Search results for: Communication channel model; Broadband Powerlinecommunication; Branched network; OFDM; Delay Spread
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11149

Search results for: Communication channel model; Broadband Powerlinecommunication; Branched network; OFDM; Delay Spread

9439 Recurrent Neural Network Based Fuzzy Inference System for Identification and Control of Dynamic Plants

Authors: Rahib Hidayat Abiyev

Abstract:

This paper presents the development of recurrent neural network based fuzzy inference system for identification and control of dynamic nonlinear plant. The structure and algorithms of fuzzy system based on recurrent neural network are described. To train unknown parameters of the system the supervised learning algorithm is used. As a result of learning, the rules of neuro-fuzzy system are formed. The neuro-fuzzy system is used for the identification and control of nonlinear dynamic plant. The simulation results of identification and control systems based on recurrent neuro-fuzzy network are compared with the simulation results of other neural systems. It is found that the recurrent neuro-fuzzy based system has better performance than the others.

Keywords: Fuzzy logic, neural network, neuro-fuzzy system, control system.

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9438 Ignition Analysis in Supersonic Turbulent Mixing Layer

Authors: A. M. Tahsini

Abstract:

Numerical study of two dimensional supersonic hydrogen-air mixing layer is performed to investigate the effect of turbulence and chemical additive on ignition distance. Chemical reaction is treated using detail kinetics. Advection upstream splitting method is used to calculate the fluxes and one equation turbulence model is chosen here to simulate the considered problem. Hydrogen peroxide is used as an additive and the results show that inflow turbulence and chemical additive may drastically decrease the ignition delay in supersonic combustion.

Keywords: Ignition, Mixing layer, Numerical simulation, Supersonic combustion, Turbulence

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9437 Automatic Removal of Ocular Artifacts using JADE Algorithm and Neural Network

Authors: V Krishnaveni, S Jayaraman, A Gunasekaran, K Ramadoss

Abstract:

The ElectroEncephaloGram (EEG) is useful for clinical diagnosis and biomedical research. EEG signals often contain strong ElectroOculoGram (EOG) artifacts produced by eye movements and eye blinks especially in EEG recorded from frontal channels. These artifacts obscure the underlying brain activity, making its visual or automated inspection difficult. The goal of ocular artifact removal is to remove ocular artifacts from the recorded EEG, leaving the underlying background signals due to brain activity. In recent times, Independent Component Analysis (ICA) algorithms have demonstrated superior potential in obtaining the least dependent source components. In this paper, the independent components are obtained by using the JADE algorithm (best separating algorithm) and are classified into either artifact component or neural component. Neural Network is used for the classification of the obtained independent components. Neural Network requires input features that exactly represent the true character of the input signals so that the neural network could classify the signals based on those key characters that differentiate between various signals. In this work, Auto Regressive (AR) coefficients are used as the input features for classification. Two neural network approaches are used to learn classification rules from EEG data. First, a Polynomial Neural Network (PNN) trained by GMDH (Group Method of Data Handling) algorithm is used and secondly, feed-forward neural network classifier trained by a standard back-propagation algorithm is used for classification and the results show that JADE-FNN performs better than JADEPNN.

Keywords: Auto Regressive (AR) Coefficients, Feed Forward Neural Network (FNN), Joint Approximation Diagonalisation of Eigen matrices (JADE) Algorithm, Polynomial Neural Network (PNN).

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9436 Pseudo Last Useful Instant Queuing Strategy for Handovers in Low Earth Orbit Mobile Satellite Networks

Authors: W. Kiamouche, M. Benslama

Abstract:

This paper presents an alternative strategy of queuing handover called Pseudo Last Useful Instant PLUI scheme for Low Earth Orbit Mobile Satellite Systems LEO MSSs. The PLUI scheme uses the same approach as the Last Useful Instant LUI scheme previously proposed in literature, with less complex implementation. Simulation tests were carried out using Dynamic Channel Allocation DCA in order to evaluate the performance of this scheme and also an analytical approach has been presented to allow the performance evaluation of Fixed Channel Allocation FCA, with different handover queuing disciplines. The results show that performances achieved by the proposed strategy are close to those achieved using the LUI scheme.

Keywords: LEO mobile satellite networks, LUI and FIFOschemes, queuing handover.

