Search results for: Parallel networks of agents.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2679

Search results for: Parallel networks of agents.

2529 Multi-Agent Searching Adaptation Using Levy Flight and Inferential Reasoning

Authors: Sagir M. Yusuf, Chris Baber

Abstract:

In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Lèvy flight, situation awareness, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence.

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2528 SIP-Based QoS Management Architecture for IP Multimedia Subsystems over IP Access Networks

Authors: Umber Iqbal, Shaleeza Sohail, Muhammad Younas Javed

Abstract:

True integration of multimedia services over wired or wireless networks increase the productivity and effectiveness in today-s networks. IP Multimedia Subsystems are Next Generation Network architecture to provide the multimedia services over fixed or mobile networks. This paper proposes an extended SIP-based QoS Management architecture for IMS services over underlying IP access networks. To guarantee the end-to-end QoS for IMS services in interconnection backbone, SIP based proxy Modules are introduced to support the QoS provisioning and to reduce the handoff disruption time over IP access networks. In our approach these SIP Modules implement the combination of Diffserv and MPLS QoS mechanisms to assure the guaranteed QoS for real-time multimedia services. To guarantee QoS over access networks, SIP Modules make QoS resource reservations in advance to provide best QoS to IMS users over heterogeneous networks. To obtain more reliable multimedia services, our approach allows the use of SCTP protocol over SIP instead of UDP due to its multi-streaming feature. This architecture enables QoS provisioning for IMS roaming users to differentiate IMS network from other common IP networks for transmission of realtime multimedia services. To validate our approach simulation models are developed on short scale basis. The results show that our approach yields comparable performance for efficient delivery of IMS services over heterogeneous IP access networks.

Keywords: SIP-Based QoS Management Architecture, IPMultimedia Subsystems, IP Access Networks

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2527 Cluster-Based Multi-Path Routing Algorithm in Wireless Sensor Networks

Authors: Si-Gwan Kim

Abstract:

Small-size and low-power sensors with sensing, signal processing and wireless communication capabilities is suitable for the wireless sensor networks. Due to the limited resources and battery constraints, complex routing algorithms used for the ad-hoc networks cannot be employed in sensor networks. In this paper, we propose node-disjoint multi-path hexagon-based routing algorithms in wireless sensor networks. We suggest the details of the algorithm and compare it with other works. Simulation results show that the proposed scheme achieves better performance in terms of efficiency and message delivery ratio.

Keywords: Clustering, multi-path, routing protocol, sensor network.

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2526 XML based Safe and Scalable Multi-Agent Development Framework

Authors: Rinkaj Goyal, Pravin Chandra, Yogesh Singh

Abstract:

In this paper we describe our efforts to design and implement an agent development framework that has the potential to scale to the size of any underlying network suitable for various ECommerce activities. The main novelty in our framework is it-s capability to allow the development of sophisticated, secured agents which are simple enough to be practical. We have adopted FIPA agent platform reference Model as backbone for implementation along with XML for agent Communication and Java Cryptographic Extension and architecture to realize the security of communication information between agents. The advantage of our architecture is its support of agents development in different languages and Communicating with each other using a more open standard i.e. XML

Keywords: Agent, Agent Development Framework, Agent Coordination, Security

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2525 Parallel Vector Processing Using Multi Level Orbital DATA

Authors: Nagi Mekhiel

Abstract:

Many applications use vector operations by applying single instruction to multiple data that map to different locations in conventional memory. Transferring data from memory is limited by access latency and bandwidth affecting the performance gain of vector processing. We present a memory system that makes all of its content available to processors in time so that processors need not to access the memory, we force each location to be available to all processors at a specific time. The data move in different orbits to become available to other processors in higher orbits at different time. We use this memory to apply parallel vector operations to data streams at first orbit level. Data processed in the first level move to upper orbit one data element at a time, allowing a processor in that orbit to apply another vector operation to deal with serial code limitations inherited in all parallel applications and interleaved it with lower level vector operations.

Keywords: Memory organization, parallel processors, serial code, vector processing.

