Search results for: Social network sites

Authors: Madina Kenzhegaranova, Aibol Mukhsiynov, Houman Sanandaji

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The article is about government programs and projects and their description which are aimed at improving the socioeconomic situation in the Republic of Kazakhstan. A brief historical overview, as well as information about current socio-economic, political and transitional contexts of the country are provided. Two theories were described in the article to inform this descriptive study. According to the United Nation's Development Reports for 2005 and 2011, the country's human development index (HDI) rose by several points despite the socio-economic and political imbalances taking place in the republic since it gained its independence in 1991. It is stated in the article that government support programs are one of the crucial factors that increase the population welfare which in its turn may lead to reduction of social crisis processes in the country.

Keywords: human capital, social crisis, state programs, unemployment

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Authors: Sameh Al-Natour, Izak Benbasat

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The introduction of a multitude of new and interactive e-commerce information technology (IT) artifacts has impacted adoption research. Rather than solely functioning as productivity tools, new IT artifacts assume the roles of interaction mediators and social actors. This paper describes the varying roles assumed by IT artifacts, and proposes and distinguishes between four distinct foci of how the artifacts are evaluated. It further proposes a theoretical model that maps the different views of IT artifacts to four distinct types of evaluations.

Keywords: IT adoption, IT artifacts, similarity, social actor.

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Authors: Prashant Kumar Tiwari, Yog Raj Sood

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This paper proposes an investment cost recovery based efficient and fast sequential optimization approach to optimal allocation of thyristor controlled series compensator (TCSC) in competitive power market. The optimization technique has been used with an objective to maximizing the social welfare and minimizing the device installation cost by suitable location and rating of TCSC in the system. The effectiveness of proposed approach for location of TCSC has been compared with some existing methods of TCSC placement, in terms of its impact on social welfare, TCSC investment recovery and optimal generation as well as load patterns. The results have been obtained on modified IEEE 14-bus system.

Keywords: Double auction market, Investment cost recovery, Optimal location, Social welfare, TCSC

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Authors: Md. Ashikur Rahman Khan, M. M. Rahman, K. Kadirgama

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Artificial neural networks (ANN) are used in distinct researching fields and professions, and are prepared by cooperation of scientists in different fields such as computer engineering, electronic, structure, biology and so many different branches of science. Many models are built correlating the parameters and the outputs in electrical discharge machining (EDM) concern for different types of materials. Up till now model for Ti-5Al-2.5Sn alloy in the case of electrical discharge machining performance characteristics has not been developed. Therefore, in the present work, it is attempted to generate a model of material removal rate (MRR) for Ti-5Al-2.5Sn material by means of Artificial Neural Network. The experimentation is performed according to the design of experiment (DOE) of response surface methodology (RSM). To generate the DOE four parameters such as peak current, pulse on time, pulse off time and servo voltage and one output as MRR are considered. Ti-5Al-2.5Sn alloy is machined with positive polarity of copper electrode. Finally the developed model is tested with confirmation test. The confirmation test yields an error as within the agreeable limit. To investigate the effect of the parameters on performance sensitivity analysis is also carried out which reveals that the peak current having more effect on EDM performance.

Keywords: Ti-5Al-2.5Sn, material removal rate, copper tungsten, positive polarity, artificial neural network, multi-layer perceptron.

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Authors: Oktia Woro Kasmini Handayani, Bambang Budi Raharjo, Efa Nugroho, Bertakalswa Hermawati

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Obesity prevalence and severe malnutrition in Indonesia has increased from 2007 to 2013. The utilization of local resources in nutritional program planning can be used to program efficiency and to reach the goal. The aim of this research is to plan a nutrition program based on local resources for urban fringe areas in a developing country. This research used a qualitative approach, with a focus on local resources including social capital, social system, cultural system. The study was conducted in Mijen, Central Java, as one of the urban fringe areas in Indonesia. Purposive and snowball sampling techniques are used to determine participants. A total of 16 participants took part in the study. Observation, interviews, focus group discussion, SWOT analysis, brainstorming and Miles and Huberman models were used to analyze the data. We have identified several local resources, such as the contributions from nutrition cadres, social organizations, social financial resources, as well as the cultural system and social system. The outstanding contribution of nutrition cadres is the participation and creativity to improve nutritional status. In addition, social organizations, like the role of the integrated health center for children (Pos Pelayanan Terpadu), can be engaged in the nutrition program planning. This center is supported by House of Nutrition to assist in nutrition program planning, and provide social support to families, neighbors and communities as social capitals. The study also reported that cultural systems that show appreciation for well-nourished children are a better way to improve the problem of balanced nutrition. Social systems such as teamwork and mutual cooperation can also be a potential resource to support nutritional programs and overcome associated problems. The impact of development in urban areas such as the introduction of more green areas which improve the perceived status of local people, as well as new health services facilitated by people and companies, can also be resources to support nutrition programs. Local resources in urban fringe areas can be used in the planning of nutrition programs. The expansion of partnership with all stakeholders, empowering the community through optimizing the roles of nutrition care centers for children as our recommendation with regard to nutrition program planning.

