Search results for: social network analysis.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11642

Search results for: social network analysis.

10682 Hybrid Multipath Congestion Control

Authors: Akshit Singhal, Xuan Wang, Zhijun Wang, Hao Che, Hong Jiang

Abstract:

Multiple Path Transmission Control Protocols (MPTCPs) allow flows to explore path diversity to improve the throughput, reliability and network resource utilization. However, the existing solutions may discourage users to adopt the solutions in the face of multipath scenario where different paths are charged based on different pricing structures, e.g., WiFi vs. cellular connections, widely available for mobile phones. In this paper, we propose a Hybrid MPTCP (H-MPTCP) with a built-in mechanism to incentivize users to use multiple paths with different pricing structures. In the meantime, H-MPTCP preserves the nice properties enjoyed by the state-of-the-art MPTCP solutions. Extensive real Linux implementation results verify that H-MPTCP can indeed achieve the design objectives.

Keywords: Congestion control, Network Utility Maximization, Multipath TCP, network.

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10681 Some Aspects of Social Media Marketing (Georgian Case)

Authors: Nugzar Todua, Charita Jashi

Abstract:

This paper is focusing on the attitude of Georgian consumers toward social media, influence of social media on consumer buying behavior. The purpose of this paper is to explore the usage of social media marketing for small business companies of Georgia. The result of marketing research has revealed that social webs are mostly used by Georgian consumers, but they have little impact on the buying decision. The research method was exploratory and descriptive. Conclusions summarize the research results and offers insight to provide better understandings of consumers demand and implementation of marketing strategy through social media in Georgia.

Keywords: Marketing Research, Purchasing behavior, Social Media Marketing, Small Business, Tourism Industry.

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10680 Review for Identifying Online Opinion Leaders

Authors: Yu Wang

Abstract:

Nowadays, Internet enables its users to share the information online and to interact with others. Facing with numerous information, these Internet users are confused and begin to rely on the opinion leaders’ recommendations. The online opinion leaders are the individuals who have professional knowledge, who utilize the online channels to spread word-of-mouth information and who can affect the attitudes or even the behavior of their followers to some degree. Because utilizing the online opinion leaders is seen as an important approach to affect the potential consumers, how to identify them has become one of the hottest topics in the related field. Hence, in this article, the concepts and characteristics are introduced, and the researches related to identifying opinion leaders are collected and divided into three categories. Finally, the implications for future studies are provided.

Keywords: Online opinion leaders, user attributes analysis, text mining analysis, network structure analysis.

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10679 A Distributed Mobile Agent Based on Intrusion Detection System for MANET

Authors: Maad Kamal Al-Anni

Abstract:

This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Mobile ad hoc network, MANET, intrusion detection system, back propagation algorithm, neural networks, traffic table, multilayer perceptron, feed-forward back-propagation, network simulator 2.

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10678 Utilizing Biological Models to Determine the Recruitment of the Irish Republican Army

Authors: Erika Ann Schaub, Christian J Darken

Abstract:

Sociological models (e.g., social network analysis, small-group dynamic and gang models) have historically been used to predict the behavior of terrorist groups. However, they may not be the most appropriate method for understanding the behavior of terrorist organizations because the models were not initially intended to incorporate violent behavior of its subjects. Rather, models that incorporate life and death competition between subjects, i.e., models utilized by scientists to examine the behavior of wildlife populations, may provide a more accurate analysis. This paper suggests the use of biological models to attain a more robust method for understanding the behavior of terrorist organizations as compared to traditional methods. This study also describes how a biological population model incorporating predator-prey behavior factors can predict terrorist organizational recruitment behavior for the purpose of understanding the factors that govern the growth and decline of terrorist organizations. The Lotka-Volterra, a biological model that is based on a predator-prey relationship, is applied to a highly suggestive case study, that of the Irish Republican Army. This case study illuminates how a biological model can be utilized to understand the actions of a terrorist organization.

Keywords: Biological Models, Lotka-Volterra Predator-Prey Model, Terrorist Organizational Behavior, Terrorist Recruitment.

