Search results for: Shared Memory Parallel Computing

Authors: Shuen-Tai Wang, Chin-Hung Li, Ying-Chuan Chen

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In recent years there has been renewal of interest in the relation between Green IT and Cloud Computing. The growing use of computers in cloud platform has caused marked energy consumption, putting negative pressure on electricity cost of cloud data center. This paper proposes an effective mechanism to reduce energy utilization in cloud computing environments. We present initial work on the integration of resource and power management that aims at reducing power consumption. Our mechanism relies on recalling virtualization services dynamically according to user-s virtualization request and temporarily shutting down the physical machines after finish in order to conserve energy. Given the estimated energy consumption, this proposed effort has the potential to positively impact power consumption. The results from the experiment concluded that energy indeed can be saved by powering off the idling physical machines in cloud platforms.

Keywords: Green IT, Cloud Computing, virtualization, power consumption.

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Authors: Emilia Nercissians

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The paper attempts to contribute to the largely neglected social and anthropological discussion of technology development on the one hand, and to redirecting the emphasis in anthropology from primitive and exotic societies to problems of high relevance in contemporary era and how technology is used in everyday life. It draws upon multidimensional models of intelligence and ideal type formation. It is argued that the predominance of computational and cognitive cosmovisions have led to technology alienation. Injection of communicative competence in artificially intelligent systems and identity technologies in the coming information society are analyzed

Keywords: convergence, nomadic computing, solidarity, status.

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Authors: Mohammad Bsoul, Iain Phillips, Chris Hinde

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This paper is concerned with the design and implementation of MICOSim, an event-driven simulator written in Java for evaluating the performance of Grid entities (users, brokers and resources) under different scenarios such as varying the numbers of users, resources and brokers and varying their specifications and employed strategies.

Keywords: Grid computing, Economic Scheduling, Simulation, Event-Driven, Java.

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Authors: Inayat Ur Rehman, Georgia Sakellari

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Cloud computing has evolved into a vital technology for businesses, offering scalability, flexibility, and cost-effectiveness. However, maintaining high availability and optimal performance in the cloud is crucial for reliable services. This paper explores the significance of cloud monitoring and performance optimization in sustaining the high availability of cloud-based systems. It discusses diverse monitoring tools, techniques, and best practices for continually assessing the health and performance of cloud resources. The paper also delves into performance optimization strategies, including resource allocation, load balancing, and auto-scaling, to ensure efficient resource utilization and responsiveness. Addressing potential challenges in cloud monitoring and optimization, the paper offers insights into data security and privacy considerations. Through this thorough analysis, the paper aims to underscore the importance of cloud monitoring and performance optimization for ensuring a seamless and highly available cloud computing environment.

Keywords: Cloud computing, cloud monitoring, performance optimization, high availability.

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Authors: Shunsuke Miyoshi, Yasuyuki Nogami, Takuya Kusaka, Nariyoshi Yamai

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Elliptic curve discrete logarithm problem(ECDLP) is one of problems on which the security of pairing-based cryptography is based. This paper considers Pollard’s rho method to evaluate the security of ECDLP on Barreto-Naehrig(BN) curve that is an efficient pairing-friendly curve. Some techniques are proposed to make the rho method efficient. Especially, the group structure on BN curve, distinguished point method, and Montgomery trick are well-known techniques. This paper applies these techniques and shows its optimization. According to the experimental results for which a large-scale parallel system with MySQL is applied, 94-bit ECDLP was solved about 28 hours by parallelizing 71 computers.

Keywords: Pollard’s rho method, BN curve, Montgomery multiplication.

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Authors: Imran Ihsan, Muhammad Abdul Qadir, Nadeem Iftikhar

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Mobile devices, which are progressively surrounded in our everyday life, have created a new paradigm where they interconnect, interact and collaborate with each other. This network can be used for flexible and secure coordinated sharing. On the other hand Grid computing provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities. In this paper, efforts are made to map the concepts of Grid on Ad-Hoc networks because both exhibit similar kind of characteristics like Scalability, Dynamism and Heterogeneity. In this context we propose “Mobile Ad-Hoc Services Grid – MASGRID".

