Search results for: Multi Objective Optimization

Authors: Neethu S., Shinoy K.S., A.S. Shajilal

Abstract:

This paper presents the optimal design and development of an axial flux motor for blood pump application. With the design objective of maximizing the motor efficiency and torque, different topologies of AFPM machine has been examined. Selection of optimal magnet fraction, Halbach arrangement of rotor magnets and the use of Soft Magnetic Composite (SMC) material for the stator core results in a novel motor with improved efficiency and torque profile. The results of the 3D Finite element analysis for the novel motor have been shown.

Keywords: Axial flux motor, Finite Element Methods, Halbach array, Left Ventricular Assist Device, Soft magnetic composite.

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Authors: Yeong-Hwa Chang, Chia-Wen Chang, Hung-Wei Lin, C.W. Tao

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In this paper, an improved ant colony optimization (ACO) algorithm is proposed to enhance the performance of global optimum search. The strategy of the proposed algorithm has the capability of fuzzy pheromone updating, adaptive parameter tuning, and mechanism resetting. The proposed method is utilized to tune the parameters of the fuzzy controller for a real beam and ball system. Simulation and experimental results indicate that better performance can be achieved compared to the conventional ACO algorithms in the aspect of convergence speed and accuracy.

Keywords: Ant colony algorithm, Fuzzy control, ball and beamsystem

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Authors: Faeka M. H. Khater, Farouk I. Ahmed, Mohamed I. Abu El- Sebah

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This paper introduces application of multi degree of freedom fuzzy(MDOFF) controller in permanent magnet (PM)drive system. The drive system model is developed for FO control. Simulation of the system is carried out to predict the performance at NL and under load,. The results indicate that application of MDOFF controller is effective for sensorless PM drive system.

Keywords: Sensorless FO controller, PM drives system, MDOFF controller.

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Authors: Jawad Al Khaburi, Abbas A. Dehghani-Sanij, E. Andrea Nelson, Jerry Hutchinson

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Medical compression bandages are widely used in the treatment of chronic venous disorder. In order to design effective compression bandages, researchers have attempted to describe the interface pressure applied by multi-layer bandages using mathematical models. This paper reports on the work carried out to compare and validate the mathematical models used to describe the interface pressure applied by multi-layer bandages. Both analytical and experimental results showed that using simple multiplication of a number of bandage layers with the pressure applied by one layer of bandage or ignoring the increase in the limb radius due to former layers of bandage will result in overestimating the pressure. Experimental results showed that the mathematical models, which take into consideration the increase in the limb radius due to former bandage layers, are more accurate than the one which does not.

Keywords: Compression bandages, FlexiForce, interface pressure, venous ulcer

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Authors: M. Cangi, T. Dolar, C. Ersoy, Y. E. Aydogdu, A. I. Aydeniz, A. Mugan

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The drum is one of the critical parts in a washing machine in which the clothes are washed and spin by the rotational movement. It is activated by the drum shaft which is attached to an electric motor and subjected to dynamic loading. Being one of the critical components, failures of the drum require costly repairs of dynamic components. In this study, tolerance bands between the drum shaft and its two bearings were examined to develop a relationship between the fatigue life of the shaft and the interaction tolerances. Optimization of tolerance bands was completed in consideration of the fatigue life of the shaft as the cost function. The following methodology is followed: multibody dynamic model of a washing machine was constructed and used to calculate dynamic loading on the components. Then, these forces were used in finite element analyses to calculate the stress field in critical components which was used for fatigue life predictions. The factors affecting the fatigue life were examined to find optimum tolerance grade for a given test condition. Numerical results were verified by experimental observations.

Keywords: Fatigue life, finite element analysis, tolerance analysis, optimization.

