Parameter scan of an effective group difference pseudopotential using grid computing

Computational modeling in the health sciences is still very challenging and much of the success has been despite the difficulties involved in integrating all of the technologies, software, and other tools necessary to answer complex questions. Very large-scale problems are open to questions of spatio-temporal scale, and whether physico-chemical complexity is matched by biological complexity. For example, for many reasons, many large-scale biomedical computations today still tend to use rather simplified physics/chemistry compared with the state of knowledge of the actual biology/biochemistry. The ability to invoke modern grid technologies offers the ability to create new paradigms for computing, enabling access of resources which facilitate spanning the biological scale. Wibke Sudholt: She is a postdoc with J. A. McCammon and K. Baldridge at the University of California, San Diego and a fellow of the German Academic Exchange Service (DAAD). She received her diploma (Dipl. Chem.) at the University Dortmund, Germany in 1996, and her doctoral degree in 2001 (Dr. rer. nat.) at Heinrich-Heine-University Duesseldorf, Germany with Wolfgang Domcke on theoretical studies of a charge-transfer process. Her current research interests include the combination of quantum chemistry, molecular mechanics and continum electrostatics to describe chemical reactions in complex molecular systems. Kim K. Baldridge: She is a theoretical and computational chemist with expertise in the design, development, and application of computational quantum chemical methodology for understanding chemical and biochemical reaction processes of broad interest. Efforts include development of computational tools and associated grid technologies for the broader scientific community. She is a Fellow of the APS and AAAS, and was the 2000 Agnes Fay Morgan Awardee for Research Achievement in Chemistry. She is the Program Director for Integrative Computational Sciences at SDSC, where she has worked since 1989, and additionally holds an adjunct professorship at UCSD. David Abramson: He is currently a professor of Computer Science in the School of Computer Science and Software Engineering (CSSE) at Monash University, Australia. He is a project leader in the Co-operative Research Centre for Distributed Systems Nimrod Project and Chief Investigator on two ARC funded research projects. He is a co-founder of Active Tools P/L with Dr. Rok Sosic, established to commercialize the Nimrod project, and Guardsoft, focused on commercializing the Guard project. Abramson’s current interests are in high performance computer systems design and software engineering tools for programming parallel, distributed supercomputers. Colin Enticott: He completed a BComp (Hons) degree mid. 2002 at Monash University, Australia. His project, done under the supervision of Professor David Abramson, “The Multi Site EnFuzion Client” dealt in the area of cluster-of-clusters computing that has lead him into Grid computing. Currently employed by DSTC (Distributed Systems Technology Centre, Melbourne, Australia) working on the user front-end of Nimrod (the Nimrod Portal) and cluster implementations. Slavisa Garic: He completed Bachelor of Computer Science (Hons) degree at Monash University, Australia in November 2001. His project, “Suburban Area Networks: Security” involved working on security aspects of wireless community and suburban networks. The beginning of year 2002, he joined Distributed Systems Technology Centre, Melbourne Australia, where he currently works as a core Nimrod/G developer.     

Tradeoff and Sensitivity Analysis in Software Architecture Evaluation Using Analytic Hierarchy Process

Software architecture evaluation involves evaluating different architecture design alternatives against multiple quality-attributes. These attributes typically have intrinsic conflicts and must be considered simultaneously in order to reach a final design decision. AHP (Analytic Hierarchy Process), an important decision making technique, has been leveraged to resolve such conflicts. AHP can help provide an overall ranking of design alternatives. However it lacks the capability to explicitly identify the exact tradeoffs being made and the relative size of these tradeoffs. Moreover, the ranking produced can be sensitive such that the smallest change in intermediate priority weights can alter the final order of design alternatives. In this paper, we propose several in-depth analysis techniques applicable to AHP to identify critical tradeoffs and sensitive points in the decision process. We apply our method to an example of a real-world distributed architecture presented in the literature. The results are promising in that they make important decision consequences explicit in terms of key design tradeoffs and the architecture's capability to handle future quality attribute changes. These expose critical decisions which are otherwise too subtle to be detected in standard AHP results. Liming Zhu is a PHD candidate in the School of Computer Science and Engineering at University of New South Wales. He is also a member of the Empirical Software Engineering Group at National ICT Australia (NICTA). He obtained his BSc from Dalian University of Technology in China. After moving to Australia, he obtained his MSc in computer science from University of New South Wales. His principle research interests include software architecture evaluation and empirical software engineering. Aybüke Aurum is a senior lecturer at the School of Information Systems, Technology and Management, University of New South Wales. She received her BSc and MSc in geological engineering, and MEngSc and PhD in computer science. She also works as a visiting researcher in National ICT, Australia (NICTA). Dr. Aurum is one of the editors of “Managing Software Engineering Knowledge”, “Engineering and Managing Software Requirements” and “Value-Based Software Engineering” books. Her research interests include management of software development process, software inspection, requirements engineering, decision making and knowledge management in software development. She is on the editorial boards of Requirements Engineering Journal and Asian Academy Journal of Management. Ian Gorton is a Senior Researcher at National ICT Australia. Until Match 2004 he was Chief Architect in Information Sciences and Engineering at the US Department of Energy's Pacific Northwest National Laboratory. Previously he has worked at Microsoft and IBM, as well as in other research positions. His interests include software architectures, particularly those for large-scale, high-performance information systems that use commercial off-the-shelf (COTS) middleware technologies. He received a PhD in Computer Science from Sheffield Hallam University. Dr. Ross Jeffery is Professor of Software Engineering in the School of Computer Science and Engineering at UNSW and Program Leader in Empirical Software Engineering in National ICT Australia Ltd. (NICTA). His current research interests are in software engineering process and product modeling and improvement, electronic process guides and software knowledge management, software quality, software metrics, software technical and management reviews, and software resource modeling and estimation. His research has involved over fifty government and industry organizations over a period of 15 years and has been funded from industry, government and universities. He has co-authored four books and over one hundred and twenty research papers. He has served on the editorial board of the IEEE Transactions on Software Engineering, and the Wiley International Series in Information Systems and he is Associate Editor of the Journal of Empirical Software Engineering. He is a founding member of the International Software Engineering Research Network (ISERN). He was elected Fellow of the Australian Computer Society for his contribution to software engineering research.     

