Search results for: unbalanced networks
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1892

Search results for: unbalanced networks

752 PSO-Based Planning of Distribution Systems with Distributed Generations

Authors: Amin Hajizadeh, Ehsan Hajizadeh

Abstract:

This paper presents a multi-objective formulation for optimal siting and sizing of distributed generation (DG) resources in distribution systems in order to minimize the cost of power losses and energy not supplied. The implemented technique is based on particle swarm optimization (PSO) and weight method that employed to obtain the best compromise between these costs. Simulation results on 33-bus distribution test system are presented to demonstrate the effectiveness of the proposed procedure.

Keywords: Distributed generation, distribution networks, particle swarm optimization, reliability, weight method

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751 Averaging Mechanisms to Decision Making for Handover in GSM

Authors: S. Akhila, M. Lakshminarayana

Abstract:

In cellular networks, limited availability of resources has to be tapped to its fullest potential. In view of this aspect, a sophisticated averaging and voting technique has been discussed in this paper, wherein the radio resources available are utilized to the fullest value by taking into consideration, several network and radio parameters which decide on when the handover has to be made and thereby reducing the load on Base station .The increase in the load on the Base station might be due to several unnecessary handover taking place which can be eliminated by making judicious use of the radio and network parameters.

Keywords: Averaging and Voting, Handover, QoS.

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750 Home-Network Security Model in Ubiquitous Environment

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

Abstract:

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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749 Influential Parameters in Estimating Soil Properties from Cone Penetrating Test: An Artificial Neural Network Study

Authors: Ahmed G. Mahgoub, Dahlia H. Hafez, Mostafa A. Abu Kiefa

Abstract:

The Cone Penetration Test (CPT) is a common in-situ test which generally investigates a much greater volume of soil more quickly than possible from sampling and laboratory tests. Therefore, it has the potential to realize both cost savings and assessment of soil properties rapidly and continuously. The principle objective of this paper is to demonstrate the feasibility and efficiency of using artificial neural networks (ANNs) to predict the soil angle of internal friction (Φ) and the soil modulus of elasticity (E) from CPT results considering the uncertainties and non-linearities of the soil. In addition, ANNs are used to study the influence of different parameters and recommend which parameters should be included as input parameters to improve the prediction. Neural networks discover relationships in the input data sets through the iterative presentation of the data and intrinsic mapping characteristics of neural topologies. General Regression Neural Network (GRNN) is one of the powerful neural network architectures which is utilized in this study. A large amount of field and experimental data including CPT results, plate load tests, direct shear box, grain size distribution and calculated data of overburden pressure was obtained from a large project in the United Arab Emirates. This data was used for the training and the validation of the neural network. A comparison was made between the obtained results from the ANN's approach, and some common traditional correlations that predict Φ and E from CPT results with respect to the actual results of the collected data. The results show that the ANN is a very powerful tool. Very good agreement was obtained between estimated results from ANN and actual measured results with comparison to other correlations available in the literature. The study recommends some easily available parameters that should be included in the estimation of the soil properties to improve the prediction models. It is shown that the use of friction ration in the estimation of Φ and the use of fines content in the estimation of E considerable improve the prediction models.

Keywords: Angle of internal friction, Cone penetrating test, General regression neural network, Soil modulus of elasticity.

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748 A Study on the Relation of Corporate Governance and Pricing for Initial Public Offerings

Authors: Chei-Chang Chiou, Sen-Wei Wang, Yu-Min Wang

Abstract:

The purpose of this study is to investigate the relationship between corporate governance and pricing for initial public offerings (IPOs). Empirical result finds that the prediction of pricing of IPOs with corporate governance added can have a rather higher degree of predicting accuracy than that of non governance added during the training and testing samples. Therefore, it can be observed that corporate governance mechanism can affect the pricing of IPOs

Keywords: Artificial neural networks, corporate governance, initial public offerings.

