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      Volume 44, Issue 4

      April 2019

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


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      This paper addresses a study on the transportation problem based on dual-hesitant fuzzy environment. The dual-hesitant fuzzy set accommodates imprecise, uncertain or incomplete information and knowledge situations in real-life operational research problems that are not possible or difficult to tackle by existing fuzzy uncertainties. Here, we present the concept of uncertainty in a transportation problem using dual-hesitant fuzzy numbers. In most of the research works, fuzzy uncertainty has been considered in transportation parameters. However, we consider the dual-hesitant fuzzy numbers to formulate a mathematical model by considering the capacity of delivering the goods by a decision maker. A special emphasis of this paper is to derive an optimal solution of transportation problem with some restrictions under uncertainty by the traditional approach (cf.Vogel’s approximation method—VAM) without using any mathematical aids. In this regard, an algorithm is developed to find the optimal solution for the dual-hesitant fuzzy transportation problem including some restrictions. Thereafter, the proposed method is illustrated by giving a numerical example for showing theeffectiveness. Finally, conclusions are given with the lines of future studies based on this paper.

    • Nonlinear dynamic analysis of defective rolling element bearing using Higuchi’s fractal dimension


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      In the present study, localized surface defects are modelled in inner race and outer race, and nonlinear dynamic behaviour of the system has been observed and quantified using Higuchi’s fractal dimensions. The Hertzian contact among the rollers and races, clearance and nonlinear damping are considered assources of nonlinearity. Dynamic responses show system behaviour as periodic, quasi-periodic and chaotic at different rotor speeds. The onset of chaotic motion is identified using Poincare´ maps and Higuchi’s fractal dimensions. The system shows low peak-to-peak amplitude of vibration responses at higher speeds in thepresence of defects. Results also indicate that Higuchi’s fractal dimensions can be effectively used as a diagnostic tool for health monitoring.

    • Approximate solution for high-order fractional integro-differential equations via trigonometric basic functions


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      An approach for searching an approximate solution of high-order integro-differential equations featuring fractional derivatives has been proposed in this paper. Initially, using trigonometric basic functions (TBFs), we determine the transformation functions in association to TBFs. Next, the approximate function ispresented as a combination of TBFs and transform functions. The convergence of this approach is also presented. Using discrete derivatives of the solution to gain an approximate solution, we find the approximate solution, which satisfies the high-order integro-differential equations featuring fractional derivatives. An algorithmof this approach is applied for various examples, and one example is illustrated in detail.

    • Effect of radial magnetic field on the natural convection in a semicircular curved enclosure for different aspect ratios


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      The problem of natural convection in a (2D) semi-circular curved enclosure in the presence of a radial magnetic field is numerically studied in this paper. The selected configuration is such that the convective flow is driven by a mean temperature gradient also directed radially, and the effects of enclosure aspect ratio and the strength of the applied magnetic field are considered. Numerical simulations are carried out using a (3D) MHD code developed by our research group, first at a fixed Ra = 10⁵ and Pr = 0:71 for aspect ratios A = 2; 4; 6; 8 and Hartmann numbers in the range Ha = 0 - 100. As the aspect ratio is increased, a Rayleigh– Be´nard-like convection with the convective cells formed near the symmetric central portion of the enclosure, where the mean temperature gradient is anti-parallel to the gravity, is found to be triggered. Except at the transition, the effect of the imposed radial magnetic field is found to decrease the fluid motion in general, and the motion is completely suppressed at Ha = 100 irrespective of the aspect ratio. The critical Hartmann number for the onset of (R–B-like) convection is found to decrease with an increase in the aspect ratio. Numerical simulations are also attempted at a fixed A = 10 and Ra = 8000 for Prandtl numbers Pr = 10; 0:1; 0:01 and Hartmann numbers Ha = 0; 3; 6; 9; 12. In the absence of the applied magnetic field, the flow is found to exhibit periodic oscillations of increased amplitude and time-period when Pr is decreased, except at Pr = 10, where a steady-state solution is found. For Pr = 0:01, the oscillatory flow is observed to persist even when the magnetic field strength is increased in the range Ha =3 - 12. Moreover, the temporal frequency of these flow oscillations is found to be nearly the same for Ha≤9.

