Search results for: social network sites

Authors: Mohamed Mahmoud Hasan, Hoda M. O. Mokhtar

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With the gigantic increment in portable applications use and the spread of positioning and location-aware technologies that we are seeing today, new procedures and methodologies for location-based strategies are required. Location recommendation is one of the highly demanded location-aware applications uniquely with the wide accessibility of social network applications that are location-aware including Facebook check-ins, Foursquare, and others. In this paper, we aim to present a new methodology for location recommendation. The proposed approach coordinates customary spatial traits alongside other essential components including shortest distance, and user interests. We also present another idea namely, "activity trajectory" that represents trajectory that fulfills the set of activities that the user is intrigued to do. The approach dispatched acquaints the related distance value to select trajectory(ies) with minimum cost value (distance) and spatial-area to prune unneeded directions. The proposed calculation utilizes the idea of movement direction to prescribe most comparable N-trajectory(ies) that matches the client's required action design with least voyaging separation. To upgrade the execution of the proposed approach, parallel handling is applied through the employment of a MapReduce based approach. Experiments taking into account genuine information sets were built up and tested for assessing the proposed approach. The exhibited tests indicate how the proposed approach beets different strategies giving better precision and run time.

Keywords: Location-based recommendation, map-reduce, recommendation system, trajectory search.

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Authors: Maya Rupert, Salima Hassas, Carlos Li, John Sherwood

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Online Communities are an example of sociallyaware, self-organising, complex adaptive computing systems. The multi-agent systems (MAS) paradigm coordinated by self-organisation mechanisms has been used as an effective way for the simulation and modeling of such systems. In this paper, we propose a model for simulating an online health community using a situated multi-agent system approach, governed by the co-evolution of the social and spatial organisations of the agents.

Keywords: multi-agent systems, organizations, online communities.

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Authors: Hemant I. Joshi, Vivek J. Pandya

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This paper discusses the simulation and experimental work of small Smart Grid containing ten consumers. Smart Grid is characterized by a two-way flow of real-time information and energy. RTP (Real Time Pricing) based tariff is implemented in this work to reduce peak demand, PAR (peak to average ratio) and cost of energy consumed. In the experimental work described here, working of Smart Plug, HEC (Home Energy Controller), HAN (Home Area Network) and communication link between consumers and utility server are explained. Algorithms for Smart Plug, HEC, and utility server are presented and explained in this work. After receiving the Real Time Price for different time slots of the day, HEC interacts automatically by running an algorithm which is based on Linear Programming Problem (LPP) method to find the optimal energy consumption schedule. Algorithm made for utility server can handle more than one off-peak time period during the day. Simulation and experimental work are carried out for different cases. At the end of this work, comparison between simulation results and experimental results are presented to show the effectiveness of the minimization method adopted.

Keywords: Smart Grid, Real Time Pricing, Peak to Average Ratio, Home Area Network, Home Energy Controller, Smart Plug, Utility Server, Linear Programming Problem.

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Authors: Hsien-Chou Liao, Yu-Shiang Wang

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Surveillance system is widely used in the traffic monitoring. The deployment of cameras is moving toward a ubiquitous camera (UbiCam) environment. In our previous study, a novel service, called GPS-VT, was firstly proposed by incorporating global positioning system (GPS) and visual tracking techniques for the UbiCam environment. The first prototype is called GODTA (GPS-based Moving Object Detection and Tracking Approach). For a moving person carried GPS-enabled mobile device, he can be tracking when he enters the field-of-view (FOV) of a camera according to his real-time GPS coordinate. In this paper, GPS-VT service is applied to the tracking of vehicles. The moving speed of a vehicle is much faster than a person. It means that the time passing through the FOV is much shorter than that of a person. Besides, the update interval of GPS coordinate is once per second, it is asynchronous with the frame rate of the real-time image. The above asynchronous is worsen by the network transmission delay. These factors are the main challenging to fulfill GPS-VT service on a vehicle.In order to overcome the influence of the above factors, a back-propagation neural network (BPNN) is used to predict the possible lane before the vehicle enters the FOV of a camera. Then, a template matching technique is used for the visual tracking of a target vehicle. The experimental result shows that the target vehicle can be located and tracking successfully. The success location rate of the implemented prototype is higher than that of the previous GODTA.