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Authors: Victor R. Thulari, John Akach, Haleden Chiririwa, Aoyi Ochieng

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Solar-light activated titanium dioxide photocatalysts were prepared by hydrolysis of titanium (IV) isopropoxide with thiourea, followed by calcinations at 450 °C. The experiments demonstrated that methyl orange in aqueous solutions were successfully degraded under solar light using doped TiO₂. The photocatalytic oxidation of a mono azo methyl-orange dye has been investigated in multi ion doped TiO₂ and solar light. Solutions were irradiated by solar-light until high removal was achieved. It was found that there was no degradation of methyl orange in the dark and in the absence of TiO₂. Varieties of laboratory prepared TiO₂ catalysts both un-doped and doped using titanium (IV) isopropoxide and thiourea as a dopant were tested in order to compare their photoreactivity. As a result, it was found that the efficiency of the process strongly depends on the working conditions. The highest degradation rate of methyl orange was obtained at optimum dosage using commercially produced TiO₂. Our work focused on laboratory synthesized catalyst and the maximum methyl orange removal was achieved at 81% with catalyst loading of 0.04 g/L, initial pH of 3 and methyl orange concentration of 0.005 g/L using multi-ion doped catalyst. The kinetics of photocatalytic methyl orange dye stuff degradation was found to follow a pseudo-first-order rate law. The presence of the multi-ion dopant (thiourea) enhanced the photoefficiency of the titanium dioxide catalyst.

Keywords: Degradation, kinetics, methyl orange, photocatalysis.

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Authors: K. K. Starkov, A. Y. Pogromsky, I. J. B. F. Adan, J. E. Rooda

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In this paper we present our results on the performance analysis of a multi-product manufacturing line. We study the influence of external perturbations, intermediate buffer content and the number of manufacturing stages on the production tracking error of each machine in the multi-product line operated under a surplusbased production control policy. Starting by the analysis of a single machine with multiple production stages (one for each product type), we provide bounds on the production error of each stage. Then, we extend our analysis to a line of multi-stage machines, where similarly, bounds on each production tracking error for each product type, as well as buffer content are obtained. Details on performance of the closed-loop flow line model are illustrated in numerical simulations.

Keywords: Flexible manufacturing systems, tracking systems, discrete time systems, production control, boundary conditions.

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Authors: Aaqif Afzaal Abbasi, Javaid Iqbal, Akhtar Nawaz Malik

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4G Communication Networks provide heterogeneous wireless technologies to mobile subscribers through IP based networks and users can avail high speed access while roaming across multiple wireless channels; possible by an organized way to manage the Quality of Service (QoS) functionalities in these networks. This paper proposes the idea of developing a novel QoS optimization architecture that will judge the user requirements and knowing peak times of services utilization can save the bandwidth/cost factors. The proposed architecture can be customized according to the network usage priorities so as to considerably improve a network-s QoS performance.

Keywords: QoS, Network Coverage Boundary, ServicesArchives Units (SAU), Cumulative Services Archives Units (CSAU).

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Authors: Shahana T. K., Babita R. Jose, K. Poulose Jacob, Sreela Sasi

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The demand for new telecommunication services requiring higher capacities, data rates and different operating modes have motivated the development of new generation multi-standard wireless transceivers. A multi-standard design often involves extensive system level analysis and architectural partitioning, typically requiring extensive calculations. In this research, a decimation filter design tool for wireless communication standards consisting of GSM, WCDMA, WLANa, WLANb, WLANg and WiMAX is developed in MATLAB® using GUIDE environment for visual analysis. The user can select a required wireless communication standard, and obtain the corresponding multistage decimation filter implementation using this toolbox. The toolbox helps the user or design engineer to perform a quick design and analysis of decimation filter for multiple standards without doing extensive calculation of the underlying methods.

Keywords: Decimation filter, MATLAB® toolbox, Multistandard transceivers, Sigma-delta A/D converter.

