Search results for: neighbor area network.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5051

Search results for: neighbor area network.

3941 Simulations of Routing Protocols of Wireless Sensor Networks

Authors: Kristoffer Clyde Magsino, H. Srikanth Kamath

Abstract:

Wireless Sensor Network is widely used in electronics. Wireless sensor networks are now used in many applications including military, environmental, healthcare applications, home automation and traffic control. We will study one area of wireless sensor networks, which is the routing protocol. Routing protocols are needed to send data between sensor nodes and the base station. In this paper, we will discuss two routing protocols, such as datacentric and hierarchical routing protocol. We will show the output of the protocols using the NS-2 simulator. This paper will compare the simulation output of the two routing protocol using Nam. We will simulate using Xgraph to find the throughput and delay of the protocol.

Keywords: data-centric routing protocol, hierarchical routingprotocol, Nam, NS-2, Routing Protocol, sensor nodes, SPIN, throughput, Xgraph

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3940 Improving Quality of Business Networks for Information Systems

Authors: Hazem M. El-Bakry, Ahmed Atwan

Abstract:

Computer networks are essential part in computerbased information systems. The performance of these networks has a great influence on the whole information system. Measuring the usability criteria and customers satisfaction on small computer network is very important. In this article, an effective approach for measuring the usability of business network in an information system is introduced. The usability process for networking provides us with a flexible and a cost-effective way to assess the usability of a network and its products. In addition, the proposed approach can be used to certify network product usability late in the development cycle. Furthermore, it can be used to help in developing usable interfaces very early in the cycle and to give a way to measure, track, and improve usability. Moreover, a new approach for fast information processing over computer networks is presented. The entire data are collected together in a long vector and then tested as a one input pattern. Proposed fast time delay neural networks (FTDNNs) use cross correlation in the frequency domain between the tested data and the input weights of neural networks. It is proved mathematically and practically that the number of computation steps required for the presented time delay neural networks is less than that needed by conventional time delay neural networks (CTDNNs). Simulation results using MATLAB confirm the theoretical computations.

Keywords: Usability Criteria, Computer Networks, Fast Information Processing, Cross Correlation, Frequency Domain.

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3939 Automatic Road Network Recognition and Extraction for Urban Planning

Authors: D. B. L. Bong, K.C. Lai, A. Joseph

Abstract:

The uses of road map in daily activities are numerous but it is a hassle to construct and update a road map whenever there are changes. In Universiti Malaysia Sarawak, research on Automatic Road Extraction (ARE) was explored to solve the difficulties in updating road map. The research started with using Satellite Image (SI), or in short, the ARE-SI project. A Hybrid Simple Colour Space Segmentation & Edge Detection (Hybrid SCSS-EDGE) algorithm was developed to extract roads automatically from satellite-taken images. In order to extract the road network accurately, the satellite image must be analyzed prior to the extraction process. The characteristics of these elements are analyzed and consequently the relationships among them are determined. In this study, the road regions are extracted based on colour space elements and edge details of roads. Besides, edge detection method is applied to further filter out the non-road regions. The extracted road regions are validated by using a segmentation method. These results are valuable for building road map and detecting the changes of the existing road database. The proposed Hybrid Simple Colour Space Segmentation and Edge Detection (Hybrid SCSS-EDGE) algorithm can perform the tasks fully automatic, where the user only needs to input a high-resolution satellite image and wait for the result. Moreover, this system can work on complex road network and generate the extraction result in seconds.

Keywords: Road Network Recognition, Colour Space, Edge Detection, Urban Planning.

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3938 Separation Characteristics of Dissolved Gases from Water Using a Polypropylene Hollow Fiber Membrane Module with High Surface Area

Authors: Pil Woo Heo, In Sub Park

Abstract:

A polypropylene hollow fiber membrane module is used for separating dissolved gases which contain dissolved oxygen from water. These dissolved gases can be used for underwater breathing. To be used for a human, the minimum amount of oxygen is essential. To increase separation of dissolved gases, much water and high surface area of hollow fibers are requested. For efficient separation system, performance of single membrane module with high surface area needs to be investigated.