STAMP: A Model for Generating Adaptable Multimedia Presentations

The STAMP model addresses the dynamic generation of multimedia presentations in the domain of Multimedia Web-based Information Systems. STAMP allows the presentation of multimedia data obtained from XML compatible data sources by means of query. Assuming that the size and the nature of the elements of information provided by a data source is not known a priori, STAMP proposes templates which describe the spatial, temporal, navigational structuration of multimedia presentations whose content varies. The instantiation of a template is done with respect to the set of spatial and temporal constraints associated with the delivery context. A set of adaptations preserving the initial intention of the presentation is proposed.Ioan Marius Bilasco is a Ph.D. student at the University Joseph Fourier in Grenoble, France, since 2003. He received his BS degree in Computer Science form the University Babes Bolyai in Cluj-Napoca, Romania and his MS degree in Computer Science from the University Joseph Fourier in Grenoble, France. He joined the LSR-IMAG Laboratory in Grenoble in 2001. His research interests include adaptability in Web-based Information Systems, 3D multimedia data modelling and mobile communications.Jérôme Gensel is an Assistant Professor at the University Pierre Mendès France in Grenoble, France, since 1996. He received his Ph.D. in 1995 from the University of Grenoble for his work on Constraint Programming and Knowledge Representation in the Sherpa project at the French National Institute of Computer Sciences and Automatics (INRIA). He joined the LSR-IMAG Laboratory in Grenoble in 2001. His research interests include adaptability and cooperation in Web-based Information Systems, multimedia data (especially video) modeling, semi-structured and object-based knowledge representation and constraint programming.Marlène Villanova-Oliver is an Assistant Professor at the University Pierre Mendès France in Grenoble, France, since 2003. In 1999, she received her MS degree in Computer Science from the University Joseph Fourier of Grenoble and the European Diploma of 3rd cycle in Management and Technology of Information Systems (MATIS). She received her Ph.D. in 2002 from the National Polytechnic Institute of Grenoble (INPG). She is a member of the LSR-IMAG Laboratory in Grenoble since 1998. Her research interests include adaptability in Web-based Information Systems, user modeling, adaptable Web Services.     

Public opinion channel for communities in the information age

In this paper, we propose as a new challenge a public opinion channel which can provide a novel communication medium for sharing and exchanging opinions in a community. Rather than simply developing a means of investigating public opinion, we aim at an active medium that can facilitate mutual understanding, discussion, and public opinion formation. First, we elaborate the idea of public opinion channels and identify key issues. Second, we describe our first step towards the goal using the talking virtualized egos metaphor. Finally, we discuss a research agenda towards the goal. Toyoaki Nishida, Dr.Eng.: He is a professor of Department of Information and Communication Engineering, School of Engineering, The University of Tokyo. He received the B.E., the M.E., and the Doctor of Engineering degrees from Kyoto University in 1977, 1979, and 1984 respectively. His research centers on artificial intelligence in general. His current research focuses on community computing and support systems, including knowledge sharing, knowledge media, and agent technology. He has been leading the Breakthrough 21 Nishida Project, sponsored by Ministry of Posts and Telecommunications, Japan, aiming at understanding and assisting networked communities. Since 1997, he is a trustee for JSAI (Japanese Society for Artificial Intelligence), and serves as the program chair of 1999 JSAI Annual Convention. He is an area editor (intelligent systems) of New Generation Computing and an editor of Autonomous Agents and Multiagent Systems. Nobuhiko Fujihara, Ph.D.: He is a fellow of Breakthrough 21 Nishida project, Communications Research Laboratory sponsored by Ministry of Posts and Telecommunications, Japan. He received the B.E., the M.E., and the Ph.D. in Human Sciences degrees from Osaka University in 1992, 1994, and 1998 respectively. He has a cognitive psychological background. His current research focuses on: (1) cognitive psychological analysis of human behavior in a networked community, (2) investigation of information comprehension process, (3) assessment and proposition of communication tools in networking society. Shintaro Azechi: He is a fellow of Breakthrough 21 Nishida project, Communications Research Laboratory sponsored by Ministry of Posts and Telecommunications, Japan. He received the B.E. and the M.E. of Human Sciences degrees from Osaka University in 1994 and 1996 respectively. He is a Doctoral Candidate of Graduate School of Human Sciences, Osaka University. His current researches focus on (1) human behavior in networking community (2) social infomation process in human mind (3) development of acessment technique for communication tools in networkingsociety. His approach is from social psychological view. Kaoru Sumi, Dr.Eng.: She is a Researcher of Breakthrough 21 Nishida Project. She received her Bachelor of Science at School of Physics, Science University of Tokyo. She received her Master of Systems Management at Graduate School of Systems Management, The university of Tsukuba. She received her Doctor of engineering at Graduate School of Engineering, The University of Tokyo. Her research interests include knowledge-based systems, creativity supporting systems, and their applications for facilitating human collaboration. She is a member of the Information Processing Society of Japan (IPSJ), the Japanese Society for Artificial Intelligence (JSAI). Hiroyuki Yano, Dr.Eng.: He is a senior research official of Kansai Advanced Research Center, Communications Research Laboratory, Ministry of Posts and Telecommunications. He received the B.E., the M.E., and the Doctor of Engineering degrees from Tohoku University in 1986, 1988, and 1993 respectively. His interests of research include cognitive mechanism of human communications. His current research focuses on discourse structure, human interface, and dialogue systems for human natural dialogues. He is a member of the Japanese Society for Artificial Intelligence, the Association for Natural Language Processing, and the Japanese Cognitive Science Society. Takashi Hirata: He is a doctor course student in Graduate School of Information Scienc at Nara Institute of Science and Technology (NAIST). He received a master of engineering from NAIST in 1998. His research interest is knowledge media and knowledge sharing. He is a member of Information Processing Society of Japan (IPSJ), Japan Association for Artificial Intelligence (JSAI) and The Institute of Systems, Control and Information Engineers (ISCIE).     

