Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 792

Search results for: hybrid rule-extraction algorithms

792 Hybrid Adaptive Modeling to Enhance Robustness of Real-Time Optimization

Authors: Hussain Syed Asad, Richard Kwok Kit Yuen, Gongsheng Huang

Abstract:

Real-time optimization has been considered an effective approach for improving energy efficient operation of heating, ventilation, and air-conditioning (HVAC) systems. In model-based real-time optimization, model mismatches cannot be avoided. When model mismatches are significant, the performance of the real-time optimization will be impaired and hence the expected energy saving will be reduced. In this paper, the model mismatches for chiller plant on real-time optimization are considered. In the real-time optimization of the chiller plant, simplified semi-physical or grey box model of chiller is always used, which should be identified using available operation data. To overcome the model mismatches associated with the chiller model, hybrid Genetic Algorithms (HGAs) method is used for online real-time training of the chiller model. HGAs combines Genetic Algorithms (GAs) method (for global search) and traditional optimization method (i.e. faster and more efficient for local search) to avoid conventional hit and trial process of GAs. The identification of model parameters is synthesized as an optimization problem; and the objective function is the Least Square Error between the output from the model and the actual output from the chiller plant. A case study is used to illustrate the implementation of the proposed method. It has been shown that the proposed approach is able to provide reliability in decision making, enhance the robustness of the real-time optimization strategy and improve on energy performance.

Keywords: Energy performance, hybrid adaptive modeling, hybrid genetic algorithms, real-time optimization, heating, ventilation, and air-conditioning.

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791 Selective Harmonic Elimination of PWM AC/AC Voltage Controller Using Hybrid RGA-PS Approach

Authors: A. K. Al-Othman, Nabil A. Ahmed, A. M. Al-Kandari, H. K. Ebraheem

Abstract:

Selective harmonic elimination-pulse width modulation techniques offer a tight control of the harmonic spectrum of a given voltage waveform generated by a power electronic converter along with a low number of switching transitions. Traditional optimization methods suffer from various drawbacks, such as prolonged and tedious computational steps and convergence to local optima; thus, the more the number of harmonics to be eliminated, the larger the computational complexity and time. This paper presents a novel method for output voltage harmonic elimination and voltage control of PWM AC/AC voltage converters using the principle of hybrid Real-Coded Genetic Algorithm-Pattern Search (RGA-PS) method. RGA is the primary optimizer exploiting its global search capabilities, PS is then employed to fine tune the best solution provided by RGA in each evolution. The proposed method enables linear control of the fundamental component of the output voltage and complete elimination of its harmonic contents up to a specified order. Theoretical studies have been carried out to show the effectiveness and robustness of the proposed method of selective harmonic elimination. Theoretical results are validated through simulation studies using PSIM software package.

Keywords: PWM, AC/AC voltage converters, selectiveharmonic elimination, direct search method, pattern search method, Real-coded Genetic algorithms, evolutionary algorithms andoptimization.

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790 Extraction of Symbolic Rules from Artificial Neural Networks

Authors: S. M. Kamruzzaman, Md. Monirul Islam

Abstract:

Although backpropagation ANNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions cannot be explained as those of decision trees. In many applications, it is desirable to extract knowledge from trained ANNs for the users to gain a better understanding of how the networks solve the problems. A new rule extraction algorithm, called rule extraction from artificial neural networks (REANN) is proposed and implemented to extract symbolic rules from ANNs. A standard three-layer feedforward ANN is the basis of the algorithm. A four-phase training algorithm is proposed for backpropagation learning. Explicitness of the extracted rules is supported by comparing them to the symbolic rules generated by other methods. Extracted rules are comparable with other methods in terms of number of rules, average number of conditions for a rule, and predictive accuracy. Extensive experimental studies on several benchmarks classification problems, such as breast cancer, iris, diabetes, and season classification problems, demonstrate the effectiveness of the proposed approach with good generalization ability.

Keywords: Backpropagation, clustering algorithm, constructivealgorithm, continuous activation function, pruning algorithm, ruleextraction algorithm, symbolic rules.

