Search results for: Vendor Selection.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1031

Search results for: Vendor Selection.

761 A Model for Collaborative COTS Software Acquisition (COSA)

Authors: Torsti Rantapuska, Sariseelia Sore

Abstract:

Acquiring commercial off-the-shelf (COTS) software applications is becoming routine in organizations. However, eliciting user requirements, finding the candidate COTS products and making the decision is a complex task, especially for SMEs who do not have the time and knowledge needed to do the task properly. The existing models intended to help the decision makers are originally designed for professional use. SMEs are obligated to rely on the software vendor’s ability to solve the problem with the systems provided.  In this paper, we develop a model for SMEs for the acquisition of Commercial Off-The-Shelf (COTS) software products. A leading idea of the model is that the ICT investment is basically a change initiative and therefore it should also be taken as a process of organizational learning. The model is designed bearing three objectives in mind: 1) business orientation, 2) agility, and 3) Learning and knowledge management orientation. The model can be applied to ICT investments in SMEs which have a professional team leader with basic business and IT knowledge. 

 

Keywords: COTS acquisition, ICT investment, organizational learning, ICT adoption.

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760 PSO-based Possibilistic Portfolio Model with Transaction Costs

Authors: Wei Chen, Cui-you Yao, Yue Qiu

Abstract:

This paper deals with a portfolio selection problem based on the possibility theory under the assumption that the returns of assets are LR-type fuzzy numbers. A possibilistic portfolio model with transaction costs is proposed, in which the possibilistic mean value of the return is termed measure of investment return, and the possibilistic variance of the return is termed measure of investment risk. Due to considering transaction costs, the existing traditional optimization algorithms usually fail to find the optimal solution efficiently and heuristic algorithms can be the best method. Therefore, a particle swarm optimization is designed to solve the corresponding optimization problem. At last, a numerical example is given to illustrate our proposed effective means and approaches.

Keywords: Possibility theory, portfolio selection, transaction costs, particle swarm optimization.

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759 Breast Cancer Survivability Prediction via Classifier Ensemble

Authors: Mohamed Al-Badrashiny, Abdelghani Bellaachia

Abstract:

This paper presents a classifier ensemble approach for predicting the survivability of the breast cancer patients using the latest database version of the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. The system consists of two main components; features selection and classifier ensemble components. The features selection component divides the features in SEER database into four groups. After that it tries to find the most important features among the four groups that maximizes the weighted average F-score of a certain classification algorithm. The ensemble component uses three different classifiers, each of which models different set of features from SEER through the features selection module. On top of them, another classifier is used to give the final decision based on the output decisions and confidence scores from each of the underlying classifiers. Different classification algorithms have been examined; the best setup found is by using the decision tree, Bayesian network, and Na¨ıve Bayes algorithms for the underlying classifiers and Na¨ıve Bayes for the classifier ensemble step. The system outperforms all published systems to date when evaluated against the exact same data of SEER (period of 1973-2002). It gives 87.39% weighted average F-score compared to 85.82% and 81.34% of the other published systems. By increasing the data size to cover the whole database (period of 1973-2014), the overall weighted average F-score jumps to 92.4% on the held out unseen test set.

Keywords: Classifier ensemble, breast cancer survivability, data mining, SEER.

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758 Microscopic Simulation of Toll Plaza Safety and Operations

Authors: Bekir O. Bartin, Kaan Ozbay, Sandeep Mudigonda, Hong Yang

Abstract:

The use of microscopic traffic simulation in evaluating the operational and safety conditions at toll plazas is demonstrated. Two toll plazas in New Jersey are selected as case studies and were developed and validated in Paramics traffic simulation software. In order to simulate drivers’ lane selection behavior in Paramics, a utility-based lane selection approach is implemented in Paramics Application Programming Interface (API). For each vehicle approaching the toll plaza, a utility value is assigned to each toll lane by taking into account the factors that are likely to impact drivers’ lane selection behavior, such as approach lane, exit lane and queue lengths. The results demonstrate that similar operational conditions, such as lane-by-lane toll plaza traffic volume can be attained using this approach. In addition, assessment of safety at toll plazas is conducted via a surrogate safety measure. In particular, the crash index (CI), an improved surrogate measure of time-to-collision (TTC), which reflects the severity of a crash is used in the simulation analyses. The results indicate that the spatial and temporal frequency of observed crashes can be simulated using the proposed methodology. Further analyses can be conducted to evaluate and compare various different operational decisions and safety measures using microscopic simulation models.

