Search results for: Network security
2962 Development of Algorithms for the Study of the Image in Digital Form for Satellite Applications: Extraction of a Road Network and Its Nodes
Authors: Z. Nougrara
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In this paper we propose a novel methodology for extracting a road network and its nodes from satellite images of Algeria country. This developed technique is a progress of our previous research works. It is founded on the information theory and the mathematical morphology; the information theory and the mathematical morphology are combined together to extract and link the road segments to form a road network and its nodes. We therefore have to define objects as sets of pixels and to study the shape of these objects and the relations that exist between them. In this approach, geometric and radiometric features of roads are integrated by a cost function and a set of selected points of a crossing road. Its performances were tested on satellite images of Algeria country.Keywords: Satellite image, road network, nodes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16842961 A Multi-Objective Evolutionary Algorithm of Neural Network for Medical Diseases Problems
Authors: Sultan Noman Qasem
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This paper presents an evolutionary algorithm for solving multi-objective optimization problems-based artificial neural network (ANN). The multi-objective evolutionary algorithm used in this study is genetic algorithm while ANN used is radial basis function network (RBFN). The proposed algorithm named memetic elitist Pareto non-dominated sorting genetic algorithm-based RBFN (MEPGAN). The proposed algorithm is implemented on medical diseases problems. The experimental results indicate that the proposed algorithm is viable, and provides an effective means to design multi-objective RBFNs with good generalization capability and compact network structure. This study shows that MEPGAN generates RBFNs coming with an appropriate balance between accuracy and simplicity, comparing to the other algorithms found in literature.
Keywords: Radial basis function network, Hybrid learning, Multi-objective optimization, Genetic algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22372960 Evaluating Performance of an Anomaly Detection Module with Artificial Neural Network Implementation
Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez
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Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.
Keywords: Network Intrusion Detection, Machine learning, Artificial Neural Network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20652959 Implementation of a New Neural Network Function Block to Programmable Logic Controllers Library Function
Authors: Hamid Abdi, Abolfazl Salami, Abolfazl Ahmadi
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Programmable logic controllers are the main controllers in the today's industries; they are used for several applications in industrial control systems and there are lots of examples exist from the PLC applications in industries especially in big companies and plants such as refineries, power plants, petrochemical companies, steel companies, and food and production companies. In the PLCs there are some functions in the function library in software that can be used in PLC programs as basic program elements. The aim of this project are introducing and implementing a new function block of a neural network to the function library of PLC. This block can be applied for some control applications or nonlinear functions calculations after it has been trained for these applications. The implemented neural network is a Perceptron neural network with three layers, three input nodes and one output node. The block can be used in manual or automatic mode. In this paper the structure of the implemented function block, the parameters and the training method of the network are presented by considering the especial method of PLC programming and its complexities. Finally the application of the new block is compared with a classic simulated block and the results are presented.Keywords: Programmable Logic Controller, PLC Programming, Neural Networks, Perception Network, Intelligent Control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37902958 Analytical Model of Connection Establishment Duration Calculation in Wireless Networks
Authors: Y. Chaiko
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It is important to provide possibility of so called “handover" for the mobile subscriber from GSM network to Wi-Fi network and back. To solve specified problem it is necessary to estimate connection time between base station and wireless access point. Difficulty to estimate this parameter is that it doesn-t described in specifications of the standard and, hence, no recommended value is given. In this paper, the analytical model is presented that allows the estimating connection time between base station and IEEE 802.11 access point.Keywords: Access point, connection procedure, Wi-Fi network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17072957 Keyword Network Analysis on the Research Trends of Life-Long Education for People with Disabilities in Korea
Authors: Jakyoung Kim, Sungwook Jang