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10677 Adaptive Pulse Coupled Neural Network Parameters for Image Segmentation

Authors: Thejaswi H. Raya, Vineetha Bettaiah, Heggere S. Ranganath

Abstract:

For over a decade, the Pulse Coupled Neural Network (PCNN) based algorithms have been successfully used in image interpretation applications including image segmentation. There are several versions of the PCNN based image segmentation methods, and the segmentation accuracy of all of them is very sensitive to the values of the network parameters. Most methods treat PCNN parameters like linking coefficient and primary firing threshold as global parameters, and determine them by trial-and-error. The automatic determination of appropriate values for linking coefficient, and primary firing threshold is a challenging problem and deserves further research. This paper presents a method for obtaining global as well as local values for the linking coefficient and the primary firing threshold for neurons directly from the image statistics. Extensive simulation results show that the proposed approach achieves excellent segmentation accuracy comparable to the best accuracy obtainable by trial-and-error for a variety of images.

Keywords: Automatic Selection of PCNN Parameters, Image Segmentation, Neural Networks, Pulse Coupled Neural Network

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10676 Design of a Three Phase Active Power Filter with Sliding Mode Control and Energy Feedback

Authors: M. Nayeripour, T. Niknam

Abstract:

Nonlinear and unbalance loads in three phase networks create harmonics and losses. Active and passive filters are used for elimination or reduction of these effects. Passive filters have some limitations. For example, they are designed only for a specific frequency and they may cause to resonance in the network at the point of common coupling. The other drawback of a passive filter is that the sizes of required elements are normally large. The active filter can improve some of limitations of passive filter for example; they can eliminate more than one harmonic and don't cause resonance in the network. In this paper inverter analysis have been done simultaneously in three phase and the RL impedance of the line have been considered. A sliding mode control based on energy feedback of capacitors is employed in the design with this method, the dynamic speed of the filter is improved effectively and harmonics and load unbalance is compensating quickly.

Keywords: Shunt active filter, harmonic, inverter, sliding mode control, energy feedback.

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10675 Smart Technology for Hygrothermal Performance of Low Carbon Material Using an Artificial Neural Network Model

Authors: Manal Bouasria, Mohammed-Hichem Benzaama, Valérie Pralong, Yassine El Mendili

Abstract:

Reducing the quantity of cement in cementitious composites can help to reduce the environmental effect of construction materials. Byproducts such as ferronickel slags (FNS), fly ash (FA), and waste as Crepidula fornicata shells (CR) are promising options for cement replacement. In this work, we investigated the relevance of substituting cement with FNS-CR and FA-CR on the mechanical properties of mortar and on the thermal properties of concrete. Foraging intervals ranging from 2 days to 28 days, the mechanical properties are obtained by 3-point bending and compression tests. The chosen mix is used to construct a prototype in order to study the material’s hygrothermal performance. The data collected by the sensors placed on the prototype were utilized to build an artificial neural network.

Keywords: Artificial neural network, cement, circular economy, concrete, byproducts.

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10674 Earth Station Neural Network Control Methodology and Simulation

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

Abstract:

Renewable energy resources are inexhaustible, clean as compared with conventional resources. Also, it is used to supply regions with no grid, no telephone lines, and often with difficult accessibility by common transport. Satellite earth stations which located in remote areas are the most important application of renewable energy. Neural control is a branch of the general field of intelligent control, which is based on the concept of artificial intelligence. This paper presents the mathematical modeling of satellite earth station power system which is required for simulating the system.Aswan is selected to be the site under consideration because it is a rich region with solar energy. The complete power system is simulated using MATLAB–SIMULINK.An artificial neural network (ANN) based model has been developed for the optimum operation of earth station power system. An ANN is trained using a back propagation with Levenberg–Marquardt algorithm. The best validation performance is obtained for minimum mean square error. The regression between the network output and the corresponding target is equal to 96% which means a high accuracy. Neural network controller architecture gives satisfactory results with small number of neurons, hence better in terms of memory and time are required for NNC implementation. The results indicate that the proposed control unit using ANN can be successfully used for controlling the satellite earth station power system.

Keywords: Satellite, neural network, MATLAB, power system.

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10673 Enhancing the Connectedness in Ad–hoc Mesh Networks using the Terranet Technology

Authors: Obeidat I., Bsoul M., Khasawneh A., Kilani Y.