Mining user access patterns with traversal constraint for predicting web page requests

The recent increase in HyperText Transfer Protocol (HTTP) traffic on the World Wide Web (WWW) has generated an enormous amount of log records on Web server databases. Applying Web mining techniques on these server log records can discover potentially useful patterns and reveal user access behaviors on the Web site. In this paper, we propose a new approach for mining user access patterns for predicting Web page requests, which consists of two steps. First, the Minimum Reaching Distance (MRD) algorithm is applied to find the distances between the Web pages. Second, the association rule mining technique is applied to form a set of predictive rules, and the MRD information is used to prune the results from the association rule mining process. Experimental results from a real Web data set show that our approach improved the performance over the existing Markov-model approach in precision, recall, and the reduction of user browsing time. Mei-Ling Shyu received her Ph.D. degree from the School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN in 1999, and three Master's degrees from Computer Science, Electrical Engineering, and Restaurant, Hotel, Institutional, and Tourism Management from Purdue University. She has been an Associate Professor in the Department of Electrical and Computer Engineering (ECE) at the University of Miami (UM), Coral Gables, FL, since June 2005, Prior to that, she was an Assistant Professor in ECE at UM dating from January 2000. Her research interests include data mining, multimedia database systems, multimedia networking, database systems, and security. She has authored and co-authored more than 120 technical papers published in various prestigious journals, refereed conference/symposium/workshop proceedings, and book chapters. She is/was the guest editor of several journal special issues. Choochart Haruechaiyasak received his Ph.D. degree from the Department of Electrical and Computer Engineering, University of Miami, in 2003 with the Outstanding Departmental Graduating Student award from the College of Engineering. After receiving his degree, he has joined the National Electronics and Computer Technology Center (NECTEC), located in Thailand Science Park, as a researcher in Information Research and Development Division (RDI). His current research interests include data/ text/ Web mining, Natural Language Processing, Information Retrieval, Search Engines, and Recommender Systems. He is currently leading a small group of researchers and programmer to develop an open-source search engine for Thai language. One of his objectives is to promote the use of data mining technology and other advanced applications in Information Technology in Thailand. He is also a visiting lecturer for Data Mining, Artificial Intelligence and Decision Support Systems courses in many universities in Thailand. Shu-Ching Chen received his Ph.D. from the School of Electrical and Computer Engineering at Purdue University, West Lafayette, IN, USA in December, 1998. He also received Master's degrees in Computer Science, Electrical Engineering, and Civil Engineering from Purdue University. He has been an Associate Professor in the School of Computing and Information Sciences (SCIS), Florida International University (FIU) since August, 2004. Prior to that, he was an Assistant Professor in SCIS at FIU dating from August, 1999. His main research interests include distributed multimedia database systems and multimedia data mining. Dr. Chen has authored and co-authored more than 140 research papers in journals, refereed conference/symposium/workshop proceedings, and book chapters. In 2005, he was awarded the IEEE Systems, Man, and Cybernetics Society's Outstanding Contribution Award. He was also awarded a University Outstanding Faculty Research Award from FIU in 2004, Outstanding Faculty Service Award from SCIS in 2004 and Outstanding Faculty Research Award from SCIS in 2002.     