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Authors: Cheng-Hong Yang, Yu-Huei Cheng, Hsueh-Wei Chang, Li-Yeh Chuang

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Before performing polymerase chain reactions (PCR), a feasible primer set is required. Many primer design methods have been proposed for design a feasible primer set. However, the majority of these methods require a relatively long time to obtain an optimal solution since large quantities of template DNA need to be analyzed. Furthermore, the designed primer sets usually do not provide a specific PCR product. In recent years, evolutionary computation has been applied to PCR primer design and yielded promising results. In this paper, a particle swarm optimization (PSO) algorithm is proposed to solve primer design problems associated with providing a specific product for PCR experiments. A test set of the gene CYP1A1, associated with a heightened lung cancer risk was analyzed and the comparison of accuracy and running time with the genetic algorithm (GA) and memetic algorithm (MA) was performed. A comparison of results indicated that the proposed PSO method for primer design finds optimal or near-optimal primer sets and effective PCR products in a relatively short time.

Keywords: polymerase chain reaction (PCR), primer design, evolutionary computation, particle swarm optimization (PSO).

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Authors: Hanadi Mubarak AL-Mubaraki, Aruna, M., Michael Busler

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The objective of this paper is twofold: (1) discuss and analyze the successful case studies worldwide, and (2) identify the similarities and differences of case studies worldwide. Design methodology/approach: The nature of this research is mainly method qualitative (multi-case studies, literature review). This investigation uses ten case studies, and the data was mainly collected and organizational documents from the international countries. Finding: The finding of this research can help incubator manager, policy maker and government parties for successful implementation. Originality/value: This paper contributes to the current literate review on the best practices worldwide. Additionally, it presents future perspective for academicians and practitioners.

Keywords: Incubators, Economic Development, Entrepreneurship, Innovation.

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Authors: Zh. B. Suleimenova, Zh. K. Rakhmetova, R. K. Blieva, A. E. Nurlybayeva

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The overall objective of this research is a strain improvement technology for efficient pectinase production. A novel cells cultivation technology by immobilization of fungal cells has been studied in long time continuous fermentations. Immobilization was achieved by using of new material for absorption of stores of immobilized cultures which was for the first time used for immobilization of microorganisms. Effects of various conditions of nitrogen and carbon nutrition on the biosynthesis of pectolytic enzymes in Aspergillus awamori 1-8 strain were studied. Proposed cultivation technology along with optimization of media components for pectinase overproduction led to increased pectinase productivity in Aspergillus awamori 1-8 from 7 to 8 times. Proposed technology can be applied successfully for production of major industrial enzymes such as α-amylase, protease, collagenase etc.

Keywords: Aspergillus awamori, immobilization, pectolytic enzymes.

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Authors: A. Shayeghi, H. Shayeghi, H. Eimani Kalasar

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In recent years, tuned mass damper (TMD) control systems for civil engineering structures have attracted considerable attention. This paper emphasizes on the application of particle swarm application (PSO) to design and optimize the parameters of the TMD control scheme for achieving the best results in the reduction of the building response under earthquake excitations. The Integral of the Time multiplied Absolute value of the Error (ITAE) based on relative displacement of all floors in the building is taken as a performance index of the optimization criterion. The problem of robustly TMD controller design is formatted as an optimization problem based on the ITAE performance index to be solved using the PSO technique which has a story ability to find the most optimistic results. An 11- story realistic building, located in the city of Rasht, Iran is considered as a test system to demonstrate effectiveness of the proposed method. The results analysis through the time-domain simulation and some performance indices reveals that the designed PSO based TMD controller has an excellent capability in reduction of the seismically excited example building.

Keywords: TMD, Particle Swarm Optimization, Tall Buildings, Structural Dynamics.

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Authors: Fares Senouci, Bachir Imine

Abstract:

This document provides numerical and experimental optimization of the aerodynamic performance of a drone equipped with three types of horizontal stabilizer. To build this optimal configuration, an experimental and numerical study was conducted on three parameters: the geometry of the stabilizer (horizontal form or reverse V form), the position of the horizontal stabilizer (up or down), and the landing gear position (closed or open). The results show that up-stabilizer position with respect to the horizontal plane of the fuselage provides better aerodynamic performance, and that the landing gear increases the lift in the zone of stability, that is to say where the flow is not separated.