    • Probing defects in friction stir welding process using temperature profile


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      Detection of defects in friction stir welding process is a challenging task since most of the defects are internal or subsurface. An attempt has been made to explore the methodologies based on temperature signal for possible detection of defects in friction stir welding process using different tool profiles. The presence ofdefect is affected by temperature diffusion and is better reflected by the change of temperature over time. Temperature signals are acquired using thermocouples inserted in specific locations on advancing and retreating side of the welds. The rate of change of temperature and wavelet-analysis-based indicator computed from temperature signal against each experiment reveal appreciable difference for defective and defect-free welds. Threshold values are computed that clearly set a boundary for classifying the defective welds from defect-free welds. The proposed approaches can effectively reduce the post-processing steps essential for other nondestructive evaluation of the welds and can work as a first level of safeguard in the identification of defects during friction stir welding process. The methodologies can be extended towards monitoring of the process in industrial applications.

    • Mixed convection heat transfer of water about a vertical surface of variable heat flux with density inversion


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      Laminar mixed convection boundary layer flow of water about a vertical plate is studied including density inversion effects. The plate surface is subjected to an arbitrary heat flux that is a function of vertical distance from the leading edge. Both aiding and opposing mixed convection situations are considered in thestudy. The dimensionless forms of stream function and temperature are expanded in terms of perturbation elements and universal functions. The differentials of the heat flux, which are functions of vertical distance, are used as perturbation elements to obtain universal functions. The results for universal functions required to find temperature and velocity profiles are obtained. The obtained universal functions are valid for any arbitrary wall heat flux variation. The universal applicability of results is demonstrated for power-law variation of wall heatflux. The velocity and temperature variation, boundary layer thickness, Nusselt numbers and skin friction coefficient are presented for various values of mixed convection parameter, wall flux power index, for both aiding and opposing mixed convection. For a given combination of Grashof and Reynolds numbers, the heattransfer rates and skin friction coefficient are found to increase almost linearly with wall flux power index, in the parameter range of the study, for both the cases of aiding and opposing mixed convection. The present results ofspecial cases are found to match well with the results available in the literature.

    • Non-reactive solute transport modelling with time-dependent dispersion through stratified porous media


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      We present a numerical solution of the mobile–immobile model (MIM) with time-dependent dispersion coefficient to simulate solute transport through heterogeneous porous media. Observed experimental data of non-reactive solute transport through hydraulically coupled stratified porous media have been simulated using asymptotic and linear time-dependent dispersion functions. Non-Gaussian breakthrough curves comprising long tails are simulated well with the MIM incorporating asymptotic time-dependent dispersion model.The system is under the strong influence of physical nonequilibrium, which is evident by variable mass transfer coefficient estimated at different down-gradient distances. Asymptotic time-dependent functions are capable of capturing the rising limb of the solution phase breakthrough curves with improved accuracy, whereas tailing part simulation capabilities are similar for both asymptotic and linear time-dependent dispersion functions. Further, the temporal moment analysis demonstrated increased spreading, variance for linear dispersion model ascompared with asymptotic dispersion model. It is also observed that the first-order mass transfer coefficient varies inversely with travel distance from the input source. It can be concluded from the study that MIM with time-dependent dispersion function is simpler yet sensitive to account for medium’s heterogeneity in a better manner even for small observation distances from the source.

