Search results for: hybrid bearings
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 835

Search results for: hybrid bearings

475 GEP Considering Purchase Prices, Profits of IPPs and Reliability Criteria Using Hybrid GA and PSO

Authors: H. Shayeghi, H. Hosseini, A. Shabani, M. Mahdavi

Abstract:

In this paper, optimal generation expansion planning (GEP) is investigated considering purchase prices, profits of independent power producers (IPPs) and reliability criteria using a new method based on hybrid coded Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). In this approach, optimal purchase price of each IPP is obtained by HCGA and reliability criteria are calculated by PSO technique. It should be noted that reliability criteria and the rate of carbon dioxide (CO2) emission have been considered as constraints of the GEP problem. Finally, the proposed method has been tested on the case study system. The results evaluation show that the proposed method can simply obtain optimal purchase prices of IPPs and is a fast method for calculation of reliability criteria in expansion planning. Also, considering the optimal purchase prices and profits of IPPs in generation expansion planning are caused that the expansion costs are decreased and the problem is solved more exactly.

Keywords: GEP Problem, IPPs, Reliability Criteria, GA, PSO.

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474 Hybrid Artificial Immune System for Job Shop Scheduling Problem

Authors: Bin Cai, Shilong Wang, Haibo Hu

Abstract:

The job shop scheduling problem (JSSP) is a notoriously difficult problem in combinatorial optimization. This paper presents a hybrid artificial immune system for the JSSP with the objective of minimizing makespan. The proposed approach combines the artificial immune system, which has a powerful global exploration capability, with the local search method, which can exploit the optimal antibody. The antibody coding scheme is based on the operation based representation. The decoding procedure limits the search space to the set of full active schedules. In each generation, a local search heuristic based on the neighborhood structure proposed by Nowicki and Smutnicki is applied to improve the solutions. The approach is tested on 43 benchmark problems taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.

Keywords: Artificial immune system, Job shop scheduling problem, Local search, Metaheuristic algorithm

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473 Hybrid Approach for Memory Analysis in Windows System

Authors: Khairul Akram Zainol Ariffin, Ahmad Kamil Mahmood, Jafreezal Jaafar, Solahuddin Shamsuddin

Abstract:

Random Access Memory (RAM) is an important device in computer system. It can represent the snapshot on how the computer has been used by the user. With the growth of its importance, the computer memory has been an issue that has been discussed in digital forensics. A number of tools have been developed to retrieve the information from the memory. However, most of the tools have their limitation in the ability of retrieving the important information from the computer memory. Hence, this paper is aimed to discuss the limitation and the setback for two main techniques such as process signature search and process enumeration. Then, a new hybrid approach will be presented to minimize the setback in both individual techniques. This new approach combines both techniques with the purpose to retrieve the information from the process block and other objects in the computer memory. Nevertheless, the basic theory in address translation for x86 platforms will be demonstrated in this paper.

Keywords: Algorithms, Digital Forensics, Memory Analysis, Signature Search.

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472 Providing Energy Management of a Fuel Cell-Battery Hybrid Electric Vehicle

Authors: Fatma Keskin Arabul, Ibrahim Senol, Ahmet Yigit Arabul, Ali Rifat Boynuegri

Abstract:

On account of the concern of the fossil fuel is depleting and its negative effects on the environment, interest in alternative energy sources is increasing day by day. However, considering the importance of transportation in human life, instead of oil and its derivatives fueled vehicles with internal combustion engines, electric vehicles which are sensitive to the environment and working with electrical energy has begun to develop. In this study, simulation was carried out for providing energy management and recovering regenerative braking in fuel cell-battery hybrid electric vehicle. The main power supply of the vehicle is fuel cell on the other hand not only instantaneous power is supplied by the battery but also the energy generated due to regenerative breaking is stored in the battery. Obtained results of the simulation is analyzed and discussed.

Keywords: Electric vehicles, fuel cell, battery, regenerative braking, energy management.