In this study, we set up experimental devices for analyzing separation characteristics of dissolved gases including oxygen from water using a polypropylene hollow fiber membrane module. Separation of dissolved gases from water is investigated with variations of water flow rates. Composition of dissolved gases is also measured using GC. These results expect to be used in developing the portable separation system.

Keywords: High surface area, breathing, vacuum, composition.

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3937 Guidelines for Sustainable Urban Mobility in Historic Districts from International Experiences

Authors: Tamer ElSerafi

Abstract:

In recent approaches to heritage conservation, the whole context of historic areas becomes as important as the single historic building. This makes the provision of infrastructure and network of mobility an effective element in the urban conservation. Sustainable urban conservation projects consider the high density of activities, the need for a good quality access system to the transit system, and the importance of the configuration of the mobility network by identifying the best way to connect the different districts of the urban area through a complex unique system that helps the synergic development to achieve a sustainable mobility system. A sustainable urban mobility is a key factor in maintaining the integrity between socio-cultural aspects and functional aspects. This paper illustrates the mobility aspects, mobility problems in historic districts, and the needs of the mobility systems in the first part. The second part is a practical analysis for different mobility plans. It is challenging to find innovative and creative conservation solutions fitting modern uses and needs without risking the loss of inherited built resources. Urban mobility management is becoming an essential and challenging issue in the urban conservation projects. Depending on literature review and practical analysis, this paper tries to define and clarify the guidelines for mobility management in historic districts as a key element in sustainability of urban conservation and development projects. Such rules and principles could control the conflict between the socio–cultural and economic activities, and the different needs for mobility in these districts in a sustainable way. The practical analysis includes a comparison between mobility plans which have been implemented in four different cities; Freiburg in Germany, Zurich in Switzerland and Bray Town in Ireland. This paper concludes with a matrix of guidelines that considers both principles of sustainability and livability factors in urban historic districts.

Keywords: Sustainable mobility, urban mobility, mobility management, historic districts.

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3936 Combinatorial Optimisation of Worm Propagationon an Unknown Network

Authors: Eric Filiol, Edouard Franc, Alessandro Gubbioli, Benoit Moquet, Guillaume Roblot

Abstract:

Worm propagation profiles have significantly changed since 2003-2004: sudden world outbreaks like Blaster or Slammer have progressively disappeared and slower but stealthier worms appeared since, most of them for botnets dissemination. Decreased worm virulence results in more difficult detection. In this paper, we describe a stealth worm propagation model which has been extensively simulated and analysed on a huge virtual network. The main features of this model is its ability to infect any Internet-like network in a few seconds, whatever may be its size while greatly limiting the reinfection attempt overhead of already infected hosts. The main simulation results shows that the combinatorial topology of routing may have a huge impact on the worm propagation and thus some servers play a more essential and significant role than others. The real-time capability to identify them may be essential to greatly hinder worm propagation.

Keywords: Combinatorial worm, worm spreading, worm virulence, stealth worm, spreading simulation, vertex cover, networktopology, WAST simulator, SuWAST simulator.

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3935 Prediction of Compressive Strength of SCC Containing Bottom Ash using Artificial Neural Networks

Authors: Yogesh Aggarwal, Paratibha Aggarwal

Abstract:

The paper presents a comparative performance of the models developed to predict 28 days compressive strengths using neural network techniques for data taken from literature (ANN-I) and data developed experimentally for SCC containing bottom ash as partial replacement of fine aggregates (ANN-II). The data used in the models are arranged in the format of six and eight input parameters that cover the contents of cement, sand, coarse aggregate, fly ash as partial replacement of cement, bottom ash as partial replacement of sand, water and water/powder ratio, superplasticizer dosage and an output parameter that is 28-days compressive strength and compressive strengths at 7 days, 28 days, 90 days and 365 days, respectively for ANN-I and ANN-II. The importance of different input parameters is also given for predicting the strengths at various ages using neural network. The model developed from literature data could be easily extended to the experimental data, with bottom ash as partial replacement of sand with some modifications.

Keywords: Self compacting concrete, bottom ash, strength, prediction, neural network, importance factor.