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The purpose of this study is to examine the research trends of life-long education for people with disabilities using a keyword network analysis. For this purpose, 151 papers were selected from 594 papers retrieved using keywords such as 'people with disabilities' and 'life-long education' in the Korean Education and Research Information Service. The Keyword network analysis was constructed by extracting and coding the keyword used in the title of the selected papers. The frequency of the extracted keywords, the centrality of degree, and betweenness was analyzed by the keyword network. The results of the keyword network analysis are as follows. First, the main keywords that appeared frequently in the study of life-long education for people with disabilities were 'people with disabilities', 'life-long education', 'developmental disabilities', 'current situations', 'development'. The research trends of life-long education for people with disabilities are focused on the current status of the life-long education and the program development. Second, the keyword network analysis and visualization showed that the keywords with high frequency of occurrences also generally have high degree centrality and betweenness centrality. In terms of the keyword network diagram, it was confirmed that research trends of life-long education for people with disabilities are centered on six prominent keywords. Based on these results, it was discussed that life-long education for people with disabilities in the future needs to expand the subjects and the supporting areas of the life-long education, and the research needs to be further expanded into more detailed and specific areas.Keywords: Life-long education, people with disabilities, research trends, keyword network analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12302956 Constant Factor Approximation Algorithm for p-Median Network Design Problem with Multiple Cable Types
Authors: Chaghoub Soraya, Zhang Xiaoyan
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This research presents the first constant approximation algorithm to the p-median network design problem with multiple cable types. This problem was addressed with a single cable type and there is a bifactor approximation algorithm for the problem. To the best of our knowledge, the algorithm proposed in this paper is the first constant approximation algorithm for the p-median network design with multiple cable types. The addressed problem is a combination of two well studied problems which are p-median problem and network design problem. The introduced algorithm is a random sampling approximation algorithm of constant factor which is conceived by using some random sampling techniques form the literature. It is based on a redistribution Lemma from the literature and a steiner tree problem as a subproblem. This algorithm is simple, and it relies on the notions of random sampling and probability. The proposed approach gives an approximation solution with one constant ratio without violating any of the constraints, in contrast to the one proposed in the literature. This paper provides a (21 + 2)-approximation algorithm for the p-median network design problem with multiple cable types using random sampling techniques.Keywords: Approximation algorithms, buy-at-bulk, combinatorial optimization, network design, p-median.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5782955 Design of Communication Primitives for Satellite Networks Management
Authors: Zhang Wenbo, Tian Ye, Sun Peigen, Xu Haifeng
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According to the mobility of the satellite network nodes and the characteristic of management domain dynamic partition in the satellite network, the login and logout mechanism of the satellite network dynamic management domain partition was proposed in the paper. In the mechanism, a ground branch-station sends the packets of login broadcasting to satellites in view. After received the packets, the SNMP agents on the satellites adopt link-delay test to respond. According to the mechanism, the SNMP primitives were extended, and the new added primitives were as follows: broadcasting, login, login confirmation,delay_testing, test responses, and logout. The definition of primitives, which followed RFC1157 criterion, could be encoded by the BER coding. The policy of the dynamic management domain partition on the basis of the login and logout mechanism, which was supported by the SNMP protocol, was realized by the design of the extended primitives.
Keywords: Satellites Network, network management, communication primitive, SNMP
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15452954 System Survivability in Networks in the Context of Defense/Attack Strategies: The Large Scale
Authors: A. Ben Yaghlane, M. N. Azaiez, M. Mrad
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We investigate the large scale of networks in the context of network survivability under attack. We use appropriate techniques to evaluate and the attacker-based- and the defenderbased- network survivability. The attacker is unaware of the operated links by the defender. Each attacked link has some pre-specified probability to be disconnected. The defender choice is so that to maximize the chance of successfully sending the flow to the destination node. The attacker however will select the cut-set with the highest chance to be disabled in order to partition the network. Moreover, we extend the problem to the case of selecting the best p paths to operate by the defender and the best k cut-sets to target by the attacker, for arbitrary integers p,k>1. We investigate some variations of the problem and suggest polynomial-time solutions.Keywords: Defense/attack strategies, large scale, networks, partitioning a network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14702953 EUDIS-An Encryption Scheme for User-Data Security in Public Networks
Authors: S. Balaji, M. Rajaram
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The method of introducing the proxy interpretation for sending and receiving requests increase the capability of the server and our approach UDIV (User-Data Identity Security) to solve the data and user authentication without extending size of the data makes better than hybrid IDS (Intrusion Detection System). And at the same time all the security stages we have framed have to pass through less through that minimize the response time of the request. Even though an anomaly detected, before rejecting it the proxy extracts its identity to prevent it to enter into system. In case of false anomalies, the request will be reshaped and transformed into legitimate request for further response. Finally we are holding the normal and abnormal requests in two different queues with own priorities.