Keywords: Mobile Ad-Hoc Networks, Grid Computing, Resource Discovery, Routing

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Authors: Muzaffar Bashir, Jürgen Kempf

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The purpose of this paper is to present a Dynamic Time Warping technique which reduces significantly the data processing time and memory size of multi-dimensional time series sampled by the biometric smart pen device BiSP. The acquisition device is a novel ballpoint pen equipped with a diversity of sensors for monitoring the kinematics and dynamics of handwriting movement. The DTW algorithm has been applied for time series analysis of five different sensor channels providing pressure, acceleration and tilt data of the pen generated during handwriting on a paper pad. But the standard DTW has processing time and memory space problems which limit its practical use for online handwriting recognition. To face with this problem the DTW has been applied to the sum of the five sensor signals after an adequate down-sampling of the data. Preliminary results have shown that processing time and memory size could significantly be reduced without deterioration of performance in single character and word recognition. Further excellent accuracy in recognition was achieved which is mainly due to the reduced dynamic time warping RDTW technique and a novel pen device BiSP.

Keywords: Biometric character recognition, biometric person authentication, biometric smart pen BiSP, dynamic time warping DTW, online-handwriting recognition, multidimensional time series.

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Authors: Z. Pooranian, A. Harounabadi, M. Shojafar, N. Hedayat

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The purpose of Grid computing is to utilize computational power of idle resources which are distributed in different areas. Given the grid dynamism and its decentralize resources, there is a need for an efficient scheduler for scheduling applications. Since task scheduling includes in the NP-hard problems various researches have focused on invented algorithms especially the genetic ones. But since genetic is an inherent algorithm which searches the problem space globally and does not have the efficiency required for local searching, therefore, its combination with local searching algorithms can compensate for this shortcomings. The aim of this paper is to combine the genetic algorithm and GELS (GAGELS) as a method to solve scheduling problem by which simultaneously pay attention to two factors of time and number of missed tasks. Results show that the proposed algorithm can decrease makespan while minimizing the number of missed tasks compared with the traditional methods.

Keywords: Grid Computing, Genetic Algorithm, Gravitational Emulation Local Search (GELS), missed task

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Authors: Yu Ren Lin, Yu Hong Li

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Vision-based intelligent vehicle applications often require large amounts of memory to handle video streaming and image processing, which in turn increases complexity of hardware and software. This paper presents an FPGA implement of a vision-based blind spot warning system. Using video frames, the information of the blind spot area turns into one-dimensional information. Analysis of the estimated entropy of image allows the detection of an object in time. This idea has been implemented in the XtremeDSP video starter kit. The blind spot warning system uses only 13% of its logic resources and 95k bits block memory, and its frame rate is over 30 frames per sec (fps).

Keywords: blind-spot area, image, FPGA

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Authors: Ashraf Abuelhaija, Klaus Solbach

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In Ultra high-field MRI scanners (3T and higher), parallel RF transmission techniques using multiple RF chains with multiple transmit elements are a promising approach to overcome the high-field MRI challenges in terms of inhomogeneity in the RF magnetic field and SAR. However, mutual coupling between the transmit array elements disturbs the desirable independent control of the RF waveforms for each element. This contribution demonstrates a 18 dB improvement of decoupling (isolation) performance due to the very low output impedance of our 1 kW power amplifier.

Keywords: EM coupling, Inter-element isolation, Magnetic resonance imaging (MRI), Parallel Transmit.

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Authors: Khin Thida Latt, Mineo Kaneko, Yoichi Shinoda

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In Partitioned Optical Passive Stars POPS network,nodes and couplers become free after slot to slot in some computation.It is necessary to efficiently utilize free couplers and nodes to be cost effective. Improving parallelism, we present the fast data summation algorithm for multiple problem spaces on P OP S(g, g) with smaller number of nodes for the case of d =n = g. For the case of d >n > g, we simulate the calculation of large number of data items dedicated to larger system with many nodes on smaller system with smaller number of nodes. The algorithm is faster than the best know algorithm and using smaller number of nodes and groups make the system low cost and practical.