Keywords: Microscopic simulation, toll plaza, surrogate safety, application programming interface.

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757 Low Cost Chip Set Selection Algorithm for Multi-way Partitioning of Digital System

Authors: Jae Young Park, Soongyu Kwon, Kyu Han Kim, Hyeong Geon Lee, Jong Tae Kim

Abstract:

This paper considers the problem of finding low cost chip set for a minimum cost partitioning of a large logic circuits. Chip sets are selected from a given library. Each chip in the library has a different price, area, and I/O pin. We propose a low cost chip set selection algorithm. Inputs to the algorithm are a netlist and a chip information in the library. Output is a list of chip sets satisfied with area and maximum partitioning number and it is sorted by cost. The algorithm finds the sorted list of chip sets from minimum cost to maximum cost. We used MCNC benchmark circuits for experiments. The experimental results show that all of chip sets found satisfy the multiple partitioning constraints.

Keywords: lowest cost chip set, MCNC benchmark, multi-way partitioning.

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756 Project Portfolio Management Phases: A Technique for Strategy Alignment

Authors: Amaral, António, Araújo, Madalena

Abstract:

This paper seeks to give a general idea of the universe of project portfolio management, from its multidisciplinary nature, to the many challenges it raises, passing through the different techniques, models and tools used to solve the multiple problems known. It is intended to contribute to the clarification, with great depth, of the impacts and relationships involved in managing the projects- portfolio. It aims at proposing a technique for the project alignment with the organisational strategy, in order to select projects that later on will be considered in the analysis and selection of the portfolio. We consider the development of a methodology for assessing the project alignment index very relevant in the global market scenario. It can help organisations to gain a greater awareness of market dynamics, speed up the decision process and increase its consistency, thus enabling the strategic alignment and the improvement of the organisational performance.

Keywords: Project Portfolio Management Cycle, Project Portfolio Selection, Resource Assignment, Strategy Alignment technique

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755 A Review of Genetic Algorithm Optimization: Operations and Applications to Water Pipeline Systems

Authors: I. Abuiziah, N. Shakarneh

Abstract:

Genetic Algorithm (GA) is a powerful technique for solving optimization problems. It follows the idea of survival of the fittest - Better and better solutions evolve from previous generations until a near optimal solution is obtained. GA uses the main three operations, the selection, crossover and mutation to produce new generations from the old ones. GA has been widely used to solve optimization problems in many applications such as traveling salesman problem, airport traffic control, information retrieval (IR), reactive power optimization, job shop scheduling, and hydraulics systems such as water pipeline systems. In water pipeline systems we need to achieve some goals optimally such as minimum cost of construction, minimum length of pipes and diameters, and the place of protection devices. GA shows high performance over the other optimization techniques, moreover, it is easy to implement and use. Also, it searches a limited number of solutions.

Keywords: Genetic Algorithm, optimization, pipeline systems, selection, cross over.

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754 Feature Selection for Web Page Classification Using Swarm Optimization

Authors: B. Leela Devi, A. Sankar

Abstract:

The web’s increased popularity has included a huge amount of information, due to which automated web page classification systems are essential to improve search engines’ performance. Web pages have many features like HTML or XML tags, hyperlinks, URLs and text contents which can be considered during an automated classification process. It is known that Webpage classification is enhanced by hyperlinks as it reflects Web page linkages. The aim of this study is to reduce the number of features to be used to improve the accuracy of the classification of web pages. In this paper, a novel feature selection method using an improved Particle Swarm Optimization (PSO) using principle of evolution is proposed. The extracted features were tested on the WebKB dataset using a parallel Neural Network to reduce the computational cost.

Keywords: Web page classification, WebKB Dataset, Term Frequency-Inverse Document Frequency (TF-IDF), Particle Swarm Optimization (PSO).

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753 Evaluating and Selecting Optimization Software Packages: A Framework for Business Applications

Authors: Waleed Abohamad, Amr Arisha

Abstract:

Owing the fact that optimization of business process is a crucial requirement to navigate, survive and even thrive in today-s volatile business environment, this paper presents a framework for selecting a best-fit optimization package for solving complex business problems. Complexity level of the problem and/or using incorrect optimization software can lead to biased solutions of the optimization problem. Accordingly, the proposed framework identifies a number of relevant factors (e.g. decision variables, objective functions, and modeling approach) to be considered during the evaluation and selection process. Application domain, problem specifications, and available accredited optimization approaches are also to be regarded. A recommendation of one or two optimization software is the output of the framework which is believed to provide the best results of the underlying problem. In addition to a set of guidelines and recommendations on how managers can conduct an effective optimization exercise is discussed.