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2524 A Performance Evaluation of Cellular Network Suitability for VANET

Authors: Ho-Yeon Kim, Dong-Min Kang, Jun-Ho Lee, Tai-Myoung Chung

Abstract:

Recently, a vehicular ad-hoc networks(VANETs) for Intelligent Transport System(ITS) have become able safety and convenience services surpassing the simple services such as an electronic toll collection system. To provide the proper services, VANET needs infrastructure over the country infrastructure. Thus, we have to spend a huge sum of human resources. In this reason, several studies have been made on the usage of cellular networks instead of new protocols this study is to assess a performance evaluation of the cellular network for VANET. In this paper, the result of a for the suitability of cellular networks for VANET experiment, The LTE(Long Term Evolution) of cellular networks found to be most suitable among the others cellular networks

Keywords: Vehicle communication, VANET, Cellular network

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2523 A Survey on Performance Tools for OpenMP

Authors: Mubarak S. Mohsen, Rosni Abdullah, Yong M. Teo

Abstract:

Advances in processors architecture, such as multicore, increase the size of complexity of parallel computer systems. With multi-core architecture there are different parallel languages that can be used to run parallel programs. One of these languages is OpenMP which embedded in C/Cµ or FORTRAN. Because of this new architecture and the complexity, it is very important to evaluate the performance of OpenMP constructs, kernels, and application program on multi-core systems. Performance is the activity of collecting the information about the execution characteristics of a program. Performance tools consists of at least three interfacing software layers, including instrumentation, measurement, and analysis. The instrumentation layer defines the measured performance events. The measurement layer determines what performance event is actually captured and how it is measured by the tool. The analysis layer processes the performance data and summarizes it into a form that can be displayed in performance tools. In this paper, a number of OpenMP performance tools are surveyed, explaining how each is used to collect, analyse, and display data collection.

Keywords: Parallel performance tools, OpenMP, multi-core.

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2522 Analysis of Periodic Solution of Delay Fuzzy BAM Neural Networks

Authors: Qianhong Zhang, Lihui Yang, Daixi Liao

Abstract:

In this paper, by employing a new Lyapunov functional and an elementary inequality analysis technique, some sufficient conditions are derived to ensure the existence and uniqueness of periodic oscillatory solution for fuzzy bi-directional memory (BAM) neural networks with time-varying delays, and all other solutions of the fuzzy BAM neural networks converge the uniqueness periodic solution. These criteria are presented in terms of system parameters and have important leading significance in the design and applications of neural networks. Moreover an example is given to illustrate the effectiveness and feasible of results obtained.

Keywords: Fuzzy BAM neural networks, Periodic solution, Global exponential stability, Time-varying delays

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2521 Isotropic Stress Distribution in Cu/(001) Fe Two Sheets

Authors: A. Derardja, L. Baroura, M. Brioua

Abstract:

The nanotechnology based on epitaxial systems includes single or arranged misfit dislocations. In general, whatever is the type of dislocation or the geometry of the array formed by the dislocations; it is important for experimental studies to know exactly the stress distribution for which there is no analytical expression [1, 2]. This work, using a numerical analysis, deals with relaxation of epitaxial layers having at their interface a periodic network of edge misfit dislocations. The stress distribution is estimated by using isotropic elasticity. The results show that the thickness of the two sheets is a crucial parameter in the stress distributions and then in the profile of the two sheets. A comparative study between the case of single dislocation and the case of parallel network shows that the layers relaxed better when the interface is covered by a parallel arrangement of misfit. Consequently, a single dislocation at the interface produces an important stress field which can be reduced by inserting a parallel network of dislocations with suitable periodicity.

