Search results for: Performance evaluation of order picking.

Authors: Mohd Iskandar bin Illyas Tan, Iziati Saadah bt Ibrahim

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Logistics is part of the supply chain processes that plans, implements, and controls the efficient and effective forward and reverse flow and storage of goods, services, and related information between the point of origin and the point of consumption in order to meet customer requirements. This research aims to investigate the current status and future direction of the use of Information Technology (IT) for logistics, focusing on Supply Chain Management (SCM) and E-Commerce adoption in Johor. Therefore, this research stresses on the type of technology being adopted, factors, benefits and barriers affecting the innovation in SCM and ECommerce technology adoption among Logistics Service Providers (LSP). A mailed questionnaire survey was conducted to collect data from 265 logistics companies in Johor. The research revealed that SCM technology adoption among LSP was higher as they had adopted SCM technology in various business processes while they perceived a high level of benefits from SCM adoption. Obviously, ECommerce technology adoption among LSP is relatively low.

Keywords: E-Commerce, Johor, Logistics Service Providers, Supply Chain Management.

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Authors: Ghalem Belalem, Yahya Slimani

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Large scale systems such as computational Grid is a distributed computing infrastructure that can provide globally available network resources. The evolution of information processing systems in Data Grid is characterized by a strong decentralization of data in several fields whose objective is to ensure the availability and the reliability of the data in the reason to provide a fault tolerance and scalability, which cannot be possible only with the use of the techniques of replication. Unfortunately the use of these techniques has a height cost, because it is necessary to maintain consistency between the distributed data. Nevertheless, to agree to live with certain imperfections can improve the performance of the system by improving competition. In this paper, we propose a multi-layer protocol combining the pessimistic and optimistic approaches conceived for the data consistency maintenance in large scale systems. Our approach is based on a hierarchical representation model with tree layers, whose objective is with double vocation, because it initially makes it possible to reduce response times compared to completely pessimistic approach and it the second time to improve the quality of service compared to an optimistic approach.

Keywords: Data Grid, replication, consistency, optimistic approach, pessimistic approach.

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Authors: Mehdi Saati, Mohammad Bagheri, Fatemeh Zamanian

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One of the most important parameters to develop and manage urban areas is appropriate selection of land surface to develop green spaces in these areas. In this study, in order to identify the most appropriate sites and areas cultivated for ornamental species in Jiroft, Landsat Enhanced Thematic Mapper Plus (ETM+) images due to extract the most important effective climatic and adaphic parameters for growth ornamental species were used. After geometric and atmospheric corrections applied, to enhance accuracy of multi spectral (XS) bands, the fusion of Landsat XS bands by IRS-1D panchromatic band (PAN) was performed. After field sampling to evaluate the correlation between different factors in surface soil sampling location and different bands digital number (DN) of ETM+ sensor on the same points, correlation tables formed using the best computational model and the map of physical and chemical parameters of soil was produced. Then the accuracy of them was investigated by using kappa coefficient. Finally, according to produced maps, the best areas for cultivation of recommended species were introduced.

Keywords: Locate ornamental species, Remote Sensing, Adaphic parameters, ETM+, Jiroft

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Authors: Ivan Živanović, Žužana Vaštag, Senka Popović, Ljiljana Popović, Draginja Peričin

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The present work represents an investigation of the hydrolysis of hull-less pumpkin (Cucurbita Pepo L.) oil cake protein isolate (PuOC PI) by pepsin. To examine the effectiveness and suitability of pepsin towards PuOC PI the kinetic parameters for pepsin on PuOC PI were determined and then, the hydrolysis process was studied using Response Surface Methodology (RSM). The hydrolysis was carried out at temperature of 30°C and pH 3.00. Time and initial enzyme/substrate ratio (E/S) at three levels were selected as the independent parameters. The degree of hydrolysis, DH, was mesuared after 20, 30 and 40 minutes, at initial E/S of 0.7, 1 and 1.3 mA/mg proteins. Since the proposed second-order polynomial model showed good fit with the experimental data (R2 = 0.9822), the obtained mathematical model could be used for monitoring the hydrolysis of PuOC PI by pepsin, under studied experimental conditions, varying the time and initial E/S. To achieve the highest value of DH (39.13 %), the obtained optimum conditions for time and initial E/S were 30 min and 1.024 mA/mg proteins.