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9435 Implementation of TinyHash based on Hash Algorithm for Sensor Network

Authors: HangRok Lee, YongJe Choi, HoWon Kim

Abstract:

In recent years, it has been proposed security architecture for sensor network.[2][4]. One of these, TinySec by Chris Kalof, Naveen Sastry, David Wagner had proposed Link layer security architecture, considering some problems of sensor network. (i.e : energy, bandwidth, computation capability,etc). The TinySec employs CBC_mode of encryption and CBC-MAC for authentication based on SkipJack Block Cipher. Currently, This TinySec is incorporated in the TinyOS for sensor network security. This paper introduces TinyHash based on general hash algorithm. TinyHash is the module in order to replace parts of authentication and integrity in the TinySec. it implies that apply hash algorithm on TinySec architecture. For compatibility about TinySec, Components in TinyHash is constructed as similar structure of TinySec. And TinyHash implements the HMAC component for authentication and the Digest component for integrity of messages. Additionally, we define the some interfaces for service associated with hash algorithm.

Keywords: sensor network security, nesC, TinySec, TinyOS, Hash, HMAC, integrity

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9434 The Use of Crisis Workplace Technology to Protect Communication Processes of Critical Infrastructure

Authors: Jiri Barta, Jiri F. Urbanek

Abstract:

This paper deals with a protection of the national and European infrastructure. It is issue nowadays. The paper deals with the perspectives and possibilities of "smart solutions" to critical infrastructure protection. The research project deals with computers aided technologies are used from the perspective of new, better protection of selected infrastructure objects. Protection is focused on communication and information channels. These communication and information channels are very important for the functioning of the system of protection of critical infrastructure elements.

Keywords: Interoperability, Communication systems, Controlling Process, Critical Infrastructure, Crisis Workplaces. Continuity.

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9433 Estimation of the Road Traffic Emissions and Dispersion in the Developing Countries Conditions

Authors: Hicham Gourgue, Ahmed Aharoune, Ahmed Ihlal

Abstract:

We present in this work our model of road traffic emissions (line sources) and dispersion of these emissions, named DISPOLSPEM (Dispersion of Poly Sources and Pollutants Emission Model). In its emission part, this model was designed to keep the consistent bottom-up and top-down approaches. It also allows to generate emission inventories from reduced input parameters being adapted to existing conditions in Morocco and in the other developing countries. While several simplifications are made, all the performance of the model results are kept. A further important advantage of the model is that it allows the uncertainty calculation and emission rate uncertainty according to each of the input parameters. In the dispersion part of the model, an improved line source model has been developed, implemented and tested against a reference solution. It provides improvement in accuracy over previous formulas of line source Gaussian plume model, without being too demanding in terms of computational resources. In the case study presented here, the biggest errors were associated with the ends of line source sections; these errors will be canceled by adjacent sections of line sources during the simulation of a road network. In cases where the wind is parallel to the source line, the use of the combination discretized source and analytical line source formulas minimizes remarkably the error. Because this combination is applied only for a small number of wind directions, it should not excessively increase the calculation time.

Keywords: Air pollution, dispersion, emissions, line sources, road traffic, urban transport.

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9432 Towards a Security Model against Denial of Service Attacks for SIP Traffic

Authors: Arellano Karina, Diego Avila-Pesántez, Leticia Vaca-Cárdenas, Alberto Arellano, Carmen Mantilla

Abstract:

Nowadays, security threats in Voice over IP (VoIP) systems are an essential and latent concern for people in charge of security in a corporate network, because, every day, new Denial-of-Service (DoS) attacks are developed. These affect the business continuity of an organization, regarding confidentiality, availability, and integrity of services, causing frequent losses of both information and money. The purpose of this study is to establish the necessary measures to mitigate DoS threats, which affect the availability of VoIP systems, based on the Session Initiation Protocol (SIP). A Security Model called MS-DoS-SIP is proposed, which is based on two approaches. The first one analyzes the recommendations of international security standards. The second approach takes into account weaknesses and threats. The implementation of this model in a VoIP simulated system allowed to minimize the present vulnerabilities in 92% and increase the availability time of the VoIP service into an organization.

Keywords: Denial-of-service SIP attacks, MS-DoS-SIP, security model, VoIP-SIP vulnerabilities.

