Search results for: Social network analysis

Authors: Yong-Quan Zhou, Deng-Xu He, Zheng Nong

Abstract:

In this paper two models using a functional network were employed to solving classification problem. Functional networks are generalized neural networks, which permit the specification of their initial topology using knowledge about the problem at hand. In this case, and after analyzing the available data and their relations, we systematically discuss a numerical analysis method used for functional network, and apply two functional network models to solving XOR problem. The XOR problem that cannot be solved with two-layered neural network can be solved by two-layered functional network, which reveals a potent computational power of functional networks, and the performance of the proposed model was validated using classification problems.

Keywords: Functional network, neural network, XOR problem, classification, numerical analysis method.

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Authors: M. Pollar, M. Jaroensutasinee, K. Jaroensutasinee

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The population structure of the Tor tambroides was investigated with morphometric data (i.e. morphormetric measurement and truss measurement). A morphometric analysis was conducted to compare specimens from three waterfalls: Sunanta, Nan Chong Fa and Wang Muang waterfalls at Khao Nan National Park, Nakhon Si Thammarat, Southern Thailand. The results of stepwise discriminant analysis on seven morphometric variables and 21 truss variables per individual were the same as from a neural network. Fish from three waterfalls were separated into three groups based on their morphometric measurements. The morphometric data shows that the nerual network model performed better than the stepwise discriminant analysis.

Keywords: Morphometric, Tor tambroides, Stepwise Discriminant Analysis , Neural Network Analysis.

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Authors: Jooyeon Yook, Wonjun Ko

Abstract:

As the Social network game(SNG) is rising dramatically worldwide, an interesting aspect has appeared in the demographic analysis. That is the ratio of the game users by gender. Although the ratio of male and female users in online game was 60:40% previously, the ratio of male and female users in SNG stood at 47:53% which shows that the ratio of female users is higher than that of male users. Here, it should be noted that 35% in those 53% female users are the first-time users of game. This fact suggests that women who were not interested in game previously has taken an interest in SNG. Notwithstanding this issue, there have been little studies on the female users of SNG although there are many studies that analyzed the tendency of female users- online game play. This study conducted the analyzed how the game-playing tendency of SNG gamers was manifested in the game by gender. For that, this study will identify the tendency of SNG users by gender based on the preceding studies that analyzed the online game users by gender. The subject of this study was confined to the farm and urban construction simulation games which were offered based on the mobile application platform. Regarding the methodology of study, the first focus group interview(FGI) was conducted with the male and female users who had played games on Social network service(SNS) until recently. Later, the second one-on-one in-depth interview was conducted to gain an insight into the psychological state of the subjects.

Keywords: Social network Game, Gender, Play inclination, Game psychology

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Authors: Sangdeok Lee, Sangwon Han, Changtaek Hyun

Abstract:

Construction defects are major components that result in negative impacts on project performance including schedule delays and cost overruns. Since construction defects generally occur when a few associated causes combine, a thorough understanding of defect causality is required in order to more systematically prevent construction defects. To address this issue, this paper uses association rule mining (ARM) to quantify the causality between defect causes, and social network analysis (SNA) to find indirect causality among them. The suggested approach is validated with 350 defect instances from concrete works in 32 projects in Korea. The results show that the interrelationships revealed by the approach reflect the characteristics of the concrete task and the important causes that should be prevented.

Keywords: Causality, defect causes, social network analysis, association rule mining.

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Authors: B. Q. Huang, Tarik Rashid, M-T. Kechadi

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this paper presents a multi-context recurrent network for time series analysis. While simple recurrent network (SRN) are very popular among recurrent neural networks, they still have some shortcomings in terms of learning speed and accuracy that need to be addressed. To solve these problems, we proposed a multi-context recurrent network (MCRN) with three different learning algorithms. The performance of this network is evaluated on some real-world application such as handwriting recognition and energy load forecasting. We study the performance of this network and we compared it to a very well established SRN. The experimental results showed that MCRN is very efficient and very well suited to time series analysis and its applications.