Keywords: Enzymatic hydrolysis, Pepsin, Pumpkin (CucurbitaPepo L.) oil cake protein isolate, Response surface methodology.

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Authors: R. Sharma, M. Gopal

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Markov games can be effectively used to design controllers for nonlinear systems. The paper presents two novel controller design algorithms by incorporating ideas from gametheory literature that address safety and consistency issues of the 'learned' control strategy. A more widely used approach for controller design is the H∞ optimal control, which suffers from high computational demand and at times, may be infeasible. We generate an optimal control policy for the agent (controller) via a simple Linear Program enabling the controller to learn about the unknown environment. The controller is facing an unknown environment and in our formulation this environment corresponds to the behavior rules of the noise modeled as the opponent. Proposed approaches aim to achieve 'safe-consistent' and 'safe-universally consistent' controller behavior by hybridizing 'min-max', 'fictitious play' and 'cautious fictitious play' approaches drawn from game theory. We empirically evaluate the approaches on a simulated Inverted Pendulum swing-up task and compare its performance against standard Q learning.

Keywords: Fictitious Play, Cautious Fictitious Play, InvertedPendulum, Controller, Markov Games, Mobile Robot.

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Authors: Mohammad Jafarifar

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Multiphase Induction Machine (IM) is normally controlled using rotor field oriented vector control. Under phase(s) loss, the machine currents can be optimally controlled to satisfy certain optimization criteria. In this paper we discuss the performance of double manifold sliding mode observer (DM-SMO) in Sensorless control of multiphase induction machine under unsymmetrical condition (one phase loss). This observer is developed using the IM model in the stationary reference frame. DM-SMO is constructed by adding extra feedback term to conventional single mode sliding mode observer (SM-SMO) which proposed in many literature. This leads to a fully convergent observer that also yields an accurate estimate of the speed and stator currents. It will be shown by the simulation results that the estimated speed and currents by the method are very well and error between real and estimated quantities is negligible. Also parameter sensitivity analysis shows that this method is rather robust against parameter variation.

Keywords: Multiphase induction machine, field oriented control, sliding mode, unsymmetrical condition, manifold.

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Authors: Olga Tkacheva, Pavel Arkhipov, Alexey Rudenko, Yurii Zaikov

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The aluminum electrolysis process in the conventional cryolite-alumina electrolyte with cryolite ratio of 2.7 was carried out at an initial temperature of 970 °C and the anode current density of 0.5 A/cm² in a 15A lab-scale cell in order to study the formation of the side ledge during electrolysis and the alumina distribution between electrolyte and side ledge. The alumina contained 35.97% α-phase and 64.03% γ-phase with the particles size in the range of 10-120 μm. The cryolite ratio and the alumina concentration were determined in molten electrolyte during electrolysis and in frozen bath after electrolysis. The side ledge in the electrolysis cell was formed only by the 13^th hour of electrolysis. With a slight temperature decrease a significant increase in the side ledge thickness was observed. The basic components of the side ledge obtained by the XRD phase analysis were Na₃AlF₆, Na₅Al₃F₁₄, Al₂O₃, and NaF^.5CaF₂^.AlF₃. As in the industrial cell, the increased alumina concentration in the side ledge formed on the cell walls and at the ledge-electrolyte-aluminum three-phase boundary during aluminum electrolysis in the lab cell was found (FTP No 05.604.21.0239, IN RFMEFI60419X0239).

Keywords: Alumina, alumina distribution, aluminum electrolyzer, cryolite-alumina electrolyte, side ledge.

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Authors: Imen Mejri, Ahmed Mahmoudi, Mohamed A. Abbassi, Ahmed Omri

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Thermal radiation plays a very important role in the heat transfer combination through the various components of the SOFC fuel cell operating at high temperatures. Lattice Boltzmann method is used for treating conduction-radiation heat transfer in the electrolyte. The thermal radiation heat transfer is coupled to the overall energy conservation equations through the divergence of the local radiative flux. The equation of energy in one dimension is numerically resolved by using the Lattice Boltzmann method. A computing program (FORTRAN) is developed locally for this purpose in order to obtain fields of temperature in every element of the cell. The parameters investigated are: functioning temperature, cell voltages and electrolyte thickness. The results show that the radiation effect increases with increasing the electrolyte thickness, also increases with increasing the functioning temperature and decreases with the increase of the voltage of the cell.

Keywords: SOFC, lattice Boltzmann method, conduction, radiation, planar medium.

