Search results for: Databases and Information Retrieval

Authors: Guy Rosman, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel

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We present a new algorithm for nonlinear dimensionality reduction that consistently uses global information, and that enables understanding the intrinsic geometry of non-convex manifolds. Compared to methods that consider only local information, our method appears to be more robust to noise. Unlike most methods that incorporate global information, the proposed approach automatically handles non-convexity of the data manifold. We demonstrate the performance of our algorithm and compare it to state-of-the-art methods on synthetic as well as real data.

Keywords: Dimensionality reduction, manifold learning, multidimensional scaling, geodesic distance, boundary detection.

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Authors: Syed Fahad Tahir, Asifullah Khan, Abdul Majid, Anwar M. Mirza

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In this paper, we present an innovative scheme of blindly extracting message bits from an image distorted by an attack. Support Vector Machine (SVM) is used to nonlinearly classify the bits of the embedded message. Traditionally, a hard decoder is used with the assumption that the underlying modeling of the Discrete Cosine Transform (DCT) coefficients does not appreciably change. In case of an attack, the distribution of the image coefficients is heavily altered. The distribution of the sufficient statistics at the receiving end corresponding to the antipodal signals overlap and a simple hard decoder fails to classify them properly. We are considering message retrieval of antipodal signal as a binary classification problem. Machine learning techniques like SVM is used to retrieve the message, when certain specific class of attacks is most probable. In order to validate SVM based decoding scheme, we have taken Gaussian noise as a test case. We generate a data set using 125 images and 25 different keys. Polynomial kernel of SVM has achieved 100 percent accuracy on test data.

Keywords: Bit Correct Ratio (BCR), Grid Search, Intelligent Decoding, Jackknife Technique, Support Vector Machine (SVM), Watermarking.

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Authors: Mitsuhiro Taniyama, Yuu Hidaka, Masato Arai, Satoshi Kai, Hiromi Igawa, Hiroshi Yajima, Ryoichi Sasaki

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Along with the progress of our information society, various risks are becoming increasingly common, causing multiple social problems. For this reason, risk communications for establishing consensus among stakeholders who have different priorities have become important. However, it is not always easy for the decision makers to agree on measures to reduce risks based on opposing concepts, such as security, privacy and cost. Therefore, we previously developed and proposed the “Multiple Risk Communicator" (MRC) with the following functions: (1) modeling the support role of the risk specialist, (2) an optimization engine, and (3) displaying the computed results. In this paper, MRC program version 1.0 is applied to the personal information leakage problem. The application process and validation of the results are discussed.

Keywords: Decision Making, Personal Information Leakage Problem, Risk Communication, Risk Management

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Authors: Sepehr M.H.Jamarani, M.H.Moradi, H.Behnam, G.A.Rezai Rad

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This paper presents an approach for early breast cancer diagnostic by employing combination of artificial neural networks (ANN) and multiwaveletpacket based subband image decomposition. The microcalcifications correspond to high-frequency components of the image spectrum, detection of microcalcifications is achieved by decomposing the mammograms into different frequency subbands,, reconstructing the mammograms from the subbands containing only high frequencies. For this approach we employed different types of multiwaveletpacket. We used the result as an input of neural network for classification. The proposed methodology is tested using the Nijmegen and the Mammographic Image Analysis Society (MIAS) mammographic databases and images collected from local hospitals. Results are presented as the receiver operating characteristic (ROC) performance and are quantified by the area under the ROC curve.

Keywords: Breast cancer, neural networks, diagnosis, multiwavelet packet, microcalcification.

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Authors: Roelien Goede

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Information systems practitioners are frequently required to master new technology, often without the aid of formal training. They require the skill to manage their own learning and, when this skill is developed in their formal training, their adaptability to new technology may be improved. Self- directed learning is the ability of the learner to manage his or her own learning experience with some guidance from a facilitator. Self-directed learning skills are best improved when practiced. This paper reflects on a critical social research project to improve the self-directed learning skills of fourth year Information Systems students. Critical social research differs from other research paradigms in that the researcher is viewed as the agent of change to achieve the desired outcome in the problem situation.

Keywords: Action Research, Critical Social Research, Information Systems Education, Self-directed Learning.