    • Transient conjugated heat transfer in thick walled pipes with axially periodic surface temperature in downstream region

      ALI ATEŞ

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      Thermal entrance region transient conjugate heat transfer is investigated involving fluid axial heat conduction for laminar pipe flows. Constant outer wall temperature boundary condition is assumed in the upstream region of a thick walled, two regional pipe. In the downstream region, the outer wall temperature is considered changing spatially in a periodical manner. The problem is solved numerically by a finite difference method. A parametric analysis is conducted in order to determine the effects of Peclet number, wall thickness ratio, wall-to-fluid thermal conductivity ratio, wall-to-fluid thermal diffusivity ratio and axial frequency on heattransfer characteristics. It is seen that, the results are highly dependent on the parameter values and the most effective ones are the Peclet number and the wall thickness ratio. It is observed that heat is transferred towards upstream due to the axial conduction in the wall and in the fluid and with increasing values for high axialfrequency.

    • Design of phase-only reconfigurable planar array antenna in selected phi cuts using various meta-heuristic optimization algorithms


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      In this paper, a pattern synthesis based on a multiobjective optimization algorithm is proposed for the generation of a reconfigurable pencil/flat top dual-beam planar antenna array built using isotropic antenna elements in selected phi cuts. These beams claim the same amplitude excitations and differ from each other inphase excitations. Zero-phase excitations are used in pencil beam and these phases are updated with optimum phases for the flat top beam. All the excitations are obtained using Moth–flame optimization algorithm. With the support of the fitness functions, care is taken to control the expected values of the radiation pattern parameters to remain under certain fixed limit. In addition, synthesis is also done for the provision of a null in a particular direction for rejection of interference in the pencil beam in two different phi cuts. To suppress the mutual coupling effects, dynamic range ratio is kept under a threshold limit. Simulation results show the effectiveness of this proposed synthesis for phi cut planes. This algorithm is compared and proved to be better in many aspects over the standard meta-heuristic algorithms like Artificial Bee Colony and Imperialist Competitive algorithms in terms of performance parameters.

    • NURBS-based thermo-elastic analyses of laminated and sandwich composite plates


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      Present research work is based on the unique properties of isogeometric analysis (IGA) like smarter, faster and cheaper analysis for the thermo-elastic bending of laminated and sandwich composite plates. IGA, based on isoparametric concept, is a breakthrough in the area of structural analysis, which employs non-uniformrational B-spline (NURBS) as a basis function to represent less erroneous geometry. Unlike finite-element method (FEM), increasing the polynomial order in IGA gives higher continuous basis functions naturally and easily with reduced computational cost. A procedure has been developed for thermo-elastic bending analysis of laminated composite plates and sandwich structures using IGA approach. The developed NURBS-based code is validated and computational efficacy of thermo-elastic analysis is investigated. A detailed parametric study hasbeen carried out for the quadratic, cubic and quartic NURBS elements with respect to the variation of temperature. Different types of temperature profiles have been considered. Change of deflections, stresses and moment resultants are analysed with an aim to understand the thermo-elastic behaviour of laminated andsandwich composite plates. Several thermo-elastic numerical examples have been analysed extensively. Obtained numerical results are compared with available literature to show the advantage of current formulation.

    • A new method to generate artificial microstructure of dual phase steel using Teacher-Learner Based Optimization


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      The dual phase steels are widely used in the manufacturing and automobile industry. The micromechanical analysis of the dual phase steel using microstructure based representative volume elements is the effective methodology for the estimation of its macroscopic properties. The real microstructure of the dualphase steels obtained using different microscopic analysis methods depicts the two main constituents viz. martensite inclusion in the ferrite matrix. The distribution of martensite in ferrite matrix exhibits a number of control parameters to define its characteristics. Generation of the artificial microstructure of dual phase steelbased on these controlling parameters is advantageous to get a-priori estimate of the macroscopic properties and behavior. In the present work, a model is proposed for predicting the artificial microstructure of dual phase steel. The volume fraction of martensite and connectivity of the martensite in the ferrite matrix are used as controlling parameters to generate the artificial microstructure using the Teacher-Learner Based Optimization algorithm. The model has effectively predicted the microstructure of the DP590 steel. The artificial microstructure is applied for getting the tensile flow curve of the material using the finite element method. The predicted tensile response of the material is in good agreement with the experimental observations for DP590 steel. The model can be effectively applied to predict the artificial microstructure and subsequent micromechanical analysis of the dual phase steels.