Keywords: visual surveillance, visual tracking, globalpositioning system, intelligent transportation system

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Authors: Martin H¨ausl, Maximilian Auch, Johannes Forster, Peter Mandl, Alexander Schill

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In order to survive on the market, companies must constantly develop improved and new products. These products are designed to serve the needs of their customers in the best possible way. The creation of new products is also called innovation and is primarily driven by a company’s internal research and development department. However, a new approach has been taking place for some years now, involving external knowledge in the innovation process. This approach is called open innovation and identifies customer knowledge as the most important source in the innovation process. This paper presents a concept of using social media posts as an external source to support the open innovation approach in its initial phase, the Ideation phase. For this purpose, the social media posts are semantically structured with the help of an ontology and the authors are evaluated using graph-theoretical metrics such as density. For the structuring and evaluation of relevant social media posts, we also use the findings of Natural Language Processing, e. g. Named Entity Recognition, specific dictionaries, Triple Tagger and Part-of-Speech-Tagger. The selection and evaluation of the tools used are discussed in this paper. Using our ontology and metrics to structure social media posts enables users to semantically search these posts for new product ideas and thus gain an improved insight into the external sources such as customer needs.

Keywords: Idea ontology, innovation management, open innovation, semantic search.

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Authors: Natta Changchutoe

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This research aimed to study employees- perceptions and expectations toward their organization-s corporate social responsibility (CSR), to study the differences between employees- personal factors and level of perceptions and expectations toward CSR, and to study the relationship between employees- perceptions and expectations toward CSR. Purposive sampling and questionnaire were applied to collect information from 400 private company employees in Bangkok metropolitan area. The results revealed that employees had “high" level of perceptions and expectations toward CSR, of which the highest level were given on the area of “corporate governance and transparency". It was found that there was different level of expectations of employees with different period of employment, position and employment (by listed and non-listed companies). Employees of different age and period of employment also had different level of expectations. Employees- perceptions were correlated with their expectations toward CSR.

Keywords: Employees, Perceptions, Expectations, Corporate Social Responsibility (CSR).

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Authors: Mavroidis Athanasios, Karamitsos Ioannis, Saletti Paola

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In this paper is presented a Geographic Information System (GIS) approach in order to qualify and monitor the broadband lines in efficient way. The methodology used for interpolation is the Delaunay Triangular Irregular Network (TIN). This method is applied for a case study in ISP Greece monitoring 120,000 broadband lines.

Keywords: GIS loop qualification, GIS xDSL, LLU TIN.

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Authors: Dennis A. Apuan

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Categorical data based on description of the agricultural landscape imposed some mathematical and analytical limitations. This problem however can be overcome by data transformation through coding scheme and the use of non-parametric multivariate approach. The present study describes data transformation from qualitative to numerical descriptors. In a collection of 103 random soil samples over a 60 hectare field, categorical data were obtained from the following variables: levels of nitrogen, phosphorus, potassium, pH, hue, chroma, value and data on topography, vegetation type, and the presence of rocks. Categorical data were coded, and Spearman-s rho correlation was then calculated using PAST software ver. 1.78 in which Principal Component Analysis was based. Results revealed successful data transformation, generating 1030 quantitative descriptors. Visualization based on the new set of descriptors showed clear differences among sites, and amount of variation was successfully measured. Possible applications of data transformation are discussed.

Keywords: data transformation, numerical descriptors, principalcomponent analysis

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Authors: Mohammad Javad Kargar, Fatemeh Azimzadeh

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The vast amount of information on the World Wide Web is created and published by many different types of providers. Unlike books and journals, most of this information is not subject to editing or peer review by experts. This lack of quality control and the explosion of web sites make the task of finding quality information on the web especially critical. Meanwhile new facilities for producing web pages such as Blogs make this issue more significant because Blogs have simple content management tools enabling nonexperts to build easily updatable web diaries or online journals. On the other hand despite a decade of active research in information quality (IQ) there is no framework for measuring information quality on the Blogs yet. This paper presents a novel experimental framework for ranking quality of information on the Weblog. The results of data analysis revealed seven IQ dimensions for the Weblog. For each dimension, variables and related coefficients were calculated so that presented framework is able to assess IQ of Weblogs automatically.

