Search results for: sparse networks
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1928

Search results for: sparse networks

398 A High Accuracy Measurement Circuit for Soil Moisture Detection

Authors: Sheroz Khan, A. H. M. Zahirul Alam, Othman O. Khalifa, Mohd Rafiqul Islam, Zuraidah Zainudin, Muzna S. Khan, Nurul Iman Muhamad Pauzi

Abstract:

The study of soil for agriculture purposes has remained the main focus of research since the beginning of civilization as humans- food related requirements remained closely linked with the soil. The study of soil has generated an interest among the researchers for very similar other reasons including transmission, reflection and refraction of signals for deploying wireless underground sensor networks or for the monitoring of objects on (or in ) soil in the form of better understanding of soil electromagnetic characteristics properties. The moisture content has been very instrumental in such studies as it decides on the resistance of the soil, and hence the attenuation on signals traveling through soil or the attenuation the signals may suffer upon their impact on soil. This work is related testing and characterizing a measurement circuit meant for the detection of moisture level content in soil.

Keywords: Analog–digital Conversion, Bridge Circuits, Intelligent sensors, Pulse Time Modulation, Relaxation Oscillator

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397 Mobile Velocity Based Bidirectional Call Overflow Scheme in Hierarchical Cellular System

Authors: G. M. Mir, Moinuddin, N. A. Shah

Abstract:

In the age of global communications, heterogeneous networks are seen to be the best choice of strategy to ensure continuous and uninterruptible services. This will allow mobile terminal to stay in connection even they are migrating into different segment coverage through the handoff process. With the increase of teletraffic demands in mobile cellular system, hierarchical cellular systems have been adopted extensively for more efficient channel utilization and better QoS (Quality of Service). This paper presents a bidirectional call overflow scheme between two layers of microcells and macrocells, where handoffs are decided by the velocity of mobile making the call. To ensure that handoff calls are given higher priorities, it is assumed that guard channels are assigned in both macrocells and microcells. A hysteresis value introduced in mobile velocity is used to allow mobile roam in the same cell if its velocity changes back within the set threshold values. By doing this the number of handoffs is reduced thereby reducing the processing overhead and enhancing the quality of service to the end user.

Keywords: Hierarchical cellular systems, hysteresis, overflow, threshold.

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396 A Fuzzy Swarm Optimized Approach for Piece Selection in Bit Torrent Like Peer to Peer Network

Authors: M. Padmavathi, R. M. Suresh

Abstract:

Every machine plays roles of client and server simultaneously in a peer-to-peer (P2P) network. Though a P2P network has many advantages over traditional client-server models regarding efficiency and fault-tolerance, it also faces additional security threats. Users/IT administrators should be aware of risks from malicious code propagation, downloaded content legality, and P2P software’s vulnerabilities. Security and preventative measures are a must to protect networks from potential sensitive information leakage and security breaches. Bit Torrent is a popular and scalable P2P file distribution mechanism which successfully distributes large files quickly and efficiently without problems for origin server. Bit Torrent achieved excellent upload utilization according to measurement studies, but it also raised many questions as regards utilization in settings, than those measuring, fairness, and Bit Torrent’s mechanisms choice. This work proposed a block selection technique using Fuzzy ACO with optimal rules selected using ACO.

Keywords: Ant Colony Optimization (ACO), Bit Torrent, Download time, Peer-to-Peer (P2P) network, Performance.

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395 Linking OpenCourseWares and Open Education Resources: Creating an Effective Search and Recommendation System

Authors: Brett E. Shelton, Joel Duffin, Yuxuan Wang, Justin Ball

Abstract:

With a growing number of digital libraries and other open education repositories being made available throughout the world, effective search and retrieval tools are necessary to access the desired materials that surpass the effectiveness of traditional, allinclusive search engines. This paper discusses the design and use of Folksemantic, a platform that integrates OpenCourseWare search, Open Educational Resource recommendations, and social network functionality into a single open source project. The paper describes how the system was originally envisioned, its goals for users, and data that provides insight into how it is actually being used. Data sources include website click-through data, query logs, web server log files and user account data. Based on a descriptive analysis of its current use, modifications to the platform's design are recommended to better address goals of the system, along with recommendations for additional phases of research.