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Authors: P. K. Panigrahi, Saradindu Ghosh, Dayal R. Parhi

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Now-a-days autonomous mobile robots have found applications in diverse fields. An autonomous robot system must be able to behave in an intelligent manner to deal with complex and changing environment. This work proposes the performance of path planning and navigation of autonomous mobile robot using Gravitational Search Algorithm (GSA), Simulated Annealing (SA) and Particle Swarm optimization (PSO) based intelligent controllers in an unstructured environment. The approach not only finds a valid collision free path but also optimal one. The main aim of the work is to minimize the length of the path and duration of travel from a starting point to a target while moving in an unknown environment with obstacles without collision. Finally, a comparison is made between the three controllers, it is found that the path length and time duration made by the robot using GSA is better than SA and PSO based controllers for the same work.

Keywords: Autonomous Mobile Robot, Gravitational Search Algorithm, Particle Swarm Optimization, Simulated Annealing Algorithm.

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Authors: Mohammad Amin Safi, Mahmud Ashrafizaadeh, Amir Ali Ashrafizaadeh

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A highly optimized implementation of binary mixture diffusion with no initial bulk velocity on graphics processors is presented. The lattice Boltzmann model is employed for simulating the binary diffusion of oxygen and nitrogen into each other with different initial concentration distributions. Simulations have been performed using the latest proposed lattice Boltzmann model that satisfies both the indifferentiability principle and the H-theorem for multi-component gas mixtures. Contemporary numerical optimization techniques such as memory alignment and increasing the multiprocessor occupancy are exploited along with some novel optimization strategies to enhance the computational performance on graphics processors using the C for CUDA programming language. Speedup of more than two orders of magnitude over single-core processors is achieved on a variety of Graphical Processing Unit (GPU) devices ranging from conventional graphics cards to advanced, high-end GPUs, while the numerical results are in excellent agreement with the available analytical and numerical data in the literature.

Keywords: Lattice Boltzmann model, Graphical processing unit, Binary mixture diffusion, 2D flow simulations, Optimized algorithm.

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Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Tae-Hyeon Oh, Dae-Gyu Park

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Automotive interior material consisting of several material layers has the sound-absorbing function. It is difficult to predict sound absorbing coefficient because of several material layers. So, many experimental tunings are required to achieve the target of sound absorption. Therefore, while the car interior materials are developed, so much time and money is spent. In this study, we present a method to predict the sound absorbing performance of the material with multi-layer using physical properties of each material. The properties are predicted by Foam-X software using the sound absorption coefficient data measured by impedance tube. Then, we will compare and analyze the predicted sound absorption coefficient with the data measured by scaled reverberation chamber and impedance tubes for a prototype. If the method is used instead of experimental tuning in the development of car interior material, the time and money can be saved, and then, the development effort can be reduced because it can be optimized by simulation.

Keywords: Multi-layer nonwoven, sound absorption coefficient, scaled reverberation chamber, impedance tubes.

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Authors: Pankaj K. Gupta, Krishnan V. Pagalthivarthi

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The present work compares the performance of three turbulence modeling approach (based on the two-equation k -ε model) in predicting erosive wear in multi-size dense slurry flow through rotating channel. All three turbulence models include rotation modification to the production term in the turbulent kineticenergy equation. The two-phase flow field obtained numerically using Galerkin finite element methodology relates the local flow velocity and concentration to the wear rate via a suitable wear model. The wear models for both sliding wear and impact wear mechanisms account for the particle size dependence. Results of predicted wear rates using the three turbulence models are compared for a large number of cases spanning such operating parameters as rotation rate, solids concentration, flow rate, particle size distribution and so forth. The root-mean-square error between FE-generated data and the correlation between maximum wear rate and the operating parameters is found less than 2.5% for all the three models.

Keywords: Rotating channel, maximum wear rate, multi-sizeparticulate flow, k −ε turbulence models.

