamic mechanical properties and water absorption behavior of the sisal fabricreinforced epoxy composite. Influence of grams per square meter of fabric, weaving pattern of the fabric on textile properties of the fabric is studied first. Further, the effect of the same on the dynamic mechanical properties of the sisal composites is studied. Effect of fiber weight percentage and dynamic frequency ondynamic mechanical properties also studied. Results reveal that the storage modulus (G') decreases with increasing temperature in all the woven types of composites under consideration. However, Plain 2 (P2) and Weft Rib (WR) composites have shown better values of G' even after the glass transition temperature (Tg). From the results, it is also evident that storage and loss modulus (G'') increases when the yarn diameter decreases which is observed at a higher temperature also. It is also observed that fabric density also plays a significant role in the enhancement of G' and G'' values. The water absorption of Plain 1 (P1) based composites are found to be less compared to the other types of composites analyzed.

    • A novel control strategy based on hybrid instantaneous theory decoupled approach for PQ improvement in PV systems with energy storage devices and cascaded multi-level inverter


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      This paper suggests an innovative control architecture based on hybrid instantaneous theory (HIT) decoupled method for improved power quality (PQ) in a photovoltaic (PV) based microgrid utilizing energy storage devices (ESD). Further, to enhance the PV-ESD performance, an eleven-level cascaded inverter (ECI)with compact size, cost, and increase in voltage level is proposed. By considering the simplicity in design and wider application, an improved perturb and observe (IP&O) method is implemented to operate the PV-ESD system at its optimum power point (OPP). In addition to that, for achieving an improved energy management, a battery-based ESD is integrated into the system. Furthermore, the use of grid LCL filter in PV is investigated with the proposed control law design to reduce the harmonic content. To verify the robustness of the HIT approach based on the harmonics and nonlinearity, various test conditions have been examined under different cases ranging from varying environmental conditions, varying grid demand and ESD charging and discharging situations by using MATLAB/Simulink software.

    • Experimental investigations on transient cryogenic chilldown of a short horizontal copper transfer line


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      The present study investigates chilldown characteristics of a horizontal copper transfer line with 7.94 mm outer diameter, 0.81 mm wall thickness and 500 mm length. Data presented in this paper is for the experiments conducted with different mass fluxes (66 kg (m².s)⁻¹ to 102 kg (m².s)⁻¹) in a horizontal copper transfer line under terrestrial gravity conditions. Temperature measurements were recorded at six equidistantpoints to a distance of 330 mm from an inlet. Inverse problem solving method is utilized to calculate corresponding heat flux and heat transfer coefficients. Considering the thermal properties of the quenched wall, an empirical relation was developed. It is found that while employing copper transfer lines instead of stainless steel, thermal mass of the section is reduced by a factor of 100, thereby encountering a reduction of 50% in critical heat flux.

    • An information-theoretic graph-based approach for feature selection


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      Feature selection is a critical research problem in data science. The need for feature selection has become more critical with the advent of high-dimensional data sets especially related to text, image and microarray data. In this paper, a graph-theoretic approach with step-by-step visualization is proposed in the context of supervised feature selection. Mutual information criterion is used to evaluate the relevance of the features with respect to the class. A graph-based representation of the input data set, named as feature information map (FIM) is created, highlighting the vertices representing the less informative features. Amongst the more informative features, the inter-feature similarity is measured to draw edges between features having high similarity. At the end, minimal vertex cover is applied on the connected vertices to identify a subset of features potentially havingless similarity among each other. Results of the experiments conducted with standard data sets show that the proposed method gives better results than the competing algorithms for most of the data sets. The proposed algorithm also has a novel contribution of rendering a visualization of features in terms of relevance andredundancy.

    • DTMOS based Gilbert mixer design for MICS receiver using current source helpers and switched biasing technique


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      In this paper, dynamic threshold MOSFET (DTMOS) based down conversion Gilbert mixer is proposed for medical implant communication services (MICS) receiver design using UMC 180 nm CMOS process. The current source helpers and switched biasing technique are used to progress the performance of theDTMOS based Gilbert mixer. The proposed design operates at a radio frequency (RF) of 403 MHz with a maximum conversion gain of 12.5 dB at 5 dBm of LO power. The 1 dB compression point and third order input intercept point (IIP3) for the proposed design is - 8.79 dBm and 3.92 dBm respectively, with a noise figure(NF) of 6.6 dB at an intermediate frequency (IF) of 10 MHz. This design circuit works in 0.9 V supply voltage and consumes a dc power of 0.55 mW with the chip area of 0.035 9 0.037 mm2. So, this design with high conversion gain and better noise performance is a suitable block for MICS applications.