An in-depth analysis of information markets with aggregate uncertainty

The novel idea of setting up Internet-based virtual markets, information markets, to aggregate dispersed information and predict outcomes of uncertain future events has empirically found its way into many domains. But the theoretical examination of information markets has lagged relative to their implementation and use. This paper proposes a simple theoretical model of information markets to understand their information dynamics. We investigate and provide initial answers to a series of research questions that are important to understanding how information markets work, which are: (1) Does an information market converge to a consensus equilibrium? (2) If yes, how fast is the convergence process? (3) What is the best possible equilibrium of an information market? and (4) Is an information market guaranteed to converge to the best possible equilibrium? The authors acknowledge the support of the eBusiness Research Center at the Pennsylvania State University. Yiling Chen is a postdoctoral research scientist at Yahoo! Research, New York. She received her Bachelor of Economics degree in Commodity Science from Renmin University of China, in 1996, and her Master of Economics degree in Finance from Tsinghua University, China, in 1999. She worked for PriceWaterhouse Coopers China as a professional auditor from August 1999 to June 2000. From August 2000 to July 2001, she attended Iowa State University, Ames, IA, as a Ph.D. student in economics. She obtained her Ph.D. in Information Sciences and Technology from the Pennsylvania State University, University Park, PA, in 2005. Her research interests lie on the boarder of computer science, economics, and business, including information markets, auction theory, and machine learning. Tracy Mullen is an assistant professor of information sciences and technology at the Pennsylvania State University, University Park, PA. She has previously worked at Lockheed Martin, Bellcore, and NEC Research. She received her PhD in Computer Science from University of Michigan. Her research interests include information markets, multiagent systems, ecommerce, market-based resource allocation for sensor management, and supply chain simulations using intelligent agents. Her research papers have been published in Decision Support Systems, Electronic Commerce Research, IEEE Computer, ACM Transactions on Internet Technology, Mathematics and Computers in Simulation, and Operating Systems Review, among others. Chao-Hsien Chu is an associate professor of information sciences and technology and the executive director of the Center for Information Assurance at the Pennsylvania State University, University Park, PA. He was previously on the faculty at Iowa State University, Iowa and Baruch College, New York and a visiting professor at University of Tsukuba (Japan) and Hebei University of Technology (China). He is currently on leaves to the Singapore Management University (Singapore) (2005–2006). Dr. Chu received a Ph.D. in Business Administration from Penn State. His current research interests are in communication networks design, information assurance and security (especially in wireless security, intrusion detection, and cyber forensics), intelligent technologies (fuzzy logic, neural network, genetic algorithms, etc.) for data mining (e.g., bioinformatics, privacy preserving) and supply chains integration. His research papers have been published in Decision Sciences, IEEE Transactions on Evolutionary Computation, IIE Transactions, Decision Support Systems, European Journal of Operational Research, Electronic Commerce Research, Expert Systems with Applications, International Journal of Mobile Communications, Journal of Operations Management, International Journal of Production Research, among others. He is currently on the editorial review board for a number of journals.     

Optimum design of electronic communities as economic entities

Electronic communities can be designed to organize consumers, to pool their purchasing power, and to guide their purchasing decisions. Such commercial electronic communities have the potential to facilitate the creation of novel marketplaces, and even radically change the buyer-seller interaction, as physical communities did throughout the history. Commercial electronic communities are groups of consumers that participate in the marketplace as a single unit. In addition to bargaining power gained from such bundling, such communities can expand markets by reducing market uncertainty, and they have the potential to drastically reduce consumers’ transaction costs, by facilitating group transactions and bulk purchasing. Communities are characterized by their size, their pricing strategy, and their membership characteristics. Analytical models and numeric analysis is utilized to compute the optimum size of a community for given market characteristics. Two major community pricing strategies are analyzed to improve the community design, and the conditions are derived where one dominates the other. Finally, market segmentation techniques are introduced to control the membership characteristics of the community to further improve the design. Levent V. Orman is a professor of Information Systems at Cornell University, Graduate School of Management. He received a Ph.D. degree from Northwestern University. He has taught courses and written articles on electronic commerce, database management, decision support systems, and expert systems. His recent articles appeared in Journal of Information Technology and Management, Journal of MIS, Acta Informatica, and IEEE Transactions on Knowledge and Data Engineering. He is the associate editor of the Journal of Database Management, and serves on the editorial board of the Journal of Information Technology and Management.     

Evie - A developer toolkit for encoding service interaction patterns

Facilitation of collaborative business processes across organizational and infrastructural boundaries continues to present challenges to enterprise software developers. One of the greatest difficulties in this respect is achieving a streamlined pipeline from business modeling to execution infrastructures. In this paper we present Evie - an approach for rapid design and deployment of event driven collaborative processes based on significant language extensions to Java that are characterized by abstract and succinct constructs. The focus of this paper is to provide proof of concept of Evie’s expressability using a recent benchmark known as service interaction patterns. While the patterns encapsulate the breadth of required business process semantics the Evie language delivers a rapid means of encoding them at an abstract level, and subsequently compiling and executing them to create a fully fledged Java-based execution environment.

A Semantic Web data retrieval implementation with an adaptive model for supporting agent decision structures