Keywords: Gradient descent method, recurrent neural network, learning algorithms, time series, BP

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Authors: M. Kassim, M. Ismail, K. Jumari, M.I Yusof

Abstract:

this paper presented a survey analysis subjected on network bandwidth management from published papers referred in IEEE Explorer database in three years from 2009 to 2011. Network Bandwidth Management is discussed in today-s issues for computer engineering applications and systems. Detailed comparison is presented between published papers to look further in the IP based network critical research area for network bandwidth management. Important information such as the network focus area, a few modeling in the IP Based Network and filtering or scheduling used in the network applications layer is presented. Many researches on bandwidth management have been done in the broad network area but fewer are done in IP Based network specifically at the applications network layer. A few researches has contributed new scheme or enhanced modeling but still the issue of bandwidth management still arise at the applications network layer. This survey is taken as a basic research towards implementations of network bandwidth management technique, new framework model and scheduling scheme or algorithm in an IP Based network which will focus in a control bandwidth mechanism in prioritizing the network traffic the applications layer.

Keywords: Bandwidth Management (BM), IP Based network, modeling, algorithm, internet traffic, network Management, Quality of Service (QoS).

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Authors: B. Golchin, N. Riahi

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One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.

Keywords: emotion classification, sentiment analysis, social networks, deep neural networks

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Authors: Daniel Padilla, Edward Guillen

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Several wireless networks security standards have been proposed and widely implemented in both business and home environments in order to protect the network from unauthorized access. However, the implementation of such standards is usually achieved by network administrators without even knowing the standards- weaknesses and strengths. The intention of this paper is to evaluate and analyze the impact over the network-s security due to the implementation of the wireless networks security standards WEP, WPA and WLAN 802.1X.

Keywords: 802.1X, vulnerabilities analysis, WEP, wireless security, WPA.

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Authors: Hossein Esbati, Jalil Shirazi

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In this paper, in order to categorize ORL database face pictures, principle Component Analysis (PCA) and Kernel Principal Component Analysis (KPCA) methods by using Elman neural network and Support Vector Machine (SVM) categorization methods are used. Elman network as a recurrent neural network is proposed for modeling storage systems and also it is used for reviewing the effect of using PCA numbers on system categorization precision rate and database pictures categorization time. Categorization stages are conducted with various components numbers and the obtained results of both Elman neural network categorization and support vector machine are compared. In optimum manner 97.41% recognition accuracy is obtained.

Keywords: Face recognition, Principal Component Analysis, Kernel Principal Component Analysis, Neural network, Support Vector Machine.

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Authors: Mohammad Akbarpour, Reza Nasiri Mahalati, Caro Lucas

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The existence of many biological systems, especially human societies, is based on cooperative behavior [1, 2]. If natural selection favors selfish individuals, then what mechanism is at work that we see so many cooperative behaviors? One answer is the effect of network structure. On a graph, cooperators can evolve by forming network bunches [2, 3, 4]. In a research, Ohtsuki et al used the idea of iterated prisoners- dilemma on a graph to model an evolutionary game. They showed that the average number of neighbors plays an important role in determining whether cooperation is the ESS of the system or not [3]. In this paper, we are going to study the dynamics of evolution of cooperation in a social network. We show that during evolution, the ratio of cooperators among individuals with fewer neighbors to cooperators among other individuals is greater than unity. The extent to which the fitness function depends on the payoff of the game determines this ratio.

Keywords: Evolution of cooperation, Iterated prisoner's dilemma, Model dynamics, Social network structure, Intensity of selection.