Keywords: Information Quality, Weblog, Web Ranking, Web- Quality.

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Authors: Cheng-Lung Huang, Cheng-Wei Lin

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This study proposes a new recommender system based on the collaborative folksonomy. The purpose of the proposed system is to recommend Internet resources (such as books, articles, documents, pictures, audio and video) to users. The proposed method includes four steps: creating the user profile based on the tags, grouping the similar users into clusters using an agglomerative hierarchical clustering, finding similar resources based on the user-s past collections by using content-based filtering, and recommending similar items to the target user. This study examines the system-s performance for the dataset collected from “del.icio.us," which is a famous social bookmarking website. Experimental results show that the proposed tag-based collaborative and content-based filtering hybridized recommender system is promising and effectiveness in the folksonomy-based bookmarking website.

Keywords: Collaborative recommendation, Folksonomy, Social tagging

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Authors: Zeeshan Hamid, Sarwar Mehmood Azhar, Hammad Basir

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In today’s era, it is no news that organizations should demonstrate honest conduct as well as ethical administration. Therefore, the concept of corporate social responsibility (subsequently CSR) has created its tag upon the company’s focal point as well as marketing communications, and will continue in the future. The importance of CSR has increased in the last decade, and this concept has attracted global attention. The notion of CSR has strategic significance for many organizations. However, businesses are not adapting the activities of CSR that benefit to all of its stakeholders (including society). The main reason is the practitioners are unfortunately unable to comprehend its importance; and therefore, the activities of the CSR are so detached from the business activities. Hence, it is required to develop an understanding that the activities of CSR are not only beneficial for the society but it also benefit to business. This paper focuses on the concept of strategic CSR, and develops a theoretical framework that will help practitioners to filter and chose the activities of CSR that are strategic in nature.

Keywords: Economic responsibility, ethical responsibility, legal responsibility, philanthropic responsibility, strategic corporate social responsibility, value chain activities filter.

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Authors: Mohamad K. Hasan, Hameed Al-Qaheri

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Optimization plays an important role in most real world applications that support decision makers to take the right decision regarding the strategic directions and operations of the system they manage. Solutions for traffic management and traffic congestion problems are considered major problems that most decision making authorities for cities around the world are looking for. This review paper gives a full description of the traffic problem as part of the transportation planning process and present a view as a framework of urban transportation system analysis where the core of the system is a transportation network equilibrium model that is based on optimization techniques and that can also be used for evaluating an alternative solution or a combination of alternative solutions for the traffic congestion. Different transportation network equilibrium models are reviewed from the sequential approach to the multiclass combining trip generation, trip distribution, modal split, trip assignment and departure time model. A GIS-Based intelligent decision support system framework for urban transportation system analysis is suggested for implementation where the selection of optimized alternative solutions, single or packages, will be based on an intelligent agent rather than human being which would lead to reduction in time, cost and the elimination of the difficulty, by human being, for finding the best solution to the traffic congestion problem.

Keywords: Multiclass simultaneous transportation equilibrium models, transportation planning, urban transportation systems analysis, intelligent decision support system.

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Authors: Zhipeng Chen, Peng Zhang, Qingyun Liu, Li Guo

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With the Internet becoming the dominant channel for business and life, many IPs are increasingly masked using web proxies for illegal purposes such as propagating malware, impersonate phishing pages to steal sensitive data or redirect victims to other malicious targets. Moreover, as Internet traffic continues to grow in size and complexity, it has become an increasingly challenging task to detect the proxy service due to their dynamic update and high anonymity. In this paper, we present an approach based on behavioral graph analysis to study the behavior similarity of web proxy users. Specifically, we use bipartite graphs to model host communications from network traffic and build one-mode projections of bipartite graphs for discovering social-behavior similarity of web proxy users. Based on the similarity matrices of end-users from the derived one-mode projection graphs, we apply a simple yet effective spectral clustering algorithm to discover the inherent web proxy users behavior clusters. The web proxy URL may vary from time to time. Still, the inherent interest would not. So, based on the intuition, by dint of our private tools implemented by WebDriver, we examine whether the top URLs visited by the web proxy users are web proxies. Our experiment results based on real datasets show that the behavior clusters not only reduce the number of URLs analysis but also provide an effective way to detect the web proxies, especially for the unknown web proxies.