Keywords: Complex Business Problems, Optimization, Selection Criteria, Software Evaluation.

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752 Inter-Organizational Knowledge Transfer Through Malaysia E-government IT Outsourcing: A Theoretical Review

Authors: Nor Aziati Abdul Hamid, Juhana Salim

Abstract:

The main objective of this paper is to contribute the existing knowledge transfer and IT Outsourcing literature specifically in the context of Malaysia by reviewing the current practices of e-government IT outsourcing in Malaysia including the issues and challenges faced by the public agencies in transferring the knowledge during the engagement. This paper discusses various factors and different theoretical model of knowledge transfer starting from the traditional model to the recent model suggested by the scholars. The present paper attempts to align organizational knowledge from the knowledge-based view (KBV) and organizational learning (OL) lens. This review could help shape the direction of both future theoretical and empirical studies on inter-firm knowledge transfer specifically on how KBV and OL perspectives could play significant role in explaining the complex relationships between the client and vendor in inter-firm knowledge transfer and the role of organizational management information system and Transactive Memory System (TMS) to facilitate the organizational knowledge transferring process. Conclusion is drawn and further research is suggested.

Keywords: E-government, IT Outsourcing, Knowledge Management, Knowledge Transfer

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751 Strength Optimization of Induction Hardened Splined Shaft – Material and Geometric Aspects

Authors: I. Barsoum, F. Khan

Abstract:

the current study presents a modeling framework to determine the torsion strength of an induction hardened splined shaft by considering geometry and material aspects with the aim to optimize the static torsion strength by selection of spline geometry and hardness depth. Six different spline geometries and seven different hardness profiles including non-hardened and throughhardened shafts have been considered. The results reveal that the torque that causes initial yielding of the induction hardened splined shaft is strongly dependent on the hardness depth and the geometry of the spline teeth. Guidelines for selection of the appropriate hardness depth and spline geometry are given such that an optimum static torsion strength of the component can be achieved.

Keywords: Static strength, splined shaft, torsion, induction hardening, hardness profile, finite element, optimization, design.

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750 Facilitating a Cyber-Enabled Fraud Using the O.MG Cable to Incriminate the Victim

Authors: Damola O. Lawal, David W. Gresty, Diane E. Gan, Louise Hewitt

Abstract:

This paper investigates the feasibility of using a programmable USB such as the O.MG Cable to perform a file tampering attack. Here, the O.MG Cable, an apparently harmless mobile device charger is used in an unauthorised way, to alter the content of a file (an accounts record-January_Contributions.xlsx). The aim is to determine if a forensics analyst can reliably determine who has altered the target file; the O.MG Cable or the user of the machine. This work highlights some of the traces of the O.MG Cable left behind on the target computer itself such as the Product ID (PID) and Vendor ID (ID). Also discussed is the O.MG Cable’s behaviour during the experiments. We determine if a forensics analyst could identify if any evidence has been left behind by the programmable device on the target file once it has been removed from the computer to establish if the analyst would be able to link the traces left by the O.MG Cable to the file tampering. It was discovered that the forensic analyst might mistake the actions of the O.MG Cable for the computer users. Experiments carried out in this work could further the discussion as to whether an innocent user could be punished for the unauthorised changes made by a programmable device.

Keywords: O.MG Cable, programmable USB, file tampering attack, digital evidence credibility, miscarriage of justice, cyber fraud.

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749 Combine a Population-based Incremental Learning with Artificial Immune System for Intrusion Detection System

Authors: Jheng-Long Wu, Pei-Chann Chang, Hsuan-Ming Chen

Abstract:

This research focus on the intrusion detection system (IDS) development which using artificial immune system (AIS) with population based incremental learning (PBIL). AIS have powerful distinguished capability to extirpate antigen when the antigen intrude into human body. The PBIL is based on past learning experience to adjust new learning. Therefore we propose an intrusion detection system call PBIL-AIS which combine two approaches of PBIL and AIS to evolution computing. In AIS part we design three mechanisms such as clonal selection, negative selection and antibody level to intensify AIS performance. In experimental result, our PBIL-AIS IDS can capture high accuracy when an intrusion connection attacks.