Keywords: Digital libraries, open education, recommendation system, social networks

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394 Unscented Transformation for Estimating the Lyapunov Exponents of Chaotic Time Series Corrupted by Random Noise

Authors: K. Kamalanand, P. Mannar Jawahar

Abstract:

Many systems in the natural world exhibit chaos or non-linear behavior, the complexity of which is so great that they appear to be random. Identification of chaos in experimental data is essential for characterizing the system and for analyzing the predictability of the data under analysis. The Lyapunov exponents provide a quantitative measure of the sensitivity to initial conditions and are the most useful dynamical diagnostic for chaotic systems. However, it is difficult to accurately estimate the Lyapunov exponents of chaotic signals which are corrupted by a random noise. In this work, a method for estimation of Lyapunov exponents from noisy time series using unscented transformation is proposed. The proposed methodology was validated using time series obtained from known chaotic maps. In this paper, the objective of the work, the proposed methodology and validation results are discussed in detail.

Keywords: Lyapunov exponents, unscented transformation, chaos theory, neural networks.

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393 Web Personalization to Build Trust in E-Commerce: A Design Science Approach

Authors: Choon Ling Sia, Yani Shi, Jiaqi Yan, Huaping Chen

Abstract:

With the development of the Internet, E-commerce is growing at an exponential rate, and lots of online stores are built up to sell their goods online. A major factor influencing the successful adoption of E-commerce is consumer-s trust. For new or unknown Internet business, consumers- lack of trust has been cited as a major barrier to its proliferation. As web sites provide key interface for consumer use of E-Commerce, we investigate the design of web site to build trust in E-Commerce from a design science approach. A conceptual model is proposed in this paper to describe the ontology of online transaction and human-computer interaction. Based on this conceptual model, we provide a personalized webpage design approach using Bayesian networks learning method. Experimental evaluation are designed to show the effectiveness of web personalization in improving consumer-s trust in new or unknown online store.

Keywords: Trust, Web site design, Human-ComputerInteraction, E-Commerce, Design science, Bayesian network.

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392 Solar-Inducted Cluster Head Relocation Algorithm

Authors: Goran Djukanovic, Goran Popovic

Abstract:

A special area in the study of Wireless Sensor Networks (WSNs) is how to move sensor nodes, as it expands the scope of application of wireless sensors and provides new opportunities to improve network performance. On the other side, it opens a set of new problems, especially if complete clusters are mobile. Node mobility can prolong the network lifetime. In such WSN, some nodes are possibly moveable or nomadic (relocated periodically), while others are static. This paper presents an idea of mobile, solar-powered CHs that relocate themselves inside clusters in such a way that the total energy consumption in the network reduces, and the lifetime of the network extends. Positioning of CHs is made in each round based on selfish herd hypothesis, where leader retreats to the center of gravity. Based on this idea, an algorithm, together with its modified version, has been presented and tested in this paper. Simulation results show that both algorithms have benefits in network lifetime, and prolongation of network stability period duration.

Keywords: CH-active algorithm, mobile cluster head, sensors, wireless sensor network.

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391 Hybridized Technique to Analyze Workstress Related Data via the StressCafé

Authors: Anusua Ghosh, Andrew Nafalski, Jeffery Tweedale, Maureen Dollard

Abstract:

This paper presents anapproach of hybridizing two or more artificial intelligence (AI) techniques which arebeing used to fuzzify the workstress level ranking and categorize the rating accordingly. The use of two or more techniques (hybrid approach) has been considered in this case, as combining different techniques may lead to neutralizing each other-s weaknesses generating a superior hybrid solution. Recent researches have shown that there is a need for a more valid and reliable tools, for assessing work stress. Thus artificial intelligence techniques have been applied in this instance to provide a solution to a psychological application. An overview about the novel and autonomous interactive model for analysing work-stress that has been developedusing multi-agent systems is also presented in this paper. The establishment of the intelligent multi-agent decision analyser (IMADA) using hybridized technique of neural networks and fuzzy logic within the multi-agent based framework is also described.