Keywords: Bipartite graph, clustering, one-mode projection, web proxy detection.

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Authors: Insung Jung, Gi-Nam Wang

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In this paper, we present user pattern learning algorithm based MDSS (Medical Decision support system) under ubiquitous. Most of researches are focus on hardware system, hospital management and whole concept of ubiquitous environment even though it is hard to implement. Our objective of this paper is to design a MDSS framework. It helps to patient for medical treatment and prevention of the high risk patient (COPD, heart disease, Diabetes). This framework consist database, CAD (Computer Aided diagnosis support system) and CAP (computer aided user vital sign prediction system). It can be applied to develop user pattern learning algorithm based MDSS for homecare and silver town service. Especially this CAD has wise decision making competency. It compares current vital sign with user-s normal condition pattern data. In addition, the CAP computes user vital sign prediction using past data of the patient. The novel approach is using neural network method, wireless vital sign acquisition devices and personal computer DB system. An intelligent agent based MDSS will help elder people and high risk patients to prevent sudden death and disease, the physician to get the online access to patients- data, the plan of medication service priority (e.g. emergency case).

Keywords: Neural network, U-healthcare, MDSS, CAP, DSS.

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Authors: Pimploi Tirastittam, Sawanath Treesathon, Amornrath Ongkawat

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Learning Management System (LMS) is the system which uses to manage the learning in order to grouping the content and learning activity between the lecturer and learner including online examination and evaluation. Nowadays, it is the borderless learning era so the learning activities can be accessed from everywhere in the world and also anytime via the information technology and media. The learner can easily access to the knowledge so the different in time and distance is not a constraint for learning anymore. The learning pattern which was used in this research is the integration of the in-class learning and online learning via internet and will be able to monitor the progress by the Learning management system which will create the fast response and accessible learning process via the social media. In order to increase the capability and freedom of the learner, the system can show the current and history of the learning document, video conference and also has the chat room for the learner and lecturer to interact to each other. So the objectives of the “The Design and Applied of Learning Management System via Social Media on Internet: Case Study of Operating System for Business Subject” are to expand the opportunity of learning and to increase the efficiency of learning as well as increase the communication channel between lecturer and student. The data of this research was collect from 30 users of the system which are students who enroll in the subject. And the result of the research is in the “Very Good” which is conformed to the hypothesis.

Keywords: Learning Management System, Social Media.

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Authors: Zahra Ghadampour, Gholamreza Rakhshandehroo

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A concern that researchers usually face in different applications of Artificial Neural Network (ANN) is determination of the size of effective domain in time series. In this paper, trial and error method was used on groundwater depth time series to determine the size of effective domain in the series in an observation well in Union County, New Jersey, U.S. different domains of 20, 40, 60, 80, 100, and 120 preceding day were examined and the 80 days was considered as effective length of the domain. Data sets in different domains were fed to a Feed Forward Back Propagation ANN with one hidden layer and the groundwater depths were forecasted. Root Mean Square Error (RMSE) and the correlation factor (R2) of estimated and observed groundwater depths for all domains were determined. In general, groundwater depth forecast improved, as evidenced by lower RMSEs and higher R2s, when the domain length increased from 20 to 120. However, 80 days was selected as the effective domain because the improvement was less than 1% beyond that. Forecasted ground water depths utilizing measured daily data (set #1) and data averaged over the effective domain (set #2) were compared. It was postulated that more accurate nature of measured daily data was the reason for a better forecast with lower RMSE (0.1027 m compared to 0.255 m) in set #1. However, the size of input data in this set was 80 times the size of input data in set #2; a factor that may increase the computational effort unpredictably. It was concluded that 80 daily data may be successfully utilized to lower the size of input data sets considerably, while maintaining the effective information in the data set.

Keywords: Neural networks, groundwater depth, forecast.