Abstract:

This paper simulates the ad-hoc mesh network in rural areas, where such networks receive great attention due to their cost, since installing the infrastructure for regular networks in these areas is not possible due to the high cost. The distance between the communicating nodes is the most obstacles that the ad-hoc mesh network will face. For example, in Terranet technology, two nodes can communicate if they are only one kilometer far from each other. However, if the distance between them is more than one kilometer, then each node in the ad-hoc mesh networks has to act as a router that forwards the data it receives to other nodes. In this paper, we try to find the critical number of nodes which makes the network fully connected in a particular area, and then propose a method to enhance the intermediate node to accept to be a router to forward the data from the sender to the receiver. Much work was done on technological changes on peer to peer networks, but the focus of this paper will be on another feature which is to find the minimum number of nodes needed for a particular area to be fully connected and then to enhance the users to switch on their phones and accept to work as a router for other nodes. Our method raises the successful calls to 81.5% out of 100% attempt calls.

Keywords: Adjacency matrix, Ad-hoc mesh network, Connectedness, Terranet technology

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10672 Social Influence in the Adoption Process and Usage of Innovation: Gender Differences

Authors: S. Güzin Mazman, Yasemin Koçak Usluel, Vildan Çevik

Abstract:

The purpose of this study is to determine in what ways elementary education prospective teachers are being informed about innovations and to explain the role of social influence in the usage process of a technological innovation in terms of genders. The study group consisted of 300 prospective teachers, including 234 females and 66 males. Data have been collected by a questionnaire developed by the researchers. The result of the study showed that, while prospective teachers are being informed about innovations most frequently by mass media, they rarely seek to take expert advice. In addition, analysis of results showed that the social influence on females were significantly higher than males in usage process of a technological innovation.

Keywords: Gender differences, social influence, adoption, innovation.

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10671 Social and Economic Effects of Mining Industry Restructuring in Romania -Case Studies

Authors: Andra Costache, Gica Pehoiu

Abstract:

As in other countries from Central and Eastern Europe, the economic restructuring occurred in the last decade of the twentieth century affected the mining industry in Romania, an oversize and heavily subsidized sector before 1989. After more than a decade since the beginning of mining restructuring, an evaluation of current social implications of the process it is required, together with an efficiency analysis of the adaptation mechanisms developed at governmental level. This article aims to provide an insight into these issues through case studies conducted in the most important coal basin of Romania, Petroşani Depression.

Keywords: case studies, government programs, miningrestructuring, social effects.

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10670 Minimizing the Broadcast Traffic in the Jordanian Discovery Schools Network using PPPoE

Authors: Sameh H. Ghwanmeh

Abstract:

Discovery schools in Jordan are connected in one flat ATM bridge network. All Schools connected to the network will hear broadcast traffic. High percentage of unwanted traffic such as broadcast, consumes the bandwidth between schools and QRC. Routers in QRC have high CPU utilization. The number of connections on the router is very high, and may exceed recommend manufacturing specifications. One way to minimize number of connections to the routers in QRC, and minimize broadcast traffic is to use PPPoE. In this study, a PPPoE solution has been presented which shows high performance for the clients when accessing the school server resources. Despite the large number of the discovery schools at MoE, the experimental results show that the PPPoE solution is able to yield a satisfactory performance for each client at the school and noticeably reduce the traffic broadcast to the QRC.

Keywords: Education, networking, performance, e-content.

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10669 Person Identification by Using AR Model for EEG Signals

Authors: Gelareh Mohammadi, Parisa Shoushtari, Behnam Molaee Ardekani, Mohammad B. Shamsollahi

Abstract:

A direct connection between ElectroEncephaloGram (EEG) and the genetic information of individuals has been investigated by neurophysiologists and psychiatrists since 1960-s; and it opens a new research area in the science. This paper focuses on the person identification based on feature extracted from the EEG which can show a direct connection between EEG and the genetic information of subjects. In this work the full EO EEG signal of healthy individuals are estimated by an autoregressive (AR) model and the AR parameters are extracted as features. Here for feature vector constitution, two methods have been proposed; in the first method the extracted parameters of each channel are used as a feature vector in the classification step which employs a competitive neural network and in the second method a combination of different channel parameters are used as a feature vector. Correct classification scores at the range of 80% to 100% reveal the potential of our approach for person classification/identification and are in agreement to the previous researches showing evidence that the EEG signal carries genetic information. The novelty of this work is in the combination of AR parameters and the network type (competitive network) that we have used. A comparison between the first and the second approach imply preference of the second one.