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3934 The Comparison of Competitiveness of Selected Countries of the European Economic Area

Authors: Ingrid Majerová, Michaela Horúcková

Abstract:

The concept of competitiveness is currently very frequently used term. However, the interpretation of its essence is different. In this paper, one of the many concepts of competitiveness will be analyzed and that is macroeconomic competitiveness, which is understood as a process, which is based on the productivity growth through the growth of key macroeconomic indicators such as standards of living and employment, where all of these variables must have a sustainable basis. Given the competition is a relative quantity it must be constantly compared with the development of competitiveness in other economies or regions. And this comparison method is also used in the article that compares the macrocompetitiveness of selected economies of the European Economic Area – the Czech Republic, Poland, Austria, Switzerland and Germany. The aim of the paper is to verify the hypothesis concerning the direct correlation between the size of the economy and its competitiveness.

Keywords: Comparison, Competitiveness, European Economic Area, Global Competitiveness Index, Immeasurable Indicators of Competitiveness, Macro-competitiveness.

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3933 Development of the Gas Safety Management System using an Intelligent Gasmeter with Wireless ZigBee Network

Authors: Gyou-tae Park, Young-gyu Kim, Jeong-rock Kwon, Yongwoo Lee, Hiesik Kim

Abstract:

The gas safety management system using an intelligent gas meter we proposed is to monitor flow and pressure of gas, earthquake, temperature, smoke and leak of methane. Then our system takes safety measures to protect a serious risk by the result of an event, to communicate with a wall-pad including a gateway by zigbee network in buildings and to report the event to user by the safety management program in a server. Also, the inner cutoff valve of an intelligent gas meter is operated if any event occurred or abnormal at each sensor.

Keywords: micom gas-meter, gas safety, zigbee, ubiquitous

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3932 Trust and Reputation Mechanism with Path Optimization in Multipath Routing

Authors: Ramya Dorai, M. Rajaram

Abstract:

A Mobile Adhoc Network (MANET) is a collection of mobile nodes that communicate with each other with wireless links and without pre-existing communication infrastructure. Routing is an important issue which impacts network performance. As MANETs lack central administration and prior organization, their security concerns are different from those of conventional networks. Wireless links make MANETs susceptible to attacks. This study proposes a new trust mechanism to mitigate wormhole attack in MANETs. Different optimization techniques find available optimal path from source to destination. This study extends trust and reputation to an improved link quality and channel utilization based Adhoc Ondemand Multipath Distance Vector (AOMDV). Differential Evolution (DE) is used for optimization.

Keywords: Mobile Adhoc Network (MANET), Adhoc Ondemand Multi-Path Distance Vector (AOMDV), Trust and Reputation, Differential Evolution (DE), Link Quality, Channel Utilization.

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3931 An Effective Islanding Detection and Classification Method Using Neuro-Phase Space Technique

Authors: Aziah Khamis, H. Shareef

Abstract:

The purpose of planned islanding is to construct a power island during system disturbances which are commonly formed for maintenance purpose. However, in most of the cases island mode operation is not allowed. Therefore distributed generators (DGs) must sense the unplanned disconnection from the main grid. Passive technique is the most commonly used method for this purpose. However, it needs improvement in order to identify the islanding condition. In this paper an effective method for identification of islanding condition based on phase space and neural network techniques has been developed. The captured voltage waveforms at the coupling points of DGs are processed to extract the required features. For this purposed a method known as the phase space techniques is used. Based on extracted features, two neural network configuration namely radial basis function and probabilistic neural networks are trained to recognize the waveform class. According to the test result, the investigated technique can provide satisfactory identification of the islanding condition in the distribution system.

Keywords: Classification, Islanding detection, Neural network, Phase space.

