Search results for: information seeking

Authors: Martin Kendra, Tomas Skrucany, Jozef Gnap, Jan Ponicky

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Paper deals with the modeling and simulation of energy consumption and GHG production of two different modes of regional passenger transport – road and railway. These two transport modes use the same type of fuel – diesel. Modeling and simulation of the energy consumption in transport is often used due to calculation satisfactory accuracy and cost efficiency. Paper deals with the calculation based on EN standards and information collected from technical information from vehicle producers and characteristics of tracks. Calculation included maximal theoretical capacity of bus and train and real passenger’s measurement from operation. Final energy consumption and GHG production is calculated by using software simulation. In evaluation of the simulation is used system “well to wheel”.

Keywords: Bus, energy consumption, GHG, production, simulation, train.

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Authors: Nadezhda Kvatashidze

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The International Accounting Standards Board updated the conceptual framework for financial reporting. The main reason behind it is to resolve the tasks of the accounting, which are caused by the market development and business-transactions of a new economic content. Also, the investors call for higher transparency of information and responsibility for the results in order to make a more accurate risk assessment and forecast. All these make it necessary to further develop the conceptual framework for financial reporting so that the users get useful information. The market development and certain shortcomings of the conceptual framework revealed in practice require its reconsideration and finding new solutions. Some issues and concepts, such as disclosure and supply of information, its qualitative characteristics, assessment, and measurement uncertainty had to be supplemented and perfected. The criteria of recognition of certain elements (assets and liabilities) of reporting had to be updated, too and all this is set out in the updated edition of the conceptual framework for financial reporting, a comprehensive collection of concepts underlying preparation of the financial statement. The main objective of conceptual framework revision is to improve financial reporting and development of clear concepts package. This will support International Accounting Standards Board (IASB) to set common “Approach & Reflection” for similar transactions on the basis of mutually accepted concepts. As a result, companies will be able to develop coherent accounting policies for those transactions or events that are occurred from particular deals to which no standard is used or when standard allows choice of accounting policy.

Keywords: Conceptual framework, measurement basis, measurement uncertainty, neutrality, prudence, stewardship.

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Authors: Karim Heidari, Serajodin Katebi, Ali Reza Mahdavi Far

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The purpose of this paper is to study Database Models to use them efficiently in E-commerce websites. In this paper we are going to find a method which can save and retrieve information in Ecommerce websites. Thus, semantic web applications can work with, and we are also going to study different technologies of E-commerce databases and we know that one of the most important deficits in semantic web is the shortage of semantic data, since most of the information is still stored in relational databases, we present an approach to map legacy data stored in relational databases into the Semantic Web using virtually any modern RDF query language, as long as it is closed within RDF. To achieve this goal we study XML structures for relational data bases of old websites and eventually we will come up one level over XML and look for a map from relational model (RDM) to RDF. Noting that a large number of semantic webs get advantage of relational model, opening the ways which can be converted to XML and RDF in modern systems (semantic web) is important.

Keywords: E-Commerce, Semantic Web, Database, XML, RDF.

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Authors: Yunseok Noh, Chang-Uk Kwak, Sun-Joong Kim, Seong-Bae Park

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Scripts are one of the basic text resources to understand broadcasting contents. Topic modeling is the method to get the summary of the broadcasting contents from its scripts. Generally, scripts represent contents descriptively with directions and speeches, and provide scene segments that can be seen as semantic units. Therefore, a script can be topic modeled by treating a scene segment as a document. Because scene segments consist of speeches mainly, however, relatively small co-occurrences among words in the scene segments are observed. This causes inevitably the bad quality of topics by statistical learning method. To tackle this problem, we propose a method to improve topic quality with additional word co-occurrence information obtained using scene similarities. The main idea of improving topic quality is that the information that two or more texts are topically related can be useful to learn high quality of topics. In addition, more accurate topical representations lead to get information more accurate whether two texts are related or not. In this paper, we regard two scene segments are related if their topical similarity is high enough. We also consider that words are co-occurred if they are in topically related scene segments together. By iteratively inferring topics and determining semantically neighborhood scene segments, we draw a topic space represents broadcasting contents well. In the experiments, we showed the proposed method generates a higher quality of topics from Korean drama scripts than the baselines.