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Authors: W. Hou, X. Shan, X. Ye

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Bidding is a very important business function to find latent contractors of construction projects. Moreover, bid markup is one of the most important decisions for a bidder to gain a reasonable profit. Since the bidding system is a complex adaptive system, bidding agent need a learning process to get more valuable knowledge for a bid, especially from past public bidding information. In this paper, we proposed an iterative agent leaning model for bidders to make markup decisions. A classifier for public bidding information named PIBS is developed to make full use of history data for classifying new bidding information. The simulation and experimental study is performed to show the validity of the proposed classifier. Some factors that affect the validity of PIBS are also analyzed at the end of this work.

Keywords: bidding markup, decision making, agent learning, information similarity.

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Authors: Seyed Mohammad Hossein Moossavizadeh, Mehran Mohsenzadeh, Nasrin Arshadi

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the data quality is a kind of complex and unstructured concept, which is concerned by information systems managers. The reason of this attention is the high amount of Expenses for maintenance and cleaning of the inefficient data. Such a data more than its expenses of lack of quality, cause wrong statistics, analysis and decisions in organizations. Therefor the managers intend to improve the quality of their information systems' data. One of the basic subjects of quality improvement is the evaluation of the amount of it. In this paper, we present a precautionary method, which with its application the data of information systems would have a better quality. Our method would cover different dimensions of data quality; therefor it has necessary integrity. The presented method has tested on three dimensions of accuracy, value-added and believability and the results confirm the improvement and integrity of this method.

Keywords: Data quality, precaution, information system, measurement, improvement.

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Authors: Chien-Hua Wang, Wei-Hsuan Lee, Chin-Tzong Pang

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In data mining, the association rules are used to find for the associations between the different items of the transactions database. As the data collected and stored, rules of value can be found through association rules, which can be applied to help managers execute marketing strategies and establish sound market frameworks. This paper aims to use Fuzzy Frequent Pattern growth (FFP-growth) to derive from fuzzy association rules. At first, we apply fuzzy partition methods and decide a membership function of quantitative value for each transaction item. Next, we implement FFP-growth to deal with the process of data mining. In addition, in order to understand the impact of Apriori algorithm and FFP-growth algorithm on the execution time and the number of generated association rules, the experiment will be performed by using different sizes of databases and thresholds. Lastly, the experiment results show FFPgrowth algorithm is more efficient than other existing methods.

Keywords: Data mining, association rule, fuzzy frequent patterngrowth.

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Authors: Rakkrit Duangsoithong, Jermphiphut Jaruenpunyasak, Alba Garcia

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The use of foot recognition can be applied in many medical fields such as the gait pattern analysis and the knee exercises of patients in rehabilitation. Generally, a camera-based foot recognition system is intended to capture a patient image in a controlled room and background to recognize the foot in the limited views. However, this system can be inconvenient to monitor the knee exercises at home. In order to overcome these problems, this paper proposes to use the deep learning method using Convolutional Neural Networks (CNNs) for foot recognition. The results are compared with the traditional classification method using LBP and HOG features with kNN and SVM classifiers. According to the results, deep learning method provides better accuracy but with higher complexity to recognize the foot images from online databases than the traditional classification method.

Keywords: Convolutional neural networks, deep learning, foot recognition, knee rehabilitation.

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Authors: Tomohiro Ando, Satoshi Yamashita

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The objective of this study is to propose a statistical modeling method which enables simultaneous term structure estimation of the risk-free interest rate, hazard and loss given default, incorporating the characteristics of the bond issuing company such as credit rating and financial information. A reduced form model is used for this purpose. Statistical techniques such as spline estimation and Bayesian information criterion are employed for parameter estimation and model selection. An empirical analysis is conducted using the information on the Japanese bond market data. Results of the empirical analysis confirm the usefulness of the proposed method.

Keywords: Empirical Bayes, Hazard term structure, Loss given default.

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Authors: Joseph Oh, Bo-Hyun Kim, Jae-Yong Baek

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This study suggests how an order-receiving company can avoid disclosing schedule information on unit tasks to the order-placing company when carrying out a collaborative project on the value chain in an order-oriented industry. Specifically, it suggests methods for keeping schedule information confidential, and categorizes potential situations by inter-task dependency. Lastly, an approach to select the most optimal non-disclosure method is discussed. With the methods for not disclosing work-related information suggested in the study, order-receiving companies can logically deal with political issues relating to the question of whether or not to disclose information upon the execution of a collaborative project in cooperation with an order-placing firm. Moreover, order-placing companies can monitor undistorted information, while respecting the legitimate rights of an order-receiving company. Therefore, it is fair to say that the suggestions made in this study will contribute to the smooth operation of collaborative intercompany projects.