Keywords: Fuzzy logic, intelligent agent, multi-agent systems, neural network, workplace stress.

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390 Proteins Length and their Phenotypic Potential

Authors: Tom Snir, Eitan Rubin

Abstract:

Mendelian Disease Genes represent a collection of single points of failure for the various systems they constitute. Such genes have been shown, on average, to encode longer proteins than 'non-disease' proteins. Existing models suggest that this results from the increased likeli-hood of longer genes undergoing mutations. Here, we show that in saturated mutagenesis experiments performed on model organisms, where the likelihood of each gene mutating is one, a similar relationship between length and the probability of a gene being lethal was observed. We thus suggest an extended model demonstrating that the likelihood of a mutated gene to produce a severe phenotype is length-dependent. Using the occurrence of conserved domains, we bring evidence that this dependency results from a correlation between protein length and the number of functions it performs. We propose that protein length thus serves as a proxy for protein cardinality in different networks required for the organism's survival and well-being. We use this example to argue that the collection of Mendelian Disease Genes can, and should, be used to study the rules governing systems vulnerability in living organisms.

Keywords: Systems Biology, Protein Length

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389 Modern Spectrum Sensing Techniques for Cognitive Radio Networks: Practical Implementation and Performance Evaluation

Authors: Antoni Ivanov, Nikolay Dandanov, Nicole Christoff, Vladimir Poulkov

Abstract:

Spectrum underutilization has made cognitive radio a promising technology both for current and future telecommunications. This is due to the ability to exploit the unused spectrum in the bands dedicated to other wireless communication systems, and thus, increase their occupancy. The essential function, which allows the cognitive radio device to perceive the occupancy of the spectrum, is spectrum sensing. In this paper, the performance of modern adaptations of the four most widely used spectrum sensing techniques namely, energy detection (ED), cyclostationary feature detection (CSFD), matched filter (MF) and eigenvalues-based detection (EBD) is compared. The implementation has been accomplished through the PlutoSDR hardware platform and the GNU Radio software package in very low Signal-to-Noise Ratio (SNR) conditions. The optimal detection performance of the examined methods in a realistic implementation-oriented model is found for the common relevant parameters (number of observed samples, sensing time and required probability of false alarm).

Keywords: Cognitive radio, dynamic spectrum access, GNU Radio, spectrum sensing.

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388 Toward an Open Network Business Approach

Authors: Valentina Ndou, Laura Schina, Giuseppina Passiante, Pasquale Del Vecchio, Marco De Maggio

Abstract:

The aim of this paper is to propose a dynamic integrated approach, based on modularity concept and on the business ecosystem approach, that exploit different eBusiness services for SMEs under an open business network platform. The adoption of this approach enables firms to collaborate locally for delivering the best product/service to the customers as well as globally by accessing international markets, interrelate directly with the customers, create relationships and collaborate with worldwide actors. The paper will be structured as following: We will start by offering an overview of the state of the art of eBusiness platforms among SME of food and tourism firms and then we discuss the main drawbacks that characterize them. The digital business ecosystem approach and the modularity concept will be described as the theoretical ground in which our proposed integrated model is rooted. Finally, the proposed model along with a discussion of the main value creation potentialities it might create for SMEs will be presented.

Keywords: component, Complexity; Digital Business Ecosystem, e Business Platforms, Modularity, Networks.