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747 Particle Swarm Optimization with Interval-valued Genotypes and Its Application to Neuroevolution

Authors: Hidehiko Okada

Abstract:

The author proposes an extension of particle swarm optimization (PSO) for solving interval-valued optimization problems and applies the extended PSO to evolutionary training of neural networks (NNs) with interval weights. In the proposed PSO, values in the genotypes are not real numbers but intervals. Experimental results show that interval-valued NNs trained by the proposed method could well approximate hidden target functions despite the fact that no training data was explicitly provided.

Keywords: Evolutionary algorithms, swarm intelligence, particle swarm optimization, neural network, interval arithmetic.

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746 Encrypted Audio Transmission Using Synchronized Nd: YAG Lasers

Authors: R.M. López-Gutiérrez, C. Cruz-Hernández, C. Posadas-Castillo, E.E.García-Guerrero

Abstract:

Encoded information based on synchronization of coupled chaotic Nd:YAG lasers in master-slave configuration is numerically studied. Encoding, transmission, and decoding of information in optical chaotic communication with a single channel is presented. We analyze the robustness of the encrypted audio transmission in a channel noise. In order to illustrate this synchronization robustness, we present two cases of study: synchronization and transmission with a single channel without and with noise in the channel.

Keywords: Encryption, Secure coomunication, Chaos, Synchronization, Complex networks, Nd:YAG laser.

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745 IT System in the Food Supply Chain Safety: Application in SMEs Sector

Authors: Mohsen Shirani, Micaela Demichela

Abstract:

Food supply chain is one of the most complex supply chain networks due to its perishable nature and customer oriented products, and food safety is the major concern for this industry. IT system could help to minimize the production and consumption of unsafe food by controlling and monitoring the entire system. However, there have been many issues in adoption of IT system in this industry specifically within SMEs sector. With this regard, this study presents a novel approach to use IT and tractability systems in the food supply chain, using application of RFID and central database.

Keywords: Food Supply Chain, IT System, Food Safety, SME.

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744 Mapping Complex, Large – Scale Spiking Networks on Neural VLSI

Authors: Christian Mayr, Matthias Ehrlich, Stephan Henker, Karsten Wendt, René Schüffny

Abstract:

Traditionally, VLSI implementations of spiking neural nets have featured large neuron counts for fixed computations or small exploratory, configurable nets. This paper presents the system architecture of a large configurable neural net system employing a dedicated mapping algorithm for projecting the targeted biology-analog nets and dynamics onto the hardware with its attendant constraints.

Keywords: Large scale VLSI neural net, topology mapping, complex pulse communication.

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743 A Learning Agent for Knowledge Extraction from an Active Semantic Network

Authors: Simon Thiel, Stavros Dalakakis, Dieter Roller

Abstract:

This paper outlines the development of a learning retrieval agent. Task of this agent is to extract knowledge of the Active Semantic Network in respect to user-requests. Based on a reinforcement learning approach, the agent learns to interpret the user-s intention. Especially, the learning algorithm focuses on the retrieval of complex long distant relations. Increasing its learnt knowledge with every request-result-evaluation sequence, the agent enhances his capability in finding the intended information.

Keywords: Reinforcement learning, learning retrieval agent, search in semantic networks.

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742 Thermodynamic Attainable Region for Direct Synthesis of Dimethyl Ether from Synthesis Gas

Authors: Thulane Paepae, Tumisang Seodigeng

Abstract:

This paper demonstrates the use of a method of synthesizing process flowsheets using a graphical tool called the GH-plot and in particular, to look at how it can be used to compare the reactions of a combined simultaneous process with regard to their thermodynamics. The technique uses fundamental thermodynamic principles to allow the mass, energy and work balances locate the attainable region for chemical processes in a reactor. This provides guidance on what design decisions would be best suited to developing new processes that are more effective and make lower demands on raw material and energy usage.

Keywords: Attainable region, dimethyl ether synthesis, mass balance, optimal reaction networks.

