Search results for: social network ties

Authors: Omid Ataei Nia, Karim Salahshoor

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In this paper, a new precise and reliable sensor network methodology is introduced for unit processes and operations using the Constriction Coefficient Particle Swarm Optimization (CPSO) method. CPSO is introduced as a new search engine for optimal sensor network design purposes. Furthermore, a Square Root Unscented Kalman Filter (SRUKF) algorithm is employed as a new data reconciliation technique to enhance the stability and accuracy of the filter. The proposed design procedure incorporates precision, cost, observability, reliability together with importance-of-variables (IVs) as a novel measure in Instrumentation Criteria (IC). To the best of our knowledge, no comprehensive approach has yet been proposed in the literature to take into account the importance of variables in the sensor network design procedure. In this paper, specific weight is assigned to each sensor, measuring a process variable in the sensor network to indicate the importance of that variable over the others to cater to the ultimate sensor network application requirements. A set of distinct scenarios has been conducted to evaluate the performance of the proposed methodology in a simulated Continuous Stirred Tank Reactor (CSTR) as a highly nonlinear process plant benchmark. The obtained results reveal the efficacy of the proposed method, leading to significant improvement in accuracy with respect to other alternative sensor network design approaches and securing the definite allocation of sensors to the most important process variables in sensor network design as a novel achievement.

Keywords: constriction coefficient PSO, importance of variable, MRMSE, reliability, sensor network design, square root unscented Kalman filter

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Authors: Elena Pello, Martin Bobak, Yuri Nikitin

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In current issue we evaluated integration of magnesium with lipids; the attractive findings were obtained in men and women; the crucial ties of magnesium with total cholesterol in hypertensive men, with total cholesterol in concordance with low-density lipoprotein cholesterol in hypertensive women were disclosed; unanswered questions were trapped, difficulties were surmounted, and magnesium deficiency perseverance in pathogenesis of cardiovascular disease development was expressed; nutrients as well as risk factors may contribute to cardiovascular complications.

Keywords: dietary, magnesium, hypertension, lipids

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Authors: Jessica Achebe, Susan Tighe

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The reduction of material consumption and greenhouse gas emission when maintain and rehabilitating road networks can achieve added benefits including improved life cycle performance of pavements, reduced climate change impacts and human health effect due to less air pollution, improved productivity due to an optimal allocation of resources and reduced road user cost. This is the essence of incorporating environmental sustainability into pavement management. The functionality of performance measurement approach has made it one of the most valuable tool to Pavement Management Systems (PMSs) to account for different criteria in the decision-making process. However measuring the environmental performance of road network is still a far-fetched practice in road network management, more so an ostensive agency-wide environmental sustainability or sustainable maintenance specifications is missing. To address this challenge, this present research focuses on the environmental sustainability performance of network-level pavement management. The ultimate goal is to develop a framework to incorporate environmental sustainability in pavement management systems for network-level maintenance programming. In order to achieve this goal, this paper present the first step, the intention is to review the previous studies that employed environmental performance measures, as well as the suitability of environmental performance indicators for the evaluation of the sustainability of network-level pavement maintenance strategies. Through an industry practice survey, this paper provides a brief forward regarding the pavement manager motivations and barriers to making more sustainable decisions, and data needed to support the network-level environmental sustainability. The trends in network-level sustainable pavement management are also presented, existing gaps are highlighted, and ideas are proposed for network-level sustainable maintenance and rehabilitation programming.