Keywords: IDS, Data & User authentication, UDIS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18372952 Neural Network based Texture Analysis of Liver Tumor from Computed Tomography Images
Authors: K.Mala, V.Sadasivam, S.Alagappan
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Advances in clinical medical imaging have brought about the routine production of vast numbers of medical images that need to be analyzed. As a result an enormous amount of computer vision research effort has been targeted at achieving automated medical image analysis. Computed Tomography (CT) is highly accurate for diagnosing liver tumors. This study aimed to evaluate the potential role of the wavelet and the neural network in the differential diagnosis of liver tumors in CT images. The tumors considered in this study are hepatocellular carcinoma, cholangio carcinoma, hemangeoma and hepatoadenoma. Each suspicious tumor region was automatically extracted from the CT abdominal images and the textural information obtained was used to train the Probabilistic Neural Network (PNN) to classify the tumors. Results obtained were evaluated with the help of radiologists. The system differentiates the tumor with relatively high accuracy and is therefore clinically useful.
Keywords: Fuzzy c means clustering, texture analysis, probabilistic neural network, LVQ neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29712951 Studies on Determination of the Optimum Distance Between the Tmotes for Optimum Data Transfer in a Network with WLL Capability
Authors: N C Santhosh Kumar, N K Kishore
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Using mini modules of Tmotes, it is possible to automate a small personal area network. This idea can be extended to large networks too by implementing multi-hop routing. Linking the various Tmotes using Programming languages like Nesc, Java and having transmitter and receiver sections, a network can be monitored. It is foreseen that, depending on the application, a long range at a low data transfer rate or average throughput may be an acceptable trade-off. To reduce the overall costs involved, an optimum number of Tmotes to be used under various conditions (Indoor/Outdoor) is to be deduced. By analyzing the data rates or throughputs at various locations of Tmotes, it is possible to deduce an optimal number of Tmotes for a specific network. This paper deals with the determination of optimum distances to reduce the cost and increase the reliability of the entire sensor network with Wireless Local Loop (WLL) capability.