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387 Computational Fluid Dynamics Expert System using Artificial Neural Networks

Authors: Gonzalo Rubio, Eusebio Valero, Sven Lanzan

Abstract:

The design of a modern aircraft is based on three pillars: theoretical results, experimental test and computational simulations. As a results of this, Computational Fluid Dynamic (CFD) solvers are widely used in the aeronautical field. These solvers require the correct selection of many parameters in order to obtain successful results. Besides, the computational time spent in the simulation depends on the proper choice of these parameters. In this paper we create an expert system capable of making an accurate prediction of the number of iterations and time required for the convergence of a computational fluid dynamic (CFD) solver. Artificial neural network (ANN) has been used to design the expert system. It is shown that the developed expert system is capable of making an accurate prediction the number of iterations and time required for the convergence of a CFD solver.

Keywords: Artificial Neural Network, Computational Fluid Dynamics, Optimization

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386 Identification of Optimum Parameters of Deep Drawing of a Cylindrical Workpiece using Neural Network and Genetic Algorithm

Authors: D. Singh, R. Yousefi, M. Boroushaki

Abstract:

Intelligent deep-drawing is an instrumental research field in sheet metal forming. A set of 28 different experimental data have been employed in this paper, investigating the roles of die radius, punch radius, friction coefficients and drawing ratios for axisymmetric workpieces deep drawing. This paper focuses an evolutionary neural network, specifically, error back propagation in collaboration with genetic algorithm. The neural network encompasses a number of different functional nodes defined through the established principles. The input parameters, i.e., punch radii, die radii, friction coefficients and drawing ratios are set to the network; thereafter, the material outputs at two critical points are accurately calculated. The output of the network is used to establish the best parameters leading to the most uniform thickness in the product via the genetic algorithm. This research achieved satisfactory results based on demonstration of neural networks.

Keywords: Deep-drawing, Neural network, Genetic algorithm, Sheet metal forming.

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385 The Effects of Multipath on OFDM Systems for Broadband Power-Line Communications a Case of Medium Voltage Channel

Authors: Justinian Anatory, N. Theethayi, R. Thottappillil, C. Mwase, N.H. Mvungi

Abstract:

Power-line networks are widely used today for broadband data transmission. However, due to multipaths within the broadband power line communication (BPLC) systems owing to stochastic changes in the network load impedances, branches, etc., network or channel capacity performances are affected. This paper attempts to investigate the performance of typical medium voltage channels that uses Orthogonal Frequency Division Multiplexing (OFDM) techniques with Quadrature Amplitude Modulation (QAM) sub carriers. It has been observed that when the load impedances are different from line characteristic impedance channel performance decreases. Also as the number of branches in the link between the transmitter and receiver increases a loss of 4dB/branch is found in the signal to noise ratio (SNR). The information presented in the paper could be useful for an appropriate design of the BPLC systems.

Keywords: Communication channel model, Power-line communication, Transfer function, Multipath, Branched network, OFDM, QAM, performance evaluation

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384 Power-Efficient AND-EXOR-INV Based Realization of Achilles' heel Logic Functions

Authors: Padmanabhan Balasubramanian, R. Chinnadurai

Abstract:

This paper deals with a power-conscious ANDEXOR- Inverter type logic implementation for a complex class of Boolean functions, namely Achilles- heel functions. Different variants of the above function class have been considered viz. positive, negative and pure horn for analysis and simulation purposes. The proposed realization is compared with the decomposed implementation corresponding to an existing standard AND-EXOR logic minimizer; both result in Boolean networks with good testability attribute. It could be noted that an AND-OR-EXOR type logic network does not exist for the positive phase of this unique class of logic function. Experimental results report significant savings in all the power consumption components for designs based on standard cells pertaining to a 130nm UMC CMOS process The simulations have been extended to validate the savings across all three library corners (typical, best and worst case specifications).

Keywords: Achilles' heel functions, AND-EXOR-Inverter logic, CMOS technology, low power design.

