Search results for: Infrastructure and Computer Network

Authors: B. Q. Huang, Tarik Rashid, M-T. Kechadi

Abstract:

this paper presents a multi-context recurrent network for time series analysis. While simple recurrent network (SRN) are very popular among recurrent neural networks, they still have some shortcomings in terms of learning speed and accuracy that need to be addressed. To solve these problems, we proposed a multi-context recurrent network (MCRN) with three different learning algorithms. The performance of this network is evaluated on some real-world application such as handwriting recognition and energy load forecasting. We study the performance of this network and we compared it to a very well established SRN. The experimental results showed that MCRN is very efficient and very well suited to time series analysis and its applications.

Keywords: Gradient descent method, recurrent neural network, learning algorithms, time series, BP

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Authors: Elsayed A. Habib Elamir

Abstract:

In social network analysis the mean nodal degree and density of the graph can be considered as a measure of the activity of all actors in the network and this is an important property of a graph and for making comparisons among networks. Since subjects in a family or organization are subject to common environment factors, it is prime interest to study the association between responses. Therefore, we study the distribution of the mean nodal degree and density of the graph under correlated binary units. The cross product ratio is used to capture the intra-units association among subjects. Computer program and an application are given to show the benefits of the method.

Keywords: Correlated Binary data, cross product ratio, densityof the graph, multiplicative binomial distribution.

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Authors: Nassib Abdallah, Pierre Chauvet, Abd El Salam Hajjar, Bassam Daya

Abstract:

In this paper, we propose an optimized brain computer interface (BCI) system for unspoken speech recognition, based on the fact that the constructions of unspoken words rely strongly on the Wernicke area, situated in the temporal lobe. Our BCI system has four modules: (i) the EEG Acquisition module based on a non-invasive headset with 14 electrodes; (ii) the Preprocessing module to remove noise and artifacts, using the Common Average Reference method; (iii) the Features Extraction module, using Wavelet Packet Transform (WPT); (iv) the Classification module based on a one-hidden layer artificial neural network. The present study consists of comparing the recognition accuracy of 5 Arabic words, when using all the headset electrodes or only the 4 electrodes situated near the Wernicke area, as well as the selection effect of the subbands produced by the WPT module. After applying the articial neural network on the produced database, we obtain, on the test dataset, an accuracy of 83.4% with all the electrodes and all the subbands of 8 levels of the WPT decomposition. However, by using only the 4 electrodes near Wernicke Area and the 6 middle subbands of the WPT, we obtain a high reduction of the dataset size, equal to approximately 19% of the total dataset, with 67.5% of accuracy rate. This reduction appears particularly important to improve the design of a low cost and simple to use BCI, trained for several words.

Keywords: Brain-computer interface, speech recognition, electroencephalography EEG, Wernicke area, artificial neural network.

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Authors: V. Venkatachalam, S. Selvan

Abstract:

The security of computer networks plays a strategic role in modern computer systems. Intrusion Detection Systems (IDS) act as the 'second line of defense' placed inside a protected network, looking for known or potential threats in network traffic and/or audit data recorded by hosts. We developed an Intrusion Detection System using LAMSTAR neural network to learn patterns of normal and intrusive activities, to classify observed system activities and compared the performance of LAMSTAR IDS with other classification techniques using 5 classes of KDDCup99 data. LAMSAR IDS gives better performance at the cost of high Computational complexity, Training time and Testing time, when compared to other classification techniques (Binary Tree classifier, RBF classifier, Gaussian Mixture classifier). we further reduced the Computational Complexity of LAMSTAR IDS by reducing the dimension of the data using principal component analysis which in turn reduces the training and testing time with almost the same performance.

Keywords: Binary Tree Classifier, Gaussian Mixture, IntrusionDetection System, LAMSTAR, Radial Basis Function.

