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An Effective QoS Based Web Service Composition Algorithm for Integration of Travel & Tourism Resources

Procedia Computer Science 2015年 48卷 541-547页

作者： R. Sethuraman T. Sasiprabha A. Sandhya Assistant Professor Faculty of Computing Sathyabama University Chennai India Prof. & Dean Sathyabama University Chennai India Assistant Professor SRR Engineering College Chennai India

Tourism is a major revenue making domain globally. Tourism is a kind of travel to obtain leisure-time, spiritual-trip, and family or job purposes, typically for a little span of duration. Here the biggest problem is lacking in obtaining the available tourism domain resources (Places to visit, Hotel, Pilgrims, and Airways etc). Webservices is playing a vital role in the software industry. Web services are the collections of software components and standards for the next generation technologies. It also supports over the internet based standard protocols such as SOAP and XML. These technology standards strongly support the multi channel resource handling scenarios. Similarly Geographic Information System (GIS) is a computerized technique intended to save, store, manipulate, explore, control, and present every kind of spatial data irrespective of various domains. In this paper we have designed the effective composition web service algorithm to integrate Multi travel and Tourism resources. The proposed algorithm integrates with GIS application to produce interactive interface for travel and Tourism Domain.

关键词： Web services GIS XML SOAP Spatial Data.

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Hybrid Intrusion Detection System for Private Cloud: A Systematic Approach

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Procedia Computer Science 2015年 48卷 325-329页

作者： Praveen Kumar Rajendran B. Muthukumar G. Nagarajan Department of Computer Science and Engineering Sathyabama University Chennai India Professor Faculty of Computing Sathyabama University Chennai India Assistant Professor Faculty of Electrical and Electronic Engineering Sathyabama University India

Cloud computing is one of the latest and an emerging area in the Information and Technology (IT) sector, which has given a different dimension to the organizations. Performance and security aspects of private cloud and widely used public cloud are the major issues which have to be addressed in Cloud computing. Intrusion is one such critical and important security problem for Cloud computing. This paper will attempt to give an overall idea about Cloud computing, Intrusion, types of Intrusion Detection Systems and earlier works done on Intrusion Detection System. The key proposal of this paper is to give an overall idea for building a Hybrid Intrusion Detection System that would detect any type of intrusion into the cloud.

关键词： Cloud computing Types of cloud Services of Cloud Issues in Cloud Intrusion Hybrid Intrusion Detection System.

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A Novel Feature Selection Technique for Improved Survivability Diagnosis of Breast Cancer

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Procedia Computer Science 2015年 50卷 16-23页

作者： S. Sasikala S. Appavu alias Balamurugan S. Geetha Research Scholar Anna university Tamil Nadu India Professor and Head K.L.N. College of Information Technology Tamil Nadu India Professor School of Computing Science and Engineering VIT University Tamil Nadu India

In this paper we propose a novel Shapely Value Embedded Genetic Algorithm, called as SVEGA that improves the breast cancer diagnosis accuracy that selects the gene subset from the high dimensional gene data. Particularly, the embedded Shapely Value includes two memetic operators namely “include” and “remove” features (or genes) to realize the genetic algorithm (GA) solution. The method is ranking the genes according to its capability to differentiate the classes. The method selects the genes that can maximize the capability to discriminate between different classes. Thus, the dimensionality of data features is reduced and the classification accuracy rate is improved. Four classifiers such as Support vector machine (SVM), Naïve Bayes (NB), K-Nearest Neighbor (KNN) and J48 are used on the breast cancer dataset from the Kent ridge biomedical repository to classify between the normal and abnormal tissues and to diagnose as benign and malignant tumours. The obtained classification accuracy demonstrates that the proposed method contributes to the superior diagnosis of breast cancer than the existing methods.

关键词： Medical Data mining Breast Cancer diagnosis Bio medical classification Feature selection Shapley values Genetic Algorithm

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Learning Energy Consumption and Demand Models through Data Mining for Reverse engineering

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Procedia engineering 2015年 118卷 1319-1324页

作者： Hariharan Naganathan Wai K. Chong Nong Ye School of Sustainable Engineering and Built Environment Arizona State University Tempe AZ United States Professor School of Computing Informatics and Decision Systems Engineering Arizona State UniversityTempeAZUnited States

The estimation of energy demand (by power plants) has traditionally relied on historical energy use data for the region(s) that a plant produces for. Regression analysis, artificial neural network and Bayesian theory are the most common approaches for analysing these data. Such data and techniques do not generate reliable results. Consequently, excess energy has to be generated to prevent blackout; causes for energy surge are not easily determined; and potential energy use reduction from energy efficiency solutions is usually not translated into actual energy use reduction. The paper highlights the weaknesses of traditional techniques, and lays out a framework to improve the prediction of energy demand by combining energy use models of equipment, physical systems and buildings, with the proposed data mining algorithms for reverse engineering. The research team first analyses data samples from large complex energy data, and then, presents a set of computationally efficient data mining algorithms for reverse engineering. In order to develop a structural system model for reverse engineering, two focus groups are developed that has direct relation with cause and effect variables. The research findings of this paper includes testing out different sets of reverse engineering algorithms, understand their output patterns and modify algorithms to elevate accuracy of the outputs.