Keywords: Average throughput, data rate, multi-hop routing, optimum data transfer, throughput, Tmotes, wireless local loop.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13462950 Counterpropagation Neural Network for Solving Power Flow Problem
Authors: Jayendra Krishna, Laxmi Srivastava
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Power flow (PF) study, which is performed to determine the power system static states (voltage magnitudes and voltage angles) at each bus to find the steady state operating condition of a system, is very important and is the most frequently carried out study by power utilities for power system planning, operation and control. In this paper, a counterpropagation neural network (CPNN) is proposed to solve power flow problem under different loading/contingency conditions for computing bus voltage magnitudes and angles of the power system. The counterpropagation network uses a different mapping strategy namely counterpropagation and provides a practical approach for implementing a pattern mapping task, since learning is fast in this network. The composition of the input variables for the proposed neural network has been selected to emulate the solution process of a conventional power flow program. The effectiveness of the proposed CPNN based approach for solving power flow is demonstrated by computation of bus voltage magnitudes and voltage angles for different loading conditions and single line-outage contingencies in IEEE 14-bus system.Keywords: Admittance matrix, counterpropagation neural network, line outage contingency, power flow
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24172949 Metric Dimension on Line Graph of Honeycomb Networks
Authors: M. Hussain, Aqsa Farooq
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Let G = (V,E) be a connected graph and distance between any two vertices a and b in G is a−b geodesic and is denoted by d(a, b). A set of vertices W resolves a graph G if each vertex is uniquely determined by its vector of distances to the vertices in W. A metric dimension of G is the minimum cardinality of a resolving set of G. In this paper line graph of honeycomb network has been derived and then we calculated the metric dimension on line graph of honeycomb network.Keywords: Resolving set, metric dimension, honeycomb network, line graph.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7502948 Analyzing Environmental Emotive Triggers in Terrorist Propaganda
Authors: Travis Morris
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The purpose of this study is to measure the intersection of environmental security entities in terrorist propaganda. To the best of author’s knowledge, this is the first study of its kind to examine this intersection within terrorist propaganda. Rosoka, natural language processing software and frame analysis are used to advance our understanding of how environmental frames function as emotive triggers. Violent jihadi demagogues use frames to suggest violent and non-violent solutions to their grievances. Emotive triggers are framed in a way to leverage individual and collective attitudes in psychological warfare. A comparative research design is used because of the differences and similarities that exist between two variants of violent jihadi propaganda that target western audiences. Analysis is based on salience and network text analysis, which generates violent jihadi semantic networks. Findings indicate that environmental frames are used as emotive triggers across both data sets, but also as tactical and information data points. A significant finding is that certain core environmental emotive triggers like “water,” “soil,” and “trees” are significantly salient at the aggregate level across both data sets. All environmental entities can be classified into two categories, symbolic and literal. Importantly, this research illustrates how demagogues use environmental emotive triggers in cyber space from a subcultural perspective to mobilize target audiences to their ideology and praxis. Understanding the anatomy of propaganda construction is necessary in order to generate effective counter narratives in information operations. This research advances an additional method to inform practitioners and policy makers of how environmental security and propaganda intersect.
Keywords: Emotive triggers, environmental security, natural language processing, propaganda analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9432947 Recurrent Neural Network Based Fuzzy Inference System for Identification and Control of Dynamic Plants
Authors: Rahib Hidayat Abiyev
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23642946 Automatic Removal of Ocular Artifacts using JADE Algorithm and Neural Network
Authors: V Krishnaveni, S Jayaraman, A Gunasekaran, K Ramadoss
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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).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18732945 Strategies and Compromises: Towards an Integrated Energy and Climate Policy for Egypt
Authors: S.T. El Sheltawy, A. A. Refaat
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Until recently, energy security and climate change were considered separate issues to be dealt with by policymakers. The two issues are now converging, challenging the security and climate communities to develop a better understanding of how to deal with both issues simultaneously. Although Egypt is not a major contributor to the world's total GHG emissions, it is particularly vulnerable to the potential effects of global climate change such as rising sea levels and changed patterns of rainfall in the Nile Basin. Climate change is a major threat to sustainable growth and development in Egypt, and the achievement of the Millennium Development Goals. Egypt-s capacity to respond to the challenges of climate instability will be expanded by improving overall resilience, integrating climate change goals into sustainable development strategies, increasing the use of modern energy systems with reduced carbon intensity, and strengthening international initiatives. This study seeks to establish a framework for considering the complex and evolving links between energy security and climate change, applicable to Egypt.Keywords: climate change, climate policy, cnergy policy, energy security, sustainable development