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9431 Artificial Intelligence Techniques for Controlling Spacecraft Power System

Authors: Hanaa T. El-Madany, Faten H. Fahmy, Ninet M. A. El-Rahman, Hassen T. Dorrah

Abstract:

Advancements in the field of artificial intelligence (AI) made during this decade have forever changed the way we look at automating spacecraft subsystems including the electrical power system. AI have been used to solve complicated practical problems in various areas and are becoming more and more popular nowadays. In this paper, a mathematical modeling and MATLAB–SIMULINK model for the different components of the spacecraft power system is presented. Also, a control system, which includes either the Neural Network Controller (NNC) or the Fuzzy Logic Controller (FLC) is developed for achieving the coordination between the components of spacecraft power system as well as control the energy flows. The performance of the spacecraft power system is evaluated by comparing two control systems using the NNC and the FLC.

Keywords: Spacecraft, Neural network, Fuzzy logic control, Photovoltaic array.

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9430 A Novel Hybrid Mobile Agent Based Distributed Intrusion Detection System

Authors: Amir Vahid Dastjerdi, Kamalrulnizam Abu Bakar

Abstract:

The first generation of Mobile Agents based Intrusion Detection System just had two components namely data collection and single centralized analyzer. The disadvantage of this type of intrusion detection is if connection to the analyzer fails, the entire system will become useless. In this work, we propose novel hybrid model for Mobile Agent based Distributed Intrusion Detection System to overcome the current problem. The proposed model has new features such as robustness, capability of detecting intrusion against the IDS itself and capability of updating itself to detect new pattern of intrusions. In addition, our proposed model is also capable of tackling some of the weaknesses of centralized Intrusion Detection System models.

Keywords: Distributed Intrusion Detection System, Mobile Agents, Network Security.

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9429 Software to Encrypt Messages Using Public-Key Cryptography

Authors: E. Inzunza-González, C. Cruz-Hernández, R. M. López-Gutiérrez, E. E. García-Guerrero, L. Cardoza- Avendaño, H. Serrano-Guerrero

Abstract:

In this paper the development of a software to encrypt messages with asymmetric cryptography is presented. In particular, is used the RSA (Rivest, Shamir and Adleman) algorithm to encrypt alphanumeric information. The software allows to generate different public keys from two prime numbers provided by the user, the user must then select a public-key to generate the corresponding private-key. To encrypt the information, the user must provide the public-key of the recipient as well as the message to be encrypted. The generated ciphertext can be sent through an insecure channel, so that would be very difficult to be interpreted by an intruder or attacker. At the end of the communication, the recipient can decrypt the original message if provide his/her public-key and his/her corresponding private-key.

Keywords: Asymmetric cryptography, Prime number, Publickey, Private-key, Software.

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9428 A Comprehensive Survey on RAT Selection Algorithms for Heterogeneous Networks

Authors: Abdallah AL Sabbagh, Robin Braun, Mehran Abolhasan

Abstract:

Due to the coexistence of different Radio Access Technologies (RATs), Next Generation Wireless Networks (NGWN) are predicted to be heterogeneous in nature. The coexistence of different RATs requires a need for Common Radio Resource Management (CRRM) to support the provision of Quality of Service (QoS) and the efficient utilization of radio resources. RAT selection algorithms are part of the CRRM algorithms. Simply, their role is to verify if an incoming call will be suitable to fit into a heterogeneous wireless network, and to decide which of the available RATs is most suitable to fit the need of the incoming call and admit it. Guaranteeing the requirements of QoS for all accepted calls and at the same time being able to provide the most efficient utilization of the available radio resources is the goal of RAT selection algorithm. The normal call admission control algorithms are designed for homogeneous wireless networks and they do not provide a solution to fit a heterogeneous wireless network which represents the NGWN. Therefore, there is a need to develop RAT selection algorithm for heterogeneous wireless network. In this paper, we propose an approach for RAT selection which includes receiving different criteria, assessing and making decisions, then selecting the most suitable RAT for incoming calls. A comprehensive survey of different RAT selection algorithms for a heterogeneous wireless network is studied.

Keywords: Heterogeneous Wireless Network, RAT selection algorithms, Next Generation Wireless Network (NGWN), Beyond 3G Network, Common Radio Resource Management (CRRM).