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471 An Advanced Hybrid P2p Botnet 2.0

Authors: T. T. Lu, H.Y. Liao, M .F. Chen

Abstract:

Recently, malware attacks have become more serious over the Internet by e-mail, denial of service (DoS) or distributed denial of service (DDoS). The Botnets have become a significant part of the Internet malware attacks. The traditional botnets include three parts – botmaster, command and control (C&C) servers and bots. The C&C servers receive commands from botmaster and control the distributions of computers remotely. Bots use DNS to find the positions of C&C server. In this paper, we propose an advanced hybrid peer-to-peer (P2P) botnet 2.0 (AHP2P botnet 2.0) using web 2.0 technology to hide the instructions from botmaster into social sites, which are regarded as C&C servers. Servent bots are regarded as sub-C&C servers to get the instructions from social sites. The AHP2P botnet 2.0 can evaluate the performance of servent bots, reduce DNS traffics from bots to C&C servers, and achieve harder detection bots actions than IRC-based botnets over the Internet.

Keywords: Peer-to-peer, Botnets, Botnet 2.0, Hybridpeer-to-peer

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470 2 – Block 3 - Point Modified Numerov Block Methods for Solving Ordinary Differential Equations

Authors: Abdu Masanawa Sagir

Abstract:

In this paper, linear multistep technique using power series as the basis function is used to develop the block methods which are suitable for generating direct solution of the special second order ordinary differential equations of the form y′′ = f(x,y), a < = x < = b with associated initial or boundary conditions. The continuaous hybrid formulations enable us to differentiate and evaluate at some grids and off – grid points to obtain two different three discrete schemes, each of order (4,4,4)T, which were used in block form for parallel or sequential solutions of the problems. The computational burden and computer time wastage involved in the usual reduction of second order problem into system of first order equations are avoided by this approach. Furthermore, a stability analysis and efficiency of the block method are tested on linear and non-linear ordinary differential equations whose solutions are oscillatory or nearly periodic in nature, and the results obtained compared favourably with the exact solution.

Keywords: Block Method, Hybrid, Linear Multistep Method, Self – starting, Special Second Order.

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469 Mamdani Model based Adaptive Neural Fuzzy Inference System and its Application

Authors: Yuanyuan Chai, Limin Jia, Zundong Zhang

Abstract:

Hybrid algorithm is the hot issue in Computational Intelligence (CI) study. From in-depth discussion on Simulation Mechanism Based (SMB) classification method and composite patterns, this paper presents the Mamdani model based Adaptive Neural Fuzzy Inference System (M-ANFIS) and weight updating formula in consideration with qualitative representation of inference consequent parts in fuzzy neural networks. M-ANFIS model adopts Mamdani fuzzy inference system which has advantages in consequent part. Experiment results of applying M-ANFIS to evaluate traffic Level of service show that M-ANFIS, as a new hybrid algorithm in computational intelligence, has great advantages in non-linear modeling, membership functions in consequent parts, scale of training data and amount of adjusted parameters.

Keywords: Fuzzy neural networks, Mamdani fuzzy inference, M-ANFIS

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468 Comics as Third Space: An Analysis of the Continuous Negotiation of Identities in Postcolonial Philippines

Authors: Anna Camille V. Flores

Abstract:

Comics in the Philippines has taken on many uses for the Filipino people. They have been sources of entertainment, education, and political and social commentaries. History has been witnessed to the rise and fall of Philippine comics but the 21st century is seeing a revival of the medium and the industry. It is within this context that an inquiry about Filipino identity is situated. Employing the analytical framework of postcolonialism, particularly Homi K. Bhabha’s concepts of Hybridity and the Third Space, this study analyzes three contemporary Philippine comics, Trese, Filipino Heroes League, and Dead Balagtas. The study was able to draw three themes that represent how Filipinos inhabit hybrid worlds and hybridized identities. First, the third space emerged through the use of hybrid worlds in the comics. Second, (re)imagined communities are established through the use of intertextual signifiers. Third, (re)negotiated identities are expressed through visual and narrative devices such as the use of Philippine mythology, historical and contemporary contexts, and language. In conclusion, comics can be considered as Third Space where these identities have the agency and opportunity to be expressed and represented.

Keywords: Comics, hybridity and third space, Philippine comics, postcolonialism.