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17752944 Smart Grid Communication Architecture Modeling for Heterogeneous Network Based Advanced Metering Infrastructure
Authors: S. Prem Kumar, H. Thameemul Ansari, V. Saminadan
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A smart grid is an emerging technology in the power delivery system which provides an intelligent, self-recovery and homeostatic grid in delivering power to the users. Smart grid communication network provides transmission capacity for information transformation within the connected nodes in the network, in favor of functional and operational needs. In the electric grids communication network delay is based on choosing the appropriate technology and the types of devices enforced. In distinction, the combination of IEEE 802.16 based WiMAX and IEEE 802.11 based WiFi technologies provides improved coverage and gives low delay performances to meet the smart grid needs. By incorporating this method in Wide Area Monitoring System (WAMS) and Advanced Metering Infrastructure (AMI) the performance of the smart grid will be considerably improved. This work deals with the implementation of WiMAX-WLAN integrated network architecture for WAMS and AMI in the smart grid.Keywords: WiMAX, WLAN, WAMS, Smart Grid, HetNet, AMI.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10042943 A Comparison between Artificial Neural Network Prediction Models for Coronal Hole Related High-Speed Streams
Authors: Rehab Abdulmajed, Amr Hamada, Ahmed Elsaid, Hisashi Hayakawa, Ayman Mahrous
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Solar emissions have a high impact on the Earth’s magnetic field, and the prediction of solar events is of high interest. Various techniques have been used in the prediction of the solar wind using mathematical models, MHD models and neural network (NN) models. This study investigates the coronal hole (CH) derived high-speed streams (HSSs) and their correlation to the CH area and create a neural network model to predict the HSSs. Two different algorithms were used to compare different models to find a model that best simulated the HSSs. A dataset of CH synoptic maps through Carrington rotations 1601 to 2185 along with Omni-data set solar wind speed averaged over the Carrington rotations is used, which covers Solar Cycles (SC) 21, 22, 23, and most of 24.
Keywords: Artificial Neural Network, ANN, Coronal Hole Area Feed-Forward neural network models, solar High-Speed Streams, HSSs.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 942942 Adaptive Neural Network Control of Autonomous Underwater Vehicles
Authors: Ahmad Forouzantabar, Babak Gholami, Mohammad Azadi
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An adaptive neural network controller for autonomous underwater vehicles (AUVs) is presented in this paper. The AUV model is highly nonlinear because of many factors, such as hydrodynamic drag, damping, and lift forces, Coriolis and centripetal forces, gravity and buoyancy forces, as well as forces from thruster. In this regards, a nonlinear neural network is used to approximate the nonlinear uncertainties of AUV dynamics, thus overcoming some limitations of conventional controllers and ensure good performance. The uniform ultimate boundedness of AUV tracking errors and the stability of the proposed control system are guaranteed based on Lyapunov theory. Numerical simulation studies for motion control of an AUV are performed to demonstrate the effectiveness of the proposed controller.Keywords: Autonomous Underwater Vehicle (AUV), Neural Network Controller, Composite Adaptation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25132941 Zero-knowledge-like Proof of Cryptanalysis of Bluetooth Encryption
Authors: Eric Filiol
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This paper presents a protocol aiming at proving that an encryption system contains structural weaknesses without disclosing any information on those weaknesses. A verifier can check in a polynomial time that a given property of the cipher system output has been effectively realized. This property has been chosen by the prover in such a way that it cannot been achieved by known attacks or exhaustive search but only if the prover indeed knows some undisclosed weaknesses that may effectively endanger the cryptosystem security. This protocol has been denoted zero-knowledge-like proof of cryptanalysis. In this paper, we apply this protocol to the Bluetooth core encryption algorithm E0, used in many mobile environments and thus we suggest that its security can seriously be put into question.
Keywords: Bluetooth encryption, Bluetooth security, Bluetoothprotocol, Stream cipher, Zero-knowledge, Cryptanalysis
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15552940 MPPT Operation for PV Grid-connected System using RBFNN and Fuzzy Classification
Authors: A. Chaouachi, R. M. Kamel, K. Nagasaka
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This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW Photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three Radial Basis Function Neural Networks (RBFNN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated RBFNN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology, comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and non-linear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network.