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383 Bias Optimization of Mach-Zehnder Modulator Considering RF Gain on OFDM Radio-Over-Fiber System

Authors: Ghazi Al Sukkar, Yazid Khattabi, Shifen Zhong

Abstract:

Most of the recent wireless LANs, broadband access networks, and digital broadcasting use Orthogonal Frequency Division Multiplexing techniques. In addition, the increasing demand of Data and Internet makes fiber optics an important technology, as fiber optics has many characteristics that make it the best solution for transferring huge frames of Data from a point to another. Radio over fiber is the place where high quality RF is converted to optical signals over single mode fiber. Optimum values for the bias level and the switching voltage for Mach-Zehnder modulator are important for the performance of radio over fiber links. In this paper, we propose a method to optimize the two parameters simultaneously; the bias and the switching voltage point of the external modulator of a radio over fiber system considering RF gain. Simulation results show the optimum gain value under these two parameters.

Keywords: OFDM, Mach Zehnder Bias Voltage, switching voltage, radio-over-fiber, RF gain.

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382 Detection of Max. Optical Gain by Erbium Doped Fiber Amplifier

Authors: Abdulamgid.T. Bouzed, Suleiman. M. Elhamali

Abstract:

The technical realization of data transmission using glass fiber began after the development of diode laser in year 1962. The erbium doped fiber amplifiers (EDFA's) in high speed networks allow information to be transmitted over longer distances without using of signal amplification repeaters. These kinds of fibers are doped with erbium atoms which have energy levels in its atomic structure for amplifying light at 1550nm. When a carried signal wave at 1550nm enters the erbium fiber, the light stimulates the excited erbium atoms which pumped with laser beam at 980nm as additional light. The wavelength and intensity of the semiconductor lasers depend on the temperature of active zone and the injection current. The present paper shows the effect of the diode lasers temperature and injection current on the optical amplification. From the results of in- and output power one may calculate the max. optical gain by erbium doped fiber amplifier.

Keywords: Amplifier, erbium doped fiber, gain, lasers, temperature.

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381 The Relationship between Depression Interpersonal Communication and Media Using Among International Students

Authors: Birol Gülnar, Hacer Aker

Abstract:

Student-s movements have been going increasing in last decades. International students can have different psychological and sociological problems in their adaptation process. Depression is one of the most important problems in this procedure. This research purposed to reveal level of foreign students- depression, kinds of interpersonal communication networks (host/ethnic interpersonal communication) and media usage (host/ethnic media usage). Additionally study aimed to display the relationship between depression and communication (host/ethnic interpersonal communication and host/ethnic media usage) among foreign university students. A field research was performed among 283 foreign university students who have been attending 8 different universities in Turkey. A purposeful sampling technique was used in this research cause of data collect facilities. Results indicated that 58.3% of foreign students- depression stage was “intermediate" while 33.2% of foreign students- depression level was “low". Add to this, host interpersonal communication behaviors and Turkish web sites usages were negatively and significantly correlated with depression.

Keywords: International students, depression, interpersonal communication behaviors, media using.

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380 Predicting Extrusion Process Parameters Using Neural Networks

Authors: Sachin Man Bajimaya, SangChul Park, Gi-Nam Wang

Abstract:

The objective of this paper is to estimate realistic principal extrusion process parameters by means of artificial neural network. Conventionally, finite element analysis is used to derive process parameters. However, the finite element analysis of the extrusion model does not consider the manufacturing process constraints in its modeling. Therefore, the process parameters obtained through such an analysis remains highly theoretical. Alternatively, process development in industrial extrusion is to a great extent based on trial and error and often involves full-size experiments, which are both expensive and time-consuming. The artificial neural network-based estimation of the extrusion process parameters prior to plant execution helps to make the actual extrusion operation more efficient because more realistic parameters may be obtained. And so, it bridges the gap between simulation and real manufacturing execution system. In this work, a suitable neural network is designed which is trained using an appropriate learning algorithm. The network so trained is used to predict the manufacturing process parameters.