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741 Minimization of Power Loss in Distribution Networks by Different Techniques

Authors: L.Ramesh, S.P.Chowdhury, S.Chowdhury, A.A.Natarajan, C.T.Gaunt

Abstract:

Accurate loss minimization is the critical component for efficient electrical distribution power flow .The contribution of this work presents loss minimization in power distribution system through feeder restructuring, incorporating DG and placement of capacitor. The study of this work was conducted on IEEE distribution network and India Electricity Board benchmark distribution system. The executed experimental result of Indian system is recommended to board and implement practically for regulated stable output.

Keywords: Distribution system, Distributed Generation LossMinimization, Network Restructuring

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740 Off-Line Signature Recognition Based On Angle Features and GRNN Neural Networks

Authors: Laila Y. Fannas, Ahmed Y. Ben Sasi

Abstract:

This research presents a handwritten signature recognition based on angle feature vector using Artificial Neural Network (ANN). Each signature image will be represented by an Angle vector. The feature vector will constitute the input to the ANN. The collection of signature images will be divided into two sets. One set will be used for training the ANN in a supervised fashion. The other set which is never seen by the ANN will be used for testing. After training, the ANN will be tested for recognition of the signature. When the signature is classified correctly, it is considered correct recognition otherwise it is a failure.

Keywords: Signature Recognition, Artificial Neural Network, Angle Features.

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739 Detection of Diabetic Symptoms in Retina Images Using Analog Algorithms

Authors: Daniela Matei, Radu Matei

Abstract:

In this paper a class of analog algorithms based on the concept of Cellular Neural Network (CNN) is applied in some processing operations of some important medical images, namely retina images, for detecting various symptoms connected with diabetic retinopathy. Some specific processing tasks like morphological operations, linear filtering and thresholding are proposed, the corresponding template values are given and simulations on real retina images are provided.

Keywords: Diabetic retinopathy, pathology detection, cellular neural networks, analog algorithms.

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738 Inter-Area Oscillation Monitoring in Maghrebian Power Grid Using Phasor Measurement Unit

Authors: M. Tsebia, H. Bentarzi

Abstract:

In the inter-connected power systems, a phenomenon called inter-area oscillation may be caused by several defects. In this paper, a study of the Maghreb countries inter-area power networks oscillation has been investigated. The inter-area oscillation monitoring can be enhanced by integrating Phasor Measurement Unit (PMU) technology installed in different places. The data provided by PMU and recorded by PDC will be used for the monitoring, analysis, and control purposes. The proposed approach has been validated by simulation using MATLAB/Simulink.

Keywords: Inter-area oscillation, Maghrebian power system, Simulink, PMU.

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737 Mobile Communications Client Server System for Stock Exchange e-Services Access

Authors: E. Pop, M. Barbos

Abstract:

Using mobile Internet access technologies and eservices, various economic agents can efficiently offer their products or services to a large number of clients. With the support of mobile communications networks, the clients can have access to e-services, anywhere and anytime. This is a base to establish a convergence of technological and financial interests of mobile operators, software developers, mobile terminals producers and e-content providers. In this paper, a client server system is presented, using 3G, EDGE, mobile terminals, for Stock Exchange e-services access.

Keywords: Mobile communications, e-services access, stockexchange.

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736 Social Media Research and Its Effect on Our Society

Authors: A. T. M Shahjahan, Kutub Uddin Chisty

Abstract:

Social media refers to the means of interactions among people in which they create share, exchange and comment contents among themselves in virtual communities and networks. Social media or "social networking" has almost become part of our daily lives and being tossed around over the past few years. It is like any other media such as newspaper, radio and television but it is far more than just about sharing information and ideas. Social networking tools like Twitter, Facebook, Flickr and Blogs have facilitated creation and exchange of ideas so quickly and widely than the conventional media. This paper shows the choices, communication, feeling comfort, time saving and effects of social media among the people.

Keywords: Media, Choice, Effect.

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735 A New Internal Architecture Based on Feature Selection for Holonic Manufacturing System

Authors: Jihan Abdulazeez Ahmed, Adnan Mohsin Abdulazeez Brifcani

Abstract:

This paper suggests a new internal architecture of holon based on feature selection model using the combination of Bees Algorithm (BA) and Artificial Neural Network (ANN). BA is used to generate features while ANN is used as a classifier to evaluate the produced features. Proposed system is applied on the Wine dataset, the statistical result proves that the proposed system is effective and has the ability to choose informative features with high accuracy.