Keywords: Parallel array of misfit, interface, isotropic elasticity, single crystalline substrates, coherent interface

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2520 A Modified Cross Correlation in the Frequency Domain for Fast Pattern Detection Using Neural Networks

Authors: Hazem M. El-Bakry, Qiangfu Zhao

Abstract:

Recently, neural networks have shown good results for detection of a certain pattern in a given image. In our previous papers [1-5], a fast algorithm for pattern detection using neural networks was presented. Such algorithm was designed based on cross correlation in the frequency domain between the input image and the weights of neural networks. Image conversion into symmetric shape was established so that fast neural networks can give the same results as conventional neural networks. Another configuration of symmetry was suggested in [3,4] to improve the speed up ratio. In this paper, our previous algorithm for fast neural networks is developed. The frequency domain cross correlation is modified in order to compensate for the symmetric condition which is required by the input image. Two new ideas are introduced to modify the cross correlation algorithm. Both methods accelerate the speed of the fast neural networks as there is no need for converting the input image into symmetric one as previous. Theoretical and practical results show that both approaches provide faster speed up ratio than the previous algorithm.

Keywords: Fast Pattern Detection, Neural Networks, Modified Cross Correlation

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2519 RF Link Budget Analysis at 915 MHz band for Wireless Sensor Networks

Authors: Abdellah Chehri, Hussein Mouftah, Paul Fortier, Hasnaa Aniss

Abstract:

Wireless sensor network has recently emerged as enablers of several areas. Real applications of WSN are being explored and some of them are yet to come. While the potential of sensor networks has been only beginning to be realized, several challenges still remain. One of them is the experimental evaluation of WSN. Therefore, deploying and operating a testbed to study the real behavior of WSN become more and more important. The main contribution of this work is to analysis the RF link budget behavior of wireless sensor networks in underground mine gallery.

Keywords: Sensor networks, RF Link, path loss.

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2518 Use of Social Networks and Mobile Technologies in Education

Authors: Václav Maněna, Roman Dostál, Štěpán Hubálovský

Abstract:

Social networks play an important role in the lives of children and young people. Along with the high penetration of mobile technologies such as smartphones and tablets among the younger generation, there is an increasing use of social networks already in elementary school. The paper presents the results of research, which was realized at schools in the Hradec Králové region. In this research, the authors focused on issues related to communications on social networks for children, teenagers and young people in the Czech Republic. This research was conducted at selected elementary, secondary and high schools using anonymous questionnaires. The results are evaluated and compared with the results of the research, which has been realized in 2008. The authors focused on the possibilities of using social networks in education. The paper presents the possibility of using the most popular social networks in education, with emphasis on increasing motivation for learning. The paper presents comparative analysis of social networks, with regard to the possibility of using in education as well.

Keywords: Social networks, motivation, e-learning, mobile technology.

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2517 A Knowledge Acquisition Model Using Multi-Agents for KaaS

Authors: Dhanashree Nansaheb Kharde, Justus Selwyn

Abstract:

These days customer satisfaction plays vital role in any business. When customer searches for a product, significantly a junk of irrelevant information is what is given, leading to customer dissatisfaction. To provide exactly relevant information on the searched product, we are proposing a model of KaaS (Knowledge as a Service), which pre-processes the information using decision making paradigm using Multi-agents. Information obtained from various sources is taken to derive knowledge and they are linked to Cloud to capture new idea. The main focus of this work is to acquire relevant information (knowledge) related to product, then convert this knowledge into a service for customer satisfaction and deploy on cloud. For achieving these objectives we are have opted to use multi agents. They are communicating and interacting with each other, manipulate information, provide knowledge, to take decisions. The paper discusses about KaaS as an intelligent approach for Knowledge acquisition.

Keywords: Knowledge acquisition, multi-agents, intelligent user interface, ontology, intelligent agent.

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2516 On Fault Diagnosis of Asynchronous Sequential Machines with Parallel Composition

Authors: Jung-Min Yang

Abstract:

Fault diagnosis of composite asynchronous sequential machines with parallel composition is addressed in this paper. An adversarial input can infiltrate one of two submachines comprising the composite asynchronous machine, causing an unauthorized state transition. The objective is to characterize the condition under which the controller can diagnose any fault occurrence. Two control configurations, state feedback and output feedback, are considered in this paper. In the case of output feedback, the exact estimation of the state is impossible since the current state is inaccessible and the output feedback is given as the form of burst. A simple example is provided to demonstrate the proposed methodology.