Keywords: Artificial Neural Network (ANN), Indirect Extrusion, Finite Element Analysis, MES.

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379 Reference Model for the Implementation of an E-Commerce Solution in Peruvian SMEs in the Retail Sector

Authors: Julio Kauss, Miguel Cadillo, David Mauricio

Abstract:

E-commerce is a business model that allows companies to optimize the processes of buying, selling, transferring goods and exchanging services through computer networks or the Internet. In Peru, the electronic commerce is used infrequently. This situation is due, in part to the fact that there is no model that allows companies to implement an e-commerce solution, which means that most SMEs do not have adequate knowledge to adapt to electronic commerce. In this work, a reference model is proposed for the implementation of an e-commerce solution in Peruvian SMEs in the retail sector. It consists of five phases: Business Analysis, Business Modeling, Implementation, Post Implementation and Results. The present model was validated in a SME of the Peruvian retail sector through the implementation of an electronic commerce platform, through which the company increased its sales through the delivery channel by 10% in the first month of deployment. This result showed that the model is easy to implement, is economical and agile. In addition, it allowed the company to increase its business offer, adapt to e-commerce and improve customer loyalty.

Keywords: E-commerce, retail, SMEs, reference model.

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378 Detecting Defects in Textile Fabrics with Optimal Gabor Filters

Authors: K. L. Mak, P. Peng

Abstract:

This paper investigates the problem of automated defect detection for textile fabrics and proposes a new optimal filter design method to solve this problem. Gabor Wavelet Network (GWN) is chosen as the major technique to extract the texture features from textile fabrics. Based on the features extracted, an optimal Gabor filter can be designed. In view of this optimal filter, a new semi-supervised defect detection scheme is proposed, which consists of one real-valued Gabor filter and one smoothing filter. The performance of the scheme is evaluated by using an offline test database with 78 homogeneous textile images. The test results exhibit accurate defect detection with low false alarm, thus showing the effectiveness and robustness of the proposed scheme. To evaluate the detection scheme comprehensively, a prototyped detection system is developed to conduct a real time test. The experiment results obtained confirm the efficiency and effectiveness of the proposed detection scheme.

Keywords: Defect detection, Filtering, Gabor function, Gaborwavelet networks, Textile fabrics.

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377 Video-On-Demand QoE Evaluation across Different Age-Groups and Its Significance for Network Capacity

Authors: Mujtaba Roshan, John A. Schormans

Abstract:

Quality of Experience (QoE) drives churn in the broadband networks industry, and good QoE plays a large part in the retention of customers. QoE is known to be affected by the Quality of Service (QoS) factors packet loss probability (PLP), delay and delay jitter caused by the network. Earlier results have shown that the relationship between these QoS factors and QoE is non-linear, and may vary from application to application. We use the network emulator Netem as the basis for experimentation, and evaluate how QoE varies as we change the emulated QoS metrics. Focusing on Video-on-Demand, we discovered that the reported QoE may differ widely for users of different age groups, and that the most demanding age group (the youngest) can require an order of magnitude lower PLP to achieve the same QoE than is required by the most widely studied age group of users. We then used a bottleneck TCP model to evaluate the capacity cost of achieving an order of magnitude decrease in PLP, and found it be (almost always) a 3-fold increase in link capacity that was required.

Keywords: Quality of experience, quality of service, packet loss probability, network capacity.