Keywords: Person Identification, Autoregressive Model, EEG, Neural Network

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10668 Comparing Autoregressive Moving Average (ARMA) Coefficients Determination using Artificial Neural Networks with Other Techniques

Authors: Abiodun M. Aibinu, Momoh J. E. Salami, Amir A. Shafie, Athaur Rahman Najeeb

Abstract:

Autoregressive Moving average (ARMA) is a parametric based method of signal representation. It is suitable for problems in which the signal can be modeled by explicit known source functions with a few adjustable parameters. Various methods have been suggested for the coefficients determination among which are Prony, Pade, Autocorrelation, Covariance and most recently, the use of Artificial Neural Network technique. In this paper, the method of using Artificial Neural network (ANN) technique is compared with some known and widely acceptable techniques. The comparisons is entirely based on the value of the coefficients obtained. Result obtained shows that the use of ANN also gives accurate in computing the coefficients of an ARMA system.

Keywords: Autoregressive moving average, coefficients, back propagation, model parameters, neural network, weight.

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10667 The Patterns of Unemployment and the Geography of Social Housing

Authors: Sónia Alves

Abstract:

During the last few decades in the academic field, the debate has increased on the effects of social geography on the opportunities of socioeconomic integration. On one hand, it has been discussed how the contents of the urban structure and social geography affect not only the way people interact, but also their chances of social and economic integration. On the other hand, it has also been discussed how the urban structure is also constrained and transformed by the action of social actors. Without questioning the powerful influence of structural factors, related to the logic of the production system, labor markets, education and training, the research has shown the role played by place of residence in shaping individual outcomes such as unemployment. In the context of this debate the importance of territory of residence with respect to the problem of unemployment has been highlighted. Although statistics of unemployment have already demonstrated the unequal incidence of the phenomenon in social groups, the issue of uneven territorial impact on the phenomenon at intra-urban level remains relatively unknown. The purpose of this article is to show and to interpret the spatial patterns of unemployment in the city of Porto using GIS (Geographic Information System - GIS) technology. Under this analysis the overlap of the spatial patterns of unemployment with the spatial distribution of social housing, allows the discussion of the relationship that occurs between these patterns and the reasons that might explain the relative immutability of socioeconomic problems in some neighborhoods.

Keywords: Unemployment, area effects, urban planning, Porto.

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10666 Latency-Based Motion Detection in Spiking Neural Networks

Authors: Mohammad Saleh Vahdatpour, Yanqing Zhang

Abstract:

Understanding the neural mechanisms underlying motion detection in the human visual system has long been a fascinating challenge in neuroscience and artificial intelligence. This paper presents a spiking neural network model inspired by the processing of motion information in the primate visual system, particularly focusing on the Middle Temporal (MT) area. In our study, we propose a multi-layer spiking neural network model to perform motion detection tasks, leveraging the idea that synaptic delays in neuronal communication are pivotal in motion perception. Synaptic delay, determined by factors like axon length and myelin insulation, affects the temporal order of input spikes, thereby encoding motion direction and speed. Overall, our spiking neural network model demonstrates the feasibility of capturing motion detection principles observed in the primate visual system. The combination of synaptic delays, learning mechanisms, and shared weights and delays in SMD provides a promising framework for motion perception in artificial systems, with potential applications in computer vision and robotics.

Keywords: Neural networks, motion detection, signature detection, convolutional neural network.

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10665 Social Media as a ‘Service’ for Value Co-Creation by Integrating Sponsoring Companies, Sports Entities and Fans

Authors: Harri Jalonen

Abstract:

Social media has changed the ways we communicate, collaborate and connect with each other. It has also influenced our habits of consuming sports. Social media has allowed direct interaction between sponsoring companies, athletes/players and fans. Drawing on the service dominant logic of value co-creation, the conceptual paper identifies three operant resources which are beneficial for value co-creation: i) social identity and sense of community, ii) congruence and brand personality, and iii) participatory culture and fan activation. The paper contributes to the theoretical discussion on how social can be media used for value co-creation purposes in the sports industry.

Keywords: Sport, value co-creation, social media, service.