Keywords: MPPT, neuro-fuzzy, RBFN, grid-connected, photovoltaic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31692939 A Comprehensive Survey on RAT Selection Algorithms for Heterogeneous Networks
Authors: Abdallah AL Sabbagh, Robin Braun, Mehran Abolhasan
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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).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20142938 Artificial Neural Networks for Cognitive Radio Network: A Survey
Authors: Vishnu Pratap Singh Kirar
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The main aim of a communication system is to achieve maximum performance. In Cognitive Radio any user or transceiver has ability to sense best suitable channel, while channel is not in use. It means an unlicensed user can share the spectrum of a licensed user without any interference. Though, the spectrum sensing consumes a large amount of energy and it can reduce by applying various artificial intelligent methods for determining proper spectrum holes. It also increases the efficiency of Cognitive Radio Network (CRN). In this survey paper we discuss the use of different learning models and implementation of Artificial Neural Network (ANN) to increase the learning and decision making capacity of CRN without affecting bandwidth, cost and signal rate.
Keywords: Artificial Neural Network, Cognitive Radio, Cognitive Radio Networks, Back Propagation, Spectrum Sensing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 40922937 Modeling of Co-Cu Elution From Clinoptilolite using Neural Network
Authors: John Kabuba, Antoine Mulaba-Bafubiandi
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14092936 Performance Evaluation of Packet Scheduling with Channel Conditioning Aware Based On WiMAX Networks
Authors: Elmabruk Laias, Abdalla M. Hanashi, Mohammed Alnas
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Worldwide Interoperability for Microwave Access (WiMAX) became one of the most challenging issues, since it was responsible for distributing available resources of the network among all users this leaded to the demand of constructing and designing high efficient scheduling algorithms in order to improve the network utilization, to increase the network throughput, and to minimize the end-to-end delay. In this study, the proposed algorithm focuses on an efficient mechanism to serve non_real time traffic in congested networks by considering channel status.
Keywords: WiMAX, Quality of Services (QoS), OPNE, Diff-Serv (DS).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18212935 Integrating Low and High Level Object Recognition Steps
Authors: András Barta, István Vajk
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14712934 Optimal Compensation of Reactive Power in the Restructured Distribution Network
Authors: Atefeh Pourshafie, Mohsen. Saniei, S. S. Mortazavi, A. Saeedian
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21092933 Food Security in the Middle East and North Africa
Authors: Sara D. Garduño-Diaz, Philippe Y. Garduño-Diaz
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To date, one of the few comprehensive indicators for the measurement of food security is the Global Food Security Index (GFSI). This index is a dynamic quantitative and qualitative benchmarking model, constructed from 28 unique indicators, that measures drivers of food security across both developing and developed countries. Whereas the GFSI has been calculated across a set of 109 countries, in this paper we aim to present and compare, for the Middle East and North Africa (MENA), 1) the Food Security Index scores achieved and 2) the data available on affordability, availability, and quality of food. The data for this work was taken from the latest available report published by the creators of the GFSI, which in turn used information from national and international statistical sources. MENA countries rank from place 17/109 (Israel, although with resent political turmoil this is likely to have changed) to place 91/109 (Yemen) with household expenditure spent in food ranging from 15.5% (Israel) to 60% (Egypt). Lower spending on food as a share of household consumption in most countries and better food safety net programs in the MENA have contributed to a notable increase in food affordability. The region has also, however, experienced a decline in food availability, owing to more limited food supplies and higher volatility of agricultural production. In terms of food quality and safety the MENA has the top ranking country (Israel). The most frequent challenges faced by the countries of the MENA include public expenditure on agricultural research and development as well as volatility of agricultural production. Food security is a complex phenomenon that interacts with many other indicators of a country’s wellbeing; in the MENA it is slowly but markedly improving.
Keywords: Diet, food insecurity, global food security index, nutrition, sustainability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3976