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789 Design of Permanent Sensor Fault Tolerance Algorithms by Sliding Mode Observer for Smart Hybrid Powerpack

Authors: Sungsik Jo, Hyeonwoo Kim, Iksu Choi, Hunmo Kim

Abstract:

In the SHP, LVDT sensor is for detecting the length changes of the EHA output, and the thrust of the EHA is controlled by the pressure sensor. Sensor is possible to cause hardware fault by internal problem or external disturbance. The EHA of SHP is able to be uncontrollable due to control by feedback from uncertain information, on this paper; the sliding mode observer algorithm estimates the original sensor output information in permanent sensor fault. The proposed algorithm shows performance to recovery fault of disconnection and short circuit basically, also the algorithm detect various of sensor fault mode.

Keywords: Smart Hybrid Powerpack (SHP), Electro Hydraulic Actuator (EHA), Permanent Sensor fault tolerance, Sliding mode observer (SMO), Graphic User Interface (GUI).

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788 Comparative Study of Some Adaptive Fuzzy Algorithms for Manipulator Control

Authors: Sudeept Mohan, Surekha Bhanot

Abstract:

The problem of manipulator control is a highly complex problem of controlling a system which is multi-input, multioutput, non-linear and time variant. In this paper some adaptive fuzzy, and a new hybrid fuzzy control algorithm have been comparatively evaluated through simulations, for manipulator control. The adaptive fuzzy controllers consist of self-organizing, self-tuning, and coarse/fine adaptive fuzzy schemes. These controllers are tested for different trajectories and for varying manipulator parameters through simulations. Various performance indices like the RMS error, steady state error and maximum error are used for comparison. It is observed that the self-organizing fuzzy controller gives the best performance. The proposed hybrid fuzzy plus integral error controller also performs remarkably well, given its simple structure.

Keywords: Hybrid fuzzy, Self-organizing, Self-tuning, Trajectory tracking.

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787 Optimum Design of Steel Space Frames by Hybrid Teaching-Learning Based Optimization and Harmony Search Algorithms

Authors: Alper Akın, İbrahim Aydoğdu

Abstract:

This study presents a hybrid metaheuristic algorithm to obtain optimum designs for steel space buildings. The optimum design problem of three-dimensional steel frames is mathematically formulated according to provisions of LRFD-AISC (Load and Resistance factor design of American Institute of Steel Construction). Design constraints such as the strength requirements of structural members, the displacement limitations, the inter-story drift and the other structural constraints are derived from LRFD-AISC specification. In this study, a hybrid algorithm by using teachinglearning based optimization (TLBO) and harmony search (HS) algorithms is employed to solve the stated optimum design problem. These algorithms are two of the recent additions to metaheuristic techniques of numerical optimization and have been an efficient tool for solving discrete programming problems. Using these two algorithms in collaboration creates a more powerful tool and mitigates each other’s weaknesses. To demonstrate the powerful performance of presented hybrid algorithm, the optimum design of a large scale steel building is presented and the results are compared to the previously obtained results available in the literature.

Keywords: Optimum structural design, hybrid techniques, teaching-learning based optimization, harmony search algorithm, minimum weight, steel space frame.

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786 Eclectic Rule-Extraction from Support Vector Machines

Authors: Nahla Barakat, Joachim Diederich

Abstract:

Support vector machines (SVMs) have shown superior performance compared to other machine learning techniques, especially in classification problems. Yet one limitation of SVMs is the lack of an explanation capability which is crucial in some applications, e.g. in the medical and security domains. In this paper, a novel approach for eclectic rule-extraction from support vector machines is presented. This approach utilizes the knowledge acquired by the SVM and represented in its support vectors as well as the parameters associated with them. The approach includes three stages; training, propositional rule-extraction and rule quality evaluation. Results from four different experiments have demonstrated the value of the approach for extracting comprehensible rules of high accuracy and fidelity.

Keywords: Data mining, hybrid rule-extraction algorithms, medical diagnosis, SVMs

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785 Novel Hybrid Approaches For Real Coded Genetic Algorithm to Compute the Optimal Control of a Single Stage Hybrid Manufacturing Systems

Authors: M. Senthil Arumugam, M.V.C. Rao

Abstract:

This paper presents a novel two-phase hybrid optimization algorithm with hybrid genetic operators to solve the optimal control problem of a single stage hybrid manufacturing system. The proposed hybrid real coded genetic algorithm (HRCGA) is developed in such a way that a simple real coded GA acts as a base level search, which makes a quick decision to direct the search towards the optimal region, and a local search method is next employed to do fine tuning. The hybrid genetic operators involved in the proposed algorithm improve both the quality of the solution and convergence speed. The phase–1 uses conventional real coded genetic algorithm (RCGA), while optimisation by direct search and systematic reduction of the size of search region is employed in the phase – 2. A typical numerical example of an optimal control problem with the number of jobs varying from 10 to 50 is included to illustrate the efficacy of the proposed algorithm. Several statistical analyses are done to compare the validity of the proposed algorithm with the conventional RCGA and PSO techniques. Hypothesis t – test and analysis of variance (ANOVA) test are also carried out to validate the effectiveness of the proposed algorithm. The results clearly demonstrate that the proposed algorithm not only improves the quality but also is more efficient in converging to the optimal value faster. They can outperform the conventional real coded GA (RCGA) and the efficient particle swarm optimisation (PSO) algorithm in quality of the optimal solution and also in terms of convergence to the actual optimum value.

Keywords: Hybrid systems, optimal control, real coded genetic algorithm (RCGA), Particle swarm optimization (PSO), Hybrid real coded GA (HRCGA), and Hybrid genetic operators.

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784 Performance Analysis of a Hybrid DF-AF Hybrid RF/FSO System under Gamma Gamma Atmospheric Turbulence Channel Using MPPM Modulation

Authors: Hechmi Saidi, Noureddine Hamdi

Abstract:

The performance of hybrid amplify and forward - decode and forward (AF-DF) hybrid radio frequency/free space optical (RF/FSO) communication system, that adopts M-ary pulse position modulation (MPPM) techniques, is analyzed. Both exact and approximate symbol-error rates (SERs) are derived. The random variations of the received optical irradiance, produced by the atmospheric turbulence, is modeled by the gamma-gamma (GG) statistical distribution. A closed-form expression for the probability density function (PDF) is derived for the whole above system is obtained. Thanks to the use of hybrid AF-DF hybrid RF/FSO configuration and MPPM, the effects of atmospheric turbulence is mitigated; hence the capacity of combating atmospheric turbulence and the transmissitted signal quality are improved.

Keywords: FSO, RF, hybrid, AF, DF, SER, SNR, GG channel.

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783 A Hybrid Nature Inspired Algorithm for Generating Optimal Query Plan

Authors: R. Gomathi, D. Sharmila

Abstract:

The emergence of the Semantic Web technology increases day by day due to the rapid growth of multiple web pages. Many standard formats are available to store the semantic web data. The most popular format is the Resource Description Framework (RDF). Querying large RDF graphs becomes a tedious procedure with a vast increase in the amount of data. The problem of query optimization becomes an issue in querying large RDF graphs. Choosing the best query plan reduces the amount of query execution time. To address this problem, nature inspired algorithms can be used as an alternative to the traditional query optimization techniques. In this research, the optimal query plan is generated by the proposed SAPSO algorithm which is a hybrid of Simulated Annealing (SA) and Particle Swarm Optimization (PSO) algorithms. The proposed SAPSO algorithm has the ability to find the local optimistic result and it avoids the problem of local minimum. Experiments were performed on different datasets by changing the number of predicates and the amount of data. The proposed algorithm gives improved results compared to existing algorithms in terms of query execution time.

Keywords: Semantic web, RDF, Query optimization, Nature inspired algorithms, PSO, SA.

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782 Improving the Security of Internet of Things Using Encryption Algorithms

Authors: Amirhossein Safi

Abstract:

Internet of things (IOT) is a kind of advanced information technology which has drawn societies’ attention. Sensors and stimulators are usually recognized as smart devices of our environment. Simultaneously, IOT security brings up new issues. Internet connection and possibility of interaction with smart devices cause those devices to involve more in human life. Therefore, safety is a fundamental requirement in designing IOT. IOT has three remarkable features: overall perception, reliable transmission, and intelligent processing. Because of IOT span, security of conveying data is an essential factor for system security. Hybrid encryption technique is a new model that can be used in IOT. This type of encryption generates strong security and low computation. In this paper, we have proposed a hybrid encryption algorithm which has been conducted in order to reduce safety risks and enhancing encryption's speed and less computational complexity. The purpose of this hybrid algorithm is information integrity, confidentiality, non-repudiation in data exchange for IOT. Eventually, the suggested encryption algorithm has been simulated by MATLAB software, and its speed and safety efficiency were evaluated in comparison with conventional encryption algorithm.

Keywords: Internet of things, security, hybrid algorithm, privacy.