    • Development of a potential vortex-hazard index to predict cruise-level wake turbulence encounters


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      A pair of counter-rotating trailing vortices formed as a consequence of lift generation poses a potential threat to the encountering aircraft. In recent years, incidents/accidents involving wake turbulence confrontation at cruise altitude are increasing due to increase in the number of super-heavy category aircraft. Thevertical separation distance between two airplanes guided by the Federal Aviation Administration (FAA) could be inadequate in certain cases. In this article, a new approach has been proposed to predict the probable area of the persistence of trailing vortices produced by large aircraft. It includes the development of an index with multiple atmospheric effects on the vortices. Also, the impact of the wake from a distinct airplane is incorporated. The performance assessment of the index in predicting the cruise-level wake vortex encounters has been made using various scenarios that happened in the recent past. Weather Research and Forecasting (WRF) model is employed to simulate the atmospheric flow conditions of chosen situations. We found that the method successfully predicts all the cases considered in this study.

    • Objective identification of pain due to uterine contraction during the first stage of labour using continuous EEG signals and SVM


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      This study aimed to assess the utility of electroencephalography (EEG) as an objective marker of pain during the first stage of labour. EEG and cardiotocography (CTG) data were obtained from 10 parturient women during their first stage of labour. The study subjects reported the extent of their pain experienced due touterine contractions, which were recorded by the CTG tracing. Simultaneous 16-channel EEG traces were obtained for spectral analysis and a subsequent machine learning classification using Support Vector Machine (SVM) aiming to predict the pain experienced in relation to uterine contractions. It was found that pain due to uterine contraction correlated positively with relative delta and beta band activities and negatively with relative theta and alpha band activities of the EEG signals. SVM using the spectral activities, statistical and non-linearfeatures of the EEG classified the state of pain with 83% accuracy using a classification model generalizable across subjects. Furthermore, dimension reduction using Principal Component Analysis (PCA) successfullyreduced the number of features used in the classification while achieving a maximum classification accuracy of 84%. Continuous EEG affords the means to assess objectively maternal pain experienced during the active contraction phase of the first stage of labour. Monitoring of the pain experience using EEG signals may complement the clinical decision-making process behind administration of epidural anaesthesia during labour. We envision future studies to investigate EEG markers of pain in other clinical states, aiming to generalize the use of EEG as an objective method of pain assessment.

    • An error-tolerant approach for efficient AES key retrieval in the presence of cacheprefetching – experiments, results, analysis


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      The challenge in cache-based attacks on cryptographic algorithms is not merely to capture the cache footprints during their execution but to process the obtained information to deduce the secret key. Our principal contribution is to develop a theoretical framework based upon which our AES key retrieval algorithms are notonly more efficient in terms of execution time but also require up to 75% fewer blocks of ciphertext compared with previous work. Aggressive hardware prefetching greatly complicates access-driven attacks since they areunable to distinguish between a cache line fetched on demand versus one prefetched and not subsequently used during a run of a victim executing AES. We implement a multi-threaded spy code that reports accesses to theAES tables at the granularity level of a cache block. Since prefetching greatly increases side-channel noise, we sophisticated heuristics to ‘‘clean up’’ the input received from the spy threads. Our key retrieval algorithms process the sanitized input to recover the AES key using only about 25 blocks of ciphertext in thepresence of prefetching and, stunningly, a mere 2–3 blocks with prefetching disabled. We also derive analytical models that capture the effect of varying false positive and false negative rates on the number of blocks of ciphertext required for key retrieval.