Keywords: Aerodynamics, wind tunnel, turbulence model, lift, drag.

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Authors: Isao Taguchi, Yasuo Sugai

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This paper proposes an efficient learning method for the layered neural networks based on the selection of training data and input characteristics of an output layer unit. Comparing to recent neural networks; pulse neural networks, quantum neuro computation, etc, the multilayer network is widely used due to its simple structure. When learning objects are complicated, the problems, such as unsuccessful learning or a significant time required in learning, remain unsolved. Focusing on the input data during the learning stage, we undertook an experiment to identify the data that makes large errors and interferes with the learning process. Our method devides the learning process into several stages. In general, input characteristics to an output layer unit show oscillation during learning process for complicated problems. The multi-stage learning method proposes by the authors for the function approximation problems of classifying learning data in a phased manner, focusing on their learnabilities prior to learning in the multi layered neural network, and demonstrates validity of the multi-stage learning method. Specifically, this paper verifies by computer experiments that both of learning accuracy and learning time are improved of the BP method as a learning rule of the multi-stage learning method. In learning, oscillatory phenomena of a learning curve serve an important role in learning performance. The authors also discuss the occurrence mechanisms of oscillatory phenomena in learning. Furthermore, the authors discuss the reasons that errors of some data remain large value even after learning, observing behaviors during learning.

Keywords: data selection, function approximation problem, multistage leaning, neural network, voluntary oscillation.

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Authors: Saleem Z. Ramadan

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The material selection problem is concerned with the determination of the right material for a certain product to optimize certain performance indices in that product such as mass, energy density, and power-to-weight ratio. This paper is concerned about optimizing the selection of the manufacturing process along with the material used in the product under performance indices and availability constraints. In this paper, the material selection problem is formulated using binary programming and solved by genetic algorithm. The objective function of the model is to minimize the total manufacturing cost under performance indices and material and manufacturing process availability constraints.

Keywords: Optimization, Material selection, Process selection, Genetic algorithm.

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Authors: R. Ramaprabha

Abstract:

This paper presents an extraction of maximum energy from Solar Photovoltaic Array (SPVA) under partial shaded conditions by optimum selection of array size using Particle Swarm Optimization (PSO) technique. In this paper a detailed study on the output reduction of different SPVA configurations under partial shaded conditions have been carried out. A generalized MATLAB M-code based software model has been used for any required array size, configuration, shading patterns and number of bypass diodes. Comparative study has been carried out on different configurations by testing several shading scenarios. While the number of shading patterns and the rate of change are very low for stationary SPVA but these may be quite large for SPVA mounted on a mobile platforms. This paper presents the suitability of PSO technique to select optimum configuration for mobile arrays by calculating the global peak (GP) of different configurations and to transfer maximum power to the load.

Keywords: Global peak, Mobile PV arrays, Partial shading, optimization, PSO.

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Authors: S. Balaji, V. Swaminathan, K. Kannan

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The Minimum Vertex Cover (MVC) problem is a classic graph optimization NP - complete problem. In this paper a competent algorithm, called Vertex Support Algorithm (VSA), is designed to find the smallest vertex cover of a graph. The VSA is tested on a large number of random graphs and DIMACS benchmark graphs. Comparative study of this algorithm with the other existing methods has been carried out. Extensive simulation results show that the VSA can yield better solutions than other existing algorithms found in the literature for solving the minimum vertex cover problem.

Keywords: vertex cover, vertex support, approximation algorithms, NP - complete problem.