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Authors: M. Moistsrapishvili, I. Ugrekhelidze, T. Baramashvili, D. Malaghuradze

Abstract:

At the end of the 20th century it was actual the development of transport corridors and the improvement of their technical parameters. With this purpose, many countries and Georgia among them manufacture to construct new highways, railways and also reconstruction-modernization of the existing transport infrastructure. It is necessary to explore the artificial structures (bridges and tunnels) on the existing tracks as they are very old. Conference report includes the peculiarities of reconstruction of tunnels, because we think that this theme is important for the modernization of the existing road infrastructure. We must remark that the methods of determining mining pressure of tunnel reconstructions are worked out according to the jobs of new tunnels but it is necessary to foresee additional mining pressure which will be formed during their reconstruction. In this report there are given the methods of figuring the additional mining pressure while reconstruction of tunnels, there was worked out the computer program, it is determined that during reconstruction of tunnels the additional mining pressure is 1/3rd of main mining pressure.

Keywords: Mining pressure, Reconstruction of tunnels.

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Authors: Satoshi Komorita, Tsunehiko Chiba, Hidetoshi Yokota, Ashutosh Dutta, Christian Makaya, Subir Das, Dana Chee, F. Joe Lin, Henning Schulzrinne

Abstract:

The NGN (Next Generation Network), which can provide advanced multimedia services over an all-IP based network, has been the subject of much attention for years. While there have been tremendous efforts to develop its architecture and protocols, especially for IMS, which is a key technology of the NGN, it is far from being widely deployed. However, efforts to create an advanced signaling infrastructure realizing many requirements have resulted in a large number of functional components and interactions between those components. Thus, the carriers are trying to explore effective ways to deploy IMS while offering value-added services. As one such approach, we have proposed a self-organizing IMS. A self-organizing IMS enables IMS functional components and corresponding physical nodes to adapt dynamically and automatically based on situation such as network load and available system resources while continuing IMS operation. To realize this, service continuity for users is an important requirement when a reconfiguration occurs during operation. In this paper, we propose a mechanism that will provide service continuity to users and focus on the implementation and describe performance evaluation in terms of number of control signaling and processing time during reconfiguration

Keywords: IMS, SIP, Service Continuity, Self-organizing, and Performance.

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Authors: Gabriela-Andreea Despescu, Mădălina-Elena Mavrodin, Gheorghe Lăzăroiu, Florin Adrian Grădinaru

Abstract:

The purpose of this paper is to contribute to the enhancement of a hydroelectric plant protection by coordinating protection measures / existing security and introducing new measures under a risk management process. In addition, plan identifies key critical elements of a hydroelectric plant, from its level vulnerabilities and threats it is subjected to in order to achieve the necessary protection measures to reduce the level of risk.

Keywords: Critical infrastructure, risk analysis, critical infrastructure protection, vulnerability, risk management, turbine, Impact analysis.

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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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Authors: Chapman Eze Nnadozie

Abstract:

Cloud computing, a technology that is made possible through virtualization within networks represents a shift from the traditional ownership of infrastructure and other resources by distinct organization to a more scalable pattern in which computer resources are rented online to organizations on either as a pay-as-you-use basis or by subscription. In other words, cloud computing entails the renting of computing resources (such as storage space, memory, servers, applications, networks, etc.) by a third party to its clients on a pay-as-go basis. It is a new innovative technology that is globally embraced because of its renowned benefits, profound of which is its cost effectiveness on the part of organizations engaged with its services. In Nigeria, the services are provided either directly to companies mostly by the key IT players such as Microsoft, IBM, and Google; or in partnership with some other players such as Infoware, Descasio, and Sunnet. This action enables organizations to rent IT resources on a pay-as-you-go basis thereby salvaging them from wastages accruable on acquisition and maintenance of IT resources such as ownership of a separate data centre. This paper intends to appraise the challenges of cloud computing adoption in Nigeria, bearing in mind the country’s peculiarities’ in terms of infrastructural development. The methodologies used in this paper include the use of research questionnaires, formulated hypothesis, and the testing of the formulated hypothesis. The major findings of this paper include the fact that there are some addressable challenges to the adoption of cloud computing in Nigeria. Furthermore, the country will gain significantly if the challenges especially in the area of infrastructural development are well addressed. This is because the research established the fact that there are significant gains derivable by the adoption of cloud computing by organizations in Nigeria. However, these challenges can be overturned by concerted efforts in the part of government and other stakeholders.