Keywords: collaborative project, dependency, schedule management, unit task.

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Authors: Mario Spremić

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Despite the financial crisis and ongoing need for cost cutting, companies all around the world heavily invest in Information Systems (IS) and underlying Information Technology (IT). Proliferation of governance of enterprise IT helps companies manage, or rather, governs IS as a primary business function with executive management involved in making decision about IS and IT. The business value of IT is raising with the involvement of the executive management in IT decision making process and quality IT governance mechanisms in place. In this paper the practice of governing the enterprise IT will be investigated on a sample of the largest 100 Croatian companies. Research questions posed here will reveal if there are some formal IT governance mechanisms, are there any differences in perceived role of IS and IT between CIOs (Chief Information Officers) and CEOs (Chief Executive Officers) of the sampled companies and what are the mechanisms to govern massive investment in enterprise IT.

Keywords: IT governance, governance of enterprise IT, information system auditing, IT maturity.

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Authors: Despina Galani, Efthymios Gravas, Antonios Stavropoulos

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Advances in information technology, recent changes in business environment, globalization, deregulation, privatization have made running a successful business more difficult than ever before. To remain successful and to be competitive have forced companies to react to the new changes in order to survive and succeed. The implementation of an Enterprise Resource planning (ERP) system improves information flow, reduce costs, establish linkage with suppliers and reduce response time to customer needs. This paper focuses on a sample of Greek companies, investigates the ERP market in Greece, the reasons why the Greek companies are investing in ERP systems, the benefits that users have achieved and the influence of ERP systems on the use of new accounting practices. The results indicate a greater level on information integration, flexibility in information access and greater functionality provided by ERP systems but little influence on the use of new accounting practices.

Keywords: Advanced Accounting Practices, EnterpriseResource Planning, Management Accounting.

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Authors: Uttam Vijay, Nitin Gupta

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Due to heavy energy constraints in WSNs clustering is an efficient way to manage the energy in sensors. There are many methods already proposed in the area of clustering and research is still going on to make clustering more energy efficient. In our paper we are proposing a minimum spanning tree based clustering using divide and conquer approach. The MST based clustering was first proposed in 1970’s for large databases. Here we are taking divide and conquer approach and implementing it for wireless sensor networks with the constraints attached to the sensor networks. This Divide and conquer approach is implemented in a way that we don’t have to construct the whole MST before clustering but we just find the edge which will be the part of the MST to a corresponding graph and divide the graph in clusters there itself if that edge from the graph can be removed judging on certain constraints and hence saving lot of computation.

Keywords: Algorithm, Clustering, Edge-Weighted Graph, Weighted-LEACH.

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Authors: Nan Jiang, Jian Wang

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Random Oracle Model (ROM) is an effective method for measuring the practical security of cryptograph. In this paper, we try to use it into information hiding system (IHS). Because IHS has its own properties, the ROM must be modified if it is used into IHS. Firstly, we fully discuss why and how to modify each part of ROM respectively. The main changes include: 1) Divide the attacks that IHS may be suffered into two phases and divide the attacks of each phase into several kinds. 2) Distinguish Oracles and Black-boxes clearly. 3) Define Oracle and four Black-boxes that IHS used. 4) Propose the formalized adversary model. And 5) Give the definition of judge. Secondly, based on ROM of IHS, the security against known original cover attack (KOCA-KOCA-security) is defined. Then, we give an actual information hiding scheme and prove that it is KOCA-KOCA-secure. Finally, we conclude the paper and propose the open problems of further research.

Keywords: Attack, Information Hiding, Provable Security, Random Oracle Model.

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Authors: S. Nandagopalan, N. Pradeep

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The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.

Keywords: Active Contour, Bayesian, Echocardiographic image, Feature vector.

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Authors: A. Greco, N. Mammone, F.C. Morabito, M.Versaci

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This paper is mainly concerned with the application of a novel technique of data interpretation for classifying measurements of plasma columns in Tokamak reactors for nuclear fusion applications. The proposed method exploits several concepts derived from soft computing theory. In particular, Artificial Neural Networks and Multi-Class Support Vector Machines have been exploited to classify magnetic variables useful to determine shape and position of the plasma with a reduced computational complexity. The proposed technique is used to analyze simulated databases of plasma equilibria based on ITER geometry configuration. As well as demonstrating the successful recovery of scalar equilibrium parameters, we show that the technique can yield practical advantages compared with earlier methods.