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9427 Modeling of Co-Cu Elution From Clinoptilolite using Neural Network

Authors: John Kabuba, Antoine Mulaba-Bafubiandi

Abstract:

The elution process for the removal of Co and Cu from clinoptilolite as an ion-exchanger was investigated using three parameters: bed volume, pH and contact time. The present paper study has shown quantitatively that acid concentration has a significant effect on the elution process. The favorable eluant concentration was found to be 2 M HCl and 2 M H2SO4, respectively. The multi-component equilibrium relationship in the process can be very complex, and perhaps ill-defined. In such circumstances, it is preferable to use a non-parametric technique such as Neural Network to represent such an equilibrium relationship.

Keywords: Clinoptilolite, elution, modeling, neural network.

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9426 Integrating Low and High Level Object Recognition Steps

Authors: András Barta, István Vajk

Abstract:

In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic spline wavelet image bases. The method is demonstrated for a simple circuit diagram component identification problem.

Keywords: Object recognition, Bayesian network, Wavelets, Document processing.

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9425 Lateral Pressure in Squat Silos under Eccentric Discharge

Authors: Y. Z. Zhu, S. P. Meng, W. W. Sun

Abstract:

The influence of eccentric discharge of stored solids in squat silos has been highly valued by many researchers. However, calculation method of lateral pressure under eccentric flowing still needs to be deeply studied. In particular, the lateral pressure distribution on vertical wall could not be accurately recognized mainly because of its asymmetry. In order to build mechanical model of lateral pressure, flow channel and flow pattern of stored solids in squat silo are studied. In this passage, based on Janssen-s theory, the method for calculating lateral static pressure in squat silos after eccentric discharge is proposed. Calculative formulae are deduced for each of three possible cases. This method is also focusing on unsymmetrical distribution characteristic of silo wall normal pressure. Finite element model is used to analysis and compare the results of lateral pressure and the numerical results illustrate the practicability of the theoretical method.

Keywords: Squat silo, eccentric discharge, lateral pressure, asymmetric distribution

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9424 Optimal Compensation of Reactive Power in the Restructured Distribution Network

Authors: Atefeh Pourshafie, Mohsen. Saniei, S. S. Mortazavi, A. Saeedian

Abstract:

In this paper optimal capacitor placement problem has been formulated in a restructured distribution network. In this scenario the distribution network operator can consider reactive energy also as a service that can be sold to transmission system. Thus search for optimal location, size and number of capacitor banks with the objective of loss reduction, maximum income from selling reactive energy to transmission system and return on investment for capacitors, has been performed. Results is influenced with economic value of reactive energy, therefore problem has been solved for various amounts of it. The implemented optimization technique is genetic algorithm. For any value of reactive power economic value, when reverse of investment index increase and change from zero or negative values to positive values, the threshold value of selling reactive power has been obtained. This increasing price of economic parameter is reasonable until the network losses is less than loss before compensation.

Keywords: capacitor placement, deregulated electric market, distribution network optimization.

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9423 Emotion Detection in Twitter Messages Using Combination of Long Short-Term Memory and Convolutional Deep Neural Networks

Authors: B. Golchin, N. Riahi

Abstract:

One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.

Keywords: emotion classification, sentiment analysis, social networks, deep neural networks

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9422 Application of EEG Wavelet Power to Prediction of Antidepressant Treatment Response

Authors: Dorota Witkowska, Paweł Gosek, Lukasz Swiecicki, Wojciech Jernajczyk, Bruce J. West, Miroslaw Latka

Abstract:

In clinical practice, the selection of an antidepressant often degrades to lengthy trial-and-error. In this work we employ a normalized wavelet power of alpha waves as a biomarker of antidepressant treatment response. This novel EEG metric takes into account both non-stationarity and intersubject variability of alpha waves. We recorded resting, 19-channel EEG (closed eyes) in 22 inpatients suffering from unipolar (UD, n=10) or bipolar (BD, n=12) depression. The EEG measurement was done at the end of the short washout period which followed previously unsuccessful pharmacotherapy. The normalized alpha wavelet power of 11 responders was markedly different than that of 11 nonresponders at several, mostly temporoparietal sites. Using the prediction of treatment response based on the normalized alpha wavelet power, we achieved 81.8% sensitivity and 81.8% specificity for channel T4.

Keywords: Alpha waves, antidepressant, treatment outcome, wavelet.