Keywords: Developing country, local resources, nutrition program, urban fringe.

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Authors: Rong-Terng Juang

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Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: Autonomous vehicle, data recording, remote monitoring, controller area network.

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Authors: Bhim Kumar Dahal

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Transportation network development in the developing country is in rapid pace. The majority of the network belongs to railway and expressway which passes through diverse topography, landform and geological conditions despite the avoidance principle during route selection. Construction of such networks demand many low to high embankment which required improvement in the foundation soil. This paper is mainly focused on the various advanced ground improvement techniques used to improve the soft soil, modelling approach and its predictability for embankments construction. The ground improvement techniques can be broadly classified in to three groups i.e. densification group, drainage and consolidation group and reinforcement group which are discussed with some case studies.  Various methods were used in modelling of the embankments from simple 1-dimensional to complex 3-dimensional model using variety of constitutive models. However, the reliability of the predictions is not found systematically improved with the level of sophistication.  And sometimes the predictions are deviated more than 60% to the monitored value besides using same level of erudition. This deviation is found mainly due to the selection of constitutive model, assumptions made during different stages, deviation in the selection of model parameters and simplification during physical modelling of the ground condition. This deviation can be reduced by using optimization process, optimization tools and sensitivity analysis of the model parameters which will guide to select the appropriate model parameters.

Keywords: Embankment, ground improvement, modelling, model prediction.

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Authors: Ki Hyun Kim, Jang-Hee Yoo, Kyo Il Chung

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This paper proposes a VPN Accelerator Board (VPN-AB), a virtual private network (VPN) protocol designed for trust channel security system (TCSS). TCSS supports safety communication channel between security nodes in internet. It furnishes authentication, confidentiality, integrity, and access control to security node to transmit data packets with IPsec protocol. TCSS consists of internet key exchange block, security association block, and IPsec engine block. The internet key exchange block negotiates crypto algorithm and key used in IPsec engine block. Security Association blocks setting-up and manages security association information. IPsec engine block treats IPsec packets and consists of networking functions for communication. The IPsec engine block should be embodied by H/W and in-line mode transaction for high speed IPsec processing. Our VPN-AB is implemented with high speed security processor that supports many cryptographic algorithms and in-line mode. We evaluate a small TCSS communication environment, and measure a performance of VPN-AB in the environment. The experiment results show that VPN-AB gets a performance throughput of maximum 15.645Gbps when we set the IPsec protocol with 3DES-HMAC-MD5 tunnel mode.

Keywords: TCSS(Trust Channel Security System), VPN(VirtualPrivate Network), IPsec, SSL, Security Processor, Securitycommunication.

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Authors: Abdelbasit Gadour

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This study explores the function of schools’ psychosocial services within Libyan mainstream schools in relation to children’s special educational needs (SEN). This is with the aim to examine the role of school social workers and psychologists in the assessment procedure of children with SEN. A semi-structured interview was used in this study, with 21 professionals working in the schools’ psychosocial services, of whom 13 were school social workers (SSWs) and eight were school psychologists (SPs). The results of the interviews with SSWs and SPs provided insights into how SEN children are identified, assessed, and dealt with by school professionals. It appears from the results that what constitutes a problem has not changed significantly, and the link between learning difficulties and behavioural difficulties is also evident from this study. Children with behaviour difficulties are more likely to be referred to school psychosocial services than children with learning difficulties. Yet, it is not clear from the interviews with SSWs and SPs whether children are excluded merely because of their behaviour problems. Instead, they would surely be expelled from the school if they failed academically. Furthermore, the interviews with SSWs and SPs yield a rather unusual source accountable for children’s SEN; school-related difficulties were a major factor in which almost all participants attributed children’s learning and behaviour problems to teachers’ deficiencies, followed by school lack of resources.