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3930 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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3929 Application of Neural Network in Portfolio Product Companies: Integration of Boston Consulting Group Matrix and Ansoff Matrix

Authors: M. Khajezadeh, M. Saied Fallah Niasar, S. Ali Asli, D. Davani Davari, M. Godarzi, Y. Asgari

Abstract:

This study aims to explore the joint application of both Boston and Ansoff matrices in the operational development of the product. We conduct deep analysis, by utilizing the Artificial Neural Network, to predict the position of the product in the market while the company is interested in increasing its share. The data are gathered from two industries, called hygiene and detergent. In doing so, the effort is being made by investigating the behavior of top player companies and, recommend strategic orientations. In conclusion, this combination analysis is appropriate for operational development; as well, it plays an important role in providing the position of the product in the market for both hygiene and detergent industries. More importantly, it will elaborate on the company’s strategies to increase its market share related to a combination of the Boston Consulting Group (BCG) Matrix and Ansoff Matrix.

Keywords: Artificial neural network, portfolio analysis, BCG matrix, Ansoff matrix.

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3928 Supporting Densification through the Planning and Implementation of Road Infrastructure in the South African Context

Authors: K. Govender, M. Sinclair

Abstract:

This paper demonstrates a proof of concept whereby shorter trips and land use densification can be promoted through an alternative approach to planning and implementation of road infrastructure in the South African context. It briefly discusses how the development of the Compact City concept relies on a combination of promoting shorter trips and densification through a change in focus in road infrastructure provision. The methodology developed in this paper uses a traffic model to test the impact of synthesized deterrence functions on congestion locations in the road network through the assignment of traffic on the study network. The results from this study demonstrate that intelligent planning of road infrastructure can indeed promote reduced urban sprawl, increased residential density and mixed-use areas which are supported by an efficient public transport system; and reduced dependence on the freeway network with a fixed road infrastructure budget. The study has resonance for all cities where urban sprawl is seemingly unstoppable.

Keywords: Compact cities, densification, road infrastructure planning, transportation modeling.

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3927 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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3926 Coordinated Voltage Control using Multiple Regulators in Distribution System with Distributed Generators

Authors: R. Shivarudraswamy, D. N. Gaonkar

Abstract:

The continued interest in the use of distributed generation in recent years is leading to the growth in number of distributed generators connected to distribution networks. Steady state voltage rise resulting from the connection of these generators can be a major obstacle to their connection at lower voltage levels. The present electric distribution network is designed to keep the customer voltage within tolerance limit. This may require a reduction in connectable generation capacity, under utilization of appropriate generation sites. Thus distribution network operators need a proper voltage regulation method to allow the significant integration of distributed generation systems to existing network. In this work a voltage rise problem in a typical distribution system has been studied. A method for voltage regulation of distribution system with multiple DG system by coordinated operation distributed generator, capacitor and OLTC has been developed. A sensitivity based analysis has been carried out to determine the priority for individual generators in multiple DG environment. The effectiveness of the developed method has been evaluated under various cases through simulation results.

Keywords: Distributed generation, voltage control, sensitivity factor.

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3925 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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3924 Automatic Classification of Periodic Heart Sounds Using Convolutional Neural Network

Authors: Jia Xin Low, Keng Wah Choo

Abstract:

This paper presents an automatic normal and abnormal heart sound classification model developed based on deep learning algorithm. MITHSDB heart sounds datasets obtained from the 2016 PhysioNet/Computing in Cardiology Challenge database were used in this research with the assumption that the electrocardiograms (ECG) were recorded simultaneously with the heart sounds (phonocardiogram, PCG). The PCG time series are segmented per heart beat, and each sub-segment is converted to form a square intensity matrix, and classified using convolutional neural network (CNN) models. This approach removes the need to provide classification features for the supervised machine learning algorithm. Instead, the features are determined automatically through training, from the time series provided. The result proves that the prediction model is able to provide reasonable and comparable classification accuracy despite simple implementation. This approach can be used for real-time classification of heart sounds in Internet of Medical Things (IoMT), e.g. remote monitoring applications of PCG signal.

Keywords: Convolutional neural network, discrete wavelet transform, deep learning, heart sound classification.