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9421 Optimal and Generalized Multiple Descriptions Image Coding Transform in the Wavelet Domain

Authors: Bahi brahim, El hassane Ibn Elhaj, Driss Aboutajdine

Abstract:

In this paper we propose a Multiple Description Image Coding(MDIC) scheme to generate two compressed and balanced rates descriptions in the wavelet domain (Daubechies biorthogonal (9, 7) wavelet) using pairwise correlating transform optimal and application method for Generalized Multiple Description Coding (GMDC) to image coding in the wavelet domain. The GMDC produces statistically correlated streams such that lost streams can be estimated from the received data. Our performance test shown that the proposed method gives more improvement and good quality of the reconstructed image when the wavelet coefficients are normalized by Gaussian Scale Mixture (GSM) model then the Gaussian one ,.

Keywords: Multiple description coding (MDC), gaussian scale mixture (GSM) model, joint source-channel coding, pairwise correlating transform, GMDCT.

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9420 EEG Analysis of Brain Dynamics in Children with Language Disorders

Authors: Hamed Alizadeh Dashagholi, Hossein Yousefi-Banaem, Mina Naeimi

Abstract:

Current study established for EEG signal analysis in patients with language disorder. Language disorder can be defined as meaningful delay in the use or understanding of spoken or written language. The disorder can include the content or meaning of language, its form, or its use. Here we applied Z-score, power spectrum, and coherence methods to discriminate the language disorder data from healthy ones. Power spectrum of each channel in alpha, beta, gamma, delta, and theta frequency bands was measured. In addition, intra hemispheric Z-score obtained by scoring algorithm. Obtained results showed high Z-score and power spectrum in posterior regions. Therefore, we can conclude that peoples with language disorder have high brain activity in frontal region of brain in comparison with healthy peoples. Results showed that high coherence correlates with irregularities in the ERP and is often found during complex task, whereas low coherence is often found in pathological conditions. The results of the Z-score analysis of the brain dynamics showed higher Z-score peak frequency in delta, theta and beta sub bands of Language Disorder patients. In this analysis there were activity signs in both hemispheres and the left-dominant hemisphere was more active than the right.

Keywords: EEG, electroencephalography, coherence methods, language disorder, power spectrum, z-score.

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9419 Detecting Community Structure in Amino Acid Interaction Networks

Authors: Omar GACI, Stefan BALEV, Antoine DUTOT

Abstract:

In this paper we introduce the notion of protein interaction network. This is a graph whose vertices are the protein-s amino acids and whose edges are the interactions between them. Using a graph theory approach, we observe that according to their structural roles, the nodes interact differently. By leading a community structure detection, we confirm this specific behavior and describe thecommunities composition to finally propose a new approach to fold a protein interaction network.

Keywords: interaction network, protein structure, community structure detection.

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9418 Shoreline Change Estimation from Survey Image Coordinates and Neural Network Approximation

Authors: Tienfuan Kerh, Hsienchang Lu, Rob Saunders

Abstract:

Shoreline erosion problems caused by global warming and sea level rising may result in losing of land areas, so it should be examined regularly to reduce possible negative impacts. Initially in this study, three sets of survey images obtained from the years of 1990, 2001, and 2010, respectively, are digitalized by using graphical software to establish the spatial coordinates of six major beaches around the island of Taiwan. Then, by overlaying the known multi-period images, the change of shoreline can be observed from their distribution of coordinates. In addition, the neural network approximation is used to develop a model for predicting shoreline variation in the years of 2015 and 2020. The comparison results show that there is no significant change of total sandy area for all beaches in the three different periods. However, the prediction results show that two beaches may exhibit an increasing of total sandy areas under a statistical 95% confidence interval. The proposed method adopted in this study may be applicable to other shorelines of interest around the world.

Keywords: Digitalized shoreline coordinates, survey image overlaying, neural network approximation, total beach sandy areas.

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9417 The Model of Blended Learning and Its Use at Foreign Language Teaching

Authors: A. A. Kudysheva, A. N. Kudyshev

Abstract:

In present article the model of Blended Learning, its advantage at foreign language teaching, and also some problems that can arise during its use are considered. The Blended Learning is a special organization of learning, which allows to combine classroom work and modern technologies in electronic distance teaching environment. Nowadays a lot of European educational institutions and companies use such technology. Through this method: student gets the opportunity to learn in a group (classroom) with a teacher and additionally at home at a convenient time; student himself sets the optimal speed and intensity of the learning process; this method helps student to discipline himself and learn to work independently.