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Authors: Jameson McFarlane, Thorne J. McFarlane, Leon Bernard

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Social network sites (SNS) is an emerging phenomenon that is here to stay. The popularity and the ubiquity of the SNS technology are undeniable. Because most SNS are free and easy to use people from all walks of life and from almost any age are attracted to that technology. College age students are by far the largest segment of the population using SNS. Since most SNS have been adapted for mobile devices, not only do you find students using this technology in their study, while working on labs or on projects, a substantial number of students have been found to use SNS even while listening to lectures. This study found that SNS use has a significant negative impact on the grade point average of college students particularly in the first semester. However, this negative impact is greatly diminished by the end of the third semester partly because the students have adjusted satisfactorily to the challenges of college or because they have learned how to adequately manage their time. It was established that the kinds of activities the students are engaged in during the SNS use are the leading factor affecting academic performance. Of those activities, using SNS during a lecture or while studying is the foremost contributing factor to lower academic performance. This is due to “cognitive” or “information” bottleneck, a condition in which the students find it very difficult to multitask or to switch between resources leading to inefficiency in information retention and thus, educational performance.

Keywords: Social network sites, social network analysis, regression coefficient, psychological engagement.

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Authors: Kanda Runapongsa Saikaew, Patcharaporn Jiranuwattanawong, Patinya Taearak

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Currently, there is excessively growing information about places on Facebook, which is the largest social network but such information is not explicitly organized and ranked. Therefore users cannot exploit such data to recommend places conveniently and quickly. This paper proposes a Facebook application and an Android application that recommend places based on the number of check-ins of those places, the distance of those places from the current location, the number of people who like Facebook page of those places, and the number of talking about of those places. Related Facebook data is gathered via Facebook API requests. The experimental results of the developed applications show that the applications can recommend places and rank interesting places from the most to the least. We have found that the average satisfied score of the proposed Facebook application is 4.8 out of 5. The users’ satisfaction can increase by adding the app features that support personalization in terms of interests and preferences.

Keywords: Mobile computing, location-based services, recommendation system, social network analysis.

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Authors: Eman AbuKhousa, Marwan Z. Bataineh

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The 21^st century higher education and globalization challenge new faculty members to build effective professional networks and partnership with industry in order to accelerate their growth and success. This creates the need for community of practice (CoP)-oriented development approaches that focus on cognitive apprenticeship while considering individual predisposition and future career needs. This work adopts data mining, clustering analysis, and social networking technologies to present the CoP-Network as a virtual space that connects together similar career-aspiration individuals who are socially influenced to join and engage in a process for domain-related knowledge and practice acquisitions. The CoP-Network model can be integrated into higher education to extend traditional graduate and professional development programs.

Keywords: Clustering analysis, community of practice, data mining, higher education, new faculty challenges, social networks, social influence, professional development.

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Authors: Nisarg A. Patel, Hiren B. Patel

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Quantum cryptography is described as a point-to-point secure key generation technology that has emerged in recent times in providing absolute security. Researchers have started studying new innovative approaches to exploit the security of Quantum Key Distribution (QKD) for a large-scale communication system. A number of approaches and models for utilization of QKD for secure communication have been developed. The uncertainty principle in quantum mechanics created a new paradigm for QKD. One of the approaches for use of QKD involved network fashioned security. The main goal was point-to-point Quantum network that exploited QKD technology for end-to-end network security via high speed QKD. Other approaches and models equipped with QKD in network fashion are introduced in the literature as. A different approach that this paper deals with is using QKD in existing protocols, which are widely used on the Internet to enhance security with main objective of unconditional security. Our work is towards the analysis of the QKD in Mobile ad-hoc network (MANET).

Keywords: QKD, cryptography, quantum cryptography, network performance.

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

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Social interest and demand on Home-Network has been increasing greatly. Although various services are being introduced to respond to such demands, they can cause serious security problems when linked to the open network such as Internet. This paper reviews the security requirements to protect the service users with assumption that the Home-Network environment is connected to Internet and then proposes the security model based on the requirement. The proposed security model can satisfy most of the requirements and further can be dynamically applied to the future ubiquitous Home-Networks.

Keywords: Home-Network, Security, Vulnerability, Response, Countermeasure.