    • A comprehensive study of an economic order quantity model under fuzzy monsoon demand


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      This article deals with a classical economic order quantity (EOQ) model under monsoon type fuzzy demand rate. It is nothing but the generalization of cloudy fuzzy model. We split the EOQ model into three parts according to the real-time fuzzy components of the demand rate. To defuzzify the model we develop an algorithm and the solution is obtained with the help of a nonlinear optimization technique that requires maximum aspiration level of the fuzzy membership of the objective function. Moreover, for comparative study we take numerical resultsof the crisp, general fuzzy and cloudy fuzzy model also. By this study we have shown that the decision maker might have to choose the monsoon type fuzzy environment all the time to control the proposed inventory. Moreover,sensitivity analysis and graphical illustrations are made to justify the new fuzzy approach.

    • Using sparsity to estimate oscillatory mode from ambient data


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      In this paper, a sparse-technique-based representation of the signal over a learned dictionary and random decrement technique are explored to extract the oscillatory mode from the ambient data. The main contribution of the present work is to design a dictionary and compute the coefficients that best represent theclean signal to estimate the modes. In this work, the noise embedded in the ambient signal is minimized by the ambient signal in sparse domain with respect to the dictionary. Comparison between the proposed method and other methods such as nonlinear filtering, etc., has been done on the test signal, two-areapower system on the data generated through simulation in Matlab, two-area data simulated on real-time digital simulator and real measurement from Phasor data concentrator (PDC) of Indian power system and Western Electricity Coordinating Council (WECC) network.

    • Actively and passively aspirated temperature sensors in a windless environment like greenhouses


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      Windless environments are prevalent in greenhouses, where precise temperature control is critical to the health of plants and errors in temperature measurement must be avoided. A mathematical model based on heat balance is used to estimate the error in temperature sensors under different conditions and sensorgeometries. The model is then applied to two geometries and solved numerically. The sensors used are a T-type thermocouple and a Sensirion SHT 75. Experiments are carried out in a greenhouse prototype to replicateconditions in a greenhouse and validate the error model. Active ventilation of the sensors is provided by a fan and passive ventilation is provided using a model built on the concept of a ‘solar chimney’. It is shown that even small flow rates can decrease the error shown by unventilated sensors by as much as 10°C.

    • Effect of weep hole and cut-off wall on hydraulic gradient and uplift pressure under a diversion dam


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      In hydraulic structures such as diversion or gravity dams constructed on a porous foundation, the difference in water levels between upstream and downstream results in water seepage through the porous soil the dam. This seepage flow generates uplift pressure under the structure that may cause a crack on theconcrete surface of the structure’s floor. In this condition, the exit gradient may exceed the critical value and cause the piping phenomenon. In this study, the effect of the weep hole and cut-off wall on the uplift pressure and the hydraulic gradient under a diversion dam was investigated experimentally and numerically. For this purpose, four weep holes (diameter = 1 cm) were embedded along the longitudinal axis of the stilling basin. The weep holes were examined in single and combined modes. The experiments were conducted in three upstreamwater heads of 10, 15, and 20 cm. The results showed that in terms of seepage losses, hydraulic gradient, and uplift pressure, the binary combinations of weep holes are better than the other modes. Among the binary combinations, the combination of the two closest weep holes to the dam toe (weep holes 1 and 2) had the most performance. In the supplementary experiments, a cut-off wall in two depths (10 and 15 cm) was placed at the dam heel in addition to the best modes of weep holes combination. Overall, the simultaneous use of cut-off wall (especially 15 cm) and weep holes improved the hydraulic condition of seepage phenomenon under the dam.