Keywords: Artificial Neural Networks, Holonic Approach, Feature Selection, Bee Algorithm.

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734 Impact of Terrorism as an Asymmetrical Threat on the State's Conventional Security Forces

Authors: Igor Pejic

Abstract:

The main focus of this research will be on analyzing correlative links between terrorism as an asymmetrical threat and the consequences it leaves on conventional security forces. The methodology behind the research will include qualitative research methods focusing on comparative analysis of books, scientific papers, documents and other sources, in order to deduce, explore and formulate the results of the research. With the coming of the 21st century and the rising multi-polar, new world threats quickly emerged. The realistic approach in international relations deems that relations among nations are in a constant state of anarchy since there are no definitive rules and the distribution of power varies widely. International relations are further characterized by egoistic and self-orientated human nature, anarchy or absence of a higher government, security and lack of morality. The asymmetry of power is also reflected on countries' security capabilities and its abilities to project power. With the coming of the new millennia and the rising multi-polar world order, the asymmetry of power can be also added as an important trait of the global society which consequently brought new threats. Among various others, terrorism is probably the most well-known, well-based and well-spread asymmetric threat. In today's global political arena, terrorism is used by state and non-state actors to fulfill their political agendas. Terrorism is used as an all-inclusive tool for regime change, subversion or a revolution. Although the nature of terrorist groups is somewhat inconsistent, terrorism as a security and social phenomenon has a one constant which is reflected in its political dimension. The state's security apparatus, which was embodied in the form of conventional armed forces, is now becoming fragile, unable to tackle new threats and to a certain extent outdated. Conventional security forces were designed to defend or engage an exterior threat which is more or less symmetric and visible. On the other hand, terrorism as an asymmetrical threat is a part of hybrid, special or asymmetric warfare in which specialized units, institutions or facilities represent the primary pillars of security. In today's global society, terrorism is probably the most acute problem which can paralyze entire countries and their political systems. This problem, however, cannot be engaged on an open field of battle, but rather it requires a different approach in which conventional armed forces cannot be used traditionally and their role must be adjusted. The research will try to shed light on the phenomena of modern day terrorism and to prove its correlation with the state conventional armed forces. States are obliged to adjust their security apparatus to the new realism of global society and terrorism as an asymmetrical threat which is a side-product of the unbalanced world.

Keywords: Asymmetrical warfare, conventional forces, security, terrorism.

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733 Connected Objects with Optical Rectenna for Wireless Information Systems

Authors: Chayma Bahar, Chokri Baccouch, Hedi Sakli, Nizar Sakli

Abstract:

Harvesting and transport of optical and radiofrequency signals are a topical subject with multiple challenges. In this paper, we present a Optical RECTENNA system. We propose here a hybrid system solar cell antenna for 5G mobile communications networks. Thus, we propose rectifying circuit. A parametric study is done to follow the influence of load resistance and input power on Optical RECTENNA system performance. Thus, we propose a solar cell antenna structure in the frequency band of future 5G standard in 2.45 GHz bands.

Keywords: Antenna, Rectenna, solar cell, 5G, optical RECTENNA.

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732 Trust and Security in Electronic Payments: What We Have and Need to Know?

Authors: Theodosios Tsiakis, George Stephanides, George Pekos

Abstract:

The growth of open networks created the interest to commercialise it. The establishment of an electronic business mechanism must be accompanied by a digital-electronic payment system to transfer the value of transactions. Financial organizations are requested to offer a secure e-payment synthesis with equivalent levels of trust and security served in conventional paper-based payment transactions. The paper addresses the challenge of the first trade problem in e-commerce, provides a brief literature review on electronic payment and attempts to explain the underlying concept and method of trust in relevance to electronic payment.

Keywords: Electronic payment, security, trust, electronic business mechanism.