    • Verifiable top-k searchable encryption for cloud data


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      With the proliferation of data and the appealing features of cloud computing, the data owners are motivated to outsource their data to the public cloud. Privacy and security, especially for sensitive data, are still a concern, as the data owners have no physical control over the outsourced data. To ensure confidentiality,sensitive data is encrypted before outsourcing to the cloud, which obsoletes the data utilization using traditional keyword-based search. To address this issue, a verifiable top-k searchable encryption for cloud data (VSED) is proposed with provisions for dynamic update operations like addition and deletion of documents. Specifically, an encrypted inverted index is constructed using a secret orthogonal vector and partial homomorphic encryption.To support the ranked search, the widely used term frequency and inverse document frequency rule is used tofind the top-k documents. To verify the query results returned by the cloud server, this scheme provides a verifiable search using keyed hashes. Security analysis demonstrates that the proposed scheme is semantically secure, with correctness and privacy guarantees proved in the standard security simulation model. Simulations performed on real-world dataset demonstrate that the proposed scheme is efficient and practical.

    • Inverse analysis and multi-objective optimization of coupling mechanism based laser forming process


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      Laser forming of non-developable surfaces necessitates simultaneous bending and shrinkage of the sheet blank. This can be obtained by coupling mechanism based laser forming. However, soft computing based modeling of this process as well as different laser parameter sets under coupling mechanism giving differentoptimum combinations of simultaneous bending and shrinkage is rarely reported. In this work, experiments have been carried out following a design of experiments with considered suitable ranges of the input factors, i.e., laser power, travel speed and laser beam diameter activating coupling mechanism. Response surface models for the outputs namely bending and thickening (resulted due to shrinkage) were developed in terms of the considered inputs and parametric effects were analyzed. Finite element modeling was also carried out to analyze thedeformation behavior. Multi-objective optimization of laser parameters for different combinations of maximum/ minimum of bending and thickening of the sheet material undergoing coupling mechanism has been shown. Forward and inverse models of the process have been built with the help of a backpropagation neural network (BPNN) and genetic algorithm-based neural network (GANN) based on experimental data. Because of the ability of genetic algorithm (GA) to obtain global search, GANN models provide better estimation of the input parameters for inverse modeling or process synthesis compared to that by the BPNN model. Finally, several dome-shaped surfaces were built with constant line energy but different Fourier numbers and hence, different proportions of bending and shrinkage. This was to demonstrate the importance of simultaneous bending and thickening of the sheet (achievable only by coupling mechanism) to generate such non-developable surface with minimal distortion.

    • Dynamical behaviour of a porous liquid layer of an Oldroyd-B model flowing over an oscillatory heated substrate


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      The present work aims to study the time-dependent thin porous film flow of an Oldroyd-B model on a heated infinite long flat plate. The fluid and the substrate are both at rest initially. Suddenly, the plate is jolted into motion in its own plane with an oscillatory velocity. Further, an insoluble surfactant is located at the freesurface but not in the bulk of the fluid. Inversion of Laplace transform is applied to obtain numerical solutions to the problem. Due to the difficult analytical inversions back to the real-time domain, the need to use numerical inverse Laplace transforms arises, and a numerical approach for this purpose is mentioned and applied. The analytical solution of the special case of the isothermal liquid film when the Reynolds number is vanishing small is obtained and discussed. The flow rate and skin friction are investigated and plotted. Depending on the selectedparameters, it is revealed that relaxation time constant lowers the velocity, while the effect of retardation time is opposed to that of relaxation time. It is noted that the Péclet number and capillary number enhance the heat transfer rate, whereas the converse is true for elasticity number. It is also observed that the motion of the free surface grows gradually with the increase of Darcy number. The Reynolds number is found to enhance the flow rate and lower skin friction. In the special case when the Reynolds number is vanishing small, it has been shown that the capillary number has an effect, unlike the elasticity number.

    • Design and development of automated high temperature motor test facility


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      With increasing applications in high performance actuation systems as in aerospace and nuclear industries, demand for motors operating at an ambient temperature of 100°C and above has increased. Hence, it is highly necessary to validate the performance of motors at high temperature before their integration into complex critical systems. Most commercial test benches for motor available today, are designed for operation only at normal temperature. This paper describes the design, physical structure, operating principle and dataacquisition system of automated test facility developed for testing stepper motors, brushed DC motors and brushless servo motors at room temperature as well as at elevated temperatures. To make the entire measurement system automated, a graphical user interface based on C# software is developed. Through the experiments on standard motors, quality of the design, performance of test bench and implementation of control modes are validated. The results obtained show a successful intercommunication between modules such as control, drive,measurement, data acquisition and display as per the required performance.

    • Fuzzy DDBN: Fuzzy Dragon Deep Belief Neural Network and interesting features points for activity recognition


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      Activity recognition is the interest gaining research area, as the need for monitoring and controlling the public and the society to ensure the detection of the suspects and the illegal activities is of prime importance. The process of recognizing the activity of the humans is employed in various applications, mainly in the field ofsecurity to identify and detect the suspects. Accordingly, this paper uses a novel method named as the Fuzzy- DDBN classifier to categorize the human activities in the video. At first, the keyframes are extracted from the video based on the Bhattacharya similarity measure, and the keyframes are subjected to feature extraction using the Scale Invariant Feature Transform (SIFT) and the Spatio-Temporal Interest (STI) descriptor. The features extracted from the descriptors are fed to the classifier for classification that in turn, uses the GMM clustering.The classified output from the proposed Fuzzy-DDBN classifier, which is the combination of the fuzzy and the Dragon Deep Belief Neural Network (DDBN) classifier is merged using the correlation coefficients. The proposed method is experimented using two standard datasets to prove the superiority of the method with an accuracy of 0.98, specificity at a rate of 0.981, and sensitivity at a rate of 0.98 respectively.