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Authors: Khin Sandar Win

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In multi hop wireless systems, such as ad hoc and sensor networks, mobile ad hoc network applications are deployed, security emerges as a central requirement. A particularly devastating attack is known as the wormhole attack, where two or more malicious colluding nodes create a higher level virtual tunnel in the network, which is employed to transport packets between the tunnel end points. These tunnels emulate shorter links in the network. In which adversary records transmitted packets at one location in the network, tunnels them to another location, and retransmits them into the network. The wormhole attack is possible even if the attacker has not compromised any hosts and even if all communication provides authenticity and confidentiality. In this paper, we analyze wormhole attack nature in ad hoc and sensor networks and existing methods of the defending mechanism to detect wormhole attacks without require any specialized hardware. This analysis able to provide in establishing a method to reduce the rate of refresh time and the response time to become more faster.

Keywords: Ad hoc network, Sensor network, Wormhole attack, defending mechanism.

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Authors: Taras Agryzkov, Almudena Nolasco-Cirugeda, Jos´e L. Oliver, Leticia Serrano-Estrada, Leandro Tortosa, Jos´e F. Vicent

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This paper aims to represent the commercial activity of a city taking as source data the social network Foursquare. The city of Murcia is selected as case study, and the location-based social network Foursquare is the main source of information. After carrying out a reorganisation of the user-generated data extracted from Foursquare, it is possible to graphically display on a map the various city spaces and venues especially those related to commercial, food and entertainment sector businesses. The obtained visualisation provides information about activity patterns in the city of Murcia according to the people‘s interests and preferences and, moreover, interesting facts about certain characteristics of the town itself.

Keywords: Social networks, Foursquare, spatial analysis, data visualization, geocomputation.

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Authors: Zhao Linfei, Gu Qingliang

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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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Authors: Yongyoon Suh, Chulhyun Kim, Moon-soo Kim

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As increasing importance of symbiosis and cooperation among mobile communication industries, the mobile ecosystem has been especially highlighted in academia and practice. The structure of mobile ecosystem is quite complex and the ecological role of actors is important to understand that structure. In this respect, this study aims to explore structure of mobile ecosystem in the case of Korea using inter-industry network analysis. Then, the ecological roles in mobile ecosystem are identified using centrality measures as a result of network analysis: degree of centrality, closeness, and betweenness. The result shows that the manufacturing and service industries are separate. Also, the ecological roles of some actors are identified based on the characteristics of ecological terms: keystone, niche, and dominator. Based on the result of this paper, we expect that the policy makers can formulate the future of mobile industry and healthier mobile ecosystem can be constructed.

Keywords: Mobile ecosystem, structure, ecological roles, network analysis, network index.

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Authors: Qurban A Memon, Mohammad S. Laghari

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Integration of system process information obtained through an image processing system with an evolving knowledge database to improve the accuracy and predictability of wear debris analysis is the main focus of the paper. The objective is to automate intelligently the analysis process of wear particle using classification via self-organizing maps. This is achieved using relationship measurements among corresponding attributes of various measurements for wear debris. Finally, visualization technique is proposed that helps the viewer in understanding and utilizing these relationships that enable accurate diagnostics.

Keywords: Relationship Network, Relationship Measurement, Self-organizing Clusters, Wear Debris Analysis, Kohonen Network

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Authors: Yasemin Gülşen Yılmaz, Süleyman Hakan Yılmaz, Muhammet Erbay

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Social media is among the most important means of communication. Social media offers individuals and groups with an opportunity for participatory socialization over the internet, which is free of any time and place restrictions. Social media is a kind of interactive communication and bilateral social network. Various communication contents can be shared and put into mass circulation easily and quickly through social media. These sharings are not only limited to individuals but also happen to groups, institutions, and different constitutions. Their contents consist of any type of written message, audio and video files. We are living in the social media era now. It is not surprising that social media which has extensive communication facilities and massive prevalence is used in politics. Therefore, the use of social media (Facebook) by political parties during the Turkish general elections held on June 7, 2015, has been chosen as our research subject. Four parties namely, AKP, CHP, MHP and HDP who have the majority of votes in Turkey and participate in elections in Konya have been selected for our study. Their provincial centers’ and parliamentary candidates` use of social media (Facebook) on the last three days prior to the election have been examined and subjected to a qualitative analysis by means of content analysis.