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Authors: Beste Kaysı, Yasemin Topaloğlu

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Usability is one of the most important quality attributes for web-based information systems. Specifically, for e-commerce applications, usability becomes more prominent. In this study, we aimed to explore the features that experienced users seek in e-commerce applications. We used eye tracking method in evaluations. Eye movement data are obtained from the eye-tracking method and analyzed based on task completion time, number of fixations, as well as heat map and gaze plot measures. The results of the analysis show that the eye movements of participants' are too static in certain areas and their areas of interest are scattered in many different places. It has been determined that this causes users to fail to complete their transactions. According to the findings, we outlined the issues to improve the usability of e-commerce websites. Then we propose solutions to identify the issues. In this way, it is expected that e-commerce sites will be developed which will make experienced users more satisfied.

Keywords: E-commerce websites, eye tracking method, usability, website evaluations.

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Authors: N. K. Satybaldina, A. G. Karabayeva, Z. N. Ismagambetova

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The modern Kazakh society is characterized by strengthen cross-cultural communication, the emergence of new powerful subcultures, accelerated change in social systems and values. The socio-political reforms in all fields have changed the quality of social relationships and spiritual life.Cross-cultural approach involves the analysis of different types of behavior and communication, including the manifestation of the conflict, and the formation of marginal destructive stereotypes.

Keywords: Attitudes, Ethnic, Communication, Cross-cultural, Multiethnic, Multicultural, Society, Stereotype, Strategy, Tolerance

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Authors: Hana Almakky, Reza Sahandi, Jacqui Taylor

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Social media continues to grow, and user interfaces may become more appealing if cultural characteristics are incorporated into their design. Facebook was designed in the west, and the original language was English. Subsequently, the words in the user interface were translated to other languages, including Arabic. Arabic words are written from right to left, and English is written from left to right. The translated version may misrepresent the original design and users’ preferences may be influenced by their culture, which should be considered in the user interface design. Previous research indicates that users are more comfortable when interacting with a user interface, which relates to their own culture. Therefore, this paper, using a survey, investigates the preferences of Saudi Arabians on the Arabic version of the user interface of Facebook.

Keywords: Culture, Facebook, Saudi Arabia, Social media, User Interface Design.

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Authors: Atiqul Islam, Shamim Akhter, Tumnun E. Mursalin

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Least Development Countries (LDC) like Bangladesh, whose 25% revenue earning is achieved from Textile export, requires producing less defective textile for minimizing production cost and time. Inspection processes done on these industries are mostly manual and time consuming. To reduce error on identifying fabric defects requires more automotive and accurate inspection process. Considering this lacking, this research implements a Textile Defect Recognizer which uses computer vision methodology with the combination of multi-layer neural networks to identify four classifications of textile defects. The recognizer, suitable for LDC countries, identifies the fabric defects within economical cost and produces less error prone inspection system in real time. In order to generate input set for the neural network, primarily the recognizer captures digital fabric images by image acquisition device and converts the RGB images into binary images by restoration process and local threshold techniques. Later, the output of the processed image, the area of the faulty portion, the number of objects of the image and the sharp factor of the image, are feed backed as an input layer to the neural network which uses back propagation algorithm to compute the weighted factors and generates the desired classifications of defects as an output.

Keywords: Computer vision, image acquisition device, machine vision, multi-layer neural networks.

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Authors: K. Somprasonk, R. Boondiskulchok

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Medical services are usually provided in hospitals; however, in developing country, some rural residences have fewer opportunities to access in healthcare services due to the limitation of transportation communication. Therefore, in Thailand, there are charitable organizations operating to provide medical treatments to these people by shifting the medical services to operation sites; this is commonly known as mobile medical service. Operation routing is important for the organization to reduce its transportation cost in order to focus more on other important activities; for instance, the development of medical apparatus. VRP is applied to solve the problem of high transportation cost of the studied organization with the searching techniques of saving algorithm to find the minimum total distance of operation route and satisfy available time constraints of voluntary medical staffs.

Keywords: Decision Support System, Mobile Medical Service Planning, Saving Algorithm, Vehicle Routing Problem

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Authors: Haroon Altarawneh, Sattam Allahawiah

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This paper has two main ideas. Firstly, it describes Evans and Wurster-s concepts “the trade-off between reach and richness", and relates them to the impact of technology on the virtual markets. Authors Evans and Wurster see the transfer of information as a 'trade'off between richness and reach-. Reach refers to the number of people who share particular information, with Richness ['Rich'] being a more complex concept combining: bandwidth, customization, interactivity, reliability, security and currency. Traditional shopping limits the number of shops the shopper is able to visit due to time and other cost constraints; the time spent traveling consequently leaves the shopper with less time to evaluate the product. The paper concludes that although the Web provides Reach, offering Richness and the sense of community required for creating and sustaining relationships with potential clients could be difficult.