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376 A Signature-Based Secure Authentication Framework for Vehicular Ad Hoc Networks

Authors: J. Jenefa, E. A. Mary Anita

Abstract:

Vehicular Ad hoc NETwork (VANET) is a kind of Mobile Ad hoc NETwork (MANET). It allows the vehicles to communicate with one another as well as with nearby Road Side Units (RSU) and Regional Trusted Authorities (RTA). Vehicles communicate through On-Board Units (OBU) in which privacy has to be assured which will avoid the misuse of private data. A secure authentication framework for VANETs is proposed in which Public Key Cryptography (PKC) based adaptive pseudonym scheme is used to generate self-generated pseudonyms. Self-generated pseudonyms are used instead of real IDs for privacy preservation and non-repudiation. The ID-Based Signature (IBS) and ID-Based Online/Offline Signature (IBOOS) schemes are used for authentication. IBS is used to authenticate between vehicle and RSU whereas IBOOS provides authentication among vehicles. Security attacks like impersonation attack in the network are resolved and the attacking nodes are rejected from the network, thereby ensuring secure communication among the vehicles in the network. Simulation results shows that the proposed system provides better authentication in VANET environment.

Keywords: Non-repudiation, privacy preservation, public key cryptography, self- generated pseudonym.

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375 Integrating Decision Tree and Spatial Cluster Analysis for Landslide Susceptibility Zonation

Authors: Chien-Min Chu, Bor-Wen Tsai, Kang-Tsung Chang

Abstract:

Landslide susceptibility map delineates the potential zones for landslide occurrence. Previous works have applied multivariate methods and neural networks for mapping landslide susceptibility. This study proposed a new approach to integrate decision tree model and spatial cluster statistic for assessing landslide susceptibility spatially. A total of 2057 landslide cells were digitized for developing the landslide decision tree model. The relationships of landslides and instability factors were explicitly represented by using tree graphs in the model. The local Getis-Ord statistics were used to cluster cells with high landslide probability. The analytic result from the local Getis-Ord statistics was classed to create a map of landslide susceptibility zones. The map was validated using new landslide data with 482 cells. Results of validation show an accuracy rate of 86.1% in predicting new landslide occurrence. This indicates that the proposed approach is useful for improving landslide susceptibility mapping.

Keywords: Landslide susceptibility Zonation, Decision treemodel, Spatial cluster, Local Getis-Ord statistics.

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374 Machine Learning Methods for Flood Hazard Mapping

Authors: S. Zappacosta, C. Bove, M. Carmela Marinelli, P. di Lauro, K. Spasenovic, L. Ostano, G. Aiello, M. Pietrosanto

Abstract:

This paper proposes a neural network approach for assessing flood hazard mapping. The core of the model is a machine learning component fed by frequency ratios, namely statistical correlations between flood event occurrences and a selected number of topographic properties. The classification capability was compared with the flood hazard mapping River Basin Plans (Piani Assetto Idrogeologico, acronimed as PAI) designed by the Italian Institute for Environmental Research and Defence, ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale), encoding four different increasing flood hazard levels. The study area of Piemonte, an Italian region, has been considered without loss of generality. The frequency ratios may be used as a standalone block to model the flood hazard mapping. Nevertheless, the mixture with a neural network improves the classification power of several percentage points, and may be proposed as a basic tool to model the flood hazard map in a wider scope.

Keywords: flood modeling, hazard map, neural networks, hydrogeological risk, flood risk assessment

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373 Coerced Delay and Multi Additive Constraints QoS Routing Schemes

Authors: P.S. Prakash, S. Selvan

Abstract:

IP networks are evolving from data communication infrastructure into many real-time applications such as video conferencing, IP telephony and require stringent Quality of Service (QoS) requirements. A rudimentary issue in QoS routing is to find a path between a source-destination pair that satisfies two or more endto- end constraints and termed to be NP hard or complete. In this context, we present an algorithm Multi Constraint Path Problem Version 3 (MCPv3), where all constraints are approximated and return a feasible path in much quicker time. We present another algorithm namely Delay Coerced Multi Constrained Routing (DCMCR) where coerce one constraint and approximate the remaining constraints. Our algorithm returns a feasible path, if exists, in polynomial time between a source-destination pair whose first weight satisfied by the first constraint and every other weight is bounded by remaining constraints by a predefined approximation factor (a). We present our experimental results with different topologies and network conditions.