Keywords: Broadcasting contents, generalized P´olya urn model, scripts, text similarity, topic model.

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Authors: Majid Forghani, Michael Khachay

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In genetics, the impact of neighboring amino acids on a target site is referred as the nearest-neighbor effect or simply neighbor effect. In this paper, a new method called wavelet particle decomposition representing the one-dimensional neighbor effect using wavelet packet decomposition is proposed. The main idea lies in known dependence of wavelet packet sub-bands on location and order of neighboring samples. The method decomposes the value of a signal sample into small values called particles that represent a part of the neighbor effect information. The results have shown that the information obtained from the particle decomposition can be used to create better model variables or features. As an example, the approach has been applied to improve the correlation of test and reference sequence distance with titer in the hemagglutination inhibition assay.

Keywords: Antigenic variants, neighbor effect, wavelet packet, wavelet particle decomposition.

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Authors: Souvik Bhattacharyya, Aparajita Khan, Indradip Banerjee, Gautam Sanyal

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Steganography is the art and science that hides the information in an appropriate cover carrier like image, text, audio and video media. In this work the authors propose a new image based steganographic method for hiding information within the complex bit planes of the image. After slicing into bit planes the cover image is analyzed to extract the most complex planes in decreasing order based on their bit plane complexity. The complexity function next determines the complex noisy blocks of the chosen bit plane and finally pixel mapping method (PMM) has been used to embed secret bits into those regions of the bit plane. The novel approach of using pixel mapping method (PMM) in bit plane domain adaptively embeds data on most complex regions of image, provides high embedding capacity, better imperceptibility and resistance to steganalysis attack.

Keywords: PMM (Pixel Mapping Method), Bit Plane, Steganography, SSIM, KL-Divergence.

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Authors: Robert Koch, Mario Golling, Gabi Dreo

Abstract:

During the last couple of years, the degree of dependence on IT systems has reached a dimension nobody imagined to be possible 10 years ago. The increased usage of mobile devices (e.g., smart phones), wireless sensor networks and embedded devices (Internet of Things) are only some examples of the dependency of modern societies on cyber space. At the same time, the complexity of IT applications, e.g., because of the increasing use of cloud computing, is rising continuously. Along with this, the threats to IT security have increased both quantitatively and qualitatively, as recent examples like STUXNET or the supposed cyber attack on Illinois water system are proofing impressively. Once isolated control systems are nowadays often publicly available - a fact that has never been intended by the developers. Threats to IT systems don’t care about areas of responsibility. Especially with regard to Cyber Warfare, IT threats are no longer limited to company or industry boundaries, administrative jurisdictions or state boundaries. One of the important countermeasures is increased cooperation among the participants especially in the field of Cyber Defence. Besides political and legal challenges, there are technical ones as well. A better, at least partially automated exchange of information is essential to (i) enable sophisticated situational awareness and to (ii) counter the attacker in a coordinated way. Therefore, this publication performs an evaluation of state of the art Intrusion Detection Message Exchange protocols in order to guarantee a secure information exchange between different entities.

Keywords: Cyber Defence, Cyber Warfare, Intrusion Detection Information Exchange, Early Warning Systems, Joint Intrusion Detection, Cyber Conflict

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Authors: Hu Haibo, Zhao Hong

Abstract:

Gaussian mixture background model is widely used in moving target detection of the image sequences. However, traditional Gaussian mixture background model usually considers the time continuity of the pixels, and establishes background through statistical distribution of pixels without taking into account the pixels- spatial similarity, which will cause noise, imperfection and other problems. This paper proposes a new Gaussian mixture modeling approach, which combines the color and gradient of the spatial information, and integrates the spatial information of the pixel sequences to establish Gaussian mixture background. The experimental results show that the movement background can be extracted accurately and efficiently, and the algorithm is more robust, and can work in real time in tracking applications.

Keywords: Gaussian mixture model, real-time tracking, sequence image, gradient.

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Authors: Keun-Chang Kwak

Abstract:

This paper is concerned with motion recognition based fuzzy WP(Wavelet Packet) feature extraction approach from Vicon physical data sets. For this purpose, we use an efficient fuzzy mutual-information-based WP transform for feature extraction. This method estimates the required mutual information using a novel approach based on fuzzy membership function. The physical action data set includes 10 normal and 10 aggressive physical actions that measure the human activity. The data have been collected from 10 subjects using the Vicon 3D tracker. The experiments consist of running, seating, and walking as physical activity motion among various activities. The experimental results revealed that the presented feature extraction approach showed good recognition performance.