Keywords: Artificial immune system, intrusion detection, population-based incremental learning, evolution computing.

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748 Information Filtering using Index Word Selection based on the Topics

Authors: Takeru YOKOI, Hidekazu YANAGIMOTO, Sigeru OMATU

Abstract:

We have proposed an information filtering system using index word selection from a document set based on the topics included in a set of documents. This method narrows down the particularly characteristic words in a document set and the topics are obtained by Sparse Non-negative Matrix Factorization. In information filtering, a document is often represented with the vector in which the elements correspond to the weight of the index words, and the dimension of the vector becomes larger as the number of documents is increased. Therefore, it is possible that useless words as index words for the information filtering are included. In order to address the problem, the dimension needs to be reduced. Our proposal reduces the dimension by selecting index words based on the topics included in a document set. We have applied the Sparse Non-negative Matrix Factorization to the document set to obtain these topics. The filtering is carried out based on a centroid of the learning document set. The centroid is regarded as the user-s interest. In addition, the centroid is represented with a document vector whose elements consist of the weight of the selected index words. Using the English test collection MEDLINE, thus, we confirm the effectiveness of our proposal. Hence, our proposed selection can confirm the improvement of the recommendation accuracy from the other previous methods when selecting the appropriate number of index words. In addition, we discussed the selected index words by our proposal and we found our proposal was able to select the index words covered some minor topics included in the document set.

Keywords: Information Filtering, Sparse NMF, Index wordSelection, User Profile, Chi-squared Measure

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747 An Automatic Bayesian Classification System for File Format Selection

Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

Abstract:

This paper presents an approach for the classification of an unstructured format description for identification of file formats. The main contribution of this work is the employment of data mining techniques to support file format selection with just the unstructured text description that comprises the most important format features for a particular organisation. Subsequently, the file format indentification method employs file format classifier and associated configurations to support digital preservation experts with an estimation of required file format. Our goal is to make use of a format specification knowledge base aggregated from a different Web sources in order to select file format for a particular institution. Using the naive Bayes method, the decision support system recommends to an expert, the file format for his institution. The proposed methods facilitate the selection of file format and the quality of a digital preservation process. The presented approach is meant to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and specifications of file formats. To facilitate decision-making, the aggregated information about the file formats is presented as a file format vocabulary that comprises most common terms that are characteristic for all researched formats. The goal is to suggest a particular file format based on this vocabulary for analysis by an expert. The sample file format calculation and the calculation results including probabilities are presented in the evaluation section.

Keywords: Data mining, digital libraries, digital preservation, file format.

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746 Target Concept Selection by Property Overlap in Ontology Population

Authors: Seong-Bae Park, Sang-Soo Kim, Sewook Oh, Zooyl Zeong, Hojin Lee, Seong Rae Park

Abstract:

An ontology is widely used in many kinds of applications as a knowledge representation tool for domain knowledge. However, even though an ontology schema is well prepared by domain experts, it is tedious and cost-intensive to add instances into the ontology. The most confident and trust-worthy way to add instances into the ontology is to gather instances from tables in the related Web pages. In automatic populating of instances, the primary task is to find the most proper concept among all possible concepts within the ontology for a given table. This paper proposes a novel method for this problem by defining the similarity between the table and the concept using the overlap of their properties. According to a series of experiments, the proposed method achieves 76.98% of accuracy. This implies that the proposed method is a plausible way for automatic ontology population from Web tables.

Keywords: Ontology population, domain knowledge consolidation, target concept selection, property overlap.

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745 A Scenario Oriented Supplier Selection by Considering a Multi Tier Supplier Network

Authors: Mohammad Najafi Nobar, Bahareh Pourmehr, Mehdi Hajimirarab

Abstract:

One of the main processes of supply chain management is supplier selection process which its accurate implementation can dramatically increase company competitiveness. In presented article model developed based on the features of second tiers suppliers and four scenarios are predicted in order to help the decision maker (DM) in making up his/her mind. In addition two tiers of suppliers have been considered as a chain of suppliers. Then the proposed approach is solved by a method combined of concepts of fuzzy set theory (FST) and linear programming (LP) which has been nourished by real data extracted from an engineering design and supplying parts company. At the end results reveal the high importance of considering second tier suppliers features as criteria for selecting the best supplier.