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467 A Hybrid Fuzzy AGC in a Competitive Electricity Environment

Authors: H. Shayeghi, A. Jalili

Abstract:

This paper presents a new Hybrid Fuzzy (HF) PID type controller based on Genetic Algorithms (GA-s) for solution of the Automatic generation Control (AGC) problem in a deregulated electricity environment. In order for a fuzzy rule based control system to perform well, the fuzzy sets must be carefully designed. A major problem plaguing the effective use of this method is the difficulty of accurately constructing the membership functions, because it is a computationally expensive combinatorial optimization problem. On the other hand, GAs is a technique that emulates biological evolutionary theories to solve complex optimization problems by using directed random searches to derive a set of optimal solutions. For this reason, the membership functions are tuned automatically using a modified GA-s based on the hill climbing method. The motivation for using the modified GA-s is to reduce fuzzy system effort and take large parametric uncertainties into account. The global optimum value is guaranteed using the proposed method and the speed of the algorithm-s convergence is extremely improved, too. This newly developed control strategy combines the advantage of GA-s and fuzzy system control techniques and leads to a flexible controller with simple stricture that is easy to implement. The proposed GA based HF (GAHF) controller is tested on a threearea deregulated power system under different operating conditions and contract variations. The results of the proposed GAHF controller are compared with those of Multi Stage Fuzzy (MSF) controller, robust mixed H2/H∞ and classical PID controllers through some performance indices to illustrate its robust performance for a wide range of system parameters and load changes.

Keywords: AGC, Hybrid Fuzzy Controller, Deregulated Power System, Power System Control, GAs.

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466 Experimental Analysis and Numerical Simulation of Smart Sandwich Beams Behavior in Honeycomb Magnetorheological Elastomer

Authors: A. Khebli, S. Aguib, Y. Kateb, L. Guenfoud, N. Chikh, M. Tourab, T. Djedid, W. Dilmi, A. Hadidi, H. Meglouli

Abstract:

Composite structures based on magnetorheological elastomers (MREs) are widely used in many industrial sectors, such as automotive, naval, railway, aeronautical, aerospace, and building industries because of their adjustable mechanical properties by an external stimulus. In this work, experimental tests and numerical simulations carried out have shown that the use of these new structures, developed from honeycomb core, and MRE with aluminum skins, make it possible to improve particularly the overall rigidity and to reduce the vibration amplitudes. The results found showed that these hybrid structures have a very good mechanical resistance due mainly to the honeycomb core, and a very good shock absorber due mainly to the core of the MRE. The elaborated composite structure is intended to be used in industrial sectors subject to great efforts and a high amplitude of vibration such as helicopter wings and air turbines.

Keywords: Hybrid sandwich structures, magnetorheological elastomer, honeycomb, 3-point bending, mechanical strength.

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465 New EEM/BEM Hybrid Method for Electric Field Calculation in Cable Joints

Authors: Nebojsa B. Raicevic, Slavoljub R. Aleksic, Sasa S. Ilic

Abstract:

A power cable is widely used for power supply in power distributing networks and power transmission lines. Due to limitations in the production, delivery and setting up power cables, they are produced and delivered in several separate lengths. Cable itself, consists of two cable terminations and arbitrary number of cable joints, depending on the cable route length. Electrical stress control is needed to prevent a dielectric breakdown at the end of the insulation shield in both the air and cable insulation. Reliability of cable joint depends on its materials, design, installation and operating environment. The paper describes design and performance results for new modeled cable joints. Design concepts, based on numerical calculations, must be correct. An Equivalent Electrodes Method/Boundary Elements Method-hybrid approach that allows electromagnetic field calculations in multilayer dielectric media, including inhomogeneous regions, is presented.

Keywords: Cable joints, deflector's cones, equivalent electrodemethod, electric field distribution

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464 Performance Evaluation of Karanja Oil Based Biodiesel Engine Using Modified Genetic Algorithm

Authors: G. Bhushan, S. Dhingra, K. K. Dubey

Abstract:

This paper presents the evaluation of performance (BSFC and BTE), combustion (Pmax) and emission (CO, NOx, HC and smoke opacity) parameters of karanja biodiesel in a single cylinder, four stroke, direct injection diesel engine by considering significant engine input parameters (blending ratio, compression ratio and load torque). Multi-objective optimization of performance, combustion and emission parameters is also carried out in a karanja biodiesel engine using hybrid RSM-NSGA-II technique. The pareto optimum solutions are predicted by running the hybrid RSM-NSGA-II technique. Each pareto optimal solution is having its own importance. Confirmation tests are also conducted at randomly selected few pareto solutions to check the authenticity of the results.