Keywords: Social media, June 7 general elections, politics, Facebook.

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Authors: Marko A. Rodriguez

Abstract:

There exists an injective, information-preserving function that maps a semantic network (i.e a directed labeled network) to a directed network (i.e. a directed unlabeled network). The edge label in the semantic network is represented as a topological feature of the directed network. Also, there exists an injective function that maps a directed network to an undirected network (i.e. an undirected unlabeled network). The edge directionality in the directed network is represented as a topological feature of the undirected network. Through function composition, there exists an injective function that maps a semantic network to an undirected network. Thus, aside from space constraints, the semantic network construct does not have any modeling functionality that is not possible with either a directed or undirected network representation. Two proofs of this idea will be presented. The first is a proof of the aforementioned function composition concept. The second is a simpler proof involving an undirected binary encoding of a semantic network.

Keywords: general-modeling, multi-relational networks, semantic networks

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Authors: Nidhi Gupta, Sanjoy Das, Khushal Singh

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A Mobile Ad-hoc Network (MANET) is a self managing network consists of versatile nodes that are capable of communicating with each other without having any fixed infrastructure. These nodes may be routers and/or hosts. Due to this dynamic nature of the network, routing protocols are vulnerable to various kinds of attacks. The black hole attack is one of the conspicuous security threats in MANETs. As the route discovery process is obligatory and customary, attackers make use of this loophole to get success in their motives to destruct the network. In Black hole attack the packet is redirected to a node that actually does not exist in the network. Many researchers have proposed different techniques to detect and prevent this type of attack. In this paper, we have analyzed various routing protocols in this context. Further we have shown a critical comparison among various protocols. We have shown various routing metrics are required proper and significant analysis of the protocol.

Keywords: Black Hole, MANET, Performance Parameters, Routing Protocol.

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Authors: Jakyoung Kim, Sungwook Jang

Abstract:

The purpose of this study is to examine the research trends of life-long education for people with disabilities using a keyword network analysis. For this purpose, 151 papers were selected from 594 papers retrieved using keywords such as 'people with disabilities' and 'life-long education' in the Korean Education and Research Information Service. The Keyword network analysis was constructed by extracting and coding the keyword used in the title of the selected papers. The frequency of the extracted keywords, the centrality of degree, and betweenness was analyzed by the keyword network. The results of the keyword network analysis are as follows. First, the main keywords that appeared frequently in the study of life-long education for people with disabilities were 'people with disabilities', 'life-long education', 'developmental disabilities', 'current situations', 'development'. The research trends of life-long education for people with disabilities are focused on the current status of the life-long education and the program development. Second, the keyword network analysis and visualization showed that the keywords with high frequency of occurrences also generally have high degree centrality and betweenness centrality. In terms of the keyword network diagram, it was confirmed that research trends of life-long education for people with disabilities are centered on six prominent keywords. Based on these results, it was discussed that life-long education for people with disabilities in the future needs to expand the subjects and the supporting areas of the life-long education, and the research needs to be further expanded into more detailed and specific areas. 

Keywords: Life-long education, people with disabilities, research trends, keyword network analysis.