Keywords: Routing, Quality-of-Service (QoS), additive constraints, shortest path, delay coercion.

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372 Intelligent Agent Approach to the Control of Critical Infrastructure Networks

Authors: James D. Gadze, Niki Pissinou, Kia Makki

Abstract:

In this paper we propose an intelligent agent approach to control the electric power grid at a smaller granularity in order to give it self-healing capabilities. We develop a method using the influence model to transform transmission substations into information processing, analyzing and decision making (intelligent behavior) units. We also develop a wireless communication method to deliver real-time uncorrupted information to an intelligent controller in a power system environment. A combined networking and information theoretic approach is adopted in meeting both the delay and error probability requirements. We use a mobile agent approach in optimizing the achievable information rate vector and in the distribution of rates to users (sensors). We developed the concept and the quantitative tools require in the creation of cooperating semiautonomous subsystems which puts the electric grid on the path towards intelligent and self-healing system.

Keywords: Mobile agent, power system operation and control, real time, wireless communication.

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371 Segmentation and Recognition of Handwritten Numeric Chains

Authors: Salim Ouchtati, Bedda Mouldi, Abderrazak Lachouri

Abstract:

In this paper we present an off line system for the recognition of the handwritten numeric chains. Our work is divided in two big parts. The first part is the realization of a recognition system of the isolated handwritten digits. In this case the study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the digits by several methods: the distribution sequence, the Barr features and the centred moments of the different projections and profiles. The second part is the extension of our system for the reading of the handwritten numeric chains constituted of a variable number of digits. The vertical projection is used to segment the numeric chain at isolated digits and every digit (or segment) will be presented separately to the entry of the system achieved in the first part (recognition system of the isolated handwritten digits). The result of the recognition of the numeric chain will be displayed at the exit of the global system.

Keywords: Optical Characters Recognition, Neural networks, Barr features, Image processing, Pattern Recognition, Featuresextraction.

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370 Passenger Flow Characteristics of Seoul Metropolitan Subway Network

Authors: Kang Won Lee, Jung Won Lee

Abstract:

Characterizing the network flow is of fundamental importance to understand the complex dynamics of networks. And passenger flow characteristics of the subway network are very relevant for an effective transportation management in urban cities. In this study, passenger flow of Seoul metropolitan subway network is investigated and characterized through statistical analysis. Traditional betweenness centrality measure considers only topological structure of the network and ignores the transportation factors. This paper proposes a weighted betweenness centrality measure that incorporates monthly passenger flow volume. We apply the proposed measure on the Seoul metropolitan subway network involving 493 stations and 16 lines. Several interesting insights about the network are derived from the new measures. Using Kolmogorov-Smirnov test, we also find out that monthly passenger flow between any two stations follows a power-law distribution and other traffic characteristics such as congestion level and throughflow traffic follow exponential distribution.

Keywords: Betweenness centrality, correlation coefficient, power-law distribution, Korea traffic data base.

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369 Overview of Development of a Digital Platform for Building Critical Infrastructure Protection Systems in Smart Industries

Authors: Bruno Vilić Belina, Ivan Župan

Abstract:

Smart industry concepts and digital transformation are very popular in many industries. They develop their own digital platforms, which have an important role in innovations and transactions. The main idea of smart industry digital platforms is central data collection, industrial data integration and data usage for smart applications and services. This paper presents the development of a digital platform for building critical infrastructure protection systems in smart industries. Different service contraction modalities in Service Level Agreements (SLAs), Customer Relationship Management (CRM) relations, trends and changes in business architectures (especially process business architecture) for the purpose of developing infrastructural production and distribution networks, information infrastructure meta-models and generic processes by critical infrastructure owner demanded by critical infrastructure law, satisfying cybersecurity requirements and taking into account hybrid threats are researched.

Keywords: Cybersecurity, critical infrastructure, smart industries, digital platform.

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