Keywords: Supply Chain Management (SCM), SupplierSelection, Second Tier Supplier, Scenario Planning, Green Factor, Linear Programming, Fuzzy Set Theory

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744 Intrusion Detection Using a New Particle Swarm Method and Support Vector Machines

Authors: Essam Al Daoud

Abstract:

Intrusion detection is a mechanism used to protect a system and analyse and predict the behaviours of system users. An ideal intrusion detection system is hard to achieve due to nonlinearity, and irrelevant or redundant features. This study introduces a new anomaly-based intrusion detection model. The suggested model is based on particle swarm optimisation and nonlinear, multi-class and multi-kernel support vector machines. Particle swarm optimisation is used for feature selection by applying a new formula to update the position and the velocity of a particle; the support vector machine is used as a classifier. The proposed model is tested and compared with the other methods using the KDD CUP 1999 dataset. The results indicate that this new method achieves better accuracy rates than previous methods.

Keywords: Feature selection, Intrusion detection, Support vector machine, Particle swarm.

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743 The Study on the Stationarity of Energy Consumption in US States: Considering Structural Breaks, Nonlinearity, and Cross- Sectional Dependency

Authors: Wen-Chi Liu

Abstract:

This study applies the sequential panel selection method (SPSM) procedure proposed by Chortareas and Kapetanios (2009) to investigate the time-series properties of energy consumption in 50 US states from 1963 to 2009. SPSM involves the classification of the entire panel into a group of stationary series and a group of non-stationary series to identify how many and which series in the panel are stationary processes. Empirical results obtained through SPSM with the panel KSS unit root test developed by Ucar and Omay (2009) combined with a Fourier function indicate that energy consumption in all the 50 US states are stationary. The results of this study have important policy implications for the 50 US states.

Keywords: Energy Consumption, Panel Unit Root, Sequential Panel Selection Method, Fourier Function, US states.

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742 High Quality Speech Coding using Combined Parametric and Perceptual Modules

Authors: M. Kulesza, G. Szwoch, A. Czyżewski

Abstract:

A novel approach to speech coding using the hybrid architecture is presented. Advantages of parametric and perceptual coding methods are utilized together in order to create a speech coding algorithm assuring better signal quality than in traditional CELP parametric codec. Two approaches are discussed. One is based on selection of voiced signal components that are encoded using parametric algorithm, unvoiced components that are encoded perceptually and transients that remain unencoded. The second approach uses perceptual encoding of the residual signal in CELP codec. The algorithm applied for precise transient selection is described. Signal quality achieved using the proposed hybrid codec is compared to quality of some standard speech codecs.

Keywords: CELP residual coding, hybrid codec architecture, perceptual speech coding, speech codecs comparison.

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741 A Comparative Analysis Approach Based on Fuzzy AHP, TOPSIS and PROMETHEE for the Selection Problem of GSCM Solutions

Authors: Omar Boutkhoum, Mohamed Hanine, Abdessadek Bendarag

Abstract:

Sustainable economic growth is nowadays driving firms to extend toward the adoption of many green supply chain management (GSCM) solutions. However, the evaluation and selection of these solutions is a matter of concern that needs very serious decisions, involving complexity owing to the presence of various associated factors. To resolve this problem, a comparative analysis approach based on multi-criteria decision-making methods is proposed for adequate evaluation of sustainable supply chain management solutions. In the present paper, we propose an integrated decision-making model based on FAHP (Fuzzy Analytic Hierarchy Process), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluations) to contribute to a better understanding and development of new sustainable strategies for industrial organizations. Due to the varied importance of the selected criteria, FAHP is used to identify the evaluation criteria and assign the importance weights for each criterion, while TOPSIS and PROMETHEE methods employ these weighted criteria as inputs to evaluate and rank the alternatives. The main objective is to provide a comparative analysis based on TOPSIS and PROMETHEE processes to help make sound and reasoned decisions related to the selection problem of GSCM solution.

Keywords: GSCM solutions, multi-criteria analysis, FAHP, TOPSIS, PROMETHEE, decision support system.