Keywords: Foreign language, information and communication technology (ICT), model of Blended Learning, virtual cool room, technophobia

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9416 Particle Filter Applied to Noisy Synchronization in Polynomial Chaotic Maps

Authors: Moussa Yahia, Pascal Acco, Malek Benslama

Abstract:

Polynomial maps offer analytical properties used to obtain better performances in the scope of chaos synchronization under noisy channels. This paper presents a new method to simplify equations of the Exact Polynomial Kalman Filter (ExPKF) given in [1]. This faster algorithm is compared to other estimators showing that performances of all considered observers vanish rapidly with the channel noise making application of chaos synchronization intractable. Simulation of ExPKF shows that saturation drawn on the emitter to keep it stable impacts badly performances for low channel noise. Then we propose a particle filter that outperforms all other Kalman structured observers in the case of noisy channels.

Keywords: Chaos synchronization, Saturation, Fast ExPKF, Particlefilter, Polynomial maps.

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9415 Imposter Detection Based on Location in Vehicular Ad-Hoc Network

Authors: Sanjoy Das, Akash Arya, Rishi Pal Singh

Abstract:

Vehicular Ad hoc Network is basically the solution of several problems associated while vehicles are plying on the road. In this paper, we have focused on the detection of imposter node while it has stolen the ID's of the authenticated vehicle in the network. The purpose is to harm the network through imposter messages. Here, we have proposed a protocol namely Imposter Detection based on Location (IDBL), which will store the location coordinate of the each vehicle as the key of the authenticity of the message so that imposter node can be detected. The imposter nodes send messages from a stolen ID and show that it is from an authentic node ID. So, to detect this anomaly, the first location is checked and observed different from original vehicle location. This node is known as imposter node. We have implemented the algorithm through JAVA and tested various types of node distribution and observed the detection probability of imposter node.

Keywords: Authentication, detection, IDBL protocol, imposter node, node detection.

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9414 Performance Evaluation of Discrete Fourier Transform Algorithm Based PMU for Wide Area Measurement System

Authors: Alpesh Adeshara, Rajendrasinh Jadeja, Praghnesh Bhatt

Abstract:

Implementation of advanced technologies requires sophisticated instruments that deal with the operation, control, restoration and protection of rapidly growing power system network under normal and abnormal conditions. Presently, the applications of Phasor Measurement Unit (PMU) are widely found in real time operation, monitoring, controlling and analysis of power system network as it eliminates the various limitations of supervisory control and data acquisition system (SCADA) conventionally used in power system. The use of PMU data is very rapidly increasing its importance for online and offline analysis. Wide area measurement system (WAMS) is developed as new technology by use of multiple PMUs in power system. The present paper proposes a model of Matlab based PMU using Discrete Fourier Transform (DFT) algorithm and evaluation of its operation under different contingencies. In this paper, PMU based two bus system having WAMS network is presented as a case study.

Keywords: DFT-Discrete Fourier Transform, GPS-Global Positioning System, PMU-Phasor Measurement System, WAMS-Wide Area Monitoring System.

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9413 Network Reconfiguration for Load Balancing in Distribution System with Distributed Generation and Capacitor Placement

Authors: T. Lantharthong, N. Rugthaicharoencheep

Abstract:

This paper presents an efficient algorithm for optimization of radial distribution systems by a network reconfiguration to balance feeder loads and eliminate overload conditions. The system load-balancing index is used to determine the loading conditions of the system and maximum system loading capacity. The index value has to be minimum in the optimal network reconfiguration of load balancing. A method based on Tabu search algorithm, The Tabu search algorithm is employed to search for the optimal network reconfiguration. The basic idea behind the search is a move from a current solution to its neighborhood by effectively utilizing a memory to provide an efficient search for optimality. It presents low computational effort and is able to find good quality configurations. Simulation results for a radial 69-bus system with distributed generations and capacitors placement. The study results show that the optimal on/off patterns of the switches can be identified to give the best network reconfiguration involving balancing of feeder loads while respecting all the constraints.