Keywords: Asynchronous sequential machines, parallel composition, fault diagnosis.

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2515 Conditions for Fault Recovery of Interconnected Asynchronous Sequential Machines with State Feedback

Authors: Jung–Min Yang

Abstract:

In this paper, fault recovery for parallel interconnected asynchronous sequential machines is studied. An adversarial input can infiltrate into one of two submachines comprising parallel composition of the considered asynchronous sequential machine, causing an unauthorized state transition. The control objective is to elucidate the condition for the existence of a corrective controller that makes the closed-loop system immune against any occurrence of adversarial inputs. In particular, an efficient existence condition is presented that does not need the complete modeling of the interconnected asynchronous sequential machine.

Keywords: Asynchronous sequential machines, parallel composition, corrective control, fault tolerance.

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2514 Use of Cell Phone by Farmers and its Implication on Farmers- Production Capacity in Oyo State Nigeria

Authors: Bolarinwa, K. K., Oyeyinka, R. A.

Abstract:

Relevant agricultural information disseminator (extension agent) ratio of 1:3500 farm families which become a menace to agricultural production capacity in developing countries necessitate this study. Out of 4 zones in the state, 24 extension agents in each zone, 4 extension agents using cell phones and 120 farmers using cell phone and 120 other farmers not using cell phone were purposively selected to give 240 farmers that participated in the research. Data were collected using interview guide and analysized using frequency, percentage and t-test.. Frequency of contact with agricultural information centers revealed that cell phone user farmers had greater means score of X 41.43 contact as against the low mean X19.32 contact recorded by farmers receiving agricultural information from extension agents not using cell phone and their production was statistically significant at P < 0.05. Usage of cell phone increase extension agent contact and increase farmers- production capacity.

Keywords: Cell phone, contact, extension agents and production.

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2513 Application of Wavelet Neural Networks in Optimization of Skeletal Buildings under Frequency Constraints

Authors: Mohammad Reza Ghasemi, Amin Ghorbani

Abstract:

The main goal of the present work is to decrease the computational burden for optimum design of steel frames with frequency constraints using a new type of neural networks called Wavelet Neural Network. It is contested to train a suitable neural network for frequency approximation work as the analysis program. The combination of wavelet theory and Neural Networks (NN) has lead to the development of wavelet neural networks. Wavelet neural networks are feed-forward networks using wavelet as activation function. Wavelets are mathematical functions within suitable inner parameters, which help them to approximate arbitrary functions. WNN was used to predict the frequency of the structures. In WNN a RAtional function with Second order Poles (RASP) wavelet was used as a transfer function. It is shown that the convergence speed was faster than other neural networks. Also comparisons of WNN with the embedded Artificial Neural Network (ANN) and with approximate techniques and also with analytical solutions are available in the literature.

Keywords: Weight Minimization, Frequency Constraints, Steel Frames, ANN, WNN, RASP Function.

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2512 Hybrid Prefix Adder Architecture for Minimizing the Power Delay Product

Authors: P.Ramanathan, P.T.Vanathi

Abstract:

Parallel Prefix addition is a technique for improving the speed of binary addition. Due to continuing integrating intensity and the growing needs of portable devices, low-power and highperformance designs are of prime importance. The classical parallel prefix adder structures presented in the literature over the years optimize for logic depth, area, fan-out and interconnect count of logic circuits. In this paper, a new architecture for performing 8-bit, 16-bit and 32-bit Parallel Prefix addition is proposed. The proposed prefix adder structures is compared with several classical adders of same bit width in terms of power, delay and number of computational nodes. The results reveal that the proposed structures have the least power delay product when compared with its peer existing Prefix adder structures. Tanner EDA tool was used for simulating the adder designs in the TSMC 180 nm and TSMC 130 nm technologies.