This paper proposes an adaptive learning approach that yields decision models that can be applied by a transactions agent. This model can learn effectively with a variety of data distributions. This research uses the Semantic Web as a data access approach. The Semantic Web is a method that sellers can use to publish semantically meaningful information on Websites so automated applications can reliably access that information. We implemented a Semantic Web composed of 30 vendors’ Web pages and a spider to search those pages to obtain product and vendor information. This information was used to train a learning agent, which then provided a decision model to a transaction agent. James Hansen is J. Owen Cherrington Professor in the Information Systems Department of the Marriott School of Management at Brigham Young University. He is an associate editor for IEEE Intelligent Systems and Information Systems Frontiers. His research is in machine learning and planning as model checking. James B. McDonald is Professor of Economics at Brigham Young University. His research interests are in econometrics and quantitative methods. He has recently published in Econometrica, Journal of the American Statistical Association, Management Science, and Journal of Business Conan C. Albrecht is a professor of Information Systems at Brigham Young University. He teaches classes in enterprise development, middleware, and business programming. Conan researches computer-based fraud detection techniques, ecommerce platforms, and online group dynamics. He has published articles on fraud detection and information theory in The Journal of Forensic Accounting, The Journal of Accounting, The Communications of the ACM, Decision Support Systems, Information and Management, and other academic and professional outlets. Conan is currently working on an open source framework for computer-based fraud detection. The core of this research is detectlets, which encode background and detection information for specific fraud schemes. He is researching with the United Nations and the World Bank to use detectlets to prevent and detect fraud in third world countries. In the next few years, he hopes the system will serve as the foundation of a large, online repository of detectlets about all types of fraud. Douglas L. Dean is an Associate Professor at the Marriott School of Management at Brigham Young University. He is also research coordinator for the Rollins Center for E-business. He received his Ph.D. in MIS from the University of Arizona in 1995. Dr. Dean’s research interests include electronic commerce technology and strategy, online communities, requirements analysis, and collaborative tools and methods. His work has been published in Management Science, Journal of Management Information Systems, Information and Management, The DATA BASE for Advances in Information Systems, Communications of the AIS, Expert Systems with Applications, Group Decision and Negotiation, and IEEE Transactions on Systems, Man, and Cybernetics. Bonnie Brinton Anderson is the LeAnn Albrecht Fellow and an Assistant Professor in the Information Systems Department of the Marriott School at Brigham Young University (Provo, UT). She received her Ph.D. from Carnegie Mellon University. Dr. Anderson has published in Decision Support Systems; IEEE Transactions on Systems, Man, and Cybernetics; Communications of the ACM; Journal of Accountancy, among others. She researches in the areas of knowledge management, information systems security, and intelligent agents.     

Multi-objective optimisation of bijective s-boxes

In this paper we investigate the heuristic construction of bijective s-boxes that satisfy a wide range of cryptographic criteria including algebraic complexity, high nonlinearity, low autocorrelation and have none of the known weaknesses including linear structures, fixed points or linear redundancy. We demonstrate that the power mappings can be evolved (by iterated mutation operators alone) to generate bijective s-boxes with the best known tradeoffs among the considered criteria. The s-boxes found are suitable for use directly in modern encryption algorithms. Joanne Fuller, Ph.D.: She is a research associate at the Information Security Institute of Queensland University of Technology in Brisbane, Australia. She received her Ph.D. from out in 2004. William Millan, Ph.D.: He is a postdoctoral research fellow at the Information Security Institute of Queensland University of Technology in Brisbane, Australia. He pioneered the use of Evolutionary Computation techniques to develop new cryptographic primitives, notably new Boolean functions and S-boxes for block and stream ciphers, and has published many papers in this area. Ed Dawson, Ph.D.: He is the Director of the Information Security Institute of Queensland University of Technology in Brisbane, Australia. He has published more than 200 papers in Crypto conferences and Journals. He has served as Program Committee Member for more than 50 International Conferences in Cryptology and Network Security. He is currently a member of the Board of Directors of International Association for Cryptologic Research (IACR).     

Mobile communities: How viable are their business models? An exemplary investigation of the leisure industry

Communities (especially Virtual Communities) of Interest have been the focus of substantial discussion in academic literature. This paper addresses Communities of Interest within the leisure industry and discusses possible business models for the parties operating the platform. The described community platform is an innovative value added service concept for a mobile coordination support for individuals—A Mobile Community Support System. In this paper we extend the discussion about mobile communities to hybrid communities. The communities are hybrid in two ways: they use two different access channels, the Web and mobile devices, and they are built on real-world leisure communities that constitute themselves in the form of buddy lists in the virtual world of an ICT supported platform. We briefly depict the state of the art of IT in the leisure industry and describe the empirical aspects of the project objectives of the MCOR (Mobile Community Online Reservation) system. We conclude with some final remarks about design considerations and a blueprint for future research. Felix Hampe holds a chair for Corporate Communication Systems and is Director of the Institute for IS Research at the Faculty of Informatics of the University of Koblenz-Landau in Germany. He studied at the Free University of Berlin and worked later for the University of Bielefeld and the Philipps-University of Marburg prior to his appointment to Koblenz. In 2004/2005, he spent one year as a visiting professor at the University of South Australia, School of Computer and Information Systems. Beside his research interest in application aspects of communication systems, Professor Hampe started very early research in the area of mobile applications and especially mobile commerce. He was cofounder and board member of the Mobile Application Research Center (MARC), a German network for joint research on mobile business. Professor Hampe authored several international conference articles in the area and served for many international conferences.     

Evaluation of local dependencies of images wavelet decomposition

An approach to identifying local area structure that is used in the spatial interaction models adapted to the image characteristic properties using mutual information criterion is reviewed in this article. Experimental results that demonstrate the value of using the represented method are shown. The text was submitted by authors in English. Arcady Lvovich Zhiznyakov. Candidate of engineering science. Docent of the Department of Information Systems at the Murom Institute of Vladimir State University. The field of science interests is digital image processing and analysis. He is the author of more than 150 science publications. Vasilii Evgenevich Gai. A postgraduate student of the Department of Information Systems at the Murom Institute of Vladimir State University. The field of science interests is digital image processing and analysis. He is the author of about 40 science publications. Sultan Sadykovich Sadykov. Doctor of engineering science, professor. Professor of the Department of Information Systems at the Murom Institute of Vladimir State University. The field of science interests is digital image processing and analysis. He is the author of more than 200 science publications.     