Keywords: Cloud computing, data centre, infrastructure, IT resources, network, servers, virtualization.

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Authors: H. Iranmanesh, M. Madadi

Abstract:

Work Breakdown Structure (WBS) is one of the most vital planning processes of the project management since it is considered to be the fundamental of other processes like scheduling, controlling, assigning responsibilities, etc. In fact WBS or activity list is the heart of a project and omission of a simple task can lead to an irrecoverable result. There are some tools in order to generate a project WBS. One of the most powerful tools is mind mapping which is the basis of this article. Mind map is a method for thinking together and helps a project manager to stimulate the mind of project team members to generate project WBS. Here we try to generate a WBS of a sample project involving with the building construction using the aid of mind map and the artificial intelligence (AI) programming language. Since mind map structure can not represent data in a computerized way, we convert it to a semantic network which can be used by the computer and then extract the final WBS from the semantic network by the prolog programming language. This method will result a comprehensive WBS and decrease the probability of omitting project tasks.

Keywords: Expert System, Mind map, Semantic network, Work breakdown structure,

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Authors: Mohamed H. S. Mohamed, Yang Xiao-zong, Liu Hong-wei, Wu Zhi-bo

Abstract:

The reliability of distributed systems and computer networks have been modeled by a probabilistic network or a graph G. Computing the residual connectedness reliability (RCR), denoted by R(G), under the node fault model is very useful, but is an NP-hard problem. Since it may need exponential time of the network size to compute the exact value of R(G), it is important to calculate its tight approximate value, especially its lower bound, at a moderate calculation time. In this paper, we propose an efficient algorithm for reliability lower bound of distributed systems with unreliable nodes. We also applied our algorithm to several typical classes of networks to evaluate the lower bounds and show the effectiveness of our algorithm.

Keywords: Distributed systems, probabilistic network, residual connectedness reliability, lower bound.

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Authors: Stanislovas Buteliauskas, Aušrius Juozapavičius

Abstract:

City road transport contributes significantly to climate change, and the ongoing world urbanization is only increasing the problem. The paper describes a city planning concept minimizing the number of vehicles on the roads while increasing overall mobility. This becomes possible by utilizing a recently invented two-level road junction with a unique property of serving both as an intersection of uninterrupted traffic and an easily accessible transport hub capable of accumulating private vehicles, and therefore becoming an especially effective park-and-ride solution, and a logistics or business center. Optimized layouts of city road infrastructure, living and work areas, and major roads are presented. The layouts are suitable both for the development of new cities as well as for the expansion of existing ones. Costs of the infrastructure and a positive impact on climate are evaluated in comparison to current city growth patterns.

Keywords: Congestion, city infrastructure, park-and-ride, road junctions.

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Authors: Kyonghoon Kim, Wonyoung Park, Taeil Park

Abstract:

Aging infrastructures became a serious social problem. This brought out the increased need for the legislation of a new strict guideline for infrastructure management. Although existing guidelines provided basics of how to evaluate and manage the condition of infrastructures, they needed improvements for their evaluation procedures. Most guidelines mainly focused on the structural condition of infrastructures and did not properly reflect service aspects of infrastructures such as performance, public demand, capacity, etc., which were significantly valuable to public. Regardless of the importance, these factors were often neglected in infrastructure evaluations, because they were quite subjective and difficult to quantify in rational manner. Thus, this study proposed a framework to properly identify and evaluate the service indicators. This study showed that service indicators could be grouped into two categories and properly evaluated using AHP and Fuzzy. Overall, proposed framework is expected to assist governmental agency in establishing effective investment strategies for infrastructure improvements.

Keywords: Infrastructure, evaluation, serviceability, fuzzy.

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Authors: K. Akilandeswari, G. M. Nasira

Abstract:

Brain-Computer Interfaces (BCIs) measure brain signals activity, intentionally and unintentionally induced by users, and provides a communication channel without depending on the brain’s normal peripheral nerves and muscles output pathway. Feature Selection (FS) is a global optimization machine learning problem that reduces features, removes irrelevant and noisy data resulting in acceptable recognition accuracy. It is a vital step affecting pattern recognition system performance. This study presents a new Binary Particle Swarm Optimization (BPSO) based feature selection algorithm. Multi-layer Perceptron Neural Network (MLPNN) classifier with backpropagation training algorithm and Levenberg-Marquardt training algorithm classify selected features.