Keywords: Tokamak, Classification, Artificial Neural Network, Support Vector Machines.

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Authors: Ahlem Fatnassi, Hamza Gharsellaoui, Sadok Bouamama

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This paper deals with the study of interest in the fields of Steganography and Steganalysis. Steganography involves hiding information in a cover media to obtain the stego media in such a way that the cover media is perceived not to have any embedded message for its unintended recipients. Steganalysis is the mechanism of detecting the presence of hidden information in the stego media and it can lead to the prevention of disastrous security incidents. In this paper, we provide a critical review of the steganalysis algorithms available to analyze the characteristics of an image stego media against the corresponding cover media and understand the process of embedding the information and its detection. We anticipate that this paper can also give a clear picture of the current trends in steganography so that we can develop and improvise appropriate steganalysis algorithms.

Keywords: Optimization, heuristics and metaheuristics algorithms, embedded systems, low-power consumption, Steganalysis Heuristic approach.

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Authors: Pratoom Rekklang

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The purposes of this study are to study political information exposure, politicians- perceptions, political attitudes and political participations among people in Bangkok Metropolitan Area. The sample consisted of 420 which were selected by using accidental sampling method. Questionnaires were administered to all of the respondents to obtain the data for this research. T-test, one-way ANOVA and Pearson-s correlation coefficient were used to analyze the data. The findings are as follows: The difference in gender, education, income and occupation has significantly effect upon political information exposures. The difference in age, income has significantly effect upon politicians- perceptions. The difference in income has significantly effect upon political attitudes. The difference in gender, income and occupation has significantly effect upon political participations. There were a significantly relations between political information exposures, political attitudes, political participations and between politicians- perceptions, political attitudes and political participations.

Keywords: Political Information Exposures, Politicians' Perceptions, Political Attitudes, Political Participations.

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Authors: Manduth Ramchander

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Evaluating expressions involving multiplication and division can give rise to the fallacy that brackets can be arbitrarily inserted into expressions involving multiplication and division. The aim of this article was to draw upon mathematical theory to prove that brackets cannot be arbitrarily inserted into expressions involving multiplication and division and in particular in expressions where division precedes multiplication. In doing so, it demonstrates that the notion that two different answers are possible, when evaluating expressions involving multiplication and division, is indeed a false one. Searches conducted in a number of scholarly databases unearthed the rules to be applied when removing brackets from expressions, which revealed that consideration needs to be given to sign changes when brackets are removed. The rule pertaining to expressions involving multiplication and division was then extended upon, in its reverse format, to prove that brackets cannot be arbitrarily inserted into expressions involving multiplication and division. The application of the rule demonstrates that an expression involving multiplication and division can have only one correct answer. It is recommended that both the rule and its reverse be included in the curriculum, preferably at the juncture when manipulation with brackets is introduced.

Keywords: Brackets, multiplication, division, operations, order.

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Authors: Chao-Linag Hsieh, Zheng-Wei Ye, Chen-Kang Huang, Yeun-Chung Lee, Chih-Hong Sun, Tzai-Hung Wen, Jehn-Yih Juang, Joe-Air Jiang

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Air pollution and climate warming become more and more intensified in many areas, especially in urban areas. Environmental parameters are critical information to air pollution and weather monitoring. Thus, it is necessary to develop a suitable air pollution and weather monitoring system for urban areas. In this study, a vehicle monitoring system (VMS) based on the IoT technique is developed. Cars are selected as the research tool because it can reach a greater number of streets to collect data. The VMS can monitor different environmental parameters, including ambient temperature and humidity, and air quality parameters, including PM2.5, NO₂, CO, and O₃. The VMS can provide other information, including GPS signals and the vibration information through driving a car on the street. Different sensor modules are used to measure the parameters and collect the measured data and transmit them to a cloud server through the LoRa protocol. A user interface is used to show the sensing data storing at the cloud server. To examine the performance of the system, a researcher drove a Nissan x-trail 1998 to the area close to the Da’an District office in Taipei to collect monitoring data. The collected data are instantly shown on the user interface. The four kinds of information are provided by the interface: GPS positions, weather parameters, vehicle information, and air quality information. With the VMS, users can obtain the information regarding air quality and weather conditions when they drive their car to an urban area. Also, government agencies can make decisions on traffic planning based on the information provided by the proposed VMS.