Keywords: Internet, Web sites, Richness and Reach, Ecommerce, virtual markets.

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Authors: Sándor Juhász, Renáta Iváncsy

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This paper describes an enhanced cookie-based method for counting the visitors of web sites by using a web log processing system that aims to cope with the ambitious goal of creating countrywide statistics about the browsing practices of real human individuals. The focus is put on describing a new more efficient way of detecting human beings behind web users by placing different identifiers on the client computers. We briefly introduce our processing system designed to handle the massive amount of data records continuously gathered from the most important content providers of the Hungary. We conclude by showing statistics of different time spans comparing the efficiency of multiple visitor counting methods to the one presented here, and some interesting charts about content providers and web usage based on real data recorded in 2007 will also be presented.

Keywords: Cookie based identification, real data, user activitytracking, web auditing, web log processing

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Authors: Mohammadamin Zanganeh, Vahid Khalajzadeh

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The problems associated with wind predictions of WAsP model in complex terrain are already the target of several studies in the last decade. In this paper, the influence of surrounding orography on accuracy of wind data analysis of a train is investigated. For the case study, a site with complex surrounding orography is considered. This site is located in Manjil, one of the windiest cities of Iran. For having precise evaluation of wind regime in the site, one-year wind data measurements from two metrological masts are used. To validate the obtained results from WAsP, the cross prediction between each mast is performed. The analysis reveals that WAsP model can estimate the wind speed behavior accurately. In addition, results show that this software can be used for predicting the wind regime in flat sites with complex surrounding orography.

Keywords: Complex terrain, Meteorological mast, WAsPmodel, Wind prediction

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Authors: Julia Moehrmann, Gunter Heidemann, Oliver Siemoneit, Christoph Hubig, Uwe-Philipp Kaeppeler, Paul Levi

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Image data holds a large amount of different context information. However, as of today, these resources remain largely untouched. It is thus the aim of this paper to present a basic technical framework which allows for a quick and easy exploitation of context information from image data especially by non-expert users. Furthermore, the proposed framework is discussed in detail concerning important social and ethical issues which demand special requirements in system design. Finally, a first sensor prototype is presented which meets the identified requirements. Additionally, necessary implications for the software and hardware design of the system are discussed, rendering a sensor system which could be regarded as a good, acceptable and justifiable technical and thereby enabling the extraction of context information from image data.

Keywords: Context-aware computing, ethical and social issues, image recognition, requirements in system design.

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Authors: Wann-Ming Wey

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In recent years, the problems of global climate change and natural disasters have induced the concerns and attentions of environmental sustainability issues for the public. Aside from the environmental planning efforts done for human environment, Transit-Oriented Development (TOD) has been widely used as one of the future solutions for the sustainable city development. In order to be more consistent with the urban sustainable development, the development of the built environment planning based on the concept of Green TOD which combines both TOD and Green Urbanism is adapted here. The connotation of the urban development under the green TOD including the design toward environment protect, the maximum enhancement resources and the efficiency of energy use, use technology to construct green buildings and protected areas, natural ecosystems and communities linked, etc. Green TOD is not only to provide the solution to urban traffic problems, but to direct more sustainable and greener consideration for future urban development planning and design. In this study, we use both the TOD and Green Urbanism concepts to proceed to the study of the built environment planning and design. Fuzzy Delphi Technique (FDT) is utilized to screen suitable criteria of the green TOD. Furthermore, Fuzzy Analytic Network Process (FANP) and Quality Function Deployment (QFD) were then developed to evaluate the criteria and prioritize the alternatives. The study results can be regarded as the future guidelines of the built environment planning and designing under green TOD development in Taiwan.

Keywords: Green transit-oriented development, built environment, fuzzy Delphi technique, quality function deployment, fuzzy analytic network process.