Social influence process in the acceptance of a virtual community service

This study investigates the effect of subjective norms, tendency to social comparison, and social identity on behavioral intention to use an Avatar service. Use of a virtual community service can be regarded as social behavior or a behavior affected by social factors. This study relies on the link between subjective norms and behavioral intention in the theory of reasoned action, social identity theory, and social comparison literature. The proposed model was tested using survey data with the results lending support for the proposed model. The implications from this study are expected to contribute to the literature by shedding light on the social influence process in two ways. First, this study unveils how social factors including subjective norms, social identity, and tendency to social comparison affect behavioral intention to use a specific service from virtual communities. Second, this study will aid managers and academics to further understand the social nature of customer behavior with regard to using virtual community services and thus provide insight for the development of technology driven e-commerce. Jaeki Song is Assistant Professor of Information Systems and Quantitative Sciences at the Rawls College of Business Administration at Texas Tech University. His research interests include electronic commerce, web design, information systems strategy, and technology adoption. His work has appeared in Management Science, IEEE Transactions on Professional Communication, Information & Management, and International Journal of Information Management. He also has published book chapters on Global Information Technologies and Electronic Commerce. Yong Jin Kim is Assistant Professor of Management Information Systems at the School of Management at the State University of New York at Binghamton. He holds a Ph.D. in MIS from the State University of New York at Buffalo. He has 10 year industry experience. His research interests are in knowledge management, technological innovation, IS success, e-business, and information technology valuation. He has published papers in outlets such as MIS Quarterly, Communications of the ACM, Decision Support Systems, International Journal of Information Management, JITTA, and Knowledge and Process Management. He also has published book chapters on IS Success and e-learning.     

A note on consistency in asynchronous multicaches

Summary This note examines and contrasts the choice of finite versus infinite histories as the framework for analysing the behaviour of an asynchronous multicache scheme. Mike Livesey is currently a Lecturer in Computer Science at the University of St. Andrews, Scotland. His research interests are centred on distributed systems, particularly the specification and verification of distributed protocols. Dr. Livesey received a BA in mathematics from Cambridge University in 1970, an MSc in computer science from Essex University in 1973 and a PhD in computer science form St. Andrews University in 1987. He has also taught at other universities in Britain and New Zealand, and been employed by Marconi-Elliott Computer Systems Ltd.     

A framework for designing the enterprise-wide e-commerce portal for evolving organizations

The number of organizations offering e-commerce solutions is growing exponentially each year. Without a doubt, e-commerce will no longer be a choice for organizations rather it will be a competitive necessity to ensure business prosperity. Integral to the success of e-commerce is having good e-commerce software that can enable organizations to offer online products and services as well as integrate their business processes and supply chains within and with their collaborators or partners in a perfect, seamless manner. One of the main obstacles for adoption of e-commerce faced by many organizations; however, has been the lack of such proper integrated e-commerce software. There have been few ready-made software solutions offered by vendors, which can be customized for organizations’ business models and processes, and these solutions are based on “piece meal” approaches and thus lack much of the enterprise capabilities organizations need to adopt. In this paper, we suggest a framework for developing an enterprise-wide integrated e-commerce portal for evolving organizations. Such a framework will help any organization to design a distributed, extensible, cross-platform, collaborative and integrated e-commerce portal. Sushil K. Sharma is currently an Associate Professor in the Department of Information Systems and Operations Management at Ball State University, Muncie, Indiana. Prior to joining the faculty at Ball State, Dr. Sharma held the Associate Professor position at the Indian Institute of Management in Lucknow (India) and Visiting Research Associate Professor at the Department of Management Science at the University of Waterloo, Canada. He is of two text books (Programming in C, and Understanding Unix), and Co-editor of four edited books. Dr. Sharma has published more than 100 refereed research papers in many peer-reviewed national and international journals and conference proceedings. His contributions have appeared in journals such as; International Journal of Information Management, International Journal of Healthcare Technology and Management (IJHTM), Electronic Government Journal, Journal of Electronic Commerce in Organizations (JECO), Journal of Global Information Technology Management (JGITM), The Journal of Computer Information Systems (CIS), Journal of Logistics Information Management (JLIM), and International Journal of Management. He currently serves as an Associate Editor for International Journal of Cases on Electronic Commerce (IJCEC) and is on Editorial board for the International Journal of Electronic Finance (IJEF) and the Journal of Electronic Commerce in Organizations (JECO). In the past, he has also been a guest editor for special issue of Global Journal of Flexible Systems Management and Journal of Global Information Technology Management (JGITM). Dr. Sharma’s primary teaching and research interests are in e-commerce, computer and network security, ERP Systems, database management systems, and knowledge management. Jatinder (Jeet) N. D. Gupta is currently Eminent Scholar of Management of Technology, Professor of Management Information Systems, Industrial and Systems Engineering and Engineering Management at the University of Alabama in Huntsville, Huntsville, Alabama. Most recently, he was Professor of Management, Information and Communication Sciences, and Industry and Technology at Ball State University, Muncie, Indiana. He holds a PhD in Industrial Engineering (with specialization in Production Management and Information Systems) from Texas Tech University. Co-author of a textbook in Operations Research, Dr. Gupta serves on the editorial boards of several national and international journals. Recipient of the Outstanding Faculty and Outstanding Researcher awards from Ball State University, he has published numerous papers in such journals as Journal of Management Information Systems, International Journal of Information Management, Operations Research, INFORMS Journal of Computing, Annals of Operations Research, and Mathematics of Operations Research. More recently, he served as a co-editor of several special issues including the Neural Networks in Business of Computers and Operations Research and books that included Decision Making Support Systems: Achievements and Challenges for the New Decade and Creating Knowledge-based Healthcare Organizations published by Idea Group Publishing. He is also the coeditor of the book: Managing E-Business published by Heidelberg Press, Heidelberg, Australia. His current research interests include e-Commerce, Supply Chain Management, Information and Decision Technologies, Scheduling, Planning and Control, Organizational Learning and Effectiveness, Systems Education, Knowledge Management, Information Security, and Enterprise Integration. Dr. Gupta has held elected and appointed positions in several academic and professional societies including the Association for Information Systems, Production and Operations Management Society (POMS), the Decision Sciences Institute (DSI), and the Information Resources Management Association (IRMA). Nilmini Wickramasinghe, PhD, MBA, GradDipMgtSt, BSc. Amus.A (piano) Amus.A(violin): Currently, Dr Wickramasinghe is an associate professor and the associate director of the Center for the Management of Medical Technologies at Stuart Graduate School of Business, Illinois Institute of Technology. Her teaching interests cover the areas of knowledge management as well as e-commerce and m-commerce, IT for competitive advantage, organizational impacts of technology and healthcare issues. In addition, Dr Wickramasinghe teaches and presents regularly in many universities in Europe and Australiasia. She is currently carrying out research and is well published having written numerous book chapters, refereed journal articles and some books in the areas of management of technology, in the field of healthcare as well as focusing on IS issues especially as they relate to knowledge work and e-business. Dr Wickramasinghe is honored to be able to represent the United States of America for the Health Care Technology Management (HCTM) Association (URL http://www.hctm.net/events/2005/conference_2005.html).     