Keywords: Vehicle, monitoring system, LoRa, smart city.

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Authors: Ahmad T. Al-Taani, Abdullah M. AL-Issa

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In this work we propose a novel Steganographic method for hiding information within the spatial domain of the gray scale image. The proposed approach works by dividing the cover into blocks of equal sizes and then embeds the message in the edge of the block depending on the number of ones in left four bits of the pixel. The proposed approach is tested on a database consists of 100 different images. Experimental results, compared with other methods, showed that the proposed approach hide more large information and gave a good visual quality stego-image that can be seen by human eyes.

Keywords: Data Embedding, Cryptography, Watermarking, Steganography, Least Significant Bit, Information Hiding.

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Authors: Rozo D. Juan Felipe, Ramírez L. Leonardo Juan, Puerta A. Gabriel Alberto

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The telemedicine services require correct computing resource management to guarantee productivity and efficiency for medical and non-medical staff. The aim of this study was to examine web management strategies to ensure the availability of resources and services in telemedicine so as to provide medical information management with an accessible strategy. In addition, to evaluate the quality-of-service parameters, the followings were measured: delays, throughput, jitter, latency, available bandwidth, percent of access and denial of services based of web management performance map with profiles permissions and database management. Through 24 different test scenarios, the results show 100% in availability of medical information, in relation to access of medical staff to web services, and quality of service (QoS) of 99% because of network delay and performance of computer network. The findings of this study suggest that the proposed strategy of web management is an ideal solution to guarantee the availability, reliability, and accessibility of medical information. Finally, this strategy offers seven user profile used at telemedicine center of Bogota-Colombia keeping QoS parameters suitable to telemedicine services.

Keywords: Availability, medical information, QoS, strategy, telemedicine.

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Authors: Agah Tuğrul Korucu, Handan Atun

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Diversity and usefulness of information that used in education are have increased due to development of technology. Web technologies have made enormous contributions to the distance learning system especially. Mobile systems, one of the most widely used technology in distance education, made much easier to access web technologies. Not bounding by space and time, individuals have had the opportunity to access the information on web. In addition to this, the storage of educational information and resources and accessing these information and resources is crucial for both students and teachers. Because of this importance, development and dissemination of web technologies supply ease of access to information and resources are provided by web technologies. Dynamic web technologies introduced as new technologies that enable sharing and reuse of information, resource or applications via the Internet and bring websites into expandable platforms are commonly known as Web 2.0 technologies. Cloud systems are one of the dynamic web technologies that defined as a model provides approaching the demanded information independent from time and space in appropriate circumstances and developed by NIST. One of the most important advantages of cloud systems is meeting the requirements of users directly on the web regardless of hardware, software, and dealing with install. Hence, this study aims at using cloud services in education and investigating the services provided by the cloud computing. Survey method has been used as research method. In the findings of this research the fact that cloud systems are used such studies as resource sharing, collaborative work, assignment submission and feedback, developing project in the field of education, and also, it is revealed that cloud systems have plenty of significant advantages in terms of facilitating teaching activities and the interaction between teacher, student and environment.

Keywords: Cloud systems, cloud systems in education, distance learning, e-learning, integration of information technologies, online learning environment.

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Authors: Gianluigi De Mare, Pierluigi Morano, Antonio Nesticò

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Among the numerous economic evaluation techniques currently available, Multi-criteria Spatial Analysis lends itself to solving localization problems of property complexes and, in particular, production plants. The methodology involves the use of Geographical Information Systems (GIS) and the mapping overlay technique, which overlaps the different information layers of a territory in order to obtain an overview of the parameters that characterize it. This first phase is used to detect possible settlement surfaces of a new agglomeration, subsequently selected through Analytic Hierarchy Process (AHP), so as to choose the best alternative. The result ensures the synthesis of a multidimensional profile that expresses both the quantitative and qualitative effects. Each criterion can be given a different weight.

Keywords: Multi-criteria Spatial Analysis, Analytic Hierarchy Process, Geographical Information Systems, localization of industrial areas.