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731 Spatial Analysis and Statistics for Zoning of Urban Areas

Authors: Benedetto Manganelli, Beniamino Murgante

Abstract:

The use of statistical data and of the neural networks, capable of elaborate a series of data and territorial info, have allowed the making of a model useful in the subdivision of urban places into homogeneous zone under the profile of a social, real estate, environmental and urbanist background of a city. The development of homogeneous zone has fiscal and urbanist advantages. The tools in the model proposed, able to be adapted to the dynamic changes of the city, allow the application of the zoning fast and dynamic.

Keywords: Homogeneous Urban Areas, Multidimensional Scaling, Neural Network, Real Estate Market, Urban Planning.

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730 Per Flow Packet Scheduling Scheme to Improve the End-to-End Fairness in Mobile Ad Hoc Wireless Network

Authors: K. Sasikala, R. S. D Wahidabanu

Abstract:

Various fairness models and criteria proposed by academia and industries for wired networks can be applied for ad hoc wireless network. The end-to-end fairness in an ad hoc wireless network is a challenging task compared to wired networks, which has not been addressed effectively. Most of the traffic in an ad hoc network are transport layer flows and thus the fairness of transport layer flows has attracted the interest of the researchers. The factors such as MAC protocol, routing protocol, the length of a route, buffer size, active queue management algorithm and the congestion control algorithms affects the fairness of transport layer flows. In this paper, we have considered the rate of data transmission, the queue management and packet scheduling technique. The ad hoc network is dynamic in nature due to various parameters such as transmission of control packets, multihop nature of forwarding packets, changes in source and destination nodes, changes in the routing path influences determining throughput and fairness among the concurrent flows. In addition, the effect of interaction between the protocol in the data link and transport layers has also plays a role in determining the rate of the data transmission. We maintain queue for each flow and the delay information of each flow is maintained accordingly. The pre-processing of flow is done up to the network layer only. The source and destination address information is used for separating the flow and the transport layer information is not used. This minimizes the delay in the network. Each flow is attached to a timer and is updated dynamically. Finite State Machine (FSM) is proposed for queue and transmission control mechanism. The performance of the proposed approach is evaluated in ns-2 simulation environment. The throughput and fairness based on mobility for different flows used as performance metrics. We have compared the performance of the proposed approach with ATP and the transport layer information is used. This minimizes the delay in the network. Each flow is attached to a timer and is updated dynamically. Finite State Machine (FSM) is proposed for queue and transmission control mechanism. The performance of the proposed approach is evaluated in ns-2 simulation environment. The throughput and fairness based on not mobility for different flows used as performance metrics. We have compared the performance of the proposed approach with ATP and MC-MLAS and the performance of the proposed approach is encouraging.

Keywords: ATP, End-to-End fairness, FSM, MAC, QoS.

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729 Traffic Flow on Road Junctions

Authors: Wah Wah Aung, Cho Cho San

Abstract:

The paper deals with a mathematical model for fluid dynamic flows on road networks which is based on conservation laws. This nonlinear framework is based on the conservation of cars. We focus on traffic circle, which is a finite number of roads that meet at some junctions. The traffic circle with junctions having either one incoming and two outgoing or two incoming and one outgoing roads. We describe the numerical schemes with the particular boundary conditions used to produce approximated solutions of the problem.

Keywords: boundary conditions, conservation laws, finite difference Schemes, traffic flow.

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728 A Direct Down-conversion Receiver for Low-power Wireless Sensor Networks

Authors: Gianluca Cornetta, Abdellah Touhafi, David J. Santos, Jose Manuel Vazquez

Abstract:

A direct downconversion receiver implemented in 0.13 μm 1P8M process is presented. The circuit is formed by a single-end LNA, an active balun for conversion into balanced mode, a quadrature double-balanced passive switch mixer and a quadrature voltage-controlled oscillator. The receiver operates in the 2.4 GHz ISM band and complies with IEEE 802.15.4 (ZigBee) specifications. The circuit exhibits a very low noise figure of only 2.27 dB and dissipates only 14.6 mW with a 1.2 V supply voltage and is hence suitable for low-power applications.