    • The effect of duplex surface treatment on erosion performance of QRO 90 Supreme steel


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      In this study, CrN and TiAlN thin films were deposited on plasma-nitrided QRO 90 Supreme hot work tool steel by physical vapor deposition process and analysed with regard to their erosion performance under hydro-abrasive erosion conditions. The as-received specimens were quenched to room temperature from 1050°C and tempered gradually at 605°C for 2 h and at 560°C for 4 h. These specimens were plasma-nitrided for 10 h at 500°C at a pressure of 250 Pa in a gas mixture of 80% N₂ + 20% H₂ and then coated with TiAlN or CrN coatings by cathode arc evaporation. The specimens were characterized by metallographic techniques,SEM, EDS and micro-hardness test. Plasma nitriding and duplex surface treatments significantly increased thehardness of the specimens and thus significantly reduced the erosion of the specimens. The hardnesses on the surface of plasma-nitrided, CrN-deposited and TiAlN-deposited QRO 90 steels were 1092 HV₀.₀₂₅, 2436 HV₀.₀₂₅ and 3578 HV₀.₀₂₅, respectively. TiAlN-coated specimens were about 17-fold harder than the as-received specimens and over 3-fold harder than the plasma-nitrided specimens. The erosion resistance of CrN-coatedspecimens was increased by a factor of 3.6 and 1.5 compared with that of the as-received and plasma-nitrided specimens, respectively. A brittle fracture phenomenon was observed on the eroded surface of the duplex-treatedspecimens while a ductile material removal was observed on the as-received and the tempered specimens. The plasma-nitrided specimens showed a mixed behaviour of ductility and brittleness.

    • Whale–crow optimization (WCO)-based Optimal Regression model for Software Cost Estimation


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      Software Cost Estimation (SCE) is the emerging concern of the software companies during the development phase of the software, as it requires effort and cost factors for modelling the software. These factors are modelled using the Artificial Intelligence models, which seem to be less accurate and non-reliable byincreasing the risk factor of the software projects. Thus, for estimating the software cost, meta-heuristics are employed. This paper proposes an algorithm, termed as whale–crow optimization (WCO) algorithm, which is the integration of the whale optimization algorithm (WOA) and the crow search algorithm (CSA). The mainfunction of the WCO algorithm is to determine the Optimal Regression coefficients for the regression models, such as the Linear Regression model and the Kernel Logistic Regression model, to develop an Optimal Regression model to estimate the software cost. The experimentation is carried out using four datasets takenfrom the Promise software engineering repository to perform effective performance analysis. Analysis is carried out regarding the mean magnitude of relative error (MMRE) that proves that the proposed method of SCE is effective, attaining the average MMRE at a rate of 0.2442 for the proposed Linear Regression model and 0.2692 for the proposed Kernel Regression model.

    • An inventory system for varying deteriorating pharmaceutical items with price-sensitive demand and variable holding cost under partial backlogging in healthcare industries


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      This paper presents an inventory system for deteriorating pharmaceutical items with price-sensitive demand. Mostly existing studies of pharmaceutical inventory models consider the rate of deterioration as constant, which is not logical in the context of healthcare industries because pharmaceutical products (medicineor drugs) deteriorate significantly. Hence, the rate of deterioration is considered as time-dependent and follows a three-parameter Weibull distribution. In most of the developed models it is believed that the different costs related with inventory remain the same all the time whereas in realistic situations, manufacturing cost ofmedicine, the cost of maintaining the pharmaceutical products in the cold store or even the cost of keeping the patient’s record increases with time. Thus, the cost of the holding of items is taken as time-dependent. Shortages are allowed in this study and are partially backlogged. The main objective of this study is to optimize the total average cost of the system by computing the optimal ordering quantity and the optimal time interval. Finally, a numerical illustration with sensitivity analysis is given to exemplify the proposed study.

    • Lubrication performance analysis of sealing structures in rodless open cylinders


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      As the lubrication performance of sealing structures in rodless open cylinders varies with sliding velocity, the concept of a critical velocity is proposed based on the aforementioned characteristics and the lubrication performance of sealing structure is analysed. A finite-element model of sealing structure is establishedand the oil film load under dynamic lubrication condition is obtained. A two-dimensional theoretical model of lubrication performance in sealing structure is established based on the proposed critical velocity. The influence on critical velocity of parameters including pre-compression, geometry size and microscopic morphology is analysed. Considering surface microscopic morphology, generation of heat by friction, heat flux distribution and other factors, a three-dimensional numerical model of lubrication performance of sealing structure is established to reveal the influence of texture mechanism on lubrication performance. As concluded, with the increase of pre-compression, the lip angle and the temperature of lubrication oil, the critical velocity increases. The three-dimensional microscopic morphology of seal ring is found to pose obvious influence on critical velocity, and the isotropic microscopic morphology tends to form total lubrication under the same conditions.