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781 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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780 A Hybrid Machine Learning System for Stock Market Forecasting

Authors: Rohit Choudhry, Kumkum Garg

Abstract:

In this paper, we propose a hybrid machine learning system based on Genetic Algorithm (GA) and Support Vector Machines (SVM) for stock market prediction. A variety of indicators from the technical analysis field of study are used as input features. We also make use of the correlation between stock prices of different companies to forecast the price of a stock, making use of technical indicators of highly correlated stocks, not only the stock to be predicted. The genetic algorithm is used to select the set of most informative input features from among all the technical indicators. The results show that the hybrid GA-SVM system outperforms the stand alone SVM system.

Keywords: Genetic Algorithms, Support Vector Machines, Stock Market Forecasting.

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779 A Hybrid Approach for Color Image Quantization Using K-means and Firefly Algorithms

Authors: Parisut Jitpakdee, Pakinee Aimmanee, Bunyarit Uyyanonvara

Abstract:

Color Image quantization (CQ) is an important problem in computer graphics, image and processing. The aim of quantization is to reduce colors in an image with minimum distortion. Clustering is a widely used technique for color quantization; all colors in an image are grouped to small clusters. In this paper, we proposed a new hybrid approach for color quantization using firefly algorithm (FA) and K-means algorithm. Firefly algorithm is a swarmbased algorithm that can be used for solving optimization problems. The proposed method can overcome the drawbacks of both algorithms such as the local optima converge problem in K-means and the early converge of firefly algorithm. Experiments on three commonly used images and the comparison results shows that the proposed algorithm surpasses both the base-line technique k-means clustering and original firefly algorithm.

Keywords: Clustering, Color quantization, Firefly algorithm, Kmeans.

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778 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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777 On a Way for Constructing Numerical Methods on the Joint of Multistep and Hybrid Methods

Authors: G.Mehdiyeva, M.Imanova, V.Ibrahimov

Abstract:

Taking into account that many problems of natural sciences and engineering are reduced to solving initial-value problem for ordinary differential equations, beginning from Newton, the scientists investigate approximate solution of ordinary differential equations. There are papers of different authors devoted to the solution of initial value problem for ODE. The Euler-s known method that was developed under the guidance of the famous scientists Adams, Runge and Kutta is the most popular one among these methods. Recently the scientists began to construct the methods preserving some properties of Adams and Runge-Kutta methods and called them hybrid methods. The constructions of such methods are investigated from the middle of the XX century. Here we investigate one generalization of multistep and hybrid methods and on their base we construct specific methods of accuracy order p = 5 and p = 6 for k = 1 ( k is the order of the difference method).

Keywords: Multistep and hybrid methods, initial value problem, degree and stability of hybrid methods

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776 Design and Fabrication of Hybrid Composite Flywheel Rotor

Authors: Jung D. Kwon, Seong J. Kim, Sana U. Nasir, Sung K. Ha

Abstract:

An advanced composite flywheel rotor consisting of intra and inter hybrid rims was designed to optimally increase the energy capacity, and was manufactured using filament winding with in-situ curing. The flywheel has recently attracted considerable attention from many investigators since it possesses great potential in many energy storage applications, including electric utilities, hybrid or electric automobiles, and space vehicles. In this investigation, a comprehensive study was conducted with the intent to implement composites in high performance flywheel applications.The inner two intra-hybrid rims (rims 1 and 2) were manufactured as a whole part through continuous filament winding under in-situ curing conditions, and so were the outer two rims (rims 3 and 4). The outer surface of rim 2 and the inner surface of rim 3 were CNC-tapered for press-fitting. Machined rims were finally press-fitted using a hydraulic press with a maximum compressive force of approximately 1000 ton.

Keywords: composite flywheel rotor, inter hybrid, intra hybrid, multi-rim, interference, in-situ cure, press-fit

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775 Hybrid Markov Game Controller Design Algorithms for Nonlinear Systems

Authors: R. Sharma, M. Gopal

Abstract:

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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774 Cost Analysis of Hybrid Wind Energy Generating System Considering CO2 Emissions

Authors: M. A. Badr, M.N. El Kordy, A. N. Mohib, M. M. Ibrahim

Abstract:

The basic objective of the research is to study the effect of hybrid wind energy on the cost of generated electricity considering the cost of reduction CO2 emissions. The system consists of small wind turbine(s), storage battery bank and a diesel generator (W/D/B). Using an optimization software package, different system configurations are investigated to reach optimum configuration based on the net present cost (NPC) and cost of energy (COE) as economic optimization criteria. The cost of avoided CO2 is taken into consideration. The system is intended to supply the electrical load of a small community (gathering six families) in a remote Egyptian area. The investigated system is not connected to the electricity grid and may replace an existing conventional diesel powered electric supply system to reduce fuel consumption and CO2 emissions. The simulation results showed that W/D energy system is more economic than diesel alone. The estimated COE is 0.308$/kWh and extracting the cost of avoided CO2, the COE reached 0.226 $/kWh which is an external benefit of wind turbine, as there are no pollutant emissions through operational phase.