Keywords: Partitioned optical passive stars network, parallelcomputing, optical computing, data sum

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Authors: Azhar Hussain, Kashif Shahzad, Chunming Tang

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this paper gives a novel approach towards real-time speed estimation of multiple traffic vehicles using fuzzy logic and image processing techniques with proper arrangement of camera parameters. The described algorithm consists of several important steps. First, the background is estimated by computing median over time window of specific frames. Second, the foreground is extracted using fuzzy similarity approach (FSA) between estimated background pixels and the current frame pixels containing foreground and background. Third, the traffic lanes are divided into two parts for both direction vehicles for parallel processing. Finally, the speeds of vehicles are estimated by Maximum a Posterior Probability (MAP) estimator. True ground speed is determined by utilizing infrared sensors for three different vehicles and the results are compared to the proposed algorithm with an accuracy of ± 0.74 kmph.

Keywords: Defuzzification, Fuzzy similarity approach, lane cropping, Maximum a Posterior Probability (MAP) estimator, Speed estimation

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Authors: R. Santhosh, T. Ravichandran

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This paper evaluates the accrual based scheduling for cloud in single and multi-resource system. Numerous organizations benefit from Cloud computing by hosting their applications. The cloud model provides needed access to computing with potentially unlimited resources. Scheduling is tasks and resources mapping to a certain optimal goal principle. Scheduling, schedules tasks to virtual machines in accordance with adaptable time, in sequence under transaction logic constraints. A good scheduling algorithm improves CPU use, turnaround time, and throughput. In this paper, three realtime cloud services scheduling algorithm for single resources and multiple resources are investigated. Experimental results show Resource matching algorithm performance to be superior for both single and multi-resource scheduling when compared to benefit first scheduling, Migration, Checkpoint algorithms.

Keywords: Cloud computing, Scheduling, Migration, Checkpoint, Resource Matching.

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Authors: Shuen-Tai Wang, Hsi-Ya Chang

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Cloud virtualization technologies are becoming more and more prevalent, cloud users usually encounter the problem of how to access to the virtualized remote desktops easily over the web without requiring the installation of special clients. To resolve this issue, we took advantage of the HTML5 technology and developed web-based remote desktop. It permits users to access the terminal which running in our cloud platform from anywhere. We implemented a sketch of web interface following the cloud computing concept that seeks to enable collaboration and communication among users for high performance computing. Given the development of remote desktop virtualization, it allows to shift the user’s desktop from the traditional PC environment to the cloud platform, which is stored on a remote virtual machine rather than locally. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for online cloud service. This is also made possible by the low administrative costs as well as relatively inexpensive end-user terminals and reduced energy expenses.

Keywords: Virtualization, Remote Desktop, HTML5, Cloud Computing.

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Authors: Chih-Hao Chen, Hsing-Chung Lee, Qingdong Ling, Hsiao-Jung Chen, Sun-Chong Wang, Li-Ching Wu, H.C. Lee

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Segmentation, filtering out of measurement errors and identification of breakpoints are integral parts of any analysis of microarray data for the detection of copy number variation (CNV). Existing algorithms designed for these tasks have had some successes in the past, but they tend to be O(N2) in either computation time or memory requirement, or both, and the rapid advance of microarray resolution has practically rendered such algorithms useless. Here we propose an algorithm, SAD, that is much faster and much less thirsty for memory – O(N) in both computation time and memory requirement -- and offers higher accuracy. The two key ingredients of SAD are the fundamental assumption in statistics that measurement errors are normally distributed and the mathematical relation that the product of two Gaussians is another Gaussian (function). We have produced a computer program for analyzing CNV based on SAD. In addition to being fast and small it offers two important features: quantitative statistics for predictions and, with only two user-decided parameters, ease of use. Its speed shows little dependence on genomic profile. Running on an average modern computer, it completes CNV analyses for a 262 thousand-probe array in ~1 second and a 1.8 million-probe array in 9 seconds

Keywords: Cancer, pathogenesis, chromosomal aberration, copy number variation, segmentation analysis.