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3923 Survey on Jamming Wireless Networks: Attacks and Prevention Strategies

Authors: S. Raja Ratna, R. Ravi

Abstract:

Wireless networks are built upon the open shared medium which makes easy for attackers to conduct malicious activities. Jamming is one of the most serious security threats to information economy and it must be dealt efficiently. Jammer prevents legitimate data to reach the receiver side and also it seriously degrades the network performance. The objective of this paper is to provide a general overview of jamming in wireless network. It covers relevant works, different jamming techniques, various types of jammers and typical prevention techniques. Challenges associated with comparing several anti-jamming techniques are also highlighted.

Keywords: Channel, Cryptography, Frequency, Jamming, Legitimate, Security, Wavelength.

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3922 Power System Voltage Control using LP and Artificial Neural Network

Authors: A. Sina, A. Aeenmehr, H. Mohamadian

Abstract:

Optimization and control of reactive power distribution in the power systems leads to the better operation of the reactive power resources. Reactive power control reduces considerably the power losses and effective loads and improves the power factor of the power systems. Another important reason of the reactive power control is improving the voltage profile of the power system. In this paper, voltage and reactive power control using Neural Network techniques have been applied to the 33 shines- Tehran Electric Company. In this suggested ANN, the voltages of PQ shines have been considered as the input of the ANN. Also, the generators voltages, tap transformers and shunt compensators have been considered as the output of ANN. Results of this techniques have been compared with the Linear Programming. Minimization of the transmission line power losses has been considered as the objective function of the linear programming technique. The comparison of the results of the ANN technique with the LP shows that the ANN technique improves the precision and reduces the computation time. ANN technique also has a simple structure and this causes to use the operator experience.

Keywords: voltage control, linear programming, artificial neural network, power systems

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3921 Impact of Liquidity Crunch on Interbank Network

Authors: I. Lucas, N. Schomberg, F-A. Couturier

Abstract:

Most empirical studies have analyzed how liquidity risks faced by individual institutions turn into systemic risk. Recent banking crisis has highlighted the importance of grasping and controlling the systemic risk, and the acceptance by Central Banks to ease their monetary policies for saving default or illiquid banks. This last point shows that banks would pay less attention to liquidity risk which, in turn, can become a new important channel of loss. The financial regulation focuses on the most important and “systemic” banks in the global network. However, to quantify the expected loss associated with liquidity risk, it is worth to analyze sensitivity to this channel for the various elements of the global bank network. A small bank is not considered as potentially systemic; however the interaction of small banks all together can become a systemic element. This paper analyzes the impact of medium and small banks interaction on a set of banks which is considered as the core of the network. The proposed method uses the structure of agent-based model in a two-class environment. In first class, the data from actual balance sheets of 22 large and systemic banks (such as BNP Paribas or Barclays) are collected. In second one, to model a network as closely as possible to actual interbank market, 578 fictitious banks smaller than the ones belonging to first class have been split into two groups of small and medium ones. All banks are active on the European interbank network and have deposit and market activity. A simulation of 12 three month periods representing a midterm time interval three years is projected. In each period, there is a set of behavioral descriptions: repayment of matured loans, liquidation of deposits, income from securities, collection of new deposits, new demands of credit, and securities sale. The last two actions are part of refunding process developed in this paper. To strengthen reliability of proposed model, random parameters dynamics are managed with stochastic equations as rates the variations of which are generated by Vasicek model. The Central Bank is considered as the lender of last resort which allows banks to borrow at REPO rate and some ejection conditions of banks from the system are introduced.

Liquidity crunch due to exogenous crisis is simulated in the first class and the loss impact on other bank classes is analyzed though aggregate values representing the aggregate of loans and/or the aggregate of borrowing between classes. It is mainly shown that the three groups of European interbank network do not have the same response, and that intermediate banks are the most sensitive to liquidity risk.

Keywords: Systemic Risk, Financial Contagion, Liquidity Risk, Interbank Market, Network Model.

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3920 Performance of Laboratory Experiments over the Internet: Towards an Intelligent Tutoring System on Automatic Control

Authors: Kleanthis Prekas, Maria Rangoussi, Savvas Vassiliadis, George Prekas

Abstract:

Intelligent tutoring systems constitute an evolution of computer-aided educational software. We present here the modules of an intelligent tutoring system for Automatic Control, developed in our department. Through the software application developed,students can perform complete automatic control laboratory experiments, either over the departmental local area network or over the Internet. Monitoring of access to the system (local as well as international), along with student performance statistics, has yielded strongly encouraging results (as of fall 2004), despite the advanced technical content of the presented paradigm, thus showing the potential of the system developed for education and for training.