Keywords: Motion recognition, fuzzy wavelet packet, Vicon physical data.

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Authors: Abbas Hani

Abstract:

The concentrations of As, Hg, Co, Cr and Cd were tested for each soil sample, and their spatial patterns were analyzed by the semivariogram approach of geostatistics and geographical information system technology. Multivariate statistic approaches (principal component analysis and cluster analysis) were used to identify heavy metal sources and their spatial pattern. Principal component analysis coupled with correlation between heavy metals showed that primary inputs of As, Hg and Cd were due to anthropogenic while, Co, and Cr were associated with pedogenic factors. Ordinary kriging was carried out to map the spatial patters of heavy metals. The high pollution sources evaluated was related with usage of urban and industrial wastewater. The results of this study helpful for risk assessment of environmental pollution for decision making for industrial adjustment and remedy soil pollution.

Keywords: Geographic Information system, Geostatistics, Kaveh, Multivariate Statistical Analysis.

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Authors: Celal Dudak, Aslı Utku, Burak Yağlioğlu

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Uninterrupted and continuous satellite communication through the whole orbit time is becoming more indispensable every day. Data relay systems are developed and built for various high/low data rate information exchanges like TDRSS of USA and EDRSS of Europe. In these missions, a couple of task-dedicated communication satellites exist. In this regard, for Turkey a data relay system is attempted to be defined exchanging low data rate information (i.e. TTC) for Earth-observing LEO satellites appointing commercial GEO communication satellites all over the world. First, justification of this attempt is given, demonstrating duration enhancements in the link. Discussion of preference of RF communication is, also, given instead of laser communication. Then, preferred communication GEOs – including TURKSAT4A already belonging to Turkey- are given, together with the coverage enhancements through STK simulations and the corresponding link budget. Also, a block diagram of the communication system is given on the LEO satellite.

Keywords: Communication, satellite, data relay system, coverage.

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Authors: Syed Salman Ahmed, Zahid Halim, Rauf Baig, Shariq Bashir

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With the rapid growth in business size, today's businesses orient towards electronic technologies. Amazon.com and e-bay.com are some of the major stakeholders in this regard. Unfortunately the enormous size and hugely unstructured data on the web, even for a single commodity, has become a cause of ambiguity for consumers. Extracting valuable information from such an everincreasing data is an extremely tedious task and is fast becoming critical towards the success of businesses. Web content mining can play a major role in solving these issues. It involves using efficient algorithmic techniques to search and retrieve the desired information from a seemingly impossible to search unstructured data on the Internet. Application of web content mining can be very encouraging in the areas of Customer Relations Modeling, billing records, logistics investigations, product cataloguing and quality management. In this paper we present a review of some very interesting, efficient yet implementable techniques from the field of web content mining and study their impact in the area specific to business user needs focusing both on the customer as well as the producer. The techniques we would be reviewing include, mining by developing a knowledge-base repository of the domain, iterative refinement of user queries for personalized search, using a graphbased approach for the development of a web-crawler and filtering information for personalized search using website captions. These techniques have been analyzed and compared on the basis of their execution time and relevance of the result they produced against a particular search.

Keywords: Data mining, web mining, search engines, knowledge discovery.

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Authors: Hichem Omrani, Philippe Gerber, Patrick Bousch

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The problem of Small Area Estimation (SAE) is complex because of various information sources and insufficient data. In this paper, an approach for SAE is presented for decision-making at national, regional and local level. We propose an Empirical Best Linear Unbiased Predictor (EBLUP) as an estimator in order to combine several information sources to evaluate various indicators. First, we present the urban audit project and its environmental, social and economic indicators. Secondly, we propose an approach for decision making in order to estimate indicators. An application is used to validate the theoretical proposal. Finally, a decision support system is presented based on open-source environment.

Keywords: Small area estimation, statistical method, sampling, empirical best linear unbiased predictor (EBLUP), decision-making.