关键词： Reverse engineering Data mining Energy consumption Statistical Analysis Supply-Demand Characteristics

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Monitoring-based analysis of agriculture in Iraq

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IOP Conference Series: Earth and Environmental Science 2016年第1期43卷

作者： O Tokareva O Pasko A Alshaibi M Mochalov Associate professor of computer engineering department candidate of technical science Tomsk Polytechnic University 30 Lenina ave. 634050Tomsk Russia Professor of Tomsk Polytechnic University doctor of agricultural science 30 Lenina ave. 634050 Tomsk Russia Master student of computing engineering department Tomsk Polytechnic University 30 Lenina ave. 634050Tomsk Russia Manager of innovation programs and projects division research department Tomsk State University 36 Lenina ave. 634050 Tomsk Russia

The paper deals with change in area and structure of Iraq agricultural lands. It revealed the main reasons for the change: crisis (war, sanctions, etc.); economic (swamp and lake drainage, melioration, etc.); weather condition. Land-use intensification as a reason for reduction of agricultural land areas was not proved. The area of cultivated lands proved to correlate significantly with the level of precipitation, wheat productivity -with the average temperature in Iraq.

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An Introduction to Verification of Visualization Techniques

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2015年

作者： Tiago Etiene Robert M. Kirby Claudio T. Silva

ISBN: (数字)9781627058346

As we increase our reliance on computer-generated information, often using it as part of our decision-making process, we must devise tools to assess the correctness of that information. Consider, for example, software embedded on vehicles, used for simulating aircraft performance, or used in medical imaging. In those cases, software correctness is of paramount importance as there"s little room for error. Software verification is one of the tools available to attain such goals. Verification is a well known and widely studied subfield of computer science and computational science and the goal is to help us increase confidence in the software implementation by verifying that the software does what it is supposed to do. The goal of this book is to introduce the reader to software verification in the context of visualization. In the same way we became more dependent on commercial software, we have also increased our reliance on visualization software. The reason is simple: visualization is the lens through which users can understand complex data, and as such it must be verified. The explosion in our ability to amass data requires tools not only to store and analyze data, but also to visualize it. This book is comprised of six chapters. After an introduction to the goals of the book, we present a brief description of both worlds of visualization (Chapter 2) and verification (Chapter 3). We then proceed to illustrate the main steps of the verification pipeline for visualization algorithms. We focus on two classic volume visualization techniques, namely, Isosurface Extraction (Chapter 4) and Direct Volume Rendering (Chapter 5). We explain how to verify implementations of those techniques and report the latest results in the field of verification of visualization techniques. The last chapter concludes the book and highlights new research topics for the future.

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Distributed search engine architecture based on topic specific searches

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AIP Conference Proceedings 2015年第1期1660卷

作者： Yousra Abudaqqa Ahmed Patel aSchool of Computer Science Centre of Software Technology and Management (SOFTAM) Faculty of Information Science and Technology (FTSM) Universiti Kebangsaan Malaysia 43600 UKM Bangi Selangor Malaysia bSchool of Computer Science Centre of Software Technology and Management (SOFTAM) Faculty of Information Science and Technology (FTSM) Universiti Kebangsaan Malaysia 43600 UKM Bangi Selangor Malaysia cVisiting Professor School of Computing and Information Systems Faculty of Science Engineering and Computing Kingston University Kingston upon Thames KT1 2EE United Kingdom

Indisputably, search engines (SEs) abound. The monumental growth of users performing online searches on the Web is a contending issue in the contemporary world nowadays. For example, there are tens of billions of searches performed everyday, which typically offer the users many irrelevant results which are time consuming and costly to the user. Based on the afore-going problem it has become a herculean task for existing Web SEs to provide complete, relevant and up-to-date information response to users’ search queries. To overcome this problem, we developed the Distributed Search Engine Architecture (DSEA), which is a new means of smart information query and retrieval of the World Wide Web (WWW). In DSEAs, multiple autonomous search engines, owned by different organizations or individuals, cooperate and act as a single search engine. This paper includes the work reported in this research focusing on development of DSEA, based on topic-specific specialised search engines. In DSEA, the results to specific queries could be provided by any of the participating search engines, for which the user is unaware of. The important design goal of using topic-specific search engines in the research is to build systems that can effectively be used by larger number of users simultaneously. Efficient and effective usage with good response is important, because it involves leveraging the vast amount of searched data from the World Wide Web, by categorising it into condensed focused topic -specific results that meet the user’s queries. This design model and the development of the DSEA adopt a Service Directory (SD) to route queries towards topic-specific document hosting SEs. It displays the most acceptable performance which is consistent with the requirements of the users. The evaluation results of the model return a very high priority score which is associated with each frequency of a keyword.