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Authors: Yu Ren Lin, Yi Feng Su

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Using vision based solution in intelligent vehicle application often needs large memory to handle video stream and image process which increase complexity of hardware and software. In this paper, we present a FPGA implement of a vision based lane departure warning system. By taking frame of videos, the line gradient of line is estimated and the lane marks are found. By analysis the position of lane mark, departure of vehicle will be detected in time. This idea has been implemented in Xilinx Spartan6 FPGA. The lane departure warning system used 39% logic resources and no memory of the device. The average availability is 92.5%. The frame rate is more than 30 frames per second (fps).

Keywords: Lane departure warning system, image, FPGA.

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Authors: Yousef Daneshvar Rouyandozagh, Ece. K. Açikgöz

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Conservation of historical urban patterns in the traditional neighborhoods is a part of creating integrated urban environments that are socially more sustainable. Urbanization reflects on life conditions and social, physical, economical characteristics of the society. In this regard, historical zones and traditional regions are affected by dramatic interventions on these characteristics. This article focuses on the Uch Dukkan neighborhood located in Ardabil City in Azarbaijani region of Iran, which has been up to such interventions that leaded its transformation from the past to the present. After introducing a brief inventory of the main elements of the historical zone and the neighborhood; this study explores the changes and transformations in different periods; and their impacts on the quality of the environment and its social sustainability. The survey conducted in the neighborhood as part of this research study revealed that the Uch Dukkan neighborhood and the unique architectural heritage that it possesses have become more inactive physically and functionally in a decade. This condition requires an exploration and comparison of the present and the expected transformations of the meaning of social space from the most private unit to the urban scale. From this token, it is argued that an architectural point of view that is based on space order; use and meaning of space as a social and cultural image, should not be ignored. Based on the interplay between social sustainability, collective memory, and the urban environment, study aims to make the invisible portion of ignorance clear, that ends up with a weakness in defining the collective meaning of the neighborhood as a historic urban district. It reveals that the spatial possessions of the neighborhood are valuable not only for their historical and physical characteristics, but also for their social memory that is to be remembered and constructed further.

Keywords: Urban integrity, social sustainability, collective memory, social decay.

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Authors: S. S. Mishra

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In this paper, an attempt is made to compute the total optimal cost of interdependent queuing system with controllable arrival rates as an important performance measure of the system. An example of application has also been presented to exhibit the use of the model. Finally, numerical demonstration based on a computing algorithm and variational effects of the model with the help of the graph have also been presented.

Keywords: Computing, Controllable arrival rate, Optimum performance measure.

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Authors: Xiang Li, Zhixian Chen, Zheng Fang, Aashit Kamath, Xinpeng Wang, Navab Singh, Guo-Qiang Lo, Dim-Lee Kwong

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We integrate TiN/Ni/HfO2/Si RRAM cell with a vertical gate-all-around (GAA) nanowire transistor to achieve compact 4F2 footprint in a 1T1R configuration. The tip of the Si nanowire (source of the transistor) serves as bottom electrode of the memory cell. Fabricated devices with nanowire diameter ~ 50nm demonstrate ultra-low current/power switching; unipolar switching with 10μA/30μW SET and 20μA/30μW RESET and bipolar switching with 20nA/85nW SET and 0.2nA/0.7nW RESET. Further, the switching current is found to scale with nanowire diameter making the architecture promising for future scaling.

Keywords: RRAM, 1T1R, gate-all-around FET, nanowire FET, vertical MOSFETs

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Authors: Tim Nedyalkov

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A business decision to move to the cloud brings fundamental changes in how an organization develops and delivers its Information Technology solutions. The accelerated pace of digital transformation across businesses and government agencies increases the reliance on cloud-based services. Collecting, managing, and retaining large amounts of data in cloud environments make information security and data privacy protection essential. It becomes even more important to understand what key factors drive successful cloud adoption following the commencement of the Privacy Amendment Notifiable Data Breaches (NDB) Act 2017 in Australia as the regulatory changes impact many organizations and industries. This quantitative correlational research investigated the governance, risk management, and compliance factors contributing to cloud security success. The factors influence the adoption of cloud computing within an organizational context after the commencement of the NDB scheme. The results and findings demonstrated that corporate information security policies, data storage location, management understanding of data governance responsibilities, and regular compliance assessments are the factors influencing cloud computing adoption. The research has implications for organizations, future researchers, practitioners, policymakers, and cloud computing providers to meet the rapidly changing regulatory and compliance requirements.