Keywords: Automatic control, tutoring system, Internet access, laboratory experiments.

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3919 Project Complexity Indices based on Topology Features

Authors: Amer A. Boushaala

Abstract:

The heuristic decision rules used for project scheduling will vary depending upon the project-s size, complexity, duration, personnel, and owner requirements. The concept of project complexity has received little detailed attention. The need to differentiate between easy and hard problem instances and the interest in isolating the fundamental factors that determine the computing effort required by these procedures inspired a number of researchers to develop various complexity measures. In this study, the most common measures of project complexity are presented. A new measure of project complexity is developed. The main privilege of the proposed measure is that, it considers size, shape and logic characteristics, time characteristics, resource demands and availability characteristics as well as number of critical activities and critical paths. The degree of sensitivity of the proposed measure for complexity of project networks has been tested and evaluated against the other measures of complexity of the considered fifty project networks under consideration in the current study. The developed measure showed more sensitivity to the changes in the network data and gives accurate quantified results when comparing the complexities of networks.

Keywords: Activity networks, Complexity index, Networkcomplexity measure, Network topology, Project Network.

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3918 Routing Algorithm for a Clustered Network

Authors: Hemanth KumarA.R, Sudhakara G., Satyanarayana B.S.

Abstract:

The Cluster Dimension of a network is defined as, which is the minimum cardinality of a subset S of the set of nodes having the property that for any two distinct nodes x and y, there exist the node Si, s2 (need not be distinct) in S such that ld(x,s1) — d(y, s1)1 > 1 and d(x,s2) < d(x,$) for all s E S — {s2}. In this paper, strictly non overlap¬ping clusters are constructed. The concept of LandMarks for Unique Addressing and Clustering (LMUAC) routing scheme is developed. With the help of LMUAC routing scheme, It is shown that path length (upper bound)PLN,d < PLD, Maximum memory space requirement for the networkMSLmuAc(Az) < MSEmuAc < MSH3L < MSric and Maximum Link utilization factor MLLMUAC(i=3) < MLLMUAC(z03) < M Lc

Keywords: Metric dimension, Cluster dimension, Cluster.

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3917 VANETs: Security Challenges and Future Directions

Authors: Jared Oluoch

Abstract:

Connected vehicles are equipped with wireless sensors that aid in Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication. These vehicles will in the near future provide road safety, improve transport efficiency, and reduce traffic congestion. One of the challenges for connected vehicles is how to ensure that information sent across the network is secure. If security of the network is not guaranteed, several attacks can occur, thereby compromising the robustness, reliability, and efficiency of the network. This paper discusses existing security mechanisms and unique properties of connected vehicles. The methodology employed in this work is exploratory. The paper reviews existing security solutions for connected vehicles. More concretely, it discusses various cryptographic mechanisms available, and suggests areas of improvement. The study proposes a combination of symmetric key encryption and public key cryptography to improve security. The study further proposes message aggregation as a technique to overcome message redundancy. This paper offers a comprehensive overview of connected vehicles technology, its applications, its security mechanisms, open challenges, and potential areas of future research.

Keywords: VANET, connected vehicles, 802.11p, WAVE, DSRC, trust, security, cryptography.

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3916 Corporate Social Responsibility in China Apparel Industry

Authors: Zhao Linfei, Gu Qingliang

Abstract:

China apparel industry, which is deeply embedded in the global production network (GPN), faces the dual pressures of social upgrading and economic upgrading. Based on the survey in Ningbo apparel cluster, the paper shows the state of corporate social responsibility (CSR) in China apparel industry is better than before. And the investigation indicates that the firms who practice CSR actively perform better both socially and economically than those who inactively. The research demonstrates that CSR can be an initial capital rather than cost, and “doing well by doing good" is also existed in labor intensive industry.