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Wind power forecasting using emotional neural networks

Wind power forecasting using emotional neural networks

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IEEE International Conference on Systems, Man and Cybernetics

作者： Ehsan Lotfi Abbas Khosravi M-R. Akbarzadeh-T Saeid Nahavandi Department of Computer Engineering Islamic Azad University Torbat-e-Jam Iran Center for Intelligence Systems Research Deakin University Geelong Australia Center of Excellence on Soft Computing and Intelligent Information Processing Ferdowsi University of Mashhad Iran Alfred Deakin Professor Deakin University Waurn Ponds Victoria Australia

Emotional neural network (ENN) is a recently developed methodology that uses simulated emotions aiding its learning process. ENN is motivated by neurophysiological knowledge of the human's emotional brain. In this paper, ENNs are developed and examined for prediction tasks. Genetic algorithm is applied for optimal tuning of crisp numerical parameters of ENN. The performance of the proposed ENN is examined using data sets for a couple of synthetic (with constant and variable noise) and real world (wind farm power generation data) case studies. A traditional artificial neural network (ANN) is also implemented for comparison purposes. Numerical results indicate the superiority of ENN over ANN in terms of accuracy and stability.

关键词： Wind power generation Forecasting Artificial neural networks Brain models Genetic algorithms Biological cells

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Role of particle stimulated nucleation in recrystallization of hot extruded Al 6061/SiC_p composites

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Transactions of Nonferrous Metals Society of China 2013年第1期23卷 53-58页

作者： C.S.RAMESH R.KESHAVAMURTHY Praveennath G.KOPPAD K.T.KASHYAP Department of Mechanical Engineering PES Institute of TechnologyBangalore 560085India Visiting Professor School of DesignEngineering and ComputingBournemouth UniversityUnited Kingdom Central Manufacturing Technology Institute Tumkur RoadBangalore 560022India

Studies on texture and microstructure evolution in hot extruded Al 6061 aluminium alloy reinforced with uncoated and nickel coated SiC p were carried out by electron backscattered diffraction *** of both the alloy and its composite with nickel coated SiC p do exhibit strong β fiber with its axis parallel to the direction of *** addition to the dominant cube texture（001） 100,fully recrystallized grains with partially equiaxed structure have been observed in the alloy reinforced with uncoated SiC *** recrystallization texture of this composite can be attributed to the particle stimulated nucleation（PSN） due to the presence of SiC p with size less than 5 μ*** these conditions,the low value of Zener-Hollomon,Z（～1012s-1） confirms that PSN is one of the dominant mechanisms for recrystallization and is governed by formation of deformation zone rather than stored energy.

关键词： metal matrix composites 6061/SiC p composite extrusion particle stimulated nucleation recrystallization stored energy

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Modeling Course Design and Delivery Processes: A Case Study in an Egyptian Higher Education Institution

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Procedia - Social and Behavioral Sciences 2013年 93卷 864-867页

作者： Noha Gamil Keith Phalp Khaled S. El-Kilany Assistant Lecturer Productivity and Quality Institute – Arab Academy for Science Technology and Maritime Transport 661 Horreya St.-Janaklis Alexandria Egypt Associate Dean-Head of Academic Group – Computing and Informatics School of Design Engineering & Computing Bournemouth University Fern Barrow Poole Dorset BH12 5BB United Kingdom Associate Professor and Chairman Department of Industrial and Management Engineering College of Engineering and Technology Arab Academy for Science Technology and Maritime Transport P.O. Box. 1029 Alexandria Egypt

In a competitive environment where academic institutions are under pressure to develop employable graduates, the quality of education has become a crucial differentiator. Hence, a major pragmatic motivation for this article was to be able to improve the quality of education: in particular, to improve the course design and delivery processes of one of the postgraduate programs within an Egyptian higher education institution. This improvement was achieved using process modeling approaches; a mixture of hard and soft modeling techniques were applied, and a case study approach was used to analyze findings both with respect to the utility of tools and the process improvement itself. Lessons learned led to suggestions for the best ways of combing approaches which included a ‘novel’ hybrid RAD-SSM model being suggested. This combined approach promises to be useful for analyzing different processes and identifying possible areas for improving educational processes.

关键词： Higher education process modeling case study hybrid model.

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