Keywords: Brain-Computer Interfaces (BCI), Feature Selection (FS), Walsh–Hadamard Transform (WHT), Binary Particle Swarm Optimization (BPSO), Multi-Layer Perceptron (MLP), Levenberg–Marquardt algorithm.

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Authors: Chih Chin Yang

Abstract:

The paper proposed a new theory of intellectual capital (so called IC) and a value approach in associated with production and market. After an in-depth review and research analysis of leading firms in this field, a holistic intellectual capital model is discussed, which involves transport, delivery supporting, and interface and systems of on intellectual capital. Through a quantity study, it is found that there is a significant relationship between the product value and infrastructure in a company. The product values are transferred from intellectual capital elements which includes three elements of content and the enterprise includes three elements of infrastructure in its market and product values of enterprise. 

Keywords: Enterprise, product value, intellectual capital.

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Authors: Jun-Kwon Jung, Sung-Min Jung, Tae-Kyung Kim, Tai-Myoung Chung

Abstract:

CloudSim is a useful tool to simulate the cloud environment. It shows the service availability, the power consumption, and the network traffic of services on the cloud environment. Moreover, it supports to calculate a network communication delay through a network topology data easily. CloudSim allows inputting a file of topology data, but it does not provide any generating process. Thus, it needs the file of topology data generated from some other tools. The BRITE is typical network topology generator. Also, it supports various type of topology generating algorithms. If CloudSim can include the BRITE, network simulation for clouds is easier than existing version. This paper shows the potential of connection between BRITE and CloudSim. Also, it proposes the direction to link between them.

Keywords: Cloud, simulation, topology, BRITE, network.

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Authors: Rony H. Rahman, Lutfar Rahman

Abstract:

Ad hoc networks are characterized by multi-hop wireless connectivity and frequently changing network topology. Forming security association among a group of nodes in ad-hoc networks is more challenging than in conventional networks due to the lack of central authority, i.e. fixed infrastructure. With that view in mind, group key management plays an important building block of any secure group communication. The main contribution of this paper is a low complexity key management scheme that is suitable for fully self-organized ad-hoc networks. The protocol is also password authenticated, making it resilient against active attacks. Unlike other existing key agreement protocols, ours make no assumption about the structure of the underlying wireless network, making it suitable for “truly ad-hoc" networks. Finally, we will analyze our protocol to show the computation and communication burden on individual nodes for key establishment.

Keywords: Ad-hoc Networks, Group Key Management, Key Management Protocols, Password Authentication

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Authors: N. Veerasamy, C. J. Cheyne

Abstract:

Users of computer systems may often require the private transfer of messages/communications between parties across a network. Information warfare and the protection and dominance of information in the military context is a prime example of an application area in which the confidentiality of data needs to be maintained. The safe transportation of critical data is therefore often a vital requirement for many private communications. However, unwanted interception/sniffing of communications is also a possibility. An elementary stealthy transfer scheme is therefore proposed by the authors. This scheme makes use of encoding, splitting of a message and the use of a hashing algorithm to verify the correctness of the reconstructed message. For this proof-of-concept purpose, the authors have experimented with the random sending of encoded parts of a message and the construction thereof to demonstrate how data can stealthily be transferred across a network so as to prevent the obvious retrieval of data.

Keywords: Construction, encode, interception, stealthy.

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Authors: A. Pajaziti, H. Cana

Abstract:

In this paper, the structural genetic algorithm is used to optimize the neural network to control the joint movements of robotic arm. The robotic arm has also been modeled in 3D and simulated in real-time in MATLAB. It is found that Neural Networks provide a simple and effective way to control the robot tasks. Computer simulation examples are given to illustrate the significance of this method. By combining Genetic Algorithm optimization method and Neural Networks for the given robotic arm with 5 D.O.F. the obtained the results shown that the base joint movements overshooting time without controller was about 0.5 seconds, while with Neural Network controller (optimized with Genetic Algorithm) was about 0.2 seconds, and the population size of 150 gave best results.