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740 Goal-Based Request Cloud Resource Broker in Medical Application

Authors: Mohamad Izuddin Nordin, Azween Abdullah, Mahamat Issa Hassan

Abstract:

In this paper, cloud resource broker using goalbased request in medical application is proposed. To handle recent huge production of digital images and data in medical informatics application, the cloud resource broker could be used by medical practitioner for proper process in discovering and selecting correct information and application. This paper summarizes several reviewed articles to relate medical informatics application with current broker technology and presents a research work in applying goal-based request in cloud resource broker to optimize the use of resources in cloud environment. The objective of proposing a new kind of resource broker is to enhance the current resource scheduling, discovery, and selection procedures. We believed that it could help to maximize resources allocation in medical informatics application.

Keywords: Broker, Cloud Computing, Medical Informatics, Resources Discovery, Resource Selection.

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739 Green Lean TQM Practices in Malaysian Automotive Companies

Authors: Noor Azlina Mohd Salleh, Salmiah Kasolang, Ahmed Jaffar

Abstract:

Green Lean Total Quality Management (TQM) System is a system comprises of Environmental Management System (EMS) practices which is integrated to TQM with Lean Manufacturing (LM) principles. The ultimate goal of this system is to focus on achieving total customer satisfaction and environmental care by removing eight wastes available in any process in an organization. A survey questionnaire was developed and distributed to 30 highly active automotive vendors in Malaysia and analyzed by SPSS v.17. It was found out that some vendors have been practicing TQM and LM while some have started to implement EMS. This study is only focusing on highly active companies that have been involved in MAJAICO Program and Proton Vendor Development Program. This is the first study conducted to know the current status of TQM, LM and EMS practices in highly active automotive companies in Malaysia. It was found out that EMS has been practiced by 16 companies out of 30. Within these 16 companies the approach is more holistic and green. This is a preliminary study that combined 4 awards practices, ISO/TS16949, Toyota Production System SAEJ4000, MAJAICO Lean Production System and EMS.

Keywords: Automotive Industry, Lean Manufacturing, Operational Engineering Management, Total Quality Management. Environmental Management System.

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738 Exploring the Importance of Different Product Cues on the Selection for Chocolate from the Consumer Perspective

Authors: Ezeni Brzovska, Durdana Ozretic-Dosen

Abstract:

The purpose of this paper is to deepen the understanding of the product cues that influence purchase decision for a specific product category – chocolate, and to identify demographic differences in the buying behavior. ANOVA was employed for analyzing the significance level for nine product cues, and the survey showed statistically significant differences among different age and gender groups, and between respondents with different levels of education. From the theoretical perspective, the study adds to the existing knowledge by contributing with the research results from the new environment (Southeast Europe, Macedonia), which has been neglected so far. Establishing the level of significance for the product cues that affect buying behavior in the chocolate consumption context might help managers to improve marketing decision-making, and better meet consumer needs through identifying opportunities for packaging innovations and/or personalization toward different target groups.

Keywords: Chocolate consumption context, chocolate selection, demographic characteristics, product cues.

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737 Optimum Working Fluid Selection for Automotive Cogeneration System

Authors: Wonsim Cha, Kibum Kim, Kyungwook Choi, Kihyung Lee

Abstract:

A co-generation system in automobile can improve thermal efficiency of vehicle in some degree. The waste heat from the engine exhaust and coolant is still attractive energy source that reaches around 60% of the total energy converted from fuel. To maximize the effectiveness of heat exchangers for recovering the waste heat, it is vital to select the most suitable working fluid for the system, not to mention that it is important to find the optimum design for the heat exchangers. The design of heat exchanger is out of scoop of this study; rather, the main focus has been on the right selection of working fluid for the co-generation system. Simulation study was carried out to find the most suitable working fluid that can allow the system to achieve the optimum efficiency in terms of the heat recovery rate and thermal efficiency.

Keywords: Cycle Analysis, Heat Recovery, Rankine Cycle, Waste Heat Recovery, Working Fluid.

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736 Genetic Algorithm for Feature Subset Selection with Exploitation of Feature Correlations from Continuous Wavelet Transform: a real-case Application

Authors: G. Van Dijck, M. M. Van Hulle, M. Wevers

Abstract:

A genetic algorithm (GA) based feature subset selection algorithm is proposed in which the correlation structure of the features is exploited. The subset of features is validated according to the classification performance. Features derived from the continuous wavelet transform are potentially strongly correlated. GA-s that do not take the correlation structure of features into account are inefficient. The proposed algorithm forms clusters of correlated features and searches for a good candidate set of clusters. Secondly a search within the clusters is performed. Different simulations of the algorithm on a real-case data set with strong correlations between features show the increased classification performance. Comparison is performed with a standard GA without use of the correlation structure.