Keywords: Cloud compliance, cloud security, cloud security governance, data governance, privacy protection.

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Authors: Mubarak Saif Mohsen, Zurinahni Zainol, Rosalina Abdul Salam, Wahidah Husain

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One of the major problems in genomic field is to perform sequence comparison on DNA and protein sequences. Executing sequence comparison on the DNA and protein data is a computationally intensive task. Sequence comparison is the basic step for all algorithms in protein sequences similarity. Parallel computing is an attractive solution to provide the computational power needed to speedup the lengthy process of the sequence comparison. Our main research is to enhance the protein sequence algorithm using dynamic programming method. In our approach, we parallelize the dynamic programming algorithm using multithreaded program to perform the sequence comparison and also developed a distributed protein database among many PCs using Remote Method Interface (RMI). As a result, we showed how different sizes of protein sequences data and computation of scoring matrix of these protein sequence on different number of processors affected the processing time and speed, as oppose to sequential processing.

Keywords: Protein sequence algorithm, dynamic programming algorithm, multithread

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Authors: Moeiz Miraoui, Chakib Tadj, Chokri ben Amar

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Devices in a pervasive computing system (PCS) are characterized by their context-awareness. It permits them to provide proactively adapted services to the user and applications. To do so, context must be well understood and modeled in an appropriate form which enhance its sharing between devices and provide a high level of abstraction. The most interesting methods for modeling context are those based on ontology however the majority of the proposed methods fail in proposing a generic ontology for context which limit their usability and keep them specific to a particular domain. The adaptation task must be done automatically and without an explicit intervention of the user. Devices of a PCS must acquire some intelligence which permits them to sense the current context and trigger the appropriate service or provide a service in a better suitable form. In this paper we will propose a generic service ontology for context modeling and a context-aware service adaptation based on a service oriented definition of context.

Keywords: Pervasive computing system, context, contextawareness, service, context modeling, ontology, adaptation, machine learning.

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Authors: Sandeep Sharma, Sarabjit Singh, Meenakshi Sharma

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Load balancing is the process of improving the performance of a parallel and distributed system through a redistribution of load among the processors [1] [5]. In this paper we present the performance analysis of various load balancing algorithms based on different parameters, considering two typical load balancing approaches static and dynamic. The analysis indicates that static and dynamic both types of algorithm can have advancements as well as weaknesses over each other. Deciding type of algorithm to be implemented will be based on type of parallel applications to solve. The main purpose of this paper is to help in design of new algorithms in future by studying the behavior of various existing algorithms.

Keywords: Load balancing (LB), workload, distributed systems, Static Load balancing, Dynamic Load Balancing

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Authors: Joachim Kimmerle, Johannes Moskaliuk, Ulrike Cress

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The development of Internet technology in recent years has led to a more active role of users in creating Web content. This has significant effects both on individual learning and collaborative knowledge building. This paper will present an integrative framework model to describe and explain learning and knowledge building with shared digital artifacts on the basis of Luhmann-s systems theory and Piaget-s model of equilibration. In this model, knowledge progress is based on cognitive conflicts resulting from incongruities between an individual-s prior knowledge and the information which is contained in a digital artifact. Empirical support for the model will be provided by 1) applying it descriptively to texts from Wikipedia, 2) examining knowledge-building processes using a social network analysis, and 3) presenting a survey of a series of experimental laboratory studies.

Keywords: Individual learning, collaborative knowledge building, systems theory, equilibration.

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Authors: Yasser F. Hassan, Marwa Abdeen, Mustafa Fahmy

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In recent years multi-agent systems have emerged as one of the interesting architectures facilitating distributed collaboration and distributed problem solving. Each node (agent) of the network might pursue its own agenda, exploit its environment, develop its own problem solving strategy and establish required communication strategies. Within each node of the network, one could encounter a diversity of problem-solving approaches. Quite commonly the agents can realize their processing at the level of information granules that is the most suitable from their local points of view. Information granules can come at various levels of granularity. Each agent could exploit a certain formalism of information granulation engaging a machinery of fuzzy sets, interval analysis, rough sets, just to name a few dominant technologies of granular computing. Having this in mind, arises a fundamental issue of forming effective interaction linkages between the agents so that they fully broadcast their findings and benefit from interacting with others.