Keywords: LNA, Active Balun, Passive Mixer, VCO, IEEE 802.15.4(ZigBee).

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727 Application of the Neural Network to the Synthesis of Multibeam Antennas Arrays

Authors: Ridha Ghayoula, Mbarek Traii, Ali Gharsallah

Abstract:

In this paper, we intend to study the synthesis of the multibeam arrays. The synthesis implementation-s method for this type of arrays permits to approach the appropriated radiance-s diagram. The used approach is based on neural network that are capable to model the multibeam arrays, consider predetermined general criteria-s, and finally it permits to predict the appropriated diagram from the neural model. Our main contribution in this paper is the extension of a synthesis model of these multibeam arrays.

Keywords: Multibeam, modelling, neural networks, synthesis, antennas.

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726 Bitrate Reduction Using FMO for Video Streaming over Packet Networks

Authors: Le Thanh Ha, Hye-Soo Kim, Chun-Su Park, Seung-Won Jung, Sung-Jea Ko

Abstract:

Flexible macroblock ordering (FMO), adopted in the H.264 standard, allows to partition all macroblocks (MBs) in a frame into separate groups of MBs called Slice Groups (SGs). FMO can not only support error-resilience, but also control the size of video packets for different network types. However, it is well-known that the number of bits required for encoding the frame is increased by adopting FMO. In this paper, we propose a novel algorithm that can reduce the bitrate overhead caused by utilizing FMO. In the proposed algorithm, all MBs are grouped in SGs based on the similarity of the transform coefficients. Experimental results show that our algorithm can reduce the bitrate as compared with conventional FMO.

Keywords: Data Partition, Entropy Coding, Greedy Algorithm, H.264/AVC, Slice Group.

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725 An Adaptive Model for Blind Image Restoration using Bayesian Approach

Authors: S.K. Satpathy, S.K. Nayak, K. K. Nagwanshi, S. Panda, C. Ardil

Abstract:

Image restoration involves elimination of noise. Filtering techniques were adopted so far to restore images since last five decades. In this paper, we consider the problem of image restoration degraded by a blur function and corrupted by random noise. A method for reducing additive noise in images by explicit analysis of local image statistics is introduced and compared to other noise reduction methods. The proposed method, which makes use of an a priori noise model, has been evaluated on various types of images. Bayesian based algorithms and technique of image processing have been described and substantiated with experimentation using MATLAB.

Keywords: Image Restoration, Probability DensityFunction (PDF), Neural Networks, Bayesian Classifier.

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724 Applications of Stable Distributions in Time Series Analysis, Computer Sciences and Financial Markets

Authors: Mohammad Ali Baradaran Ghahfarokhi, Parvin Baradaran Ghahfarokhi

Abstract:

In this paper, first we introduce the stable distribution, stable process and theirs characteristics. The a -stable distribution family has received great interest in the last decade due to its success in modeling data, which are too impulsive to be accommodated by the Gaussian distribution. In the second part, we propose major applications of alpha stable distribution in telecommunication, computer science such as network delays and signal processing and financial markets. At the end, we focus on using stable distribution to estimate measure of risk in stock markets and show simulated data with statistical softwares.

Keywords: stable distribution, SaS, infinite variance, heavy tail networks, VaR.

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723 Implementation of IEEE 802.15.4 Packet Analyzer

Authors: Sung Jun Ban, Hyeonwoo Cho, ChangWoo Lee, Sang Woo Kim

Abstract:

A packet analyzer is a tool for debugging sensor network systems and is convenient for developers. In this paper, we introduce a new packet analyzer based on an embedded system. The proposed packet analyzer is compatible with IEEE 802.15.4, which is suitable for the wireless communication standard for sensor networks, and is available for remote control by adopting a server-client scheme based on the Ethernet interface. To confirm the operations of the packet analyzer, we have developed two types of sensor nodes based on PIC4620 and ATmega128L microprocessors and tested the functions of the proposed packet analyzer by obtaining the packets from the sensor nodes.

Keywords: Sensor network, embedded system, packet analyzer.

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