    • Identification of efficient algorithms for web search through implementation of learning-to-rank algorithms


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      Today, amount of information on the web such as number of publicly accessible web pages, hosts and web data is increasing rapidly and exhibiting an enormous growth at an exponential rate. Thus, information retrieval on web is becoming more difficult. Conventional methods of information retrieval are not very effective in ranking since they rank the results without automatically learning the model. Machine learning domain called learning-to-rank comes to the aid to rank the obtained results. Different state-of-the-art methodologies have been developed for learning-to-rank to date. This paper focuses on finding out the bestalgorithm for web search by implementation of different state-of-the-art algorithms for learning-to-rank. Our work in this paper marks the implementation of learning-to-rank algorithms and analyses effect of topmost performing algorithms on respective datasets. It presents an overall review on the approaches designed under learning-to-rank and their evaluation strategies.

    • Mechanical characteristics and flexural behaviour of fibre-reinforced cementitious composite containing PVA and basalt fibres


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      Fibre-reinforced cementitious composite (FRCC) is a type of composite that uses high volume of fibres to attain ductile properties. In this research, the effects of two different fibres, namely polyvinyl alcohol (PVA) and basalt, on the mechanical properties of FRCC such as compressive, splitting tensile and flexuralstrengths were investigated. The fibres were used in varying volume fraction, which includes 1.0%, 1.5% and 2.0% and a hybrid combination of 1.5% basalt fibre with 1.5% PVA fibre for the preparation of the FRCC. The results showed that while the fibres had minimal effect on the compressive strength of FRCC, significant improvements in the splitting tensile and flexural strengths were found. In the comparison of the flexural performances, the introduction of PVA fibre in FRCC led to superior properties and it exhibited more ductile failure mode compared with basalt fibre and the optimum fibre dosage to be added was determined to be 1.5%.

    • Novel RNS-to-binary converters for the three-moduli set {2m - 1, 2m, 2m + 1}


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      In this paper, Mixed Radix Conversion (MRC)-based Residue Number System (RNS)-to-binary converters for the three-moduli set {2m - 1, 2m, 2m ? 1} are presented. The proposed reverse converters are evaluated and compared to reverse converters proposed earlier in literature using Chinese Remainder Theorem(CRT) and New CRT for this moduli set as well as two four-moduli sets {2n - 1, 2n, 2n + 1, 2n+1 - 1} and {2n - 1, 2n, 2n + 1, 2n+1 + 1} regarding hardware requirement and conversion time.

    • Simultaneous estimation of unknown parameters using a-priori knowledge for the estimation of interfacial heat transfer coefficient during solidification of Sn–5wt%Pb alloy—an ANN-driven Bayesian approach


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      The present methodology focuses on model reduction in which the prevalent one-dimensional transient heat conduction equation for a horizontal solidification of Sn–5wt%Pb alloy is replaced with Artificial Neural Network (ANN) in order to estimate the unknown constants present in the interfacial heat transfercoefficient correlation. As a novel approach, ANN-driven forward model is synergistically combined with Bayesian framework and Genetic algorithm to simultaneously estimate the unknown parameters and modellingerror. Gaussian noise is then added to the temperature distribution obtained using the forward approach to represent real-time experiments. The hallmark of the present work is to reduce the computational time of both the forward and the inverse methods and to simultaneously estimate the unknown parameters using a-priori engineering knowledge. The results of the present methodology prove that the simultaneous estimation of unknown parameters can be effectively obtained only with the use of Bayesian framework.

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