Keywords: Hybrid wind turbine systems, remote areas electrification, simulation of hybrid energy systems, techno-economic study.

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773 Modeling and Simulation of a Hybrid Scooter

Authors: W. K. Yap, V. Karri

Abstract:

This paper presents a hybrid electric scooter model developed and simulated using Matlab/Simulink. This hybrid scooter modeled has a parallel hybrid structure. The main propulsion units consist of a two stroke internal combustion engine and a hub motor attached to the front wheel of the scooter. The methodology used to optimize the energy and fuel consumption of the hybrid electric scooter is the multi-mode approach. Various case studies were presented to check the model and were compared to the literatures. Results shown that the model developed was feasible and valuable.

Keywords: Hybrid electric scooters, modeling and simulation, hybrid scooter energy management.

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772 Hybrid Rocket Motor Performance Parameters: Theoretical and Experimental Evaluation

Authors: A. El-S. Makled, M. K. Al-Tamimi

Abstract:

A mathematical model to predict the performance parameters (thrusts, chamber pressures, fuel mass flow rates, mixture ratios, and regression rates during firing time) of hybrid rocket motor (HRM) is evaluated. The internal ballistic (IB) hybrid combustion model assumes that the solid fuel surface regression rate is controlled only by heat transfer (convective and radiative) from flame zone to solid fuel burning surface. A laboratory HRM is designed, manufactured, and tested for low thrust profile space missions (10-15 N) and for validating the mathematical model (computer program). The polymer material and gaseous oxidizer which are selected for this experimental work are polymethyle-methacrylate (PMMA) and polyethylene (PE) as solid fuel grain and gaseous oxygen (GO2) as oxidizer. The variation of various operational parameters with time is determined systematically and experimentally in firing of up to 20 seconds, and an average combustion efficiency of 95% of theory is achieved, which was the goal of these experiments. The comparison between recording fire data and predicting analytical parameters shows good agreement with the error that does not exceed 4.5% during all firing time. The current mathematical (computer) code can be used as a powerful tool for HRM analytical design parameters.

Keywords: Hybrid combustion, internal ballistics, hybrid rocket motor, performance parameters.

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771 Simultaneous Optimization of Design and Maintenance through a Hybrid Process Using Genetic Algorithms

Authors: O. Adjoul, A. Feugier, K. Benfriha, A. Aoussat

Abstract:

In general, issues related to design and maintenance are considered in an independent manner. However, the decisions made in these two sets influence each other. The design for maintenance is considered an opportunity to optimize the life cycle cost of a product, particularly in the nuclear or aeronautical field, where maintenance expenses represent more than 60% of life cycle costs. The design of large-scale systems starts with product architecture, a choice of components in terms of cost, reliability, weight and other attributes, corresponding to the specifications. On the other hand, the design must take into account maintenance by improving, in particular, real-time monitoring of equipment through the integration of new technologies such as connected sensors and intelligent actuators. We noticed that different approaches used in the Design For Maintenance (DFM) methods are limited to the simultaneous characterization of the reliability and maintainability of a multi-component system. This article proposes a method of DFM that assists designers to propose dynamic maintenance for multi-component industrial systems. The term "dynamic" refers to the ability to integrate available monitoring data to adapt the maintenance decision in real time. The goal is to maximize the availability of the system at a given life cycle cost. This paper presents an approach for simultaneous optimization of the design and maintenance of multi-component systems. Here the design is characterized by four decision variables for each component (reliability level, maintainability level, redundancy level, and level of monitoring data). The maintenance is characterized by two decision variables (the dates of the maintenance stops and the maintenance operations to be performed on the system during these stops). The DFM model helps the designers choose technical solutions for the large-scale industrial products. Large-scale refers to the complex multi-component industrial systems and long life-cycle, such as trains, aircraft, etc. The method is based on a two-level hybrid algorithm for simultaneous optimization of design and maintenance, using genetic algorithms. The first level is to select a design solution for a given system that considers the life cycle cost and the reliability. The second level consists of determining a dynamic and optimal maintenance plan to be deployed for a design solution. This level is based on the Maintenance Free Operating Period (MFOP) concept, which takes into account the decision criteria such as, total reliability, maintenance cost and maintenance time. Depending on the life cycle duration, the desired availability, and the desired business model (sales or rental), this tool provides visibility of overall costs and optimal product architecture.