Keywords: Special education, school, social workers, psychologist.

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Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

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Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: Multiclass classification, convolution neural network, OpenCV, Data Augmentation.

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Authors: N. Z. Baderisham, H. A. Hamid, N. Osman

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The powders of Ba(Ce_1-xZr_x)_0.90Y_0.1O_3-δ (BCZY) with 0.2 ≤ x ≤ 0.6 have been prepared by a modified sol-gel method. Triethylenetetramine (TETA) was employed as chelating agent. Phase formation of calcined powders at 1100^oC and sintered pellets at 1400^oC of BCZY were examined by an X-ray diffractrometer (XRD). XRD results showed the calcined powder and sintered pellet formed a single perovskite phase over the entire range of x values. As the amount of zirconium substitution (x values) increase, the main peaks are shifted to the higher 2theta values which suggest a complete substitution of zirconium into cerium sites. All the obtained calcined powders and sintered pellets possess cubic structure (Pm-3m) at all x values.

Keywords: Structure, phase formation, modified sol-gel, cerate-zirconate electrolye, XRD.

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Authors: Mohammad Namazi, Mohammad Sadeghzadeh Maharluie

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Predicting earnings management is vital for the capital market participants, financial analysts and managers. The aim of this research is attempting to respond to this query: Is there a significant difference between the regression model and neural networks’ models in predicting earnings management, and which one leads to a superior prediction of it? In approaching this question, a Linear Regression (LR) model was compared with two neural networks including Multi-Layer Perceptron (MLP), and Generalized Regression Neural Network (GRNN). The population of this study includes 94 listed companies in Tehran Stock Exchange (TSE) market from 2003 to 2011. After the results of all models were acquired, ANOVA was exerted to test the hypotheses. In general, the summary of statistical results showed that the precision of GRNN did not exhibit a significant difference in comparison with MLP. In addition, the mean square error of the MLP and GRNN showed a significant difference with the multi variable LR model. These findings support the notion of nonlinear behavior of the earnings management. Therefore, it is more appropriate for capital market participants to analyze earnings management based upon neural networks techniques, and not to adopt linear regression models.

Keywords: Earnings management, generalized regression neural networks, linear regression, multi-layer perceptron, Tehran stock exchange.

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Authors: Koko Iwan Agus Kurniawan, Dwi Purnomo, Anas Bunyamin, Arif Rahman Jaya

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Fruters model is a concept of technopreneurship-based on empowerment, in which technology research results were designed to create high value-added products and implemented as a locomotive of collaborative empowerment; thereby, the impact was widely spread. This model still needs to be inventoried and validated concerning the influenced variables in the business growth process. Model validation accompanied by mapping was required to be applicable to Small Medium Enterprises (SMEs) agro-industry based on sustainable social business and existing real cases. This research explained the empowerment model of Yourgood, an SME, which emphasized on empowering the farmers/ breeders in farmers in rural areas, Cipageran, Cimahi, to housewives in urban areas, Bandung, West Java, Indonesia. This research reviewed some works of literature discussing the agro-industrial development associated with the empowerment and social business process and gained a unique business model picture with the social business platform as well. Through the mapped business model, there were several advantages such as technology acquisition, independence, capital generation, good investment growth, strengthening of collaboration, and improvement of social impacts that can be replicated on other businesses. This research used analytical-descriptive research method consisting of qualitative analysis with design thinking approach and that of quantitative with the AHP (Analytical Hierarchy Process). Based on the results, the development of the enterprise’s process was highly affected by supplying farmers with the score of 0.248 out of 1, being the most valuable for the existence of the enterprise. It was followed by university (0.178), supplying farmers (0.153), business actors (0.128), government (0.100), distributor (0.092), techno-preneurship laboratory (0.069), banking (0.033), and Non-Government Organization (NGO) (0.031).

Keywords: Agro-Industry, small medium enterprises (SMEs), empowerment, design thinking, AHP, business model canvas, social business.