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Authors: Y. Harold Robinson, E. Golden Julie, S. Balaji

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The scheduling based routing scheme is presented in this paper to avoid link failure. The main objective of this system is to introduce a cross-layer protocol framework that integrates routing with priority-based traffic management and distributed transmission scheduling. The reservation scheme is based on ID. The presented scheme guarantees that bandwidth reserved time slot is used by another packet in which end-to-end reservation is achieved. The Bandwidth and Delay Aware Routing Protocol with Scheduling Algorithm is presented to allocate channels efficiently. The experimental results show that the presented schemes performed well in various parameters compared to existing methods.

Keywords: Integrated routing, scheduling, MAC layer, IEEE 802.11.

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Authors: Ismail El Gayar, Ossama Ismail, Yousri El Gamal

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This paper presented a technique to solve one of the transportation problems that faces us in real life which is the Bus Scheduling Problem. Most of the countries using buses in schools, companies and traveling offices as an example to transfer multiple passengers from many places to specific place and vice versa. This transferring process can cost time and money, so we build a decision support system that can solve this problem. In this paper, a genetic algorithm with the shortest path technique is used to generate a competitive solution to other well-known techniques. It also presents a comparison between our solution and other solutions for this problem.

Keywords: Bus scheduling problem, decision support system, genetic algorithm, operation planning, shortest path, transportation.

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Authors: Javad Marzbanrad, Mostafa Pahlavani

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This study has investigated a vehicle Lumped Parameter Model (LPM) in frontal crash. There are several ways for determining spring and damper characteristics and type of problem shall be considered as system identification. This study use Genetic Algorithm (GA) procedure, being an effective procedure in case of optimization issues, for optimizing errors, between target data (experimental data) and calculated results (being obtained by analytical solving). In this study analyzed model in 5-DOF then compared our results with 5-DOF serial model. Finally, the response of model due to external excitement is investigated.

Keywords: Vehicle, Lumped-Parameter Model, GeneticAlgorithm, Optimization

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Authors: Njiri J. G., Ikua B. W., Nyakoe G. N.

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Optimization of cutting parameters important in precision machining in regards to efficiency and surface integrity of the machined part. Usually productivity and precision in machining is limited by the forces emanating from the cutting process. Due to the inherent varying nature of the workpiece in terms of geometry and material composition, the peak cutting forces vary from point to point during machining process. In order to increase productivity without compromising on machining accuracy, it is important to control these cutting forces. In this paper a fuzzy logic control algorithm is developed that can be applied in the control of peak cutting forces in milling of spherical surfaces using ball end mills. The controller can adaptively vary the feedrate to maintain allowable cutting force on the tool. This control algorithm is implemented in a computer numerical control (CNC) machine. It has been demonstrated that the controller can provide stable machining and improve the performance of the CNC milling process by varying feedrate.

Keywords: Ball-end mill, feedrate, fuzzy logic controller, machining optimization, spherical surface.

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Authors: Rohana Mahmud, Hairul Aysa Abdul Halim Sithiq, Haryuna Mohd Taharim

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In this paper, the authors present architecture of a multi agent consultation system for obesity related problems, which hybrid the technology of an expert system (ES) and an intelligent agent (IA). The strength of the ES which is capable of pulling the expert knowledge is consulted and presented to the end user via the autonomous and friendly pushing environment of the intelligent agent.

Keywords: Expert System, Hybrid Technology, Intelligent Agent, Medical Informatics, Multi Agent Consultation System.

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Authors: Navid Javidtash, Abdolmohamad Davodi, Mojtaba Hakimzadeh, Abdolreza Roozbeh

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Economic dispatch (ED) is considered to be one of the key functions in electric power system operation. This paper presents a new hybrid approach based genetic algorithm (GA) to economic dispatch problems. GA is most commonly used optimizing algorithm predicated on principal of natural evolution. Utilization of chaotic queue with GA generates several neighborhoods of near optimal solutions to keep solution variation. It could avoid the search process from becoming pre-mature. For the objective of chaotic queue generation, utilization of tent equation as opposed to logistic equation results in improvement of iterative speed. The results of the proposed approach were compared in terms of fuel cost, with existing differential evolution and other methods in literature.