Keywords: Karanja biodiesel, single cylinder direct injection diesel engine, response surface methodology, central composite rotatable design, genetic algorithm.

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463 A Hybrid Approach for Quantification of Novelty in Rule Discovery

Authors: Vasudha Bhatnagar, Ahmed Sultan Al-Hegami, Naveen Kumar

Abstract:

Rule Discovery is an important technique for mining knowledge from large databases. Use of objective measures for discovering interesting rules lead to another data mining problem, although of reduced complexity. Data mining researchers have studied subjective measures of interestingness to reduce the volume of discovered rules to ultimately improve the overall efficiency of KDD process. In this paper we study novelty of the discovered rules as a subjective measure of interestingness. We propose a hybrid approach that uses objective and subjective measures to quantify novelty of the discovered rules in terms of their deviations from the known rules. We analyze the types of deviation that can arise between two rules and categorize the discovered rules according to the user specified threshold. We implement the proposed framework and experiment with some public datasets. The experimental results are quite promising.

Keywords: Knowledge Discovery in Databases (KDD), Data Mining, Rule Discovery, Interestingness, Subjective Measures, Novelty Measure.

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462 Coverage and Connectivity Problem in Sensor Networks

Authors: Meenakshi Bansal, Iqbal Singh, Parvinder S. Sandhu

Abstract:

In over deployed sensor networks, one approach to Conserve energy is to keep only a small subset of sensors active at Any instant. For the coverage problems, the monitoring area in a set of points that require sensing, called demand points, and consider that the node coverage area is a circle of range R, where R is the sensing range, If the Distance between a demand point and a sensor node is less than R, the node is able to cover this point. We consider a wireless sensor network consisting of a set of sensors deployed randomly. A point in the monitored area is covered if it is within the sensing range of a sensor. In some applications, when the network is sufficiently dense, area coverage can be approximated by guaranteeing point coverage. In this case, all the points of wireless devices could be used to represent the whole area, and the working sensors are supposed to cover all the sensors. We also introduce Hybrid Algorithm and challenges related to coverage in sensor networks.

Keywords: Wireless sensor networks, network coverage, Energy conservation, Hybrid Algorithms.

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461 Modified Hybrid Genetic Algorithm-Based Artificial Neural Network Application on Wall Shear Stress Prediction

Authors: Zohreh Sheikh Khozani, Wan Hanna Melini Wan Mohtar, Mojtaba Porhemmat

Abstract:

Prediction of wall shear stress in a rectangular channel, with non-homogeneous roughness distribution, was studied. Estimation of shear stress is an important subject in hydraulic engineering, since it affects the flow structure directly. In this study, the Genetic Algorithm Artificial (GAA) neural network is introduced as a hybrid methodology of the Artificial Neural Network (ANN) and modified Genetic Algorithm (GA) combination. This GAA method was employed to predict the wall shear stress. Various input combinations and transfer functions were considered to find the most appropriate GAA model. The results show that the proposed GAA method could predict the wall shear stress of open channels with high accuracy, by Root Mean Square Error (RMSE) of 0.064 in the test dataset. Thus, using GAA provides an accurate and practical simple-to-use equation.

Keywords: Artificial neural network, genetic algorithm, genetic programming, rectangular channel, shear stress.

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460 A Hybrid Overset Algorithm for Aerodynamic Problems with Moving Objects

Authors: S. M. H. Karimian, F. S. Salehi, H. Alisadeghi

Abstract:

A two-dimensional moving mesh algorithm is developed to simulate the general motion of two rotating bodies with relative translational motion. The grid includes a background grid and two sets of grids around the moving bodies. With this grid arrangement rotational and translational motions of two bodies are handled separately, with no complications. Inter-grid boundaries are determined based on their distances from two bodies. In this method, the overset concept is applied to hybrid grid, and flow variables are interpolated using a simple stencil. To evaluate this moving mesh algorithm unsteady Euler flow is solved for different cases using dual-time method of Jameson. Numerical results show excellent agreement with experimental data and other numerical results. To demonstrate the capability of present algorithm for accurate solution of flow fields around moving bodies, some benchmark problems have been defined in this paper.

Keywords: Moving mesh, Overset grid, Unsteady Euler, Relative motion.