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Authors: Adil Loya, Kamran Maqsood, Muhammad Duraid

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Aerodynamic stability coefficients are necessary to be known before any unmanned aircraft flight is performed. This requires expertise on aerodynamics and stability control of the aircraft. To enable efficacious performance of aircraft requires that a well-defined flight path and aerodynamics should be defined beforehand. This paper presents a study on the aerodynamics of an unmanned aero vehicle (UAV) during flight conditions. Current research holds comparative studies of different parameters for flight aerodynamic, measured using two different open source analytical software programs. These software packages are DATCOM and XLRF5, which help in depicting the flight aerodynamic variables. Computational fluid dynamics (CFD) was also used to perform aerodynamic analysis for which Star CCM+ was used. Output trends of the study demonstrate high accuracies between the two software programs with that of CFD. It can be seen that the Coefficient of Lift (CL) obtained from DATCOM and XFLR is similar to CL of CFD simulation. In the similar manner, other potential aerodynamic stability parameters obtained from analytical software are in good agreement with CFD.

Keywords: XFLR5, DATCOM, computational fluid dynamic, unmanned aero vehicle.

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Authors: Feras Al-Obeidat, Nabil Belacel, Juan A. Carretero, Prabhat Mahanti,

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In this paper, a new learning algorithm based on a hybrid metaheuristic integrating Differential Evolution (DE) and Reduced Variable Neighborhood Search (RVNS) is introduced to train the classification method PROAFTN. To apply PROAFTN, values of several parameters need to be determined prior to classification. These parameters include boundaries of intervals and relative weights for each attribute. Based on these requirements, the hybrid approach, named DEPRO-RVNS, is presented in this study. In some cases, the major problem when applying DE to some classification problems was the premature convergence of some individuals to local optima. To eliminate this shortcoming and to improve the exploration and exploitation capabilities of DE, such individuals were set to iteratively re-explored using RVNS. Based on the generated results on both training and testing data, it is shown that the performance of PROAFTN is significantly improved. Furthermore, the experimental study shows that DEPRO-RVNS outperforms well-known machine learning classifiers in a variety of problems.

Keywords: Knowledge Discovery, Differential Evolution, Reduced Variable Neighborhood Search, Multiple criteria classification, PROAFTN, Supervised Learning.

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Authors: Samson Henry Dogo, Allan Clark, Elena Kulinskaya

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The objective of meta-analysis is to combine results from several independent studies in order to create generalization and provide evidence base for decision making. But recent studies show that the magnitude of effect size estimates reported in many areas of research significantly changed over time and this can impair the results and conclusions of meta-analysis. A number of sequential methods have been proposed for monitoring the effect size estimates in meta-analysis. However they are based on statistical theory applicable only to fixed effect model (FEM) of meta-analysis. For random-effects model (REM), the analysis incorporates the heterogeneity variance, τ 2 and its estimation create complications. In this paper we study the use of a truncated CUSUM-type test with asymptotically valid critical values for sequential monitoring in REM. Simulation results show that the test does not control the Type I error well, and is not recommended. Further work required to derive an appropriate test in this important area of applications.

Keywords: Meta-analysis, random-effects model, sequential testing, temporal changes in effect sizes.

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Authors: S. Nazar, M. A. Ismaeil

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This paper presents a comparative study of static analysis procedure for seismic performance based on UBC-1997 and SBC-301-2007(Saudi Arabia). These building codes define different ductility classes and corresponding response reduction factors based on material, configuration and detailing of reinforcements. Codes differ significantly in specifying the procedures to estimate base shear, drift and effective stiffness of structural members. One of the major improvements made in new SBC (based on IBC-2003) is ground motion parameters used for seismic design. In old SBC (based on UBC) maps have been based on seismic zones. However new SBC provide contour maps giving spectral response quantities. In this approach, a case study of RC frame building located in two different cities and with different ductility classes has been performed. Moreover, equivalent static method based on SBC-301 and UBC-1997 is used to explore the variation in results based on two codes, particularly design base shear, lateral loads and story drifts.

Keywords: Ductility Classes, Equivalent Static method, RC Frames, SBC-301-2007, Story drifts, UBC-1997.

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Authors: Hamad N. Altalyan, Brian G. Jones, John Bradd

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A comprehensive study was conducted to examine the removal of inorganic contaminants that exist in surface and groundwater in the Illawarra and Sydney regions. The ability of multi-walled carbon nanotubes (MWCNT), as a generation of membrane technology, was examined using a dead-end filtration cell setup. A set of ten compounds were examined in this study that represent the significant inorganic cations and anions commonly found in contaminated surface and groundwater. The performance of MWCNT buckypaper membranes in excluding anions was found to be better than that of its cation exclusion. This phenomenon can be attributed to the Donnan exclusion mechanism (charge repulsion mechanism). Furthermore, the results revealed that phosphate recorded the highest exclusion value reaching 69.2%, whereas the lowest rejection value was for potassium where no removal occurred (0%). The reason for this is that the molecular weight of phosphate (95.0 g/mol) is greater than the molecular weight of potassium (39.10 g/mol).

