• Volume 45, All articles

      Continuous Article Publishing mode

    • 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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