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459 Signature Recognition and Verification using Hybrid Features and Clustered Artificial Neural Network(ANN)s

Authors: Manasjyoti Bhuyan, Kandarpa Kumar Sarma, Hirendra Das

Abstract:

Signature represents an individual characteristic of a person which can be used for his / her validation. For such application proper modeling is essential. Here we propose an offline signature recognition and verification scheme which is based on extraction of several features including one hybrid set from the input signature and compare them with the already trained forms. Feature points are classified using statistical parameters like mean and variance. The scanned signature is normalized in slant using a very simple algorithm with an intention to make the system robust which is found to be very helpful. The slant correction is further aided by the use of an Artificial Neural Network (ANN). The suggested scheme discriminates between originals and forged signatures from simple and random forgeries. The primary objective is to reduce the two crucial parameters-False Acceptance Rate (FAR) and False Rejection Rate (FRR) with lesser training time with an intension to make the system dynamic using a cluster of ANNs forming a multiple classifier system.

Keywords: offline, algorithm, FAR, FRR, ANN.

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458 FEA-Based Calculation of Performances of IPM Machines with Five Topologies for Hybrid- Electric Vehicle Traction

Authors: Aimeng Wang, Dejun Ma, Hui Wang

Abstract:

The paper presents a detailed calculation of characteristic of five different topology permanent magnet machines for high performance traction including hybrid -electric vehicles using finite element analysis (FEA) method. These machines include V-shape single layer interior PM, W-shape single-layer interior PM, Segment interior PM and surface PM on the rotor and with distributed winding on the stator. The performance characteristics which include the back-emf voltage and its harmonic, magnet mass, iron loss and ripple torque are compared and analyzed. One of a 7.5kW IPM prototype was tested and verified finite-element analysis results. The aim of the paper is given some guidance and reference for machine designer which are interested in IPM machine selection for high performance traction application.

Keywords: Interior permanent magnet machine, finite-element analysis (FEA), five topologies, electric vehicle.

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457 A Hybrid Gene Selection Technique Using Improved Mutual Information and Fisher Score for Cancer Classification Using Microarrays

Authors: M. Anidha, K. Premalatha

Abstract:

Feature Selection is significant in order to perform constructive classification in the area of cancer diagnosis. However, a large number of features compared to the number of samples makes the task of classification computationally very hard and prone to errors in microarray gene expression datasets. In this paper, we present an innovative method for selecting highly informative gene subsets of gene expression data that effectively classifies the cancer data into tumorous and non-tumorous. The hybrid gene selection technique comprises of combined Mutual Information and Fisher score to select informative genes. The gene selection is validated by classification using Support Vector Machine (SVM) which is a supervised learning algorithm capable of solving complex classification problems. The results obtained from improved Mutual Information and F-Score with SVM as a classifier has produced efficient results.

Keywords: Gene selection, mutual information, Fisher score, classification, SVM.

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456 Iron(III)-Tosylate Doped PEDOT and PEG: A Nanoscale Conductivity Study of an Electrochemical System with Biosensing Applications

Authors: Giulio Rosati, Luciano Sappia, Rossana Madrid, Noemi Rozlòsnik

Abstract:

The addition of PEG of different molecular weights has important effects on the physical, electrical and electrochemical properties of iron(III)-tosylate doped PEDOT. This particular polymer can be easily spin coated over plastic discs, optimizing thickness and uniformity of the PEDOT-PEG films. The conductivity and morphological analysis of the hybrid PEDOT-PEG polymer by 4-point probe (4PP), 12-point probe (12PP), and conductive AFM (C-AFM) show strong effects of the PEG doping. Moreover, the conductive films kinetics at the nanoscale, in response to different bias voltages, change radically depending on the PEG molecular weight. The hybrid conductive films show also interesting electrochemical properties, making the PEDOT PEG doping appealing for biosensing applications both for EIS-based and amperometric affinity/catalytic biosensors.

Keywords: Atomic force microscopy, biosensors, four-point probe, nano-films, PEDOT.