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Authors: Nasim Fallahi, Erasmo Carrera, Alfonso Pagani

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Variable angle tow describes the fibres which are curvilinearly steered in a composite lamina. Significantly, stiffness tailoring freedom of VAT composite laminate can be enlarged and enabled. Composite structures with curvilinear fibres have been shown to improve the buckling load carrying capability in contrast with the straight laminate composites. However, the optimal design and analysis of VAT are faced with high computational efforts due to the increasing number of variables. In this article, an efficient optimum solution has been used in combination with 1D Carrera’s Unified Formulation (CUF) to investigate the optimum fibre orientation angles for buckling analysis. The particular emphasis is on the LE-based CUF models, which provide a Lagrange Expansions to address a layerwise description of the problem unknowns. The first critical buckling load has been considered under simply supported boundary conditions. Special attention is lead to the sensitivity of buckling load corresponding to the fibre orientation angle in comparison with the results which obtain through the Genetic Algorithm (GA) optimization frame and then Artificial Neural Network (ANN) is applied to investigate the accuracy of the optimized model. As a result, numerical CUF approach with an optimal solution demonstrates the robustness and computational efficiency of proposed optimum methodology.

Keywords: Beam structures, layerwise, optimization, variable angle tow, neural network

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Authors: S.I Sulaiman, T.K Abdul Rahman, I. Musirin, S. Shaari

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This paper presents performance analysis of the Evolutionary Programming-Artificial Neural Network (EPANN) based technique to optimize the architecture and training parameters of a one-hidden layer feedforward ANN model for the prediction of energy output from a grid connected photovoltaic system. The ANN utilizes solar radiation and ambient temperature as its inputs while the output is the total watt-hour energy produced from the grid-connected PV system. EP is used to optimize the regression performance of the ANN model by determining the optimum values for the number of nodes in the hidden layer as well as the optimal momentum rate and learning rate for the training. The EPANN model is tested using two types of transfer function for the hidden layer, namely the tangent sigmoid and logarithmic sigmoid. The best transfer function, neural topology and learning parameters were selected based on the highest regression performance obtained during the ANN training and testing process. It is observed that the best transfer function configuration for the prediction model is [logarithmic sigmoid, purely linear].

Keywords: Artificial neural network (ANN), Correlation coefficient (R), Evolutionary programming-ANN (EPANN), Photovoltaic (PV), logarithmic sigmoid and tangent sigmoid.

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Authors: G. Schuh, S. Aghassi

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In order to bridge the gap between research and industry, promoting technology and knowledge transfer becomes increasingly important. Especially small- and medium-sized enterprises, having only little R&D resources themselves, depend on external technology development activities for remaining innovative. Academia research on the other hand needs potential industrial partners, who are capable and willing to commercialize their technologies as most public funding programs require some sort of technology transfer or dissemination activities. Modern web technologies offer more and more “social” functionalities and open up new ways of user interaction. In the past years several technology transfer platforms were developed, making use of modern web technologies in order to enable and support technology transfer. In this paper we report on the results of a state-of-the art analyses of existing technology transfer platforms, point out their advantages and deficits and give a perspective to the development of an improved technology transfer platform.

Keywords: Knowledge transfer, social software, technology management, technology transfer.

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Authors: Justinian Anatory, Nelson Theethayi

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The paper compares different channel models used for modeling Broadband Power-Line Communication (BPLC) system. The models compared are Zimmermann and Dostert, Philipps, Anatory et al and Anatory et al generalized Transmission Line (TL) model. The validity of each model was compared in time domain with ATP-EMTP software which uses transmission line approach. It is found that for a power-line network with minimum number of branches all the models give similar signal/pulse time responses compared with ATP-EMTP software; however, Zimmermann and Dostert model indicates the same amplitude but different time delay. It is observed that when the numbers of branches are increased only generalized TL theory approach results are comparable with ATPEMTP results. Also the Multi-Carrier Spread Spectrum (MC-SS) system was applied to check the implication of such behavior on the modulation schemes. It is observed that using Philipps on the underground cable can predict the performance up to 25dB better than other channel models which can misread the actual performance of the system. Also modified Zimmermann and Dostert under multipath can predict a better performance of about 5dB better than the actual predicted by Generalized TL theory. It is therefore suggested for a realistic BPLC system design and analyses the model based on generalized TL theory be used.