Keywords: pavement management, environment sustainability, network-level evaluation, performance measures

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Authors: Saman Keshavarzi

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The process of planning, designing and building neighborhoods is a complex and multidimensional part of urban planning. Understanding the elements that give a neighborhood a sense of identity can lead to successful city planning and result in a cohesive and functional community where people feel a sense of belonging. These factors are important in ensuring that the needs of the urban population are met to live in a safe, pleasant and healthy society. This research paper aims to identify the elements of the identity of traditional neighborhoods in Isfahan and analyzes ways of using these elements in the design of modern neighborhoods to increase social interaction between communities and cultural reunification of people. The neighborhood of Jolfa in Isfahan has a unique socio-cultural identity as it dates back to the Safavid Dynasty of the 16^th century, and most of its inhabitants are Christian Armenians of a religious minority. The elements of the identity of Jolfa were analyzed through the following research methods: field observations, distribution of questionnaires and qualitative analysis. The basic methodology that was used to further understand the Jolfa neighborhood and deconstruct the identity image that residents associate with their respective neighborhoods was a qualitative research method. This was done through utilizing questionnaires that respondents had to fill out in response to a series of research questions. From collecting these qualitative data, the major finding was that traditional neighborhoods that have elements of identity embedded in them are seen to have closer-knit communities whose residents have strong societal ties. This area of study in urban planning is vital to ensuring that new neighborhoods are built with concepts of social cohesion, community and inclusion in mind as they are what lead to strong, connected, and prosperous societies.

Keywords: development, housing, identity, neighborhood, policy, urbanization

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Authors: Quinn Au, Amedeo Carmine, Tauheed Khan Mohd

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The Internet of Things (IoT) is emerging as a new development in information technology in recent years, with the potential to improve convenience and efficiency in life. Following the rise of IoT, the Social Internet of Things (SIoT) is another new development in which the benefits of connectivity and user-friendliness from social network services (SNS) are its main features. With the introduction of IoT, the world will be much more modernized, convenient, and industrialized. This paper will discuss the applications of IoT in different sectors such as healthcare services, education, and lifestyle. The privacy challenges that IoT still poses to user data will also be discussed. Finally, an empirical study to evaluate the number of active installed IoT connections in recent years demonstrates the increase in usage of IoT regardless of the privacy challenges. The study also examines some types of IoT devices that are being preferred in the market and predictions from researchers about IoT in the upcoming years.

Keywords: IoT, health care, robotics, social Internet of Things

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Authors: Alireza Pour Ebrahimi, Vahid Abasi

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Recently by the extension of internet usage, Research on the intrusion detection system takes a significant importance. Many of improvement systems prevent internal and external network attacks by providing security through firewalls and antivirus. In recently years, intrusion detection systems gradually turn from host-based systems and depend on O.S to the distributed systems which are running on multiple O.S. In this work, by considering the diversity of computer networks whit respect to structure, architecture, resource, services, users and also security goals requirement a fully distributed collaborative intrusion detection system based on peer to peer architecture is suggested. in this platform each partner device (matched device) considered as a peer-to-peer network. All transmitted information to network are visible only for device that use security scanning of a source. Experimental results show that the distributed architecture is significantly upgradeable in respect to centralized approach.

Keywords: network, intrusion detection system, peer to peer, internal and external network

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Authors: Omojokun G. Aju, Adedayo O. Sule

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ZigBee wireless sensor and control network is one of the most popularly deployed wireless technologies in recent years. This is because ZigBee is an open standard lightweight, low-cost, low-speed, low-power protocol that allows true operability between systems. It is built on existing IEEE 802.15.4 protocol and therefore combines the IEEE 802.15.4 features and newly added features to meet required functionalities thereby finding applications in wide variety of wireless networked systems. ZigBee‘s current focus is on embedded applications of general-purpose, inexpensive, self-organising networks which requires low to medium data rates, high number of nodes and very low power consumption such as home/industrial automation, embedded sensing, medical data collection, smart lighting, safety and security sensor networks, and monitoring systems. Although the ZigBee design specification includes security features to protect data communication confidentiality and integrity, however, when simplicity and low-cost are the goals, security is normally traded-off. A lot of researches have been carried out on ZigBee technology in which emphasis has mainly been placed on ZigBee network performance characteristics such as energy efficiency, throughput, robustness, packet delay and delivery ratio in different scenarios and applications. This paper investigate and analyse the data accuracy, network implementation difficulties and security challenges of ZigBee network applications in star-based and mesh-based topologies with emphases on its home monitoring application using the ZigBee ProBee ZE-10 development boards for the network setup. The paper also expose some factors that need to be considered when designing ZigBee network applications and suggest ways in which ZigBee network can be designed to provide more resilient to network attacks.