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Authors: Nishant Rodrigues, Nicole Spanedda, Chilukuri K. Mohan, Arindam Chakraborty

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A crucial objective in quantum chemistry is the computation of the energy levels of chemical systems. This task requires electron-repulsion integrals as inputs and the steep computational cost of evaluating these integrals poses a major numerical challenge in efficient implementation of quantum chemical software. This work presents a moment-based machine learning approach for the efficient evaluation of electron-repulsion integrals. These integrals were approximated using linear combinations of a small number of moments. Machine learning algorithms were applied to estimate the coefficients in the linear combination. A random forest approach was used to identify promising features using a recursive feature elimination approach, which performed best for learning the sign of each coefficient, but not the magnitude. A neural network with two hidden layers was then used to learn the coefficient magnitudes, along with an iterative feature masking approach to perform input vector compression, identifying a small subset of orbitals whose coefficients are sufficient for the quantum state energy computation. Finally, a small ensemble of neural networks (with a median rule for decision fusion) was shown to improve results when compared to a single network.

Keywords: Quantum energy calculations, atomic orbitals, electron-repulsion integrals, ensemble machine learning, random forests, neural networks, feature extraction.

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Authors: Alexander G. Yushchenko

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From a multi-science point of view, we analyze threats to security resulting from globalization of international information space and information and communication aggression of Russia. A definition of Ruschism is formulated as an ideology supporting aggressive actions of modern Russia against the Euro-Atlantic community. Stages of the hybrid war Russia is leading against Ukraine are described, including the elements of subversive activity of the special services, the activation of the military phase and the gradual shift of the focus of confrontation to the realm of information and communication technologies. We reveal an emergence of a threat for democratic states resulting from the destabilizing impact of a target state’s mass media and social networks being exploited by Russian secret services under freedom-of-speech disguise. Thus, we underline the vulnerability of cyber- and information security of the network society in regard of hybrid war. We propose to define the latter a synergetic war. Our analysis is supported with a long-term qualitative monitoring of representation of top state officials on popular TV channels and Facebook. From the memetics point of view, we have detected a destructive psycho-information technology used by the Kremlin, a kind of information catastrophe, the essence of which is explained in detail. In the conclusion, a comprehensive plan for information protection of the public consciousness and mentality of Euro-Atlantic citizens from the aggression of the enemy is proposed.

Keywords: Cyber and information security, psycho-information technology, hybrid war, synergetic war, WWIII, Ruschism.

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Authors: Minghui Wang, Shanrui Hu

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An inverse problem of doubly center matrices is discussed. By translating the constrained problem into unconstrained problem, two iterative methods are proposed. A numerical example illustrate our algorithms.

Keywords: doubly center matrix, electric network theory, iterative methods, least-square problem.

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Authors: Sheel Chakraborty

Abstract:

Modern society in developed countries has distanced itself from the earlier norm of joint family living, and with the increase of economic pressure, parents' availability for their children during their infant years has been consistently decreasing over the past three decades. This has been promoted in the US through the legislature and funding. Early care and education may have a positive impact on young minds, but a growing number of kids facing social challenges in making friendships in their teenage years raises serious concerns about its effectiveness. The survey-based primary research presented here shows that a statistically significant number of millennials between the ages of 10 and 25 years prefer to build friendships virtually than face-to-face interactions. Moreover, many teenagers depend more on their virtual friends whom they never met. Contrary to the belief that early social interactions in a non-home setup make the kids confident and more prepared for the real world, many shy-natured kids seem to develop a sense of shakiness in forming social relationships, resulting in loneliness by the time they are young adults. Reflecting on George Mead’s theory of self that is made up of “I” and “Me”, most functioning homes provide the required freedom and forgivable, congenial environment for building the "I" of a toddler; however, daycare or preschools can barely match that. It seems social images created from the “Me” perspective in preschoolers in a daycare environment has interfered and greatly overpowered the formation of a confident "I" thus created a crisis around the inability to form friendships face to face when they grow older. Though the pervasive nature of social media cannot be ignored, the non-parental early care and education practices adopted largely by the urban population have created a favorable platform of teen psychology on which social media popularity thrived, especially providing refuge to shy Gen-Z teenagers. This can explain why young adults today perceive social media as their preferred outlet of expression and a place to form dependable friendships, despite the risk of being cyberbullied.

Keywords: Digital socialization, shyness, developmental psychology, friendship, early education.

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