Keywords: Broadband Power line Channel Models, loadimpedance, Branched network.

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Authors: Reza Dinarvand, Mahdi Sadeghian, Somaye Sadeghian

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Prediction of the ultimate bearing capacity of piles (Qu) is one of the basic issues in geotechnical engineering. So far, several methods have been used to estimate Qu, including the recently developed artificial intelligence methods. In recent years, optimization algorithms have been used to minimize artificial network errors, such as colony algorithms, genetic algorithms, imperialist competitive algorithms, and so on. In the present research, artificial neural networks based on colonial competition algorithm (ANN-ICA) were used, and their results were compared with other methods. The results of laboratory tests of short piles in clayey soils with parameters such as pile diameter, pile buried length, eccentricity of load and undrained shear resistance of soil were used for modeling and evaluation. The results showed that ICA-based artificial neural networks predicted lateral bearing capacity of short piles with a correlation coefficient of 0.9865 for training data and 0.975 for test data. Furthermore, the results of the model indicated the superiority of ICA-based artificial neural networks compared to back-propagation artificial neural networks as well as the Broms and Hansen methods.

Keywords: Lateral bearing capacity, short pile, clayey soil, artificial neural network, Imperialist competition algorithm.

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Authors: A. Doaa M. Atia, Faten H. Fahmy, Ninet M. Ahmed, Hassen T. Dorrah

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Temperature is one of the most principle factors affects aquaculture system. It can cause stress and mortality or superior environment for growth and reproduction. This paper presents the control of pond water temperature using artificial intelligence technique. The water temperature is very important parameter for shrimp growth. The required temperature for optimal growth is 34oC, if temperature increase up to 38oC it cause death of the shrimp, so it is important to control water temperature. Solar thermal water heating system is designed to supply an aquaculture pond with the required hot water in Mersa Matruh in Egypt. Neural networks are massively parallel processors that have the ability to learn patterns through a training experience. Because of this feature, they are often well suited for modeling complex and non-linear processes such as those commonly found in the heating system. Artificial neural network is proposed to control water temperature due to Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques. They have been used to solve complicated practical problems. Moreover this paper introduces a complete mathematical modeling and MATLAB SIMULINK model for the aquaculture system. The simulation results indicate that, the control unit success in keeping water temperature constant at the desired temperature by controlling the hot water flow rate.

Keywords: artificial neural networks, aquaculture, forced circulation hot water system,

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Authors: A. R. Malekpour, A.R. Seifi

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This paper discusses a genetic algorithm (GA) based optimal load shedding that can apply for electrical distribution networks with and without dispersed generators (DG). Also, the proposed method has the ability for considering constant and variable capacity deficiency caused by unscheduled outages in the bulked generation and transmission system of bulked power supply. The genetic algorithm (GA) is employed to search for the optimal load shedding strategy in distribution networks considering DGs in two cases of constant and variable modelling of bulked power supply of distribution networks. Electrical power distribution systems have a radial network and unidirectional power flows. With the advent of dispersed generations, the electrical distribution system has a locally looped network and bidirectional power flows. Therefore, installed DG in the electrical distribution systems can cause operational problems and impact on existing operational schemes. Introduction of DGs in electrical distribution systems has introduced many new issues in operational and planning level. Load shedding as one of operational issue has no exempt. The objective is to minimize the sum of curtailed load and also system losses within the frame-work of system operational and security constraints. The proposed method is tested on a radial distribution system with 33 load points for more practical applications.

Keywords: DG, Load shedding, Optimization, Capacity Deficiency Modelling.

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Authors: Mohanad Alhabo, Li Zhang, Naveed Nawaz

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Small cell deployment in 5G networks is a promising technology to enhance the capacity and coverage. However, unplanned deployment may cause high interference levels and high number of unnecessary handovers, which in turn result in an increase in the signalling overhead. To guarantee service continuity, minimize unnecessary handovers and reduce signalling overhead in heterogeneous networks, it is essential to properly model the handover decision problem. In this paper, we model the handover decision problem using Multiple Attribute Decision Making (MADM) method, specifically Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), and propose a hybrid TOPSIS method to control the handover in heterogeneous network. The proposed method adopts a hybrid weighting policy, which is a combination of entropy and standard deviation. A hybrid weighting control parameter is introduced to balance the impact of the standard deviation and entropy weighting on the network selection process and the overall performance. Our proposed method show better performance, in terms of the number of frequent handovers and the mean user throughput, compared to the existing methods.