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Authors: M. Bosques-Perez, W. Izquierdo, H. Martin, L. Deng, J. Rodriguez, T. Yan, M. Cabrerizo, A. Barreto, N. Rishe, M. Adjouadi

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Aerial imagery is a powerful tool when it comes to analyzing temporal changes in ecosystems and extracting valuable information from the observed scene. It allows us to identify and assess various elements such as objects, structures, textures, waterways, and shadows. To extract meaningful information, multispectral cameras capture data across different wavelength bands of the electromagnetic spectrum. In this study, the collected multispectral aerial images were subjected to principal component analysis (PCA) to identify independent and uncorrelated components or features that extend beyond the visible spectrum captured in standard RGB images. The results demonstrate that these principal components contain unique characteristics specific to certain wavebands, enabling effective object identification and image segmentation.

Keywords: Big data, image processing, multispectral, principal component analysis.

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Authors: M. N. Norshita, B. Z. Halimah, T. S. Tengku Mohammad

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The implementation of electronic government started since the initiation of Multimedia Super Corridor (MSC) by the Malaysia government. The introduction of ICT in the public sector especially e-Government initiatives opens up a new book in the government administration throughout the world. The aim or this paper is to discuss the implementation of e-government in Malaysia, covering the result of public user self assessment on Malaysia's electronic government applications. E-services, e-procurement, Generic Office Environment (GOE), Human Resources Management Information System (HRMIS), Project Monitoring System (PMS), Electronic Labor Exchange (ELX) and e-syariah(religion) were the seven flagship application assessed. The study adopted a crosssectional survey research approach and information system literature were used. The analysis was done for 35 responden in pilot test and there was evidence from public user's perspective to suggest that the e-government applications were generally successful.

Keywords: Electronic government, flagship, multimedia super corridor, public user.

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Authors: Lakshmi Pujitha Dachuri, Nalini Uppala

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In many applications retransmissions of lost packets are not permitted. OFDM is a multi-carrier modulation scheme having excellent performance which allows overlapping in frequency domain. With OFDM there is a simple way of dealing with multipath relatively simple DSP algorithms.

 In this paper, an image frame is compressed using DWT, and the compressed data is arranged in data vectors, each with equal number of coefficients. These vectors are quantized and binary coded to get the bit steams, which are then packetized and intelligently mapped to the OFDM system. Based on one-bit channel state information at the transmitter, the descriptions in order of descending priority are assigned to the currently good channels such that poorer sub-channels can only affect the lesser important data vectors. We consider only one-bit channel state information available at the transmitter, informing only about the sub-channels to be good or bad. For a good sub-channel, instantaneous received power should be greater than a threshold P_th. Otherwise, the sub-channel is in fading state and considered bad for that batch of coefficients. In order to reduce the system power consumption, the mapped descriptions onto the bad sub channels are dropped at the transmitter. The binary channel state information gives an opportunity to map the bit streams intelligently and to save a reasonable amount of power. By using MAT LAB simulation we can analysis the performance of our proposed scheme, in terms of system energy saving without compromising the received quality in terms of peak signal-noise ratio.

Keywords: Binary channel state, Channel state feedback, DWT-OFDM system, Energy saving, Fading broadcast channel.

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Authors: Anant Oonsivilai, Kenedy A. Greyson

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The growth and interconnection of power networks in many regions has invited complicated techniques for energy management services (EMS). State estimation techniques become a powerful tool in power system control centers, and that more information is required to achieve the objective of EMS. For the online state estimator, assuming the continuous time is equidistantly sampled with period Δt, processing events must be finished within this period. Advantage of Kalman Filtering (KF) algorithm in using system information to improve the estimation precision is utilized. Computational power is a major issue responsible for the achievement of the objective, i.e. estimators- solution at a small sampled period. This paper presents the optimum utilization of processors in a state estimator based on KF. The model used is presented using Petri net (PN) theory.

Keywords: Kalman filters, model, Petri Net, power system, sequential State estimator.