Keywords: Robotic Arm, Neural Network, Genetic Algorithm, Optimization.

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Authors: Ranjan Kumar Dash, Chita Ranjan Tripathy

Abstract:

The evaluation of residual reliability of large sized parallel computer interconnection systems is not practicable with the existing methods. Under such conditions, one must go for approximation techniques which provide the upper bound and lower bound on this reliability. In this context, a new approximation method for providing bounds on residual reliability is proposed here. The proposed method is well supported by two algorithms for simulation purpose. The bounds on residual reliability of three different categories of interconnection topologies are efficiently found by using the proposed method

Keywords: Parallel computer network, reliability, probabilisticgraph, interconnection networks.

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Authors: T.G. Basavaraju, Subir Kumar Sarkar, C Puttamadappa

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Mobile Ad hoc Networks is an autonomous system of mobile nodes connected by multi-hop wireless links without centralized infrastructure support. As mobile communication gains popularity, the need for suitable ad hoc routing protocols will continue to grow. Efficient dynamic routing is an important research challenge in such a network. Bandwidth constrained mobile devices use on-demand approach in their routing protocols because of its effectiveness and efficiency. Many researchers have conducted numerous simulations for comparing the performance of these protocols under varying conditions and constraints. Most of them are not aware of MAC Protocols, which will impact the relative performance of routing protocols considered in different network scenarios. In this paper we investigate the choice of MAC protocols affects the relative performance of ad hoc routing protocols under different scenarios. We have evaluated the performance of these protocols using NS2 simulations. Our results show that the performance of routing protocols of ad hoc networks will suffer when run over different MAC Layer protocols.

Keywords: AODV, DSR, DSDV, MAC, MANETs, relativeperformance

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Authors: Won Sup Kim, Xue-Mei Cui, Seung Kee Han

Abstract:

We present on the method of inverse coherence matrix for the estimation of network connectivity from multivariate time series of a complex system. In a model system of coupled chaotic oscillators, it is shown that the inverse coherence matrix defined as the inverse of cross coherence matrix is proportional to the network connectivity. Therefore the inverse coherence matrix could be used for the distinction between the directly connected links from indirectly connected links in a complex network. We compare the result of network estimation using the method of the inverse coherence matrix with the results obtained from the coherence matrix and the partial coherence matrix.

Keywords: Chaotic oscillator, complex network, inverse coherence matrix, network estimation.

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Authors: Michal Bidlo, Radek Bidlo, Lukas Sekanina

Abstract:

A method is presented for the construction of arbitrary even-input sorting networks exhibiting better properties than the networks created using a conventional technique of the same type. The method was discovered by means of a genetic algorithm combined with an application-specific development. Similarly to human inventions in the area of theoretical computer science, the evolved invention was analyzed: its generality was proven and area and time complexities were determined.

Keywords: Development, genetic algorithm, program, sorting network.

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Authors: W.S. Lim, M.V.C. Rao

Abstract:

In this paper, the processing of sonar signals has been carried out using Minimal Resource Allocation Network (MRAN) and a Probabilistic Neural Network (PNN) in differentiation of commonly encountered features in indoor environments. The stability-plasticity behaviors of both networks have been investigated. The experimental result shows that MRAN possesses lower network complexity but experiences higher plasticity than PNN. An enhanced version called parallel MRAN (pMRAN) is proposed to solve this problem and is proven to be stable in prediction and also outperformed the original MRAN.

Keywords: Ultrasonic sensing, target classification, minimalresource allocation network (MRAN), probabilistic neural network(PNN), stability-plasticity dilemma.

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Authors: Aboagela Dogman, Reza Saatchi, Samir Al-Khayatt

Abstract:

In this study, a network quality of service (QoS) evaluation system was proposed. The system used a combination of fuzzy C-means (FCM) and regression model to analyse and assess the QoS in a simulated network. Network QoS parameters of multimedia applications were intelligently analysed by FCM clustering algorithm. The QoS parameters for each FCM cluster centre were then inputted to a regression model in order to quantify the overall QoS. The proposed QoS evaluation system provided valuable information about the network-s QoS patterns and based on this information, the overall network-s QoS was effectively quantified.