Keywords: Nanotechnology, buckypaper, carbon nanotube, CNT, multi-walled carbon nanotube, MWCNT, Botany Bay, Russell Vale.

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Authors: Fridhi Hadia, Soua Wadhah, Hidouri Ammar, Omri Ahmed

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In order to understand the auto-ignition process in a HCCI engine better, the influence of some important parameters on the auto-ignition is investigated. The inlet temperature, the inlet pressure, and the compression ratio were varied and their influence on the ignition delays and emission characteristics were studied. The inlet temperature was changed from 400 K to 460 K (in step of 15 K), the inlet pressure from 0.9 to 3 atm, while the compression ratio varied from 15 to 23. The fuel that was investigated is isooctane. The inlet temperature, the inlet pressure, and the compression ratio appeared to decrease the ignition delays, with the inlet pressure having the least influence and the compression ratio the most. The effect of these parameters on emissions’ characteristics were also investigated. Results indicate that increasing the compression ratio results in increasing the concentration of all the species.

Keywords: Compression Ratio, intake temperature, intake pressure, HCCI engine, isooctane.

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Authors: Gizem Kodak

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The Strait of Çanakkale (Dardanelles), together with the Strait of Istanbul and the Sea of Marmara, form the Turkish Straits System. In other words, the Strait of Çanakkale is the southern gate of the system that connects the Black Sea countries with the other countries of the world. Due to the heavy maritime traffic, it is important to scientifically examine the accident characteristics in the region. In particular, the results indicated by the descriptive statistics are of critical importance in order to strengthen the safety of navigation. At this point, exploratory data analysis offers strategic outputs in terms of defining the problem and knowing the strengths and weaknesses against possible accident risk. The study aims to determine the accident characteristics in the Strait of Çanakkale with temporal and spatial analysis of historical data, using Exploratory Data Analysis (EDA) as the research method. The study's results will reveal the general characteristics of maritime accidents in the region and form the infrastructure for future studies. Therefore, the text provides a clear description of the research goals and methodology, and the study's contributions are well-defined.

Keywords: Maritime Accidents, EDA, Strait of Çanakkale, navigational safety.

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Authors: Umar Alhaji Mukhtar, Abubakar Mohammed El-jummah

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This research involved the utilization of fluid flow energy to predict power output using Lead Zirconate Titanate (PZT) piezoelectric stacks. The aim of this work is to extract energy from a controlled level of pressure fluctuation in single-phase flow which forms a part of the energy harvesting technology that powers flow meters. A device- Perspex box was developed and fixed to 50.8 mm rig to induce pressure fluctuation in the flow. An experimental test was carried out using the single-phase water flow in the developed rig in order to measure the power output generation from the piezoelectric stacks. 16 sets of experimental tests were conducted to ensure the maximum output result. The acquired signal of the pressure fluctuation was used to simulate the expected electrical output from the piezoelectric material. The results showed a maximum output voltage of 12 V with an instantaneous output power of 1 µW generated, when the pressure amplitude is 2.6 kPa at a frequency of 2.4 Hz.

Keywords: Energy harvesting, experimental test, perspex rig, pressure fluctuation.

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Authors: N. Marzban, J. K. Heydarzadeh M. Pourmohammadbagher, M. H. Hatami, A. Samia

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A nano-alumina-zirconia composite catalyst was synthesized by a simple aqueous sol-gel method using AlCl₃.6H₂O and ZrCl₄ as precursors. Thermal decomposition of the precursor and subsequent formation of γ-Al₂O₃ and t-Zr were investigated by thermal analysis. XRD analysis showed that γ-Al₂O₃ and t-ZrO₂ phases were formed at 700 °C. FT-IR analysis also indicated that the phase transition to γ-Al₂O₃ occurred in corroboration with X-ray studies. TEM analysis of the calcined powder revealed that spherical particles were in the range of 8-12 nm. The nano-alumina-zirconia composite particles were mesoporous and uniformly distributed in their crystalline phase. In order to measure the catalytic activity, esterification reaction was carried out. Biodiesel, as a renewable fuel, was formed in a continuous packed column reactor. Free fatty acid (FFA) was esterified with ethanol in a heterogeneous catalytic reactor. It was found that the synthesized γ-Al₂O₃/ZrO₂ composite had the potential to be used as a heterogeneous base catalyst for biodiesel production processes.