Keywords: Classification, genetic algorithm, hierarchicalagglomerative clustering, wavelet transform.

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735 MIMO Broadcast Scheduling for Weighted Sum-rate Maximization

Authors: Swadhin Kumar Mishra, Sidhartha Panda, C. Ardil

Abstract:

Multiple-Input-Multiple-Output (MIMO) is one of the most important communication techniques that allow wireless systems to achieve higher data rate. To overcome the practical difficulties in implementing Dirty Paper Coding (DPC), various suboptimal MIMO Broadcast (MIMO-BC) scheduling algorithms are employed which choose the best set of users among all the users. In this paper we discuss such a sub-optimal MIMO-BC scheduling algorithm which employs antenna selection at the receiver side. The channels for the users considered here are not Identical and Independent Distributed (IID) so that users at the receiver side do not get equal opportunity for communication. So we introduce a method of applying weights to channels of the users which are not IID in such a way that each of the users gets equal opportunity for communication. The effect of weights on overall sum-rate achieved by the system has been investigated and presented.

Keywords: Antenna selection, Identical and Independent Distributed (IID), Sum-rate capacity, Weighted sum rate.

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734 A Framework for Evaluating the QoS and Cost of Web Services Based on Its Functional Performance

Authors: M. Mohemmed Sha, T. Manesh, A. Mohamed Mustaq Ahmed

Abstract:

In this corporate world, the technology of Web services has grown rapidly and its significance for the development of web based applications gradually rises over time. The success of Business to Business integration rely on finding novel partners and their services in a global business environment. However, the selection of the most suitable Web service from the list of services with the identical functionality is more vital. The satisfaction level of the customer and the provider’s reputation of the Web service are primarily depending on the range it reaches the customer’s requirements. In most cases, the customer of the Web service feels that he is spending for the service which is undelivered. This is because the customer always thinks that the real functionality of the web service is not reached. This will lead to change of the service frequently. In this paper, a framework is proposed to evaluate the Quality of Service (QoS) and its cost that makes the optimal correlation between each other. In addition, this research work proposes some management decision against the functional deviancy of the web service that is guaranteed at time of selection.

Keywords: Web service, service level agreement, quality of a service, cost of a service, QoS, CoS, SOA, WSLA, WsRF.

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733 The Design of Self-evolving Artificial Immune System II for Permutation Flow-shop Problem

Authors: Meng-Hui Chen, Pei-Chann Chang, Wei-Hsiu Huang

Abstract:

Artificial Immune System is adopted as a Heuristic Algorithm to solve the combinatorial problems for decades. Nevertheless, many of these applications took advantage of the benefit for applications but seldom proposed approaches for enhancing the efficiency. In this paper, we continue the previous research to develop a Self-evolving Artificial Immune System II via coordinating the T and B cell in Immune System and built a block-based artificial chromosome for speeding up the computation time and better performance for different complexities of problems. Through the design of Plasma cell and clonal selection which are relative the function of the Immune Response. The Immune Response will help the AIS have the global and local searching ability and preventing trapped in local optima. From the experimental result, the significant performance validates the SEAIS II is effective when solving the permutation flows-hop problems.

Keywords: Artificial Immune System, Clonal Selection, Immune Response, Permutation Flow-shop Scheduling Problems

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732 Reliability-based Selection of Wind Turbines for Large-Scale Wind Farms

Authors: M. Fotuhi-Firuzabad, A. Salehi Dobakhshari

Abstract:

This paper presents a reliability-based approach to select appropriate wind turbine types for a wind farm considering site-specific wind speed patterns. An actual wind farm in the northern region of Iran with the wind speed registration of one year is studied in this paper. An analytic approach based on total probability theorem is utilized in this paper to model the probabilistic behavior of both turbines- availability and wind speed. Well-known probabilistic reliability indices such as loss of load expectation (LOLE), expected energy not supplied (EENS) and incremental peak load carrying capability (IPLCC) for wind power integration in the Roy Billinton Test System (RBTS) are examined. The most appropriate turbine type achieving the highest reliability level is chosen for the studied wind farm.

Keywords: Wind Turbine Generator, Wind Farm, Power System Reliability, Wind Turbine Type Selection

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