Keywords: Fuzzy C-means; regression model, network quality of service

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Authors: Yifan Fan, Xudong Luo, Pingping Lin

Abstract:

Nowadays, dialogue systems increasingly become the way for humans to access many computer systems. So, humans can interact with computers in natural language. A dialogue system consists of three parts: understanding what humans say in natural language, managing dialogue, and generating responses in natural language. In this paper, we survey deep learning based methods for dialogue management, response generation and dialogue evaluation. Specifically, these methods are based on neural network, long short-term memory network, deep reinforcement learning, pre-training and generative adversarial network. We compare these methods and point out the further research directions.

Keywords: Dialogue management, response generation, reinforcement learning, deep learning, evaluation.

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Authors: M. R. Mustafa, M. H. Isa, R. B. Rezaur

Abstract:

The use of artificial neural network (ANN) modeling for prediction and forecasting variables in water resources engineering are being increasing rapidly. Infrastructural applications of ANN in terms of selection of inputs, architecture of networks, training algorithms, and selection of training parameters in different types of neural networks used in water resources engineering have been reported. ANN modeling conducted for water resources engineering variables (river sediment and discharge) published in high impact journals since 2002 to 2011 have been examined and presented in this review. ANN is a vigorous technique to develop immense relationship between the input and output variables, and able to extract complex behavior between the water resources variables such as river sediment and discharge. It can produce robust prediction results for many of the water resources engineering problems by appropriate learning from a set of examples. It is important to have a good understanding of the input and output variables from a statistical analysis of the data before network modeling, which can facilitate to design an efficient network. An appropriate training based ANN model is able to adopt the physical understanding between the variables and may generate more effective results than conventional prediction techniques.

Keywords: ANN, discharge, modeling, prediction, sediment,

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Authors: Srisawas Siriporn, Rotchanakitumnuai Siriluck

Abstract:

The study aims to develop a framework of social network management to enhance customer relationship. Social network management of this research is derived from social network site management, individual and organization social network usage motivation. The survey was conducted with organization employees who have used social network to interact with customers. The results reveal that content, link, privacy and security, page design and interactivity are the major issues of social network site management. Content, link, privacy and security, individual and organization motivation have major impacts on encouraging business knowledge sharing among employees. Moreover, Page design and interactivity, content, organization motivation and knowledge sharing can improve customer relationships.

Keywords: Social network management, social network site, motivation, knowledge sharing, customer relationship

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Authors: Dong-Young Yoo, Jong-Whoi Shin, Jin-Young Choi

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Social interest and demand on Home-Network has been increasing greatly. Although various services are being introduced to respond to such demands, they can cause serious security problems when linked to the open network such as Internet. This paper reviews the security requirements to protect the service users with assumption that the Home-Network environment is connected to Internet and then proposes the security model based on the requirement. The proposed security model can satisfy most of the requirements and further can be dynamically applied to the future ubiquitous Home-Networks.

Keywords: Home-Network, Security, Vulnerability, Response, Countermeasure.

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Authors: L. Sellami, D. Idoughi, P. F. Tiako

Abstract:

Cloud computing provides infrastructure to the enterprise through the Internet allowing access to cloud services at anytime and anywhere. This pervasive aspect of the services, the distributed nature of data and the wide use of information make cloud computing vulnerable to intrusions that violate the security of the cloud. This requires the use of security mechanisms to detect malicious behavior in network communications and hosts such as intrusion detection systems (IDS). In this article, we focus on the detection of intrusion into the cloud sing IDSs. We base ourselves on client authentication in the computing cloud. This technique allows to detect the abnormal use of ubiquitous service and prevents the intrusion of cloud computing. This is an approach based on client authentication data. Our IDS provides intrusion detection inside and outside cloud computing network. It is a double protection approach: The security user node and the global security cloud computing.

Keywords: Cloud computing, intrusion detection system, privacy, trust.

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