Splitting methods for decision tree induction: An exploration of the relative performance of two entropy-based families

Decision tree (DT) induction is among the more popular of the data mining techniques. An important component of DT induction algorithms is the splitting method, with the most commonly used method being based on the Conditional Entropy (CE) family. However, it is well known that there is no single splitting method that will give the best performance for all problem instances. In this paper we explore the relative performance of the Conditional Entropy family and another family that is based on the Class-Attribute Mutual Information (CAMI) measure. Our results suggest that while some datasets are insensitive to the choice of splitting methods, other datasets are very sensitive to the choice of splitting methods. For example, some of the CAMI family methods may be more appropriate than the popular Gain Ratio (GR) method for datasets which have nominal predictor attributes, and are competitive with the GR method for those datasets where all predictor attributes are numeric. Given that it is never known beforehand which splitting method will lead to the best DT for a given dataset, and given the relatively good performance of the CAMI methods, it seems appropriate to suggest that splitting methods from the CAMI family should be included in data mining toolsets. Kweku-Mauta Osei-Bryson is Professor of Information Systems at Virginia Commonwealth University, where he also served as the Coordinator of the Ph.D. program in Information Systems during 2001–2003. Previously he was Professor of Information Systems and Decision Analysis in the School of Business at Howard University, Washington, DC, U.S.A. He has also worked as an Information Systems practitioner in both industry and government. He holds a Ph.D. in Applied Mathematics (Management Science & Information Systems) from the University of Maryland at College Park, a M.S. in Systems Engineering from Howard University, and a B.Sc. in Natural Sciences from the University of the West Indies at Mona. He currently does research in various areas including: Data Mining, Expert Systems, Decision Support Systems, Group Support Systems, Information Systems Outsourcing, Multi-Criteria Decision Analysis. His papers have been published in various journals including: Information & Management, Information Systems Journal, Information Systems Frontiers, Business Process Management Journal, International Journal of Intelligent Systems, IEEE Transactions on Knowledge & Data Engineering, Data & Knowledge Engineering, Information & Software Technology, Decision Support Systems, Information Processing and Management, Computers & Operations Research, European Journal of Operational Research, Journal of the Operational Research Society, Journal of the Association for Information Systems, Journal of Multi-Criteria Decision Analysis, Applications of Management Science. Currently he serves an Associate Editor of the INFORMS Journal on Computing, and is a member of the Editorial Board of the Computers & Operations Research journal. Kendall E. Giles received the BS degree in Electrical Engineering from Virginia Tech in 1991, the MS degree in Electrical Engineering from Purdue University in 1993, the MS degree in Information Systems from Virginia Commonwealth University in 2002, and the MS degree in Computer Science from Johns Hopkins University in 2004. Currently he is a PhD student (ABD) in Computer Science at Johns Hopkins, and is a Research Assistant in the Applied Mathematics and Statistics department. He has over 15 years of work experience in industry, government, and academic institutions. His research interests can be partially summarized by the following keywords: network security, mathematical modeling, pattern classification, and high dimensional data analysis.     