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Authors: Xi Xiao, Chunhui Chen, Xinyu Liu, Guangwu Hu, Yong Jiang

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Location sharing is a fundamental service in mobile Online Social Networks (mOSNs), which raises significant privacy concerns in recent years. Now, most location-based service applications adopt client/server architecture. In this paper, a location sharing system, named CSLocShare, is presented to provide flexible privacy-preserving location sharing with client/server architecture in mOSNs. CSLocShare enables location sharing between both trusted social friends and untrusted strangers without the third-party server. In CSLocShare, Location-Storing Social Network Server (LSSNS) provides location-based services but do not know the users’ real locations. The thorough analysis indicates that the users’ location privacy is protected. Meanwhile, the storage and the communication cost are saved. CSLocShare is more suitable and effective in reality.

Keywords: Client/server architecture, location sharing, mobile online social networks, privacy-preserving.

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Authors: J. K. Shrestha, A. Benta, R. B. Lopes, N. Lopes

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This paper presents a multi-objective model for addressing two main objectives in designing rural roads networks: minimization of user operation costs and maximization of population covered. As limited budgets often exist, a reasonable trade-off must be obtained in order to account for both cost and social benefits in this type of networks. For a real-world rural road network, the model is solved, where all non-dominated solutions were obtained. Afterwards, an analysis is made on the (possibly) most interesting solutions (the ones providing better trade-offs). This analysis, coupled with the knowledge of the real world scenario (typically provided by decision makers) provides a suitable method for the evaluation of road networks in rural areas of developing countries.

Keywords: Multi-objective, user operation cost, population covered, rural road network.

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Authors: S.M. Sarwarul Islam Rizvi, Zinat Sultana, Bo Sun, Md. Washiqul Islam

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In a very simple form a Mobile Agent is an independent piece of code that has mobility and autonomy behavior. One of the main advantages of using Mobile Agent in a network is - it reduces network traffic load. In an, ad hoc network Mobile Agent can be used to protect the network by using agent based IDS or IPS. Besides, to deploy dynamic software in the network or to retrieve information from network nodes Mobile Agent can be useful. But in an ad hoc network the Mobile Agent itself needs some security. Security services should be guaranteed both for Mobile Agent and for Agent Server. In this paper to protect the Mobile Agent and Agent Server in an ad hoc network we have proposed a solution which is based on Threshold Cryptography, a new vibe in the cryptographic world where trust is distributed among multiple nodes in the network.

Keywords: Ad hoc network, Mobile Agent, Security, Threats, Threshold Cryptography.

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Authors: Chaudhuri Manoj Kumar Swain, Susmita Das

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This paper explores a detailed procedure of predicting a path loss (PL) model and its application in estimating the coverage probability in a WiMAX network. For this a hybrid approach is followed in predicting an empirical PL model of a 2.65 GHz WiMAX network deployed in a suburban environment. Data collection, statistical analysis, and regression analysis are the phases of operations incorporated in this approach and the importance of each of these phases has been discussed properly. The procedure of collecting data such as received signal strength indicator (RSSI) through experimental set up is demonstrated. From the collected data set, empirical PL and RSSI models are predicted with regression technique. Furthermore, with the aid of the predicted PL model, essential parameters such as PL exponent as well as the coverage probability of the network are evaluated. This research work may assist in the process of deployment and optimisation of any cellular network significantly.

Keywords: WiMAX, RSSI, path loss, coverage probability, regression analysis.

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Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

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Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: Network Intrusion Detection, Machine learning, Artificial Neural Network.

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Authors: Paramet Nualmuenwai, Chutima Prommak

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This paper presents the IP traffic analysis. The traffic was collected from the network of Suranaree University of Technology using the software based on the Simple Network Management Protocol (SNMP). In particular, we analyze the distribution of the aggregated traffic during the hours of peak load and light load. The traffic profiles including the parameters described the traffic distributions were derived. From the statistical analysis applying three different methods, including the Kolmogorov Smirnov test, Anderson Darling test, and Chi-Squared test, we found that the IP traffic distribution is a non-normal distribution and the distributions during the peak load and the light load are different. The experimental study and analysis show high uncertainty of the IP traffic.

Keywords: IP traffic analysis, IP traffic distribution, Traffic uncertainty

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