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10664 Analysis of Data Gathering Schemes for Layered Sensor Networks with Multihop Polling

Authors: Bhed Bahadur Bista, Danda B. Rawat

Abstract:

In this paper, we investigate multihop polling and data gathering schemes in layered sensor networks in order to extend the life time of the networks. A network consists of three layers. The lowest layer contains sensors. The middle layer contains so called super nodes with higher computational power, energy supply and longer transmission range than sensor nodes. The top layer contains a sink node. A node in each layer controls a number of nodes in lower layer by polling mechanism to gather data. We will present four types of data gathering schemes: intermediate nodes do not queue data packet, queue single packet, queue multiple packets and aggregate data, to see which data gathering scheme is more energy efficient for multihop polling in layered sensor networks.

Keywords: layered sensor network, polling, data gatheringschemes.

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10663 Design and Implementation of Client Server Network Management System for Ethernet LAN

Authors: May Paing Paing Zaw, Su Myat Marlar Soe

Abstract:

Network Management Systems have played a great important role in information systems. Management is very important and essential in any fields. There are many managements such as configuration management, fault management, performance management, security management, accounting management and etc. Among them, configuration, fault and security management is more important than others. Because these are essential and useful in any fields. Configuration management is to monitor and maintain the whole system or LAN. Fault management is to detect and troubleshoot the system. Security management is to control the whole system. This paper intends to increase the network management functionalities including configuration management, fault management and security management. In configuration management system, this paper specially can support the USB ports and devices to detect and read devices configuration and solve to detect hardware port and software ports. In security management system, this paper can provide the security feature for the user account setting and user management and proxy server feature. And all of the history of the security such as user account and proxy server history are kept in the java standard serializable file. So the user can view the history of the security and proxy server anytime. If the user uses this system, the user can ping the clients from the network and the user can view the result of the message in fault management system. And this system also provides to check the network card and can show the NIC card setting. This system is used RMI (Remote Method Invocation) and JNI (Java Native Interface) technology. This paper is to implement the client/server network management system using Java 2 Standard Edition (J2SE). This system can provide more than 10 clients. And then this paper intends to show data or message structure of client/server and how to work using TCP/IP protocol.

Keywords: TCP/ IP based client server application

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10662 On-line Identification of Continuous-time Hammerstein Systems via RBF Networks and Immune Algorithm

Authors: Tomohiro Hachino, Kengo Nagatomo, Hitoshi Takata

Abstract:

This paper deals with an on-line identification method of continuous-time Hammerstein systems by using the radial basis function (RBF) networks and immune algorithm (IA). An unknown nonlinear static part to be estimated is approximately represented by the RBF network. The IA is efficiently combined with the recursive least-squares (RLS) method. The objective function for the identification is regarded as the antigen. The candidates of the RBF parameters such as the centers and widths are coded into binary bit strings as the antibodies and searched by the IA. On the other hand, the candidates of both the weighting parameters of the RBF network and the system parameters of the linear dynamic part are updated by the RLS method. Simulation results are shown to illustrate the proposed method.

Keywords: Continuous-time System, Hammerstein System, OnlineIdentification, Immune Algorithm, RBF network.

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10661 An Approach for the Integration of the Existing Wireless Networks

Authors: Rajkumar Samanta, Abhishek Pal

Abstract:

The demand of high quality services has fueled dimensional research and development in wireless communications and networking. As a result, different wireless technologies like Wireless LAN, CDMA, GSM, UMTS, MANET, Bluetooth and satellite networks etc. have emerged in the last two decades. Future networks capable of carrying multimedia traffic need IP convergence, portability, seamless roaming and scalability among the existing networking technologies without changing the core part of the existing communications networks. To fulfill these goals, the present networking systems are required to work in cooperation to ensure technological independence, seamless roaming, high security and authentication, guaranteed Quality of Services (QoS). In this paper, a conceptual framework for a cooperative network (CN) is proposed for integration of heterogeneous existing networks to meet out the requirements of the next generation wireless networks.

Keywords: Cooperative Network, Wireless Network, Integration.