Keywords: home monitoring, IEEE 802.14.5, topology, wireless security, wireless sensor network (WSN), ZigBee

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Authors: Ci Lin, Tet Yeap, Iluju Kiringa

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This paper introduces the subspace rotation algorithm (SRA) to train the Restricted Hopfield Network (RHN) as an auto-associative memory. Subspace rotation algorithm is a gradient-free subspace tracking approach based on the singular value decomposition (SVD). In comparison with Backpropagation Through Time (BPTT) on training RHN, it is observed that SRA could always converge to the optimal solution and BPTT could not achieve the same performance when the model becomes complex, and the number of patterns is large. The AUTS case study showed that the RHN model trained by SRA could achieve a better structure of attraction basin with larger radius(in general) than the Hopfield Network(HNN) model trained by Hebbian learning rule. Through learning 10000 patterns from MNIST dataset with RHN models with different number of hidden nodes, it is observed that an several components could be adjusted to achieve a balance between recovery accuracy and noise resistance.

Keywords: hopfield neural network, restricted hopfield network, subspace rotation algorithm, hebbian learning rule

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Authors: Zhizhong Yuan, Lili Wang, Chenya Zheng, Wuqi Yang

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How to encourage and support peer-to-peer (P2P) network lending, and effectively monitor the risk of P2P network lending, has become the focus of the Chinese government departments, industrialists, experts and scholars in recent years. The reason is that this convenient online micro-credit service brings a series of credit risks and other issues. Avoiding the risks brought by the P2P network lending model, it can better play a benign role and help China's small and medium-sized private enterprises with vigorous development to solve the capital needs; otherwise, it will bring confusion to the normal financial order. As a form of financial services, P2P network lending has injected new blood into China's non-government finance in the past ten years, and has found a way out for idle funds and made up for the shortage of traditional financial services in China. However, it lacks feasible measures in credit evaluation and government supervision. This paper collects a large amount of data about P2P network lending of China. The data collection comes from the official media of the Chinese government, the public achievements of existing researchers and the analysis and collation of correlation data by the authors. The research content of this paper includes literature review; the current situation of China's P2P network lending development; the risk analysis of P2P network lending in China; the risk prevention strategy of P2P network lending in China. The focus of this paper is to try to find a specific program to strengthen supervision and avoid risks from the perspective of government regulators, operators of P2P network lending platform, investors and users of funds. These main measures include: China needs to develop self-discipline organization of P2P network lending industry and formulate self-discipline norms as soon as possible; establish a regular information disclosure system of P2P network lending platform; establish censorship of credit rating of borrowers; rectify the P2P network lending platform in compliance through the implementation of bank deposition. The results and solutions will benefit all the P2P network lending platforms, creditors, debtors, bankers, independent auditors and government agencies of China and other countries.

Keywords: peer-to-peer(P2P), regulation, risk prevention, supervision

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Authors: Katsumi Hirata

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Certain systems can function well only if they recognize the sound environment as humans do. In this research, we focus on sound classification by adopting a convolutional neural network and aim to develop a method that automatically classifies various environmental sounds. Although the neural network is a powerful technique, the performance depends on the type of input data. Therefore, we propose an approach via a slice bispectrogram, which is a third-order spectrogram and is a slice version of the amplitude for the short-time bispectrum. This paper explains the slice bispectrogram and discusses the effectiveness of the derived method by evaluating the experimental results using the ESC‑50 sound dataset. As a result, the proposed scheme gives high accuracy and stability. Furthermore, some relationship between the accuracy and non-Gaussianity of sound signals was confirmed.