Keywords: Network reconfiguration, Distributed generation Capacitor placement, Load balancing, Optimization technique

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9412 The Impact of Stakeholder Communication Strategies on Consumers- Acceptance and Financial Performance: In the Case of Fertilizer Industry in Malaysia

Authors: Hasnida Abdul Wahab, Shahrina Md Nordin, Lai Fong Woon, Hasrina Mustafa

Abstract:

There has been a growing emphasis in communication management from simple coordination of promotional tools to a complex strategic process. This study will examine the current marketing communications and engagement strategies used in addressing the key stakeholders. In the case of fertilizer industry in Malaysia, there has been little empirical research on stakeholder communication when major challenges facing the modern corporation is the need to communicate its identity, its values and products in order to distinguish itself from competitors. The study will employ both quantitative and qualitative methods and the use of Structural Equation Modeling (SEM) to establish a causal relationship amongst the key factors of stakeholder communication strategies and increment in consumers- choice/acceptance and impact on financial performance. One of the major contributions is a conceptual framework for communication strategies and engagement in increasing consumers- acceptance level and the firm-s financial performance.

Keywords: Consumers' acceptance, financial performance, stakeholder communication strategies.

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9411 Using Technology with a New Model of Management Development by Simulation of Neural Network and its Application on Intelligent Schools

Authors: Ahmad Ghayoumi, Mehdi Ghayoumi

Abstract:

Intelligent schools are those which use IT devices and technologies as media software, hardware and networks to improve learning process. On the other hand management improvement is best described as the process from which managers learn and improve their skills not only to benefit themselves but also their employing organizations Here, we present a model Management improvement System that has been applied on some schools and have made strict improvement.

Keywords: Intelligent school, Management development system, Learning station, Teaching station

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9410 Power and Delay Optimized Graph Representation for Combinational Logic Circuits

Authors: Padmanabhan Balasubramanian, Karthik Anantha

Abstract:

Structural representation and technology mapping of a Boolean function is an important problem in the design of nonregenerative digital logic circuits (also called combinational logic circuits). Library aware function manipulation offers a solution to this problem. Compact multi-level representation of binary networks, based on simple circuit structures, such as AND-Inverter Graphs (AIG) [1] [5], NAND Graphs, OR-Inverter Graphs (OIG), AND-OR Graphs (AOG), AND-OR-Inverter Graphs (AOIG), AND-XORInverter Graphs, Reduced Boolean Circuits [8] does exist in literature. In this work, we discuss a novel and efficient graph realization for combinational logic circuits, represented using a NAND-NOR-Inverter Graph (NNIG), which is composed of only two-input NAND (NAND2), NOR (NOR2) and inverter (INV) cells. The networks are constructed on the basis of irredundant disjunctive and conjunctive normal forms, after factoring, comprising terms with minimum support. Construction of a NNIG for a non-regenerative function in normal form would be straightforward, whereas for the complementary phase, it would be developed by considering a virtual instance of the function. However, the choice of best NNIG for a given function would be based upon literal count, cell count and DAG node count of the implementation at the technology independent stage. In case of a tie, the final decision would be made after extracting the physical design parameters. We have considered AIG representation for reduced disjunctive normal form and the best of OIG/AOG/AOIG for the minimized conjunctive normal forms. This is necessitated due to the nature of certain functions, such as Achilles- heel functions. NNIGs are found to exhibit 3.97% lesser node count compared to AIGs and OIG/AOG/AOIGs; consume 23.74% and 10.79% lesser library cells than AIGs and OIG/AOG/AOIGs for the various samples considered. We compare the power efficiency and delay improvement achieved by optimal NNIGs over minimal AIGs and OIG/AOG/AOIGs for various case studies. In comparison with functionally equivalent, irredundant and compact AIGs, NNIGs report mean savings in power and delay of 43.71% and 25.85% respectively, after technology mapping with a 0.35 micron TSMC CMOS process. For a comparison with OIG/AOG/AOIGs, NNIGs demonstrate average savings in power and delay by 47.51% and 24.83%. With respect to device count needed for implementation with static CMOS logic style, NNIGs utilize 37.85% and 33.95% lesser transistors than their AIG and OIG/AOG/AOIG counterparts.

Keywords: AND-Inverter Graph, OR-Inverter Graph, DirectedAcyclic Graph, Low power design, Delay optimization.

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