Keywords: Nano-alumina-zirconia, composite catalyst, thin film, biodiesel.

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Authors: Ahmad Yame, Ahad Ali, Badih Jawad, Daw Al-Werfalli Mohamed Nasser, Sabah Abro

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Industries in general have a lot of waste. Wool textile company, Baniwalid, Libya has many complex problems that led to enormous waste generated due to the lack of lean strategies, expertise, technical support and commitment. To successfully address waste at wool textile company, this study will attempt to develop a methodical approach that integrates lean manufacturing tools to optimize performance characteristics such as lead time and delivery. This methodology will utilize Value Stream Mapping (VSM) techniques to identify the process variables that affect production. Once these variables are identified, Design of Experiments (DOE) Methodology will be used to determine the significantly influential process variables, these variables are then controlled and set at their optimal to achieve optimal levels of productivity, quality, agility, efficiency and delivery to analyze the outputs of the simulation model for different lean configurations. The goal of this research is to investigate how the tools of lean manufacturing can be adapted from the discrete to the continuous manufacturing environment and to evaluate their benefits at a specific industrial.

Keywords: Lean manufacturing, DOE, value stream mapping, textiles.

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Authors: Flur R. Ismagilov, Irek Kh. Khayrullin, Vyacheslav E. Vavilov, Ruslan D. Karimov, Anton S. Gorbunov, Danis R. Farrakhov

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The paper presents another structural scheme of high-temperature starter-generator with external rotor to be installed on High Pressure Shaft (HPS) of aircraft engines (AE) to implement More Electrical Engine concept. The basic materials to make this starter-generator (SG) were selected and justified. Multi-criteria optimization of the developed structural scheme was performed using a genetic algorithm and Pareto method. The optimum (in Pareto terms) active length and thickness of permanent magnets of SG were selected as a result of the optimization. Using the dimensions obtained, allowed to reduce the weight of the designed SG by 10 kg relative to a base option at constant thermal loads. Multidisciplinary computer simulation was performed on the basis of the optimum geometric dimensions, which proved performance efficiency of the design. We further plan to make a full-scale sample of SG of HPS and publish the results of its experimental research.

Keywords: High-temperature starter-generator, More electrical engine, multi-criteria optimization, permanent magnet.

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Authors: Salma Parvin, M. A. Alim

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The convective and radiative heat transfer performance and entropy generation on forced convection through a direct absorption solar collector (DASC) is investigated numerically. Four different fluids, including Cu-water nanofluid, Al₂O₃-waternanofluid, TiO₂-waternanofluid, and pure water are used as the working fluid. Entropy production has been taken into account in addition to the collector efficiency and heat transfer enhancement. Penalty finite element method with Galerkin’s weighted residual technique is used to solve the governing non-linear partial differential equations. Numerical simulations are performed for the variation of mass flow rate. The outcomes are presented in the form of isotherms, average output temperature, the average Nusselt number, collector efficiency, average entropy generation, and Bejan number. The results present that the rate of heat transfer and collector efficiency enhance significantly for raising the values of m up to a certain range.

Keywords: DASC, forced convection, mass flow rate, nanofluid.

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Authors: B. S. Raghavendra, D. Narayana Dutt

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Many recent electrophysiological studies have revealed the importance of investigating meditation state in order to achieve an increased understanding of autonomous control of cardiovascular functions. In this paper, we characterize heart rate variability (HRV) time series acquired during meditation using nonlinear dynamical parameters. We have computed minimum embedding dimension (MED), correlation dimension (CD), largest Lyapunov exponent (LLE), and nonlinearity scores (NLS) from HRV time series of eight Chi and four Kundalini meditation practitioners. The pre-meditation state has been used as a baseline (control) state to compare the estimated parameters. The chaotic nature of HRV during both pre-meditation and meditation is confirmed by MED. The meditation state showed a significant decrease in the value of CD and increase in the value of LLE of HRV, in comparison with premeditation state, indicating a less complex and less predictable nature of HRV. In addition, it was shown that the HRV of meditation state is having highest NLS than pre-meditation state. The study indicated highly nonlinear dynamic nature of cardiac states as revealed by HRV during meditation state, rather considering it as a quiescent state.