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10660 ANN Models for Microstrip Line Synthesis and Analysis

Authors: Dr.K.Sri Rama Krishna, J.Lakshmi Narayana, Dr.L.Pratap Reddy

Abstract:

Microstrip lines, widely used for good reason, are broadband in frequency and provide circuits that are compact and light in weight. They are generally economical to produce since they are readily adaptable to hybrid and monolithic integrated circuit (IC) fabrication technologies at RF and microwave frequencies. Although, the existing EM simulation models used for the synthesis and analysis of microstrip lines are reasonably accurate, they are computationally intensive and time consuming. Neural networks recently gained attention as fast and flexible vehicles to microwave modeling, simulation and optimization. After learning and abstracting from microwave data, through a process called training, neural network models are used during microwave design to provide instant answers to the task learned.This paper presents simple and accurate ANN models for the synthesis and analysis of Microstrip lines to more accurately compute the characteristic parameters and the physical dimensions respectively for the required design specifications.

Keywords: Neural Models, Algorithms, Microstrip Lines, Analysis, Synthesis

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10659 Optimal Sizing of SSSC Controllers to Minimize Transmission Loss and a Novel Model of SSSC to Study Transient Response

Authors: A. M. El-Zonkoly

Abstract:

In this paper, based on steady-state models of Flexible AC Transmission System (FACTS) devices, the sizing of static synchronous series compensator (SSSC) controllers in transmission network is formed as an optimization problem. The objective of this problem is to reduce the transmission losses in the network. The optimization problem is solved using particle swarm optimization (PSO) technique. The Newton-Raphson load flow algorithm is modified to consider the insertion of the SSSC devices in the network. A numerical example, illustrating the effectiveness of the proposed algorithm, is introduced. In addition, a novel model of a 3- phase voltage source converter (VSC) that is suitable for series connected FACTS a controller is introduced. The model is verified by simulation using Power System Blockset (PSB) and Simulink software.

Keywords: FACTS, Modeling, PSO, SSSC, Transmission lossreduction.

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10658 Some Aspects of the Sustainable Development in Romania

Authors: Burja C., Burja V.

Abstract:

The paper presents the Romanian realities and perspectives from the point of view of reaching the sustainable development model in the context of the recent accession to the European Union, based on the analysis of the indicators listed in the EU Sustainable Development Strategy. The analysis of the economic-social potential for sustainable development and of the environment aspects show that the objectives stipulated in the renewed EU Sustainable Development Strategy of 2006 can be reached, but an extra effort must be put-in in order to overcome the existing substantial gaps in several areas in relation to the developed countries of the EU. The paper-s conclusions show that even if sustainable development is not an easy target to reach in Romania, there are resources and a growing potential, which can lead to sustainable development if used rationally.

Keywords: Ecological dimension, economic-social potential, strategy, sustainable development

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10657 Determining Earthquake Performances of Existing Reinforced Concrete Buildings by Using ANN

Authors: Musa H. Arslan, Murat Ceylan, Tayfun Koyuncu

Abstract:

In this study, an Artificial Neural Network (ANN) analytical method has been developed for analyzing earthquake performances of the Reinforced Concrete (RC) buildings. 66 RC buildings with four to ten storeys were subjected to performance analysis according to the parameters which are the existing material, loading and geometrical characteristics of the buildings. The selected parameters have been thought to be effective on the performance of RC buildings. In the performance analyses stage of the study, level of performance possible to be shown by these buildings in case of an earthquake was determined on the basis of the 4-grade performance levels specified in Turkish Earthquake Code-2007 (TEC-2007). After obtaining the 4-grade performance level, selected 23 parameters of each building have been matched with the performance level. In this stage, ANN-based fast evaluation algorithm mentioned above made an economic and rapid evaluation of four to ten storey RC buildings. According to the study, the prediction accuracy of ANN has been found about 74%.

Keywords: Artificial neural network, earthquake, performance, reinforced concrete.

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10656 Taxonomy of Threats and Vulnerabilities in Smart Grid Networks

Authors: Faisal Al Yahmadi, Muhammad R. Ahmed

Abstract:

Electric power is a fundamental necessity in the 21st century. Consequently, any break in electric power is probably going to affect the general activity. To make the power supply smooth and efficient, a smart grid network is introduced which uses communication technology. In any communication network, security is essential. It has been observed from several recent incidents that adversary causes an interruption to the operation of networks. In order to resolve the issues, it is vital to understand the threats and vulnerabilities associated with the smart grid networks. In this paper, we have investigated the threats and vulnerabilities in Smart Grid Networks (SGN) and the few solutions in the literature. Proposed solutions showed developments in electricity theft countermeasures, Denial of services attacks (DoS) and malicious injection attacks detection model, as well as malicious nodes detection using watchdog like techniques and other solutions.