Keywords: environmental sound, bispectrum, spectrogram, slice bispectrogram, convolutional neural network

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Authors: Tuğçe Yücel

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A Wireless Sensor Network(WSN) is a collection of sensor nodes which are deployed randomly in an area for surveillance. Efficient utilization of limited battery energy of sensors for increased network lifetime as well as data security are major design objectives for WSN. Moreover secure transmission of data sensed to a base station for further processing. Producing multiple copies of data packets and sending them on different paths is one of the strategies for this purpose, which leads to redundant energy consumption and hence reduced network lifetime. In this work we develop a restricted multi-copy multipath strategy where data move through ‘frequently’ or ‘heavily’ used sensors is copied by the sensor incident to such central nodes and sent on node-disjoint paths. We develop a mixed integer programing(MIP) model and heuristic approach present some preleminary test results.

Keywords: MIP, sensor, telecommunications, WSN

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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, anomaly detection module

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Authors: P. Prasanna Murali Krishna, M. V. Subramanyam, K. Satya Prasad

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File sharing in networks are generally achieved using Peer-to-Peer (P2P) applications. Structured P2P approaches are widely used in adhoc networks due to its distributed and scalability features. Efficient mechanisms are required to handle the huge amount of data distributed to all peers. The intrinsic characteristics of P2P system makes for easier content distribution when compared to client-server architecture. All the nodes in a P2P network act as both client and server, thus, distributing data takes lesser time when compared to the client-server method. CHORD protocol is a resource routing based where nodes and data items are structured into a 1- dimensional ring. The structured lookup algorithm of Chord is advantageous for distributed P2P networking applications. Though, structured approach improves lookup performance in a high bandwidth wired network it could contribute to unnecessary overhead in overlay networks leading to degradation of network performance. In this paper, the performance of existing CHORD protocol on Wireless Mesh Network (WMN) when nodes are static and dynamic is investigated.

Keywords: wireless mesh network (WMN), structured P2P networks, peer to peer resource sharing, CHORD Protocol, DHT

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Authors: Ashwaq Alsulami, Jianhua Shao

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Various organisations often need to understand discussions on social media, such as what trending topics are and characteristics of the people engaged in the discussion. A number of approaches have been proposed to extract attributes that would characterise a discussion group. However, these approaches are largely based on supervised learning, and as such they require a large amount of labelled data. We propose an approach in this paper that does not require labelled data, but rely on lexical sources to detect meaningful attributes for online discussion groups. Our findings show an acceptable level of accuracy in detecting attributes for Twitter discussion groups.

Keywords: attributed community, attribute detection, community, social network

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Authors: J. K. Adedeji, S. T. Ijatuyi

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The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p₁), fractured layer (p₂), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable g_r (gravitational resistance) can be deduced from the elevation and apparent resistivity p_a. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.

Keywords: gravitational resistance, neural network, non-linear, pattern recognition

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Authors: Sheng Fu, Yinbo Gao, Hao Lin

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In the current mine air compressors monitoring system, there are some difficulties in the installation and maintenance because of the wired connection. To solve the problem, this paper introduces a new air compressors monitoring system based on ZigBee in which the monitoring parameters are transmitted wirelessly. The collecting devices are designed to form a cluster network to collect vibration, temperature, and pressure of air cylinders and other parameters. All these devices are battery-powered. Besides, the monitoring software in PC is developed using MFC. Experiments show that the designed wireless sensor network works well in the site environmental condition and the system is very convenient to be installed since the wireless connection. This monitoring system will have a wide application prospect in the upgrade of the old monitoring system of the air compressors.