Keywords: Correlation dimension, Embedding dimension, Heartrate variability, Largest Lyapunov exponent, Meditation, Nonlinearity score.

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Authors: Sanaa Chafik, ImaneDaoudi, Mounim A. El Yacoubi, Hamid El Ouardi

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Locality Sensitive Hashing (LSH) is one of the most promising techniques for solving nearest neighbour search problem in high dimensional space. Euclidean LSH is the most popular variation of LSH that has been successfully applied in many multimedia applications. However, the Euclidean LSH presents limitations that affect structure and query performances. The main limitation of the Euclidean LSH is the large memory consumption. In order to achieve a good accuracy, a large number of hash tables is required. In this paper, we propose a new hashing algorithm to overcome the storage space problem and improve query time, while keeping a good accuracy as similar to that achieved by the original Euclidean LSH. The Experimental results on a real large-scale dataset show that the proposed approach achieves good performances and consumes less memory than the Euclidean LSH.

Keywords: Approximate Nearest Neighbor Search, Content based image retrieval (CBIR), Curse of dimensionality, Locality sensitive hashing, Multidimensional indexing, Scalability.

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Authors: Cheng-Hong Yang, Tsung-Mu Shih, Li-Yeh Chuang

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Serial Analysis of Gene Expression is a powerful quantification technique for generating cell or tissue gene expression data. The profile of the gene expression of cell or tissue in several different states is difficult for biologists to analyze because of the large number of genes typically involved. However, feature selection in machine learning can successfully reduce this problem. The method allows reducing the features (genes) in specific SAGE data, and determines only relevant genes. In this study, we used a genetic algorithm to implement feature selection, and evaluate the classification accuracy of the selected features with the K-nearest neighbor method. In order to validate the proposed method, we used two SAGE data sets for testing. The results of this study conclusively prove that the number of features of the original SAGE data set can be significantly reduced and higher classification accuracy can be achieved.

Keywords: Serial Analysis of Gene Expression, Feature selection, Genetic Algorithm, K-nearest neighbor method.

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Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

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Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: Fake news detection, types of fake news, machine learning, natural language processing, classification techniques.

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Authors: Mahmud Fotuhi-Firuzabad, Ali Abbaspour, Mohsen Mazidi, Mohamamd Rastegar

Abstract:

To tackle the air pollution issues, Plug-in Hybrid Electric Vehicles (PHEVs) are proposed as an appropriate solution. Charging a large amount of PHEV batteries, if not controlled, would have negative impacts on the distribution system. The control process of charging of these vehicles can be centralized in parking lots that may provide a chance for better coordination than the individual charging in houses. In this paper, an optimization-based approach is proposed to determine the optimum PHEV parking capacities in candidate nodes of the distribution system. In so doing, a profile for charging and discharging of PHEVs is developed in order to flatten the network load profile. Then, this profile is used in solving an optimization problem to minimize the distribution system losses. The outputs of the proposed method are the proper place for PHEV parking lots and optimum capacity for each parking. The application of the proposed method on the IEEE-34 node test feeder verifies the effectiveness of the method.

Keywords: Plug-in Hybrid Electric Vehicle (PHEV), PHEV parking lot, V2G.

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Authors: Iman Mousavinejad, Reza Kazemi, , Mohsen Bayani Khaknejad

Abstract:

Active Front Steering system (AFS) provides an electronically controlled superposition of an angle to the steering wheel angle. This additional degree of freedom enables a continuous and driving-situation dependent on adaptation of the steering characteristics. In an active steering system, there needs be no fixed relationship between the steering wheel and the angle of the road wheels. Not only can the effective steering ratio be varied with speed, for example, but also the road wheel angles can be controlled by a combination of driver and computer inputs. Features like steering comfort, effort and steering dynamics are optimized and stabilizing steering interventions can be performed. In contrast to the conventional stability control, the yaw rate was fed back to AFS controller and the stability performance was optimized with Sliding Mode control (SMC) method. In addition, tire uncertainties have been taken into account in SM controller to provide the control robustness. In this paper, 3-DOF nonlinear model is used to design the AFS controller and 8-DOF nonlinear model is used to model the controlled vehicle.

Keywords: Active Front Steering (AFS), Sliding Mode Control method (SMC), Yaw rate, Vehicle Stability, Robustness

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