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455 Modelling of Soil Structure Interaction of Integral Abutment Bridges

Authors: Thevaneyan K. David, John P. Forth

Abstract:

Integral Abutment Bridges (IAB) are defined as simple or multiple span bridges in which the bridge deck is cast monolithically with the abutment walls. This kind of bridges are becoming very popular due to different aspects such as good response under seismic loading, low initial costs, elimination of bearings, and less maintenance. However the main issue related to the analysis of this type of structures is dealing with soil-structure interaction of the abutment walls and the supporting piles. Various soil constitutive models have been used in studies of soil-structure interaction in this kind of structures by researchers. This paper is an effort to review the implementation of various finite elements model which explicitly incorporates the nonlinear soil and linear structural response considering various soil constitutive models and finite element mesh.

Keywords: Constitutive Models, FEM, Integral AbutmentBridges, Soil-structure Interactions

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454 Identification of Promising Infant Clusters to Obtain Improved Block Layout Designs

Authors: Mustahsan Mir, Ahmed Hassanin, Mohammed A. Al-Saleh

Abstract:

The layout optimization of building blocks of unequal areas has applications in many disciplines including VLSI floorplanning, macrocell placement, unequal-area facilities layout optimization, and plant or machine layout design. A number of heuristics and some analytical and hybrid techniques have been published to solve this problem. This paper presents an efficient high-quality building-block layout design technique especially suited for solving large-size problems. The higher efficiency and improved quality of optimized solutions are made possible by introducing the concept of Promising Infant Clusters in a constructive placement procedure. The results presented in the paper demonstrate the improved performance of the presented technique for benchmark problems in comparison with published heuristic, analytic, and hybrid techniques.

Keywords: Block layout problem, building-block layout design, CAD, optimization, search techniques.

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453 Hybridized Technique to Analyze Workstress Related Data via the StressCafé

Authors: Anusua Ghosh, Andrew Nafalski, Jeffery Tweedale, Maureen Dollard

Abstract:

This paper presents anapproach of hybridizing two or more artificial intelligence (AI) techniques which arebeing used to fuzzify the workstress level ranking and categorize the rating accordingly. The use of two or more techniques (hybrid approach) has been considered in this case, as combining different techniques may lead to neutralizing each other-s weaknesses generating a superior hybrid solution. Recent researches have shown that there is a need for a more valid and reliable tools, for assessing work stress. Thus artificial intelligence techniques have been applied in this instance to provide a solution to a psychological application. An overview about the novel and autonomous interactive model for analysing work-stress that has been developedusing multi-agent systems is also presented in this paper. The establishment of the intelligent multi-agent decision analyser (IMADA) using hybridized technique of neural networks and fuzzy logic within the multi-agent based framework is also described.

Keywords: Fuzzy logic, intelligent agent, multi-agent systems, neural network, workplace stress.

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452 Development of a Project Selection Method on Information System Using ANP and Fuzzy Logic

Authors: Ingu Kim, Shangmun Shin, Yongsun Choi, Nguyen Manh Thang, Edwin R. Ramos, Won-Joo Hwang

Abstract:

Project selection problems on management information system (MIS) are often considered a multi-criteria decision-making (MCDM) for a solving method. These problems contain two aspects, such as interdependencies among criteria and candidate projects and qualitative and quantitative factors of projects. However, most existing methods reported in literature consider these aspects separately even though these two aspects are simultaneously incorporated. For this reason, we proposed a hybrid method using analytic network process (ANP) and fuzzy logic in order to represent both aspects. We then propose a goal programming model to conduct an optimization for the project selection problems interpreted by a hybrid concept. Finally, a numerical example is conducted as verification purposes.

Keywords: Analytic Network Process (ANP), Multi-Criteria Decision-Making (MCDM), Fuzzy Logic, Information System Project Selection, Goal Programming.

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451 A Spatial Information Network Traffic Prediction Method Based on Hybrid Model

Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

Abstract:

Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: Spatial Information Network, Traffic prediction, Wavelet decomposition, Time series model.

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450 Vibration Analysis of the Gas Turbine Considering Dependency of Stiffness and Damping on Frequency

Authors: Hamed Jamshidi, Pooya Djamshidi

Abstract:

In this paper the complete rotor system including elastic shaft with distributed mass, allowing for the effects of oil film in bearings. Also, flexibility of foundation is modeled. As a whole this article is a relatively complete research in modeling and vibration analysis of rotor considering gyroscopic effect, damping, dependency of stiffness and damping coefficients on frequency and solving the vibration equations including these parameters. On the basis of finite element method and utilizing four element types including element of shaft, disk, bearing and foundation and using MATLAB, a computer program is written. So the responses in several cases and considering different effects are obtained. Then the results are compared with each other, with exact solutions and results of other papers.