Keywords: condition monitoring, wireless sensor network, air compressor, zigbee, data collecting

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Authors: Ali Mohammad Mobaser Azad, Alireza Akhlaghinia

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Blockchain is changing our world and launching a new generation of decentralized networks. Meanwhile, Blockchain-based networks like Ethereum have been created and they will facilitate these processes using tools like smart contracts. The Ethereum has fundamental structures, each of which affects the activity of the nodes. Our purpose in this paper is to review similar research and examine various components to demonstrate the performance of the Ethereum network and to do this, and we used the data published by the Ethereum Foundation in different time spots to examine the number of changes that determine the status of network performance. This will help other researchers understand better Ethereum in different situations.

Keywords: blockchain, ethereum, smart contract, decentralization consensus algorithm

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Authors: Wanying Xie

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Under the background of the increasing Sino-US trade friction, the two nations pay more attention to the medias’ words. This paper mainly studies the causality, effectiveness, and influence of discourse construction between traditional media and social media. Based on the Network Agenda Setting theory, a kind of associative memory pattern in Psychology, who focuses on how media affect audiences’ cognition of issues and attributes, as well as the significance of the relation between people and matters. The date of the sample chosen in this paper ranges from March 23, 2018, to April 30, 2019. A total of 395 Tweets of Donald Trump are obtained, and 731 related reports are collected from the mainstream American newspapers including New York Times, the Washington Post and the Washington Street, by using Factiva and other databases. The sample data are processed by MAXQDA while the media discourses are analyzed by SPSS and Cite Space, with an aim to study: 1) whether the inter-media discourse construction exists; 2) which media (traditional media V.S. social media) is dominant; 3) the causality between two media. The results show: 1) the discourse construction between three American mainstream newspapers and Donald Trump's Twitter is proved in some periods; 2) the dominant position is extremely depended on the events; 3) the causality between two media is decided by many reasons. New media technology shortens the time of agenda-setting effect to one day or less. By comparing the specific relation between the three major American newspapers and Donald Trump’s Twitter, whose popularity and influence could be reflected. Hopefully, this paper could enable readers to have a more comprehensive understanding of the international media language and political environment.

Keywords: discourse construction, media language, network agenda-setting theory, sino-us trade friction

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Authors: Rania Alshikhe, Vinita Jindal

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Digital innovation has played a crucial role in managing smart transportation. For this, big trajectory data collected from traveling vehicles, such as taxis through installed global positioning system (GPS)-enabled devices can be utilized. It offers an unprecedented opportunity to trace the movements of vehicles in fine spatiotemporal granularity. This paper aims to explore big trajectory data to measure the travel efficiency of road networks using the proposed statistical travel efficiency measure (STEM) across an entire city. Further, it identifies the cause of low travel efficiency by proposed least square approximation network-based causality exploration (LANCE). Finally, the resulting data analysis reveals the causes of low travel efficiency, along with the road segments that need to be optimized to improve the traffic conditions and thus minimize the average travel time from given point A to point B in the road network. Obtained results show that our proposed approach outperforms the baseline algorithms for measuring the travel efficiency of the road network.

Keywords: GPS trajectory, road network, taxi trips, digital map, big data, STEM, LANCE

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Authors: Sanchai Ratthanakwan

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This research aims to study situations and characteristics of the problems facing the urban poor. The data and information are collected by focus group and in-depth interview leader and members of Four Regions Slum Network, community representatives and the social welfare officer. The research can be concluded that the problems of the urban poor faced with three major problems: Firstly, the shortage of housing and stability issues in housing; secondly, the problem of substandard quality of life; and thirdly, the debt problem. The study found that a solution will be found in two ways: First way is the creation of housing for the urban poor in slums or community intrusion by the state. Second way is the stability in the housing and subsistence provided by the community center called “housing stability”.

Keywords: urban poor, social welfare, Bangkok metropolis, housing stability

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Authors: Angeliki Peponi, Paulo Morgado, Jorge Trindade

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Artificial Neural Networks (ANNs) and Geographic Information Systems (GIS) are applied as a robust tool for modeling and forecasting the erosion changes in Costa Caparica, Lisbon, Portugal, for 2021. ANNs present noteworthy advantages compared with other methods used for prediction and decision making in urban coastal areas. Multilayer perceptron type of ANNs was used. Sensitivity analysis was conducted on natural and social forces and dynamic relations in the dune-beach system of the study area. Variations in network’s parameters were performed in order to select the optimum topology of the network. The developed methodology appears fitted to reality; however further steps would make it better suited.