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Authors: Yu-Shuai Chen , Chien-Ching Chiu , Chung-Hsin Huang, Chien-Hung Chen

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The bit error rate (BER) performance for ultra-wide band (UWB) indoor communication with impact of metallic furniture is investigated. The impulse responses of different indoor environments for any transmitter and receiver location are computed by shooting and bouncing ray/image and inverse Fourier transform techniques. By using the impulse responses of these multipath channels, the BER performance for binary pulse amplitude modulation (BPAM) impulse radio UWB communication system are calculated. Numerical results have shown that the multi-path effect by the metallic cabinets is an important factor for BER performance. Also the outage probability for the UWB multipath environment with metallic cabinets is more serious (about 18%) than with wooden cabinets. Finally, it is worth noting that in these cases the present work provides not only comparative information but also quantitative information on the performance reduction.

Keywords: UWB, multipath, outage probability.

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Authors: Laila Yasir Al-Harthy, Ali H. Al-Badi

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As an emerging business model, cloud computing has been initiated to satisfy the need of organizations and to push Information Technology as a utility. The shift to the cloud has changed the way Information Technology departments are managed traditionally and has raised many concerns for both, public and private sectors.

The purpose of this study is to investigate the possibility of cloud computing services replacing services provided traditionally by IT departments. Therefore, it aims to 1) explore whether organizations in Oman are ready to move to the cloud; 2) identify the deciding factors leading to the adoption or rejection of cloud computing services in Oman; and 3) provide two case studies, one for a successful Cloud provider and another for a successful adopter.

This paper is based on multiple research methods including conducting a set of interviews with cloud service providers and current cloud users in Oman; and collecting data using questionnaires from experts in the field and potential users of cloud services.

Despite the limitation of bandwidth capacity and Internet coverage offered in Oman that create a challenge in adopting the cloud, it was found that many information technology professionals are encouraged to move to the cloud while few are resistant to change.

The recent launch of a new Omani cloud service provider and the entrance of other international cloud service providers in the Omani market make this research extremely valuable as it aims to provide real-life experience as well as two case studies on the successful provision of cloud services and the successful adoption of these services.

Keywords: Cloud computing, cloud deployment models, cloud service models and deciding factors.

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Authors: Andreea Maier, Diana Nicoară, Dorin Maier, Maria-Mihaela Suărăsan, Alexandra Anastasiu

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Innovation is becoming more and more important in modern society. There are a lot of researches on different kinds of innovation but marketing innovation is one kind of innovation that has not been studied frequently before. Marketing innovation is defined as a new way in which companies can market themselves to potential or existing customers. The study shows some key elements for marketing innovation that are worth paying attention to when implementing marketing innovation projects. Examples of such key elements are: paying attention to the neglected market, suitable market segmentatio reliable market information, public relationship, increased customer value, combination of market factors, explore different marketing channels and the use of technology in combination with what? Beside the key elements for marketing innovation, we also present some risks that may occur, such as cost, market uncertainty, information leakage, imitation and overdependence on experience. By proposing a set of indicators to measure marketing innovation, the article offers solutions for marketing innovation implementation so that any organization can achieve optimal results.

Keywords: Innovation, marketing innovation, performance in an organization.

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Authors: Jamaludin Sallim

Abstract:

This paper describes the challenges on the requirements engineering for developing an enterprise applications in higher education environment. The development activities include software implementation, maintenance, and enhancement and support for online transaction processing and overnight batch processing. Generally, an enterprise application for higher education environment may include Student Information System (SIS), HR/Payroll system, Financial Systems etc. By the way, there are so many challenges in requirement engineering phases in order to provide two distinctive services that are production processing support and systems development.

Keywords: enterprise applications development, enterprise information systems, business process, requirement engineering, requirement standards, software development activities, software requirement reviews.

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Authors: Margareta Ilkova, Petr Teply

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The article deals with dividends and their distribution from investors from a theoretical point of view. Some studies try to analyzed the reaction of the market on the dividend announcement and found out the change of dividend policy is associated with abnormal returns around the dividend announcement date. Another researches directly questioned the investors about their dividend preference and beliefs. Investors want the dividend from many reasons (e.g. some of them explain the dividend preference by the existence of transaction cost; investors prefer the dividend today, because there is less risky; the managers have private information about the firm). The most controversial theory of dividend policy was developed by Modigliani and Miller (1961) who demonstrated that in the perfect and complete capital markets the dividend policy is irrelevant and the value of the company is independent of its payout policy. Nevertheless, in the real world the capital markets are imperfect, because of asymmetric information, transaction costs, incomplete contracting possibilities and taxes.