Keywords: Damping coefficients , Finite element method, Modeling , Rotor vibration

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449 Design of the Miniature Maglev Using Hybrid Magnets in Magnetic Levitation System

Authors: Jeong-Min Jo, Young-Jae Han, Chang-Young Lee

Abstract:

Attracting ferromagnetic forces between magnet and reaction rail provide the supporting force in Electromagnetic Suspension. Miniature maglev using permanent magnets and electromagnets is based on the idea to generate the nominal magnetic force by permanent magnets and superimpose the variable magnetic field required for stabilization by currents flowing through control windings in electromagnets. Permanent magnets with a high energy density have lower power losses with regard to supporting force and magnet weight. So the advantage of the maglev using electromagnets and permanent magnets is partially reduced by the power required to feed the remaining onboard supply system so that the overall onboard power is diminished as compared to that of the electromagnet. In this paper we proposed the how to design and control the miniature maglev and confirmed the feasibility of the levitation system using electromagnets and permanent magnets through the manufacturing the miniature maglev

Keywords: Magnetic Levitation system, Maglev, Permanent Magnets, Hybrid Magnet.

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448 Treatment of Chrome Tannery Wastewater by Biological Process - A Mini Review

Authors: Supriyo Goswami, Debabrata Mazumder

Abstract:

Chrome tannery wastewater causes serious environmental hazard due to its high pollution potential. As a result, rigorous treatment is necessary for abatement of pollution from this type of wastewater. There are many research studies on chrome tannery wastewater treatment in the field of physical, chemical, and biological methods. In general, biological treatment process is found ineffective for direct application because of adverse effects by toxic chromium, sulphide, chloride etc. However, biological methods were employed mainly for a few sub processes generating significant amount of organic matter and without chromium, chlorides etc. In this context the present paper reviews the characteristics feature and pollution potential of wastewater generated from chrome tannery units and treatment of the same. The different biological processes used earlier and their chronological development for treatment of the chrome tannery wastewater are thoroughly reviewed in this paper. In this regard, the scope of hybrid bioreactor - an advanced technology option has also been explored, as this kind of treatment is well suited for the wastewater having inhibitory substances. 

Keywords: Composite tannery wastewater, biological treatment, Hybrid bioreactor, Organic removal

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447 A Hybrid Method for Eyes Detection in Facial Images

Authors: Muhammad Shafi, Paul W. H. Chung

Abstract:

This paper proposes a hybrid method for eyes localization in facial images. The novelty is in combining techniques that utilise colour, edge and illumination cues to improve accuracy. The method is based on the observation that eye regions have dark colour, high density of edges and low illumination as compared to other parts of face. The first step in the method is to extract connected regions from facial images using colour, edge density and illumination cues separately. Some of the regions are then removed by applying rules that are based on the general geometry and shape of eyes. The remaining connected regions obtained through these three cues are then combined in a systematic way to enhance the identification of the candidate regions for the eyes. The geometry and shape based rules are then applied again to further remove the false eye regions. The proposed method was tested using images from the PICS facial images database. The proposed method has 93.7% and 87% accuracies for initial blobs extraction and final eye detection respectively.

Keywords: Erosion, dilation, Edge-density

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446 A Hybrid Scheme for on-Line Diagnostic Decision Making Using Optimal Data Representation and Filtering Technique

Authors: Hyun-Woo Cho

Abstract:

The early diagnostic decision making in industrial processes is absolutely necessary to produce high quality final products. It helps to provide early warning for a special event in a process, and finding its assignable cause can be obtained. This work presents a hybrid diagnostic schmes for batch processes. Nonlinear representation of raw process data is combined with classification tree techniques. The nonlinear kernel-based dimension reduction is executed for nonlinear classification decision boundaries for fault classes. In order to enhance diagnosis performance for batch processes, filtering of the data is performed to get rid of the irrelevant information of the process data. For the diagnosis performance of several representation, filtering, and future observation estimation methods, four diagnostic schemes are evaluated. In this work, the performance of the presented diagnosis schemes is demonstrated using batch process data.

Keywords: Diagnostics, batch process, nonlinear representation, data filtering, multivariate statistical approach

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