Keywords: Availability, design for maintenance, DFM, dynamic maintenance, life cycle cost, LCC, maintenance free operating period, MFOP, simultaneous optimization.

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770 Revisiting Domestication and Foreignisation Methods: Translating the Quran by the Hybrid Approach

Authors: Aladdin Al-Tarawneh

Abstract:

The Quran, as it is the sacred book of Islam and considered the literal word of God (Allah) in Arabic, is highly translated into many languages; however, the foreignising or the literal approach excessively stains the quality and discredits the final product in the eyes of its receptors. Such an approach fails to capture the intended meaning of the Quran and to communicate it in any language. Therefore, this study is conducted to propose a different approach that seeks involving other ones according to a hybrid model. Indeed, this study challenges the binary adherence that is highly used in Translation Studies (TS) in general and in the translation of the Quran in particular. Drawing on the genuine fact that the Quran can be communicated in any language in terms of meaning, and the translation is not sacred; this paper approaches the translation of the Quran by blending different methods like domestication or foreignisation in a systematic way, avoiding the binary choice made by many translators. To reach this aim, the paper has a conceptual part that seeks to elucidate and clarify the main methods employed in TS, and criticise and modify them to propose the new hybrid approach (the hybrid model) for translating the Quran – that is, the deductive method. To support and validate the outcome of the previous part, a comparative model is employed in order to highlight the differences between the suggested translation and other widely used ones – that is, the inductive method. By applying this methodology, the paper proves that there is a deficiency of communicating the original meaning of the Quran in light of the foreignising approach. In conclusion, the paper suggests producing a Quran translation has to take into account the adoption of many techniques to express the meaning of the Quran as understood in the original, and to offer this understanding in English in the most native-like manner to serve the intended target readers.

Keywords: Quran translation, hybrid approach, domestication, foreignisation, hybrid model.

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769 Conventional Design and Simulation of an Urban Hybrid Bus

Authors: A. Khanipour, K. M. Ebrahimi, W. J. Seale

Abstract:

Due to heightened concerns over environmental and economic issues the growing important of air pollution, and the importance of conserving fossil fuel resources in the world, the automotive industry is now forced to produce more fuel efficient, low emission vehicles and new drive system technologies. One of the most promising technologies to receive attention is the hybrid electric vehicle (HEV), which consists of two or more energy sources that supply energy to electric traction motors that in turn drive the wheels. This paper presents the various structures of HEV systems, the basic theoretical knowledge for describing their operation and the general behaviour of the HEV in acceleration, cruise and deceleration phases. The conventional design and sizing of a series HEV is studied. A conventional bus and its series configuration are defined and evaluated using the ADVISOR. In this section the simulation of a standard driving cycle and prediction of its fuel consumption and emissions of the HEV are discussed. Finally the bus performance is investigated to establish whether it can satisfy the performance, fuel consumption and emissions requested. The validity of the simulation has been established by the close conformity between the fuel consumption of the conventional bus reported by the manufacturer to what has achieved from the simulation.

Keywords: Hybrid Electric Vehicle, Hybridization, LEV, HEV.

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768 Proton-conducting PVA/PMA Hybrid Membranes for Fuel Cell Applications

Authors: Uma Thanganathan

Abstract:

The hybrid membranes containing inorganic materials in polymer matrix are identified as a remarkable family of proton conducting hybrid electrolytes. In this work, the proton conducting inorganic/organic hybrid membranes for proton exchange membrane fuel cells (PEMFCs) were prepared using polyvinyl alcohol (PVA), tetraethoxyorthosilane (TEOS) and heteropolyacid (HPA). The synthesized hybrid membranes were characterized by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction spectroscopy (XRD), Scanning electron microscopy (SEM) and Thermogravimetry analysis (TGA). The effects of heteropolyacid incorporation on membrane properties, including morphology and thermal stability were extensively investigated.