Keywords: Economic Dispatch(ED), Optimization, Fuel Cost, Genetic Algorithm (GA).

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Authors: Chih-Cheng Kao, Hsin- Hua Chu

Abstract:

This paper mainly proposes an efficient modified particle swarm optimization (MPSO) method, to identify a slidercrank mechanism driven by a field-oriented PM synchronous motor. In system identification, we adopt the MPSO method to find parameters of the slider-crank mechanism. This new algorithm is added with “distance" term in the traditional PSO-s fitness function to avoid converging to a local optimum. It is found that the comparisons of numerical simulations and experimental results prove that the MPSO identification method for the slider-crank mechanism is feasible.

Keywords: Slider-crank mechanism, distance, systemidentification, modified particle swarm optimization.

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Authors: U. Prasopchingchana

Abstract:

The temperature distribution and the heat transfer rates through a multi-layer door of a furnace were investigated. The inside of the door was in contact with hot air and the other side of the door was in contact with room air. Radiation heat transfer from the walls of the furnace to the door and the door to the surrounding area was included in the problem. This work is a two dimensional steady state problem. The Churchill and Chu correlation was used to find local convection heat transfer coefficients at the surfaces of the furnace door. The thermophysical properties of air were the functions of the temperatures. Polynomial curve fitting for the fluid properties were carried out. Finite difference method was used to discretize for conduction heat transfer within the furnace door. The Gauss-Seidel Iteration was employed to compute the temperature distribution in the door. The temperature distribution in the horizontal mid plane of the furnace door in a two dimensional problem agrees with the one dimensional problem. The local convection heat transfer coefficients at the inside and outside surfaces of the furnace door are exhibited.

Keywords: Conduction, heat transfer, multi-layer door, natural convection

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Authors: R. Usubamatov, M. Z. Abdulmuin

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Automated production lines with so called 'hard structures' are widely used in manufacturing. Designers segmented these lines into sections by placing a buffer between the series of machine tools to increase productivity. In real production condition the capacity of a buffer system is limited and real production line can compensate only some part of the productivity losses of an automated line. The productivity of such production lines cannot be readily determined. This paper presents mathematical approach to solving the structure of section-based automated production lines by criterion of maximum productivity.

Keywords: optimization production line, productivity, sections

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Authors: P.S. Prakash, S. Selvan

Abstract:

IP networks are evolving from data communication infrastructure into many real-time applications such as video conferencing, IP telephony and require stringent Quality of Service (QoS) requirements. A rudimentary issue in QoS routing is to find a path between a source-destination pair that satisfies two or more endto- end constraints and termed to be NP hard or complete. In this context, we present an algorithm Multi Constraint Path Problem Version 3 (MCPv3), where all constraints are approximated and return a feasible path in much quicker time. We present another algorithm namely Delay Coerced Multi Constrained Routing (DCMCR) where coerce one constraint and approximate the remaining constraints. Our algorithm returns a feasible path, if exists, in polynomial time between a source-destination pair whose first weight satisfied by the first constraint and every other weight is bounded by remaining constraints by a predefined approximation factor (a). We present our experimental results with different topologies and network conditions.

Keywords: Routing, Quality-of-Service (QoS), additive constraints, shortest path, delay coercion.

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Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

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As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling. The research proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling. The paper concludes the challenges and improvement directions for Deep Reinforcement Learning-based resource scheduling algorithms.

Keywords: Resource scheduling, deep reinforcement learning, distributed system, artificial intelligence.

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Authors: Ardeshir Karami Mohammadi

Abstract:

A Variable Structure Model Reference Adaptive Controller using state variables is proposed for a class of multi input-multi output systems. Adaptation law is of variable structure type and switching functions is designed based on stability requirements. Global exponential stability is proved based on Lyapunov criterion. Transient behavior is analyzed using sliding mode control and shows perfect model following at a finite time.

Keywords: Adaptive control, Model reference, Variablestructure, MIMO system.

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