Keywords: artificial neural networks, backpropagation, coastal urban zones, erosion prediction

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Authors: Mohadese Motahari

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In general, we consider the phenomenon of "fandism" or extreme fandom to be an aspect of fandom for a person, a group, or a collection, which leads to extreme support for them. So, for example, we consider a fan or a "fanatic" (which literally means a "fanatical person") to be a person who is extremely interested in a certain topic or topics and has a special passion and fascination for that issue. It may also be beyond the scope of logic and normal behavior of the society. With the expansion of the media and the advancement of technology, the phenomenon of fandom also underwent many changes and not only became more intense, but a large economy was also formed alongside it, and it is becoming more and more important every day. This economy, which emerged from the past with the formation of the first media, has now taken a different form with the development of media and social networks, as well as the change in the interaction between celebrities and audiences. Earning huge amounts of money with special methods in every social network and every media is achieved through fans and fandoms. In this article, we have studied the relationship between fans and famous people with reference to the economic debates surrounding it.

Keywords: fandism, famous people, social media, new media

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Authors: Adel Bougamouza, Boualam Remini, Abd El Hadi Ammari, Feteh Sakhraoui

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The assessment of sediments being carried by a river is importance for planning and designing of various water resources projects. In this study, Artificial Neural Network Techniques are used to estimate the daily suspended sediment concentration for the corresponding daily discharge flow in the upstream of Foum El Gherza dam, Biskra, Algeria. The FFNN, GRNN, and RBNN models are established for estimating current suspended sediment values. Some statistics involving RMSE and R2 were used to evaluate the performance of applied models. The comparison of three AI models showed that the RBNN model performed better than the FFNN and GRNN models with R2 = 0.967 and RMSE= 5.313 mg/l. Therefore, the ANN model had capability to improve nonlinear relationships between discharge flow and suspended sediment with reasonable precision.

Keywords: artificial neural network, Oued Abiod watershed, feedforward network, generalized regression network, radial basis network, sediment concentration

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Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez, Mehdi Mrad

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We investigate the large scale of networks in the context of network survivability under attack. We use appropriate techniques to evaluate and the attacker-based- and the defender-based-network survivability. The attacker is unaware of the operated links by the defender. Each attacked link has some pre-specified probability to be disconnected. The defender choice is so that to maximize the chance of successfully sending the flow to the destination node. The attacker however will select the cut-set with the highest chance to be disabled in order to partition the network. Moreover, we extend the problem to the case of selecting the best p paths to operate by the defender and the best k cut-sets to target by the attacker, for arbitrary integers p,k > 1. We investigate some variations of the problem and suggest polynomial-time solutions.

Keywords: defense/attack strategies, large scale, networks, partitioning a network

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Authors: Vishal H. Shukla, Sanjay B. Deshmukh

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Traffic engineering, at its center, is the ability of moving traffic approximately so that traffic from a congested link is moved onto the unused capacity on another link. Traffic Engineering ensures the best possible use of the resources. Now to support traffic engineering in the today’s network, Multiprotocol Label Switching (MPLS) is being used which is very helpful for reliable packets delivery in an ongoing internet services. Here a topology is been implemented on GNS3 to focus on the analysis of the communication take place from one site to other through the ISP. The comparison is made between the IP network & MPLS network based on Bandwidth & Jitter which are one of the performance parameters using JPERF simulator.