Keywords: Global production network, corporate social responsibility, China apparel industry.

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3915 A Motion Dictionary to Real-Time Recognition of Sign Language Alphabet Using Dynamic Time Warping and Artificial Neural Network

Authors: Marcio Leal, Marta Villamil

Abstract:

Computacional recognition of sign languages aims to allow a greater social and digital inclusion of deaf people through interpretation of their language by computer. This article presents a model of recognition of two of global parameters from sign languages; hand configurations and hand movements. Hand motion is captured through an infrared technology and its joints are built into a virtual three-dimensional space. A Multilayer Perceptron Neural Network (MLP) was used to classify hand configurations and Dynamic Time Warping (DWT) recognizes hand motion. Beyond of the method of sign recognition, we provide a dataset of hand configurations and motion capture built with help of fluent professionals in sign languages. Despite this technology can be used to translate any sign from any signs dictionary, Brazilian Sign Language (Libras) was used as case study. Finally, the model presented in this paper achieved a recognition rate of 80.4%.

Keywords: Sign language recognition, computer vision, infrared, artificial neural network, dynamic time warping.

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3914 Coastal Ecological Sensitivity and Risk Assessment: A Case Study of Sea Level Change in Apodi River (Atlantic Ocean), Northeast Brazil

Authors: Mukesh Singh Boori, Venerando Eustáquio Amaro, Helenice Vital

Abstract:

The present study has been carried out with a view to calculate the coastal vulnerability index (CVI) to know the high and low sensitive areas and area of inundation due to future SLR. Both conventional and remotely sensed data were used and analyzed through the modelling technique. Out of the total study area, 8.26% is very high risk, 14.21% high, 9.36% medium, 22.46% low and 7.35% in the very low vulnerable category, due to costal components. Results of the inundation analysis indicate that 225.2 km² and 397 km² of the land area will be submerged by flooding at 1m and 10m inundation levels. The most severely affected sectors are expected to be the residential, industrial and recreational areas. As this coast is planned for future coastal developmental activities, measures such as industrializations, building regulation, urban growth planning and agriculture, development of an integrated coastal zone management, strict enforcement of the Coastal Regulation Zone (CRZ) Act, monitoring of impacts and further research in this regard are recommended for the study area.

Keywords: Coastal planning, land use, satellite data, vulnerability.

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3913 An Experimental Study of a Self-Supervised Classifier Ensemble

Authors: Neamat El Gayar

Abstract:

Learning using labeled and unlabelled data has received considerable amount of attention in the machine learning community due its potential in reducing the need for expensive labeled data. In this work we present a new method for combining labeled and unlabeled data based on classifier ensembles. The model we propose assumes each classifier in the ensemble observes the input using different set of features. Classifiers are initially trained using some labeled samples. The trained classifiers learn further through labeling the unknown patterns using a teaching signals that is generated using the decision of the classifier ensemble, i.e. the classifiers self-supervise each other. Experiments on a set of object images are presented. Our experiments investigate different classifier models, different fusing techniques, different training sizes and different input features. Experimental results reveal that the proposed self-supervised ensemble learning approach reduces classification error over the single classifier and the traditional ensemble classifier approachs.

Keywords: Multiple Classifier Systems, classifier ensembles, learning using labeled and unlabelled data, K-nearest neighbor classifier, Bayes classifier.

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3912 RBF Based Face Recognition and Expression Analysis

Authors: Praseeda Lekshmi.V, Dr.M.Sasikumar

Abstract:

Facial recognition and expression analysis is rapidly becoming an area of intense interest in computer science and humancomputer interaction design communities. The most expressive way humans display emotions is through facial expressions. In this paper skin and non-skin pixels were separated. Face regions were extracted from the detected skin regions. Facial expressions are analyzed from facial images by applying Gabor wavelet transform (GWT) and Discrete Cosine Transform (DCT) on face images. Radial Basis Function (RBF) Network is used to identify the person and to classify the facial expressions. Our method reliably works even with faces, which carry heavy expressions.

Keywords: Face Recognition, Radial Basis Function, Gabor Wavelet Transform, Discrete Cosine Transform

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