Keywords: Granular computing, rough sets, agents, traffic system.

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Authors: Aqeel S. Jaber, Abu Zaharin Ahmad, Ahmed N. Abdalla

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The artificial intelligent controller in power system plays as most important rule for many applications such as system operation and its control specially Load Frequency Controller (LFC). The main objective of LFC is to keep the frequency and tie-line power close to their decidable bounds in case of disturbance. In this paper, parallel fuzzy PI adaptive with conventional PD technique for Load Frequency Control system was proposed. PSO optimization method used to optimize both of scale fuzzy PI and tuning of PD. Two equal interconnected power system areas were used as a test system. Simulation results show the effectiveness of the proposed controller compared with different PID and classical fuzzy PI controllers in terms of speed response and damping frequency.

Keywords: Load frequency control, PSO, fuzzy control.

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Authors: K. Varesi, A. Radan

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In this paper, a new Genetic Algorithm (GA) based methodology is proposed to optimize the Degree of Hybridization (DOH) in a passenger parallel hybrid car. At first step, target parameters for the vehicle are decided and then using ADvanced VehIcle SimulatOR (ADVISOR) software, the variation pattern of these target parameters, across the different DOHs, is extracted. At the next step, a suitable cost function is defined and is optimized using GA. In this paper, also a new technique has been proposed for deciding the number of battery modules for each DOH, which leads to a great improvement in the vehicle performance. The proposed methodology is so simple, fast and at the same time, so efficient.

Keywords: Degree of Hybridization (DOH), Electric Motor, Emissions, Fuel Economy, Genetic Algorithm (GA), Hybrid ElectricVehicle (HEV), Vehicle Performance

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Authors: Hossein Sahoolizadeh, Mahdi Rahimi, Hamid Dehghani

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We introduce an algorithm based on the morphological shared-weight neural network. Being nonlinear and translation-invariant, the MSNN can be used to create better generalization during face recognition. Feature extraction is performed on grayscale images using hit-miss transforms that are independent of gray-level shifts. The output is then learned by interacting with the classification process. The feature extraction and classification networks are trained together, allowing the MSNN to simultaneously learn feature extraction and classification for a face. For evaluation, we test for robustness under variations in gray levels and noise while varying the network-s configuration to optimize recognition efficiency and processing time. Results show that the MSNN performs better for grayscale image pattern classification than ordinary neural networks.

Keywords: Face recognition, Neural Networks, Multi-layer Perceptron, masking.

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Authors: Lotfi Admane

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This paper presents a model of case based corporate memory named ReCaRo (REsource, CAse, ROle). The approach suggested in ReCaRo decomposes the domain to model through a set of components. These components represent the objects developed by the company during its activity. They are reused, and sometimes, while bringing adaptations. These components are enriched by knowledge after each reuse. ReCaRo builds the corporate memory on the basis of these components. It models two types of knowledge: 1) Business Knowledge, which constitutes the main knowledge capital of the company, refers to its basic skill, thus, directly to the components and 2) the Experience Knowledge which is a specialised knowledge and represents the experience gained during the handling of business knowledge. ReCaRo builds corporate memories which are made up of five communicating ones.

Keywords: Corporate memories, meta-model, reuse, ReCaRo.

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Authors: César Camisón-Zornoza, Beatriz Forés-Julián, Alba Puig-Denia

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The literature has argued that firms based in industrial districts enjoy advantages for creating internal knowledge and absorbing external knowledge as a consequence of to the knowledge flows and spillovers that exist in the district. However, empirical evidence to show how belonging to an industrial district affects the business processes of creation and absorption of knowledge is scarce and, moreover, empirical research has not taken into account the influence of variations in the flows of knowledge circulating in each cluster. This study aims to extend empirical evidence on the effect that the stock of shared competencies in industrial districts has on the business processes of creation and absorption of knowledge, through data from an initial study on 952 firms and 35 industrial districts in Spain.

Keywords: Absorptive capacity, industrial district, knowledge creation, organisational learning

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