An attack-norm separation approach for detecting cyber attacks

The two existing approaches to detecting cyber attacks on computers and networks, signature recognition and anomaly detection, have shortcomings related to the accuracy and efficiency of detection. This paper describes a new approach to cyber attack (intrusion) detection that aims to overcome these shortcomings through several innovations. We call our approach attack-norm separation. The attack-norm separation approach engages in the scientific discovery of data, features and characteristics for cyber signal (attack data) and noise (normal data). We use attack profiling and analytical discovery techniques to generalize the data, features and characteristics that exist in cyber attack and norm data. We also leverage well-established signal detection models in the physical space (e.g., radar signal detection), and verify them in the cyberspace. With this foundation of information, we build attack-norm separation models that incorporate both attack and norm characteristics. This enables us to take the least amount of relevant data necessary to achieve detection accuracy and efficiency. The attack-norm separation approach considers not only activity data, but also state and performance data along the cause-effect chains of cyber attacks on computers and networks. This enables us to achieve some detection adequacy lacking in existing intrusion detection systems. Nong Ye is a Professor of Industrial Engineering and an Affiliated Professor of Computer Science and Engineering at Arizona State University (ASU) the Director of the Information Systems Assurance Laboratory at ASU. Her research interests lie in security and Quality of Service assurance of information systems and infrastructures. She holds a Ph.D. degree in Industrial Engineering from Purdue University, West Lafayette, and M.S. and B.S. degrees in Computer Science from the Chinese Academy of Sciences and Peking University in China respectively. She is a senior member of IIE and IEEE, and an Associate Editor for IEEE Transactions on Systems, Man, and Cybernetics and IEEE Transactions on Reliability. Toni Farley is the Assistant Director of the Information and Systems Assurance Laboratory, and a doctoral student of Computer Science at Arizona State University (ASU), Tempe, Arizona. She is studying under a Graduate Fellowship from AT&T Labs-Research. Her research interests include graphs, networks and network security. She holds a B.S. degree in Computer Science and Engineering from ASU. She is a member of IEEE and the IEEE Computer Society. Her email address is toni@asu.edu. Deepak Lakshminarasimhan is a Research Assistant at the Information and Systems Assurance Laboratory, and a Master of Science student of Electrical engineering at Arizona State University (ASU), Tempe, Arizona. His research interests include network security, digital signal processing and statistical data analysis. He holds a B.S degree in Electronics and Communication Engineering from Bharathidasan University in India.     

Modeling semantics in composite Web service requests by utility elicitation

When meeting the challenges in automatic and semi-automatic Web service composition, capturing the user’s service demand and preferences is as important as knowing what the services can do. This paper discusses the idea of semantic service requests for composite services, and presents a multi-attribute utility theory (MAUT) based model of composite service requests. Service requests are modeled as user preferences and constraints. Two preference structures, additive independence and generalized additive independence, are utilized in calculating the expected utilities of service composition outcomes. The model is also based on an iterative and incremental scheme meant to better capture requirements in accordance with service consumers’ needs. OWL-S markup vocabularies and associated inference mechanism are used as a means to bring semantics to service requests. Ontology conceptualizations and language constructs are added to OWL-S as uniform representations of possible aspects of the requests. This model of semantics in service requests enables unambiguous understanding of the service needs and more precise generation of the desired compositions. An application scenario is presented to illustrate how the proposed model can be applied in the real business world. Qianhui Althea Liang received her Ph.D from the Department of Electrical and Computer Engineering, University of Florida in 2004. While pursuing her Ph.D, she was a member of Database Systems Research and Development Center at the University of Florida. She received both her bachelor’s and master’s from the Department of Computer Science and Engineering, Zhejiang University, China. She joined the School of Information Systems at Singapore Management University, Singapore, as an assistant professor in 2005. Her major research interests are service composition, dynamic service discovery, multimedia Web services, and applied artificial intelligence. Jen-Yao Chung received the M.S. and Ph.D degrees in computer science from the University of Illinois at Urbana-Champaign. Currently, he is the senior manager for Engineering and Technology Services Innovation, where he was responsible for identifying and creating emergent solutions. He was Chief Technology Officer for IBM Global Electronics Industry. Before that, he was program director for IBM Institute for Advanced Commerce Technology office. He is the co-founder of IEEE technical committee on e-Commerce (TCEC). He has served as general chair and program chair for many international conferences, most recently he served as the steering committee chair for the IEEE International Conference on e-Commerce Technology (CEC06) and general chair for the IEEE International Conference on e-Business Engineering (ICEBE06). He has authored or coauthored over 150 technical papers in published journals or conference proceedings. He is a senior member of the IEEE and a member of ACM. Miller is founding Dean of the School of Information Systems (SIS) at Singapore Management University, and also serves as Practice Professor of Information Systems. Since 2003, he has led efforts to launch and establish the undergraduate, graduate and professional programs of the SIS. Immediately prior to joining SMU, Dr. Miller served as Chief Architect Executive for the Business Consulting Services unit of IBM Global Services in Asia Pacific. He held prior industry appointments with Fujitsu Network Systems, and with RWD Technologies. Dr. Miller started his professional career as an Assistant Professor at Carnegie Mellon University, conducting research and teaching related to Computer-Integrated Manufacturing and Robotics applications and impacts. He has a Bachelors of Engineering Degree in Systems Engineering (Magna Cum Laude) from the University of Pennsylvania and a Masters of Science in Statistics and a Ph.D in Engineering and Public Policy from Carnegie Mellon University.     

Wavelet filtering of the structure signs of an image

In this article, an approach to filtering the edges of a halftone image is presented. The proposed approach is based on using a packet wavelet transformation of one-dimensional signals with any scale factor. The text was submitted by the authors in English. Arcady Lvovich Zhiznyakov. Candidate of engineering science. Docent of the Department of Information Systems at the Murom Institute of Vladimir State University. The field of science interests is digital image processing and analysis. He is the author of more than 150 science publications. Andrei Alexandrovich Fomin. A post-graduate student of the Department of Information Systems at the Murom Institute of Vladimir State University. The field of science interests is digital image processing and analysis. He is the author of more than 40 science publications.