Keywords: GNS3, JPERF, MPLS, traffic engineering, VMware

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Authors: Afaneen Anwer, Samara M. Kamil

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Load Forecast required prediction accuracy based on optimal operation and maintenance. A good accuracy is the basis of economic dispatch, unit commitment, and system reliability. A good load forecasting system fulfilled fast speed, automatic bad data detection, and ability to access the system automatically to get the needed data. In this paper, the formulation of the load forecasting is discussed and the solution is obtained by using artificial neural network method. A MATLAB environment has been used to solve the load forecasting schedule of Iraqi super grid network considering the daily load for three years. The obtained results showed a good accuracy in predicting the forecasted load.

Keywords: load forecasting, neural network, back-propagation algorithm, Iraqi power system

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Authors: J. A. Ageeva, Z. S. Zavyalova

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The article considers social media as a tool for business promotion. We analyze and compare the SMM experience in the western countries and Russia. A short review of Russian social networks are given including their peculiar features, and the main problems and perspectives of Russian SMM are described.

Keywords: social media, social networks, marketing, SMM

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Authors: Boukari Nassim

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This paper describes the use of odd pair autoregressive coefficients (Yule _Walker and Burg) for the feature extraction of electroencephalogram (EEG) signals. In the classification: the radial basis function neural network neural network (RBFNN) is employed. The RBFNN is described by his architecture and his characteristics: as the RBF is defined by the spread which is modified for improving the results of the classification. Five types of EEG signals are defined for this work: Set A, Set B for normal signals, Set C, Set D for interictal signals, set E for ictal signal (we can found that in Bonn university). In outputs, two classes are given (AC, AD, AE, BC, BD, BE, CE, DE), the best accuracy is calculated at 99% for the combined odd pair autoregressive coefficients. Our method is very effective for the diagnosis of epileptic EEG signals.

Keywords: epilepsy, EEG signals classification, combined odd pair autoregressive coefficients, radial basis function neural network

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Authors: Priya Sepaha

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Social media has loomed as the most effective tool in recent times to flag the causes, contents, opinions and direction of any social movement and has demonstrated that it will have a far-reaching effect on government as well. This study focuses on India which has emerged as the fastest growing community on social media. Social movement activists, in particular, have extensively utilized the power of digital social media to streamline the effectiveness of social protest on a particular issue through extensive successful mass mobilizations. This research analyses the role and impact of social media as a power to catalyze the social movements in India and further seeks to describe how certain social movements are resisted, subverted, co-opted and/or deployed by social media. The impact assessment study has been made with the help of cases, policies and some social movement which India has witnessed the assertion of numerous social issues perturbing the public which eventually paved the way for remarkable judicial decisions. The paper concludes with the observations that despite its pros and cons, the impacts of social media on the functioning of the Indian Government have demonstrated that it has already become an indispensable tool in the hands of social media-suave Indians who are committed to bring about a desired change.

Keywords: social media, social movements, impact, law, government

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Authors: Senay Yitmen

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This research investigated individual’s support and helping intentions towards Syrian refugees in Turkey. This is examined in relation to perceived threat and negative emotions, and also to the perceptions of whether one’s intimate social network (family and friends) considers Syrians a threat (descriptive network norm) and whether this network morally supports Syrian refugees (injunctive norms). A questionnaire study was conducted among Turkish participants (n= 565) and the results showed that perception of threat was associated with negative emotions which, in turn, were related to less support of Syrian refugees. Additionally, descriptive norms moderated the relationship between perceived threat and negative emotions towards Syrian refugees. Furthermore, injunctive norms moderated the relationship between negative emotions and support to Syrian refugees. Specifically, the findings indicate that perceived threat is associated with less support of Syrian refugees through negative emotions when descriptive norms are weak and injunctive norms are strong. Injunctive norms appear to trigger a dilemma over the decision to conform or not to conform: when one has negative emotions as a result of perceived threat, it becomes more difficult to conform to the moral obligation of injunctive norms which is associated with less support of Syrian refugees. Hence, these findings demonstrate that both descriptive and injunctive norms are important and play different roles in individual’s support of Syrian refugees.

Keywords: descriptive norms, emotions, injunctive norms, the perception of threat

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