Keywords: PEMFC, Hybrid membrane, FTIR, TGA, Phosphomolybdic acid

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767 Comparative Study of Scheduling Algorithms for LTE Networks

Authors: Samia Dardouri, Ridha Bouallegue

Abstract:

Scheduling is the process of dynamically allocating physical resources to User Equipment (UE) based on scheduling algorithms implemented at the LTE base station. Various algorithms have been proposed by network researchers as the implementation of scheduling algorithm which represents an open issue in Long Term Evolution (LTE) standard. This paper makes an attempt to study and compare the performance of PF, MLWDF and EXP/PF scheduling algorithms. The evaluation is considered for a single cell with interference scenario for different flows such as Best effort, Video and VoIP in a pedestrian and vehicular environment using the LTE-Sim network simulator. The comparative study is conducted in terms of system throughput, fairness index, delay, packet loss ratio (PLR) and total cell spectral efficiency.

Keywords: LTE, Multimedia flows, Scheduling algorithms.

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766 Genetic Algorithms Multi-Objective Model for Project Scheduling

Authors: Elsheikh Asser

Abstract:

Time and cost are the main goals of the construction project management. The first schedule developed may not be a suitable schedule for beginning or completing the project to achieve the target completion time at a minimum total cost. In general, there are trade-offs between time and cost (TCT) to complete the activities of a project. This research presents genetic algorithms (GAs) multiobjective model for project scheduling considering different scenarios such as least cost, least time, and target time.

Keywords: Genetic algorithms, Time-cost trade-off.

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765 Design and Analysis of a Novel 8-DOF Hybrid Manipulator

Authors: H. Mohammadipanah, H. Zohoor

Abstract:

This paper presents kinematic and dynamic analysis of a novel 8-DOF hybrid robot manipulator. The hybrid robot manipulator under consideration consists of a parallel robot which is followed by a serial mechanism. The parallel mechanism has three translational DOF, and the serial mechanism has five DOF so that the overall degree of freedom is eight. The introduced manipulator has a wide workspace and a high capability to reduce the actuating energy. The inverse and forward kinematic solutions are described in closed form. The theoretical results are verified by a numerical example. Inverse dynamic analysis of the robot is presented by utilizing the Iterative Newton-Euler and Lagrange dynamic formulation methods. Finally, for performing a multi-step arc welding process, results have indicated that the introduced manipulator is highly capable of reducing the actuating energy.

Keywords: hybrid robot, closed form, inverse dynamic, actuating energy, arc welding

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764 Control Strategy for Two-Mode Hybrid Electric Vehicle by Using Fuzzy Controller

Authors: Jia-Shiun Chen, Hsiu-Ying Hwang

Abstract:

Hybrid electric vehicles can reduce pollution and improve fuel economy. Power-split hybrid electric vehicles (HEVs) provide two power paths between the internal combustion engine (ICE) and energy storage system (ESS) through the gears of an electrically variable transmission (EVT). EVT allows ICE to operate independently from vehicle speed all the time. Therefore, the ICE can operate in the efficient region of its characteristic brake specific fuel consumption (BSFC) map. The two-mode powertrain can operate in input-split or compound-split EVT modes and in four different fixed gear configurations. Power-split architecture is advantageous because it combines conventional series and parallel power paths. This research focuses on input-split and compound-split modes in the two-mode power-split powertrain. Fuzzy Logic Control (FLC) for an internal combustion engine (ICE) and PI control for electric machines (EMs) are derived for the urban driving cycle simulation. These control algorithms reduce vehicle fuel consumption and improve ICE efficiency while maintaining the state of charge (SOC) of the energy storage system in an efficient range.

Keywords: Hybrid electric vehicle, fuel economy, two-mode hybrid, fuzzy control.

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763 Parameters Extraction for Pseudomorphic HEMTs Using Genetic Algorithms

Authors: Mazhar B. Tayel, Amr H. Yassin

Abstract:

A proposed small-signal model parameters for a pseudomorphic high electron mobility transistor (PHEMT) is presented. Both extrinsic and intrinsic circuit elements of a smallsignal model are determined using genetic algorithm (GA) as a stochastic global search and optimization tool. The parameters extraction of the small-signal model is performed on 200-μm gate width AlGaAs/InGaAs PHEMT. The equivalent circuit elements for a proposed 18 elements model are determined directly from the measured S- parameters. The GA is used to extract the parameters of the proposed small-signal model from 0.5 up to 18 GHz.

Keywords: PHEMT, Genetic Algorithms, small signal modeling, optimization.

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