Keywords: Smart grid network, security, threats, vulnerabilities.

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10655 A Genetic Algorithm Approach Considering Zero Injection Bus Constraint Modeling for Optimal Phasor Measurement Unit Placement

Authors: G. Chandana Sushma, T. R. Jyothsna

Abstract:

This paper presents optimal Phasor Measurement Unit (PMU) Placement in network using a genetic algorithm approach as it is infeasible and require high installation cost to place PMUs at every bus in network. This paper proposes optimal PMU allocation considering observability and redundancy utilizing Genetic Algorithm (GA) approach. The nonlinear constraints of buses are modeled to give accurate results. Constraints associated with Zero Injection (ZI) buses and radial buses are modeled to optimize number of locations for PMU placement. GA is modeled with ZI bus constraints to minimize number of locations without losing complete observability. Redundancy of every bus in network is computed to show optimum redundancy of complete system network. The performance of method is measured by Bus Observability Index (BOI) and Complete System Observability Performance Index (CSOPI). MATLAB simulations are carried out on IEEE -14, -30 and -57 bus-systems and compared with other methods in literature survey to show the effectiveness of the proposed approach.

Keywords: Constraints, genetic algorithm, observability, phasor measurement units, redundancy, synchrophasors, zero injection bus.

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10654 Data Projects for “Social Good”: Challenges and Opportunities

Authors: Mikel Niño, Roberto V. Zicari, Todor Ivanov, Kim Hee, Naveed Mushtaq, Marten Rosselli, Concha Sánchez-Ocaña, Karsten Tolle, José Miguel Blanco, Arantza Illarramendi, Jörg Besier, Harry Underwood

Abstract:

One of the application fields for data analysis techniques and technologies gaining momentum is the area of social good or “common good”, covering cases related to humanitarian crises, global health care, or ecology and environmental issues, among others. The promotion of data-driven projects in this field aims at increasing the efficacy and efficiency of social initiatives, improving the way these actions help humanity in general and people in need in particular. This application field, however, poses its own barriers and challenges when developing data-driven projects, lagging behind in comparison with other scenarios. These challenges derive from aspects such as the scope and scale of the social issue to solve, cultural and political barriers, the skills of main stakeholders and the technological resources available, the motivation to be engaged in such projects, or the ethical and legal issues related to sensitive data. This paper analyzes the application of data projects in the field of social good, reviewing its current state and noteworthy initiatives, and presenting a framework covering the key aspects to analyze in such projects. The goal is to provide guidelines to understand the main challenges and opportunities for this type of data project, as well as identifying the main differential issues compared to “classical” data projects in general. A case study is presented on the initial steps and stakeholder analysis of a data project for the inclusion of refugees in the city of Frankfurt, Germany, in order to empirically confront the framework with a real example.

Keywords: Data-Driven projects, humanitarian operations, personal and sensitive data, social good, stakeholders analysis.

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10653 The Use of Mobile Phones by Refugees to Create Social Connectedness: A Literature Review

Authors: Sarah Vuningoma, Maria Rosa Lorini, Wallace Chigona

Abstract:

Mobile phones are one of the main tools for promoting the wellbeing of people and supporting the integration of communities on the margins such as refugees. Information and Communication Technology has the potential to contribute towards reducing isolation, loneliness, and to assist in improving interpersonal relations and fostering acculturation processes. Therefore, the use of mobile phones by refugees might contribute to their social connectedness. This paper aims to demonstrate how existing literature has shown how the use of mobile phones by refugees should engender social connectedness amongst the refugees. Data for the study are drawn from existing literature; we searched a number of electronic databases for papers published between 2010 and 2019. The main findings of the study relate to the use of mobile phones by refugees to (i) create a sense of belonging, (ii) maintain relationships, and (iii) advance the acculturation process. The analysis highlighted a gap in the research over refugees and social connectedness. In particular, further studies should consider evaluating the differences between those who have a refugee permit, those who are waiting for the refugee permit, and those whose request was denied.

Keywords: Belonging, mobile phones, refugees, social connectedness.

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