Keywords: Parallel Prefix Adder (PPA), Dot operator, Semi-Dotoperator, Complementary Metal Oxide Semiconductor (CMOS), Odd-dot operator, Even-dot operator, Odd-semi-dot operator andEven-semi-dot operator.

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2511 Some Computational Results on MPI Parallel Implementation of Dense Simplex Method

Authors: El-Said Badr, Mahmoud Moussa, Konstantinos Paparrizos, Nikolaos Samaras, Angelo Sifaleras

Abstract:

There are two major variants of the Simplex Algorithm: the revised method and the standard, or tableau method. Today, all serious implementations are based on the revised method because it is more efficient for sparse linear programming problems. Moreover, there are a number of applications that lead to dense linear problems so our aim in this paper is to present some computational results on parallel implementation of dense Simplex Method. Our implementation is implemented on a SMP cluster using C programming language and the Message Passing Interface MPI. Preliminary computational results on randomly generated dense linear programs support our results.

Keywords: Linear Programming, MPI, Parallel Implementation, Simplex Algorithm.

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2510 Synchronization of Semiconductor Laser Networks

Authors: R. M. López-Gutiérrez, L. Cardoza-Avendaño, H. Cervantes-De Ávila, J. A. Michel-Macarty, C. Cruz-Hernández, A. Arellano-Delgado, R. Carmona-Rodríguez

Abstract:

In this paper, synchronization of multiple chaotic semiconductor lasers is achieved by appealing to complex system theory. In particular, we consider dynamical networks composed by semiconductor laser, as interconnected nodes, where the interaction in the networks are defined by coupling the first state of each node. An interest case is synchronized with master-slave configuration in star topology. Nodes of these networks are modeled for the laser and simulate by Matlab. These results are applicable to private communication.

Keywords: Synchronization, chaotic laser, network.

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2509 An Approach for the Integration of the Existing Wireless Networks

Authors: Rajkumar Samanta, Abhishek Pal

Abstract:

The demand of high quality services has fueled dimensional research and development in wireless communications and networking. As a result, different wireless technologies like Wireless LAN, CDMA, GSM, UMTS, MANET, Bluetooth and satellite networks etc. have emerged in the last two decades. Future networks capable of carrying multimedia traffic need IP convergence, portability, seamless roaming and scalability among the existing networking technologies without changing the core part of the existing communications networks. To fulfill these goals, the present networking systems are required to work in cooperation to ensure technological independence, seamless roaming, high security and authentication, guaranteed Quality of Services (QoS). In this paper, a conceptual framework for a cooperative network (CN) is proposed for integration of heterogeneous existing networks to meet out the requirements of the next generation wireless networks.

Keywords: Cooperative Network, Wireless Network, Integration.

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2508 Wireless Sensor Networks for Long Distance Pipeline Monitoring

Authors: Augustine C. Azubogu, Victor E. Idigo, Schola U. Nnebe, Obinna S. Oguejiofor, Simon E.

Abstract:

The main goal of this seminal paper is to introduce the application of Wireless Sensor Networks (WSN) in long distance infrastructure monitoring (in particular in pipeline infrastructure monitoring) – one of the on-going research projects by the Wireless Communication Research Group at the department of Electronic and Computer Engineering, Nnamdi Azikiwe University, Awka. The current sensor network architectures for monitoring long distance pipeline infrastructures are previewed. These are wired sensor networks, RF wireless sensor networks, integrated wired and wireless sensor networks. The reliability of these architectures is discussed. Three reliability factors are used to compare the architectures in terms of network connectivity, continuity of power supply for the network, and the maintainability of the network. The constraints and challenges of wireless sensor networks for monitoring and protecting long distance pipeline infrastructure are discussed.

Keywords: Connectivity, maintainability, reliability, wireless sensor networks.