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Authors: Raif Parlakkaya, Huseyin Cetin, Duygu Irdiren

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By the development of World Wide Web, the usage rate of Internet has rapidly grown globally; and provided a basis for the emergence of electronic business. As well as other sectors, the banking sector has adopted the use of internet with the developments in information and communication technologies. Due to the public disclosure and transparency principle of Corporate Governance, the importance of information disclosure of banks on their web sites has increased significantly. For the purpose of this study, a Bank Disclosure Attribute Index (BDAI) in Turkey has been constructed through classifying the information disclosure on banks’ web sites into general, financial, investors and corporate governance attributes. All 47 banks in Turkish Banking System have been evaluated according to the index with the aim of providing a comparison between banks. By Chi Square Test, Pearson Correlation, T-Test, and ANOVA statistical tools, it has been concluded that the majority of banks in Turkey have shared information on their web sites adequately with respect to their total index score. Although there is a positive correlation between various types of information on banks’ web sites, there is no uniformity among them. Also, no significant difference between various types of information disclosure and bank types has been observed. Compared with the total index score averages of the five largest banks in Turkey, there are some banks that need to improve the content of their web sites.

Keywords: Banking sector, public disclosure, Turkey, web site evaluation.

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Authors: Cédric Damour, Michel Benne, Brigitte Grondin-Perez, Jean-Pierre Chabriat

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Monitoring and control of cane sugar crystallization processes depend on the stability of the supersaturation (σ ) state. The most widely used information to represent σ is the electrical conductivity κ of the solutions. Nevertheless, previous studies point out the shortcomings of this approach: κ may be regarded as inappropriate to guarantee an accurate estimation of σ in impure solutions. To improve the process control efficiency, additional information is necessary. The mass of crystals in the solution ( c m ) and the solubility (mass ratio of sugar to water / s w m m ) are relevant to complete information. Indeed, c m inherently contains information about the mass balance and / s w m m contains information about the supersaturation state of the solution. The main problem is that c m and / s w m m are not available on-line. In this paper, a model based soft-sensor is presented for a final crystallization stage (C sugar). Simulation results obtained on industrial data show the reliability of this approach, c m and the crystal content ( cc ) being estimated with a sufficient accuracy for achieving on-line monitoring in industry

Keywords: Soft-sensor, on-line monitoring, cane sugarcrystallization.

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Authors: Yan Xu, Toshihiro Nishimura

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Segmentation in ultrasound images is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, a segmentation scheme using fuzzy c-means (FCM) clustering incorporating both intensity and texture information of images is proposed to extract breast lesions in ultrasound images. Firstly, the nonlinear structure tensor, which can facilitate to refine the edges detected by intensity, is used to extract speckle texture. And then, a spatial FCM clustering is applied on the image feature space for segmentation. In the experiments with simulated and clinical ultrasound images, the spatial FCM clustering with both intensity and texture information gets more accurate results than the conventional FCM or spatial FCM without texture information.

Keywords: fuzzy c-means, spatial information, structure tensor, ultrasound image segmentation

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Authors: Bilal Alatas, Ahmet Arslan

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The main goal of data mining is to extract accurate, comprehensible and interesting knowledge from databases that may be considered as large search spaces. In this paper, a new, efficient type of Genetic Algorithm (GA) called uniform two-level GA is proposed as a search strategy to discover truly interesting, high-level prediction rules, a difficult problem and relatively little researched, rather than discovering classification knowledge as usual in the literatures. The proposed method uses the advantage of uniform population method and addresses the task of generalized rule induction that can be regarded as a generalization of the task of classification. Although the task of generalized rule induction requires a lot of computations, which is usually not satisfied with the normal algorithms, it was demonstrated that this method increased the performance of GAs and rapidly found interesting rules.

Keywords: Classification rule mining, data mining, genetic algorithms.

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Authors: S. Kannimuthu, K. Premalatha

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This paper investigates a new data mining capability that entails mining of High Utility Itemsets (HUI) in a distributed environment. Existing research in data mining deals with only presence or absence of an items and do not consider the semantic measures like weight or cost of the items. Thus, HUI mining algorithm has evolved. HUI mining is the one kind of utility mining concept, aims to identify itemsets whose utility satisfies a given threshold. Although, the approach of mining HUIs in a distributed environment and mining of the same from XML data have not explored yet. In this work, a novel approach is proposed to mine HUIs from the XML based data in a distributed environment. This work utilizes Service Oriented Computing (SOC) paradigm which provides Knowledge as a Service (KaaS). The interesting patterns are provided via the web services with the help of knowledge server to answer the queries of the consumers. The performance of the approach is evaluated on various databases using execution time and memory consumption.

Keywords: Data mining, Knowledge as a Service, service oriented computing, utility mining.

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