Keywords: Handover, HetNets, interference, MADM, small cells, TOPSIS, weight.

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Authors: E. Kam, Z. U. Yümün, D. Kurt

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In this study, sediment samples were collected from four sampling sites located on the shores of the Gulf of İzmir. In the samples, Cd, Co, Cr, Cu, Mn, Ni, Pb and Zn concentrations were determined using inductively coupled, plasma-optical emission spectrometry (ICP-OES). The average heavy metal concentrations were: Cd < LOD (limit of detection); Co 14.145 ± 0.13 μg g⁻¹; Cr 112.868 ± 0.89 μg g⁻¹; Cu 34.045 ± 0.53 μg g⁻¹; Mn 481.43 ± 7.65 μg g⁻¹; Ni 76.538 ± 3.81 μg g⁻¹; Pb 11.059 ± 0.53 μg g⁻¹ and Zn 140.133 ± 1.37 μg g⁻¹, respectively. The results were compared with the average abundances of these elements in the Earth’s crust. The measured heavy metal concentrations can serve as reference values for further studies carried out on the shores of the Aegean Sea.

Keywords: Heavy metal, Aegean Sea, ICP-OES, sediment.

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Authors: T.Sheela, Dr.J.Raja

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Continuously growing needs for Internet applications that transmit massive amount of data have led to the emergence of high speed network. Data transfer must take place without any congestion and hence feedback parameters must be transferred from the receiver end to the sender end so as to restrict the sending rate in order to avoid congestion. Even though TCP tries to avoid congestion by restricting the sending rate and window size, it never announces the sender about the capacity of the data to be sent and also it reduces the window size by half at the time of congestion therefore resulting in the decrease of throughput, low utilization of the bandwidth and maximum delay. In this paper, XCP protocol is used and feedback parameters are calculated based on arrival rate, service rate, traffic rate and queue size and hence the receiver informs the sender about the throughput, capacity of the data to be sent and window size adjustment, resulting in no drastic decrease in window size, better increase in sending rate because of which there is a continuous flow of data without congestion. Therefore as a result of this, there is a maximum increase in throughput, high utilization of the bandwidth and minimum delay. The result of the proposed work is presented as a graph based on throughput, delay and window size. Thus in this paper, XCP protocol is well illustrated and the various parameters are thoroughly analyzed and adequately presented.

Keywords: Bandwidth-Delay Product, Congestion Control, Congestion Window, TCP/IP

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Authors: Kanda Runapongsa Saikaew, Chaluemwut Noyunsan

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Nowadays social media information, such as news, links, images, or VDOs, is shared extensively. However, the effectiveness of disseminating information through social media lacks in quality: less fact checking, more biases, and several rumors. Many researchers have investigated about credibility on Twitter, but there is no the research report about credibility information on Facebook. This paper proposes features for measuring credibility on Facebook information. We developed the system for credibility on Facebook. First, we have developed FB credibility evaluator for measuring credibility of each post by manual human’s labelling. We then collected the training data for creating a model using Support Vector Machine (SVM). Secondly, we developed a chrome extension of FB credibility for Facebook users to evaluate the credibility of each post. Based on the usage analysis of our FB credibility chrome extension, about 81% of users’ responses agree with suggested credibility automatically computed by the proposed system.

Keywords: Facebook, social media, credibility measurement.

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Authors: Melvin Ballera, Mosbah Mohamed Elssaedi, Ahmed Khalil Zohdy

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Collaborative problem solving in e-learning can take in the form of discussion among learner, creating a highly social learning environment and characterized by participation and interactivity. This paper, designed a collaborative learning environment where agent act as co-learner, can play different roles during interaction. Since different roles have been assigned to the agent, learner will assume that multiple co-learner exists to help and guide him all throughout the collaborative problem solving process, but in fact, alone during the learning process. Specifically, it answers the questions what roles of the agent should be incorporated to contribute better learning outcomes, how agent will facilitate the communication process to provide social learning and interactivity and what are the specific instructional strategies that facilitate learner participation, increased skill acquisition and develop critical thinking.

Keywords: Collaborative e-learning, collaborative problem solving, , imaginary co-learner, social learning.