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2507 Locating Center Points for Radial Basis Function Networks Using Instance Reduction Techniques

Authors: Rana Yousef, Khalil el Hindi

Abstract:

The behavior of Radial Basis Function (RBF) Networks greatly depends on how the center points of the basis functions are selected. In this work we investigate the use of instance reduction techniques, originally developed to reduce the storage requirements of instance based learners, for this purpose. Five Instance-Based Reduction Techniques were used to determine the set of center points, and RBF networks were trained using these sets of centers. The performance of the RBF networks is studied in terms of classification accuracy and training time. The results obtained were compared with two Radial Basis Function Networks: RBF networks that use all instances of the training set as center points (RBF-ALL) and Probabilistic Neural Networks (PNN). The former achieves high classification accuracies and the latter requires smaller training time. Results showed that RBF networks trained using sets of centers located by noise-filtering techniques (ALLKNN and ENN) rather than pure reduction techniques produce the best results in terms of classification accuracy. The results show that these networks require smaller training time than that of RBF-ALL and higher classification accuracy than that of PNN. Thus, using ALLKNN and ENN to select center points gives better combination of classification accuracy and training time. Our experiments also show that using the reduced sets to train the networks is beneficial especially in the presence of noise in the original training sets.

Keywords: Radial basis function networks, Instance-based reduction, PNN.

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2506 A Fitted Random Sampling Scheme for Load Distribution in Grid Networks

Authors: O. A. Rahmeh, P. Johnson, S. Lehmann

Abstract:

Grid networks provide the ability to perform higher throughput computing by taking advantage of many networked computer-s resources to solve large-scale computation problems. As the popularity of the Grid networks has increased, there is a need to efficiently distribute the load among the resources accessible on the network. In this paper, we present a stochastic network system that gives a distributed load-balancing scheme by generating almost regular networks. This network system is self-organized and depends only on local information for load distribution and resource discovery. The in-degree of each node is refers to its free resources, and job assignment and resource discovery processes required for load balancing is accomplished by using fitted random sampling. Simulation results show that the generated network system provides an effective, scalable, and reliable load-balancing scheme for the distributed resources accessible on Grid networks.

Keywords: Complex networks, grid networks, load-balancing, random sampling.

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2505 A Proposed Trust Model for the Semantic Web

Authors: Hoda Waguih

Abstract:

A serious problem on the WWW is finding reliable information. Not everything found on the Web is true and the Semantic Web does not change that in any way. The problem will be even more crucial for the Semantic Web, where agents will be integrating and using information from multiple sources. Thus, if an incorrect premise is used due to a single faulty source, then any conclusions drawn may be in error. Thus, statements published on the Semantic Web have to be seen as claims rather than as facts, and there should be a way to decide which among many possibly inconsistent sources is most reliable. In this work, we propose a trust model for the Semantic Web. The proposed model is inspired by the use trust in human society. Trust is a type of social knowledge and encodes evaluations about which agents can be taken as reliable sources of information or services. Our proposed model allows agents to decide which among different sources of information to trust and thus act rationally on the semantic web.

Keywords: Semantic Web, Trust, Web of Trust, WWW.

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2504 Using the PGAS Programming Paradigm for Biological Sequence Alignment on a Chip Multi-Threading Architecture

Authors: M. Bakhouya, S. A. Bahra, T. El-Ghazawi

Abstract:

The Partitioned Global Address Space (PGAS) programming paradigm offers ease-of-use in expressing parallelism through a global shared address space while emphasizing performance by providing locality awareness through the partitioning of this address space. Therefore, the interest in PGAS programming languages is growing and many new languages have emerged and are becoming ubiquitously available on nearly all modern parallel architectures. Recently, new parallel machines with multiple cores are designed for targeting high performance applications. Most of the efforts have gone into benchmarking but there are a few examples of real high performance applications running on multicore machines. In this paper, we present and evaluate a parallelization technique for implementing a local DNA sequence alignment algorithm using a PGAS based language, UPC (Unified Parallel C) on a chip multithreading architecture, the UltraSPARC T1.

Keywords: Partitioned Global Address Space, Unified Parallel C, Multicore machines, Multi-threading Architecture, Sequence alignment.