    • A mobile fault detection algorithm in heterogeneous wireless sensor networks: a bio-inspired approach


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      This paper puts forth a novel mobile fault detection algorithm for wireless sensor networks (WSNs) based on bacterial-inspired optimization. We introduce a bio-swarm intelligence approach to mobile fault detection in WSNs by using voltage values. At certain times, the sensor nodes in the clustered network send datapackets containing health-fitness information to cluster heads (CHs) selected by the proposed CH selection algorithm. A mobile sink (MS) collects the health status via data from all the nodes as they reach the intersection point of the CHs. After this stage, the data packets are analyzed by the MS, and hardware or software faults are detected by assessing the fitness values of the nodes. The faulty nodes are eventually discarded from the network, and recovery of the rest of the nodes in the network is satisfied. Inspired by the interaction of bacteria for feed collection, their response to chemicals, and their interaction and communication with one another, we bring an innovative approach to finding node failures or software faults in WSNs, and these failures are removed from the network to help its operation and to take measures to maintain the electrical structures. In fact, we adaptour algorithm to low energy harvesting electrical components as an example. We compare our novel algorithm with existing studies through extensive simulations in NS 2 environment based on fault detection accuracy, false alarm rate, and false positive rate criteria versus fault probability, number of nodes, and sink speed. Considering detection accuracy, the simulation results validate that our algorithm shows better performance as compared with others.

    • Electromyogram (EMG) based fingers movement recognition using sparse filtering of wavelet packet coefficients


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      Surface electromyogram (EMG) signals collected from amputee’s residual limb have been utilized to control the prosthetic limb movements for many years. The extensive research has been carried out to classify arm and hand movements by many researchers. However, for control of the more dexterous prosthetic hand,controlling of single and multiple prosthetic fingers needs to be focused. The classification of single and multiple finger movements is challenging as the large number of EMG electrodes/channels are required to classify more number of movement classes. Also the misclassification rate increases significantly with the increased number of finger movements. To enable such control, the most informative and discriminative feature set which can accurately differentiate between different finger movements must be extracted. This work proposes an accurate and novel scheme for feature set extraction and projection based on Sparse Filtering of wavelet packet coefficients. Unlike the existing feature extraction-projection techniques, the proposed method can classify a largenumber of single and multiple finger movements accurately with reduced hardware complexity. The proposed method is compared to other combinations of feature extraction-reduction methods and validated on EMG dataset collected from eight subjects performing 15 different finger movements. The experimental results showthe importance of the proposed scheme in comparison with existing feature extraction-projection schemes with an average accuracy of 99.52% ± 0.6%. The results also indicate that the subset of five EMG channels deliverssimilar accuracy (>99%) to those obtained from all eight channels. The resultant accuracy values are improved over the existing one reported in the literature, whereas only one-third numbers of channels per identified motions are employed. The experimental results and analysis of variance tests (p<0.001) prove the feasibility of the proposed work.

    • Intrusion detection system using an optimized kernel extreme learning machine and efficient features


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      In the study of Intrusion Detection System (IDS) choosing proper combination of features is of great importance. Many researchers seek to obtain appropriate features with optimization algorithms. There are several optimization algorithms that can properly select a near-optimal combination of features to reach animproved IDS. Genetic Algorithms (GA) as one of the most powerful methods have been used in this research for feature selection. In this paper, voted outputs of built models on the GA suggested features of a more recent version of KDD CUP 99 dataset, NSL KDD, based on five different labels, have been gathered as a new dataset. Kernel Extreme Learning Machine (KELM), whose parameters have been optimally set by GA, is executed on the obtained dataset and results are collected. Based on IDS criteria, our proposed method can easily outperform general classification algorithms which use all the features of the employed dataset, especially in R2L and U2R with the accuracy of 98.73% and 98.22% respectively which is the highest among the current literature.

    • Numerical analysis and experimental investigation in the machining of AISI 316 steel


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      High corrosion resistance and mechanical properties of AISI 316 stainless steel make its wide application in the nuclear power station and structural components in chemical industries. On the contrary, low thermal conductivity and high strain rate create problems during the machining of AISI 316, resulting in highcutting force and tool wear. Hence, this study investigates the thermal and mechanical behavior of AISI 316 steel during turning using a carbide tool. It is carried out in two stages: Finite element modeling (FEM) and experimental work. In the first stage, FEM is simulated using DEFORM software to study cutting forces, tool temperature, and chip morphology at different cutting speeds and feed rates. The results show that cutting speed and feed rate significantly affect the cutting force, thrust force and chip morphology. The chip morphology characteristics such as the degree of segmentation and serration frequency are studied. In the second stage, experimental trials are performed using the same input parameters to validate the simulated results. Results show a 10% error between simulated and experimental findings.

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