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Authors: Wichai Onlaor, Siriluck Rotchanakitumnuai

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The aim of this research is to develop the understanding of corporate social responsibility (CSR) from consumers- perspective toward Thai mobile service providers. Based on the survey from 400 mobile customers, the result shows that four dimensions of CSR of Thai mobile service providers consist of economic, legal, ethical and philanthropic responsibility. These four CSR factors have positive impacts on enhancing customer satisfaction except one item of economic responsibility - profitability to shareholders. Ethical dimension has the strongest impact on customer satisfaction. Economic, legal, ethical, philanthropic responsibility and customer satisfaction have major impact on loyalty, whilst philanthropic component mostly affects loyalty.

Keywords: Corporate Social Responsibility, PriceFairness, Service Quality, Privacy Concern, CustomerSatisfaction, Customer Loyalty

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Authors: S. Halioui, I. Arikan, M. Schmidt

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Tourism sector in Tunisia faces several problems that range from economic challenges to environmental degradation and social instability. These problems have been intensified because of the increased competition in the tourism market, the political instability, financial crises, and recently terrorism problems have aggravated the situation. As a consequence, a new framework that promotes sustainable tourism in the country and increases its competitiveness is urgently needed. Planning for sustainable tourism sector requires the integration of complex interactions between economic, social and environmental aspects. Sustainable tourism principles can be implemented with the help of Strategic Environmental Assessment (SEA) process, which ensures the full integration of economic, social and environmental considerations while planning for the tourism sector in Tunisia. Results of the paper have broad implications for policy makers and tourism professionals.

Keywords: Sustainable tourism, strategic environmental assessment, tourism planning, policy.

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Authors: Brahmjit Singh

Abstract:

Mobile IP has been developed to provide the continuous information network access to mobile users. In IP-based mobile networks, location management is an important component of mobility management. This management enables the system to track the location of mobile node between consecutive communications. It includes two important tasks- location update and call delivery. Location update is associated with signaling load. Frequent updates lead to degradation in the overall performance of the network and the underutilization of the resources. It is, therefore, required to devise the mechanism to minimize the update rate. Mobile IPv6 (MIPv6) and Hierarchical MIPv6 (HMIPv6) have been the potential candidates for deployments in mobile IP networks for mobility management. HMIPv6 through studies has been shown with better performance as compared to MIPv6. It reduces the signaling overhead traffic by making registration process local. In this paper, we present performance analysis of MIPv6 and HMIPv6 using an analytical model. Location update cost function is formulated based on fluid flow mobility model. The impact of cell residence time, cell residence probability and user-s mobility is investigated. Numerical results are obtained and presented in graphical form. It is shown that HMIPv6 outperforms MIPv6 for high mobility users only and for low mobility users; performance of both the schemes is almost equivalent to each other.

Keywords: Wireless networks, Mobile IP networks, Mobility management, performance analysis, Handover.

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Authors: Hamid Mamani, Negin Sharifi, Nangkula Utaberta

Abstract:

Social, culture and artistic status of a society in various historical eras is affected by numerous, and sometimes imposed, factors that better understanding requires analysis of such conditions. Throughout history Iran has been involved with determining and significant events that examining each of these events can improve the understanding of social conditions of this country in the intended time. Mongolian conquest of Iran is one of most significant events in the history of Iran with consequences that never left Iranian societies. During this tragic invasion and subsequent devastating wars, which led to establishment of Ilkhanate dynasty, numerous cultural and artistic changes occurred both in Mongolian conquerors and Iranian society. This study examines these changes with a glimpse towards art and architecture as important part of cultural aspects and social communication.

Keywords: Art and Architecture, Exchanging cultures, Ilkhanates, War

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Authors: P. Jomsri

Abstract:

Currently searching through internet is very popular especially in a field of academic. A huge of educational information such as research papers are overload for user. So community-base web sites have been developed to help user search information more easily from process of customizing a web site to need each specifies user or set of user. In this paper propose to use association rule analyze the community group on research paper bookmarking. A set of design goals for community group frameworks is developed and discussed. Additionally Researcher analyzes the initial relation by using association rule discovery between the antecedent and the consequent of a rule in the groups of user for generate the idea to improve ranking search result and development recommender system.

Keywords: association rule, information retrieval, research paper bookmarking.

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