Keywords: dividend distribution, taxation, payout policy, investor, Modigliani and Miller theorem

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Authors: Yee Ling Boo, Damminda Alahakoon

Abstract:

Biologically human brain processes information in both unimodal and multimodal approaches. In fact, information is progressively abstracted and seamlessly fused. Subsequently, the fusion of multimodal inputs allows a holistic understanding of a problem. The proliferation of technology has exponentially produced various sources of data, which could be likened to being the state of multimodality in human brain. Therefore, this is an inspiration to develop a methodology for exploring multimodal data and further identifying multi-view patterns. Specifically, we propose a brain inspired conceptual model that allows exploration and identification of patterns at different levels of granularity, different types of hierarchies and different types of modalities. A structurally adaptive neural network is deployed to implement the proposed model. Furthermore, the acquisition of multi-view patterns with the proposed model is demonstrated and discussed with some experimental results.

Keywords: Multimodal, Granularity, Hierarchical Clustering, Growing Self Organising Maps, Data Mining

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Authors: Ashok Kumar, Vinod Kumar

Abstract:

Wireless Sensor Networks (WSNs) are used to monitor/observe vast inaccessible regions through deployment of large number of sensor nodes in the sensing area. For majority of WSN applications, the collected data needs to be combined with geographic information of its origin to make it useful for the user; information received from remote Sensor Nodes (SNs) that are several hops away from base station/sink is meaningless without knowledge of its source. In addition to this, location information of SNs can also be used to propose/develop new network protocols for WSNs to improve their energy efficiency and lifetime. In this paper, range free localization protocols for WSNs have been proposed. The proposed protocols are based on weighted centroid localization technique, where the edge weights of SNs are decided by utilizing fuzzy logic inference for received signal strength and link quality between the nodes. The fuzzification is carried out using (i) Mamdani, (ii) Sugeno, and (iii) Combined Mamdani Sugeno fuzzy logic inference. Simulation results demonstrate that proposed protocols provide better accuracy in node localization compared to conventional centroid based localization protocols despite presence of unintentional radio frequency interference from radio frequency (RF) sources operating in same frequency band.

Keywords: localization, range free, received signal strength, link quality indicator, Mamdani fuzzy logic inference, Sugeno fuzzy logic inference.

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Authors: A. A Velásquez, J.Baena

Abstract:

This article presents the simulation, parameterization and optimization of an electromagnet with the C–shaped configuration, intended for the study of magnetic properties of materials. The electromagnet studied consists of a C-shaped yoke, which provides self–shielding for minimizing losses of magnetic flux density, two poles of high magnetic permeability and power coils wound on the poles. The main physical variable studied was the static magnetic flux density in a column within the gap between the poles, with 4cm2 of square cross section and a length of 5cm, seeking a suitable set of parameters that allow us to achieve a uniform magnetic flux density of 1x104 Gaussor values above this in the column, when the system operates at room temperature and with a current consumption not exceeding 5A. By means of a magnetostatic analysis by the finite element method, the magnetic flux density and the distribution of the magnetic field lines were visualized and quantified. From the results obtained by simulating an initial configuration of electromagnet, a structural optimization of the geometry of the adjustable caps for the ends of the poles was performed. The magnetic permeability effect of the soft magnetic materials used in the poles system, such as low– carbon steel (0.08% C), Permalloy (45% Ni, 54.7% Fe) and Mumetal (21.2% Fe, 78.5% Ni), was also evaluated. The intensity and uniformity of the magnetic field in the gap showed a high dependence with the factors described above. The magnetic field achieved in the column was uniform and its magnitude ranged between 1.5x104 Gauss and 1.9x104 Gauss according to the material of the pole used, with the possibility of increasing the magnetic field by choosing a suitable geometry of the cap, introducing a cooling system for the coils and adjusting the spacing between the poles. This makes the device a versatile and scalable tool to generate the magnetic field necessary to perform magnetic characterization of materials by techniques such as vibrating sample magnetometry (VSM), Hall-effect, Kerr-effect magnetometry, among others. Additionally, a CAD design of the modules of the electromagnet is presented in order to facilitate the construction and scaling of the physical device.

Keywords: Electromagnet, Finite Elements Method, Magnetostatic, Magnetometry, Modeling.