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2503 Parallel Particle Swarm Optimization Optimized LDI Controller with Lyapunov Stability Criterion for Nonlinear Structural Systems

Authors: P.-W. Tsai, W.-L. Hong, C.-W. Chen, C.-Y. Chen

Abstract:

In this paper, we present a neural-network (NN) based approach to represent a nonlinear Tagagi-Sugeno (T-S) system. A linear differential inclusion (LDI) state-space representation is utilized to deal with the NN models. Taking advantage of the LDI representation, the stability conditions and controller design are derived for a class of nonlinear structural systems. Moreover, the concept of utilizing the Parallel Particle Swarm Optimization (PPSO) algorithm to solve the common P matrix under the stability criteria is given in this paper.

Keywords: Lyapunov Stability, Parallel Particle Swarm Optimization, Linear Differential Inclusion, Artificial Intelligence.

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2502 A Modular On-line Profit Sharing Approach in Multiagent Domains

Authors: Pucheng Zhou, Bingrong Hong

Abstract:

How to coordinate the behaviors of the agents through learning is a challenging problem within multi-agent domains. Because of its complexity, recent work has focused on how coordinated strategies can be learned. Here we are interested in using reinforcement learning techniques to learn the coordinated actions of a group of agents, without requiring explicit communication among them. However, traditional reinforcement learning methods are based on the assumption that the environment can be modeled as Markov Decision Process, which usually cannot be satisfied when multiple agents coexist in the same environment. Moreover, to effectively coordinate each agent-s behavior so as to achieve the goal, it-s necessary to augment the state of each agent with the information about other existing agents. Whereas, as the number of agents in a multiagent environment increases, the state space of each agent grows exponentially, which will cause the combinational explosion problem. Profit sharing is one of the reinforcement learning methods that allow agents to learn effective behaviors from their experiences even within non-Markovian environments. In this paper, to remedy the drawback of the original profit sharing approach that needs much memory to store each state-action pair during the learning process, we firstly address a kind of on-line rational profit sharing algorithm. Then, we integrate the advantages of modular learning architecture with on-line rational profit sharing algorithm, and propose a new modular reinforcement learning model. The effectiveness of the technique is demonstrated using the pursuit problem.

Keywords: Multi-agent learning; reinforcement learning; rationalprofit sharing; modular architecture.

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2501 Green-Reduction of Covalently Functionalized Graphene Oxide with Varying Stoichiometry

Authors: A. Pruna, D. Pullini, D. Busquets

Abstract:

Graphene-based materials were prepared by chemical reduction of covalently functionalized graphene oxide with environmentally friendly agents. Two varying stoichiometry of graphene oxide (GO) induced by using different chemical preparation conditions, further covalent functionalization of the GO materials with 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride / N-hydroxysuccinimide and ascorbic acid and sodium bisulfite as reducing agents were exploited in order to obtain controllable properties of the final solution-based graphene materials. The obtained materials were characterized by thermo-gravimetric analysis, Fourier transform infrared and Raman spectroscopy and X-ray diffraction. The results showed successful functionalization of the GO materials, while a comparison of the deoxygenation efficiency of the two-type functionalized graphene oxide suspensions by the different reducing agents has been made, revealing the strong dependence of their properties on the GO structure and reducing agents.

Keywords: Graphene oxide, covalent functionalization, reduction, ascorbic acid, sodium bisulfate.

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2500 Simulation Modeling of Manufacturing Systems for the Serial Route and the Parallel One

Authors: Tadeusz Witkowski, Paweł Antczak, Arkadiusz Antczak

Abstract:

In the paper we discuss the influence of the route flexibility degree, the open rate of operations and the production type coefficient on makespan. The flexible job-open shop scheduling problem FJOSP (an extension of the classical job shop scheduling) is analyzed. For the analysis of the production process we used a hybrid heuristic of the GRASP (greedy randomized adaptive search procedure) with simulated annealing algorithm. Experiments with different levels of factors have been considered and compared. The GRASP+SA algorithm has been tested and illustrated with results for the serial route and the parallel one.

Keywords: Makespan, open shop, route flexibility, serial and parallel route, simulation modeling, type of production.

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