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Authors: Satoshi Usami

Abstract:

Among various HLM techniques, the Multivariate Hierarchical Linear Model (MHLM) is desirable to use, particularly when multivariate criterion variables are collected and the covariance structure has information valuable for data analysis. In order to reflect prior information or to obtain stable results when the sample size and the number of groups are not sufficiently large, the Bayes method has often been employed in hierarchical data analysis. In these cases, although the Markov Chain Monte Carlo (MCMC) method is a rather powerful tool for parameter estimation, Procedures regarding MCMC have not been formulated for MHLM. For this reason, this research presents concrete procedures for parameter estimation through the use of the Gibbs samplers. Lastly, several future topics for the use of MCMC approach for HLM is discussed.

Keywords: Gibbs sampler, Hierarchical Linear Model, Markov Chain Monte Carlo, Multivariate Hierarchical Linear Model

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Authors: Hossein Mirzaee, Farhad Besharati

Abstract:

Solar sunspot rotation, latitudinal bands are studied based on intelligent computation methods. A combination of image fusion method with together tree decomposition is used to obtain quantitative values about the latitudes of trajectories on sun surface that sunspots rotate around them. Daily solar images taken with SOlar and Heliospheric (SOHO) satellite are fused for each month separately .The result of fused image is decomposed with Quad Tree decomposition method in order to achieve the precise information about latitudes of sunspot trajectories. Such analysis is useful for gathering information about the regions on sun surface and coordinates in space that is more expose to solar geomagnetic storms, tremendous flares and hot plasma gases permeate interplanetary space and help human to serve their technical systems. Here sunspot images in September, November and October in 2001 are used for studying the magnetic behavior of sun.

Keywords: Quad tree decomposition, sunspot image.

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Authors: Cheng-Hsiung Hung, Hong-Jie Dai, Jason Jen-Yen Chen

Abstract:

This paper presents a new approach for intelligent agent communication based on ontology for agent community. DARPA agent markup language (DAML) is used to build the community ontology. This paper extends the agent management specification by the foundation for intelligent physical agents (FIPA) to develop an agent role called community facilitator (CF) that manages community directory and community ontology. CF helps build agent community. Precise description of agent service in this community can thus be achieved. This facilitates agent communication. Furthermore, through ontology update, agents with different ontology are capable of communicating with each other. An example of advanced traveler information system is included to illustrate practicality of this approach.

Keywords: Intelligent agent communication, DARPA agent markup language (DAML), Community ontology, Advanced Traveler Information System (ATIS).

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Authors: G.P. Nguyen, H.J. Andersen

Abstract:

Building intelligent traffic guide systems has been an interesting subject recently. A good system should be able to observe all important visual information to be able to analyze the context of the scene. To do so, signs in general, and traffic signs in particular, are usually taken into account as they contain rich information to these systems. Therefore, many researchers have put an effort on sign recognition field. Sign localization or sign detection is the most important step in the sign recognition process. This step filters out non informative area in the scene, and locates candidates in later steps. In this paper, we apply a new approach in detecting sign locations using a new color invariant model. Experiments are carried out with different datasets introduced in other works where authors claimed the difficulty in detecting signs under unfavorable imaging conditions. Our method is simple, fast and most importantly it gives a high detection rate in locating signs.

Keywords: Sign localization, color-based segmentation.

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Authors: Ashutosh Kumar Singh, Ravi Kumar P

Abstract:

This paper gives an introduction to Web mining, then describes Web Structure mining in detail, and explores the data structure used by the Web. This paper also explores different Page Rank algorithms and compare those algorithms used for Information Retrieval. In Web Mining, the basics of Web mining and the Web mining categories are explained. Different Page Rank based algorithms like PageRank (PR), WPR (Weighted PageRank), HITS (Hyperlink-Induced Topic Search), DistanceRank and DirichletRank algorithms are discussed and compared. PageRanks are calculated for PageRank and Weighted PageRank algorithms for a given hyperlink structure. Simulation Program is developed for PageRank algorithm because PageRank is the only ranking algorithm implemented in the search engine (Google). The outputs are shown in a table and chart format.

Keywords: Web Mining, Web Structure, Web Graph, LinkAnalysis, PageRank, Weighted PageRank, HITS, DistanceRank, DirichletRank,

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