Image hiding scheme using modulus function and optimal substitution table

The simple least-significant-bit (LSB) substitution technique is the easiest way to embed secret data in the host image. To avoid image degradation of the simple LSB substitution technique, Wang et al. proposed a method using the substitution table to process image hiding. Later, Thien and Lin employed the modulus function to solve the same problem. In this paper, the proposed scheme combines the modulus function and the optimal substitution table to improve the quality of the stego-image. Experimental results show that our method can achieve better quality of the stego-image than Thien and Lin’s method does. The text was submitted by the authors in English. Chin-Shiang Chan received his BS degree in Computer Science in 1999 from the National Cheng Chi University, Taipei, Taiwan and the MS degree in Computer Science and Information Engineering in 2001 from the National Chung Cheng University, ChiaYi, Taiwan. He is currently a Ph.D. student in Computer Science and Information Engineering at the National Chung Cheng University, Chiayi, Taiwan. His research fields are image hiding and image compression. Chin-Chen Chang received his BS degree in applied mathematics in 1977 and his MS degree in computer and decision sciences in 1979, both from the National Tsing Hua University, Hsinchu, Taiwan. He received his Ph.D. in computer engineering in 1982 from the National Chiao Tung University, Hsinchu, Taiwan. During the academic years of 1980–1983, he was on the faculty of the Department of Computer Engineering at the National Chiao Tung University. From 1983–1989, he was on the faculty of the Institute of Applied Mathematics, National Chung Hsing University, Taichung, Taiwan. From 1989 to 2004, he has worked as a professor in the Institute of Computer Science and Information Engineering at National Chung Cheng University, Chiayi, Taiwan. Since 2005, he has worked as a professor in the Department of Information Engineering and Computer Science at Feng Chia University, Taichung, Taiwan. Dr. Chang is a Fellow of IEEE, a Fellow of IEE and a member of the Chinese Language Computer Society, the Chinese Institute of Engineers of the Republic of China, and the Phi Tau Phi Society of the Republic of China. His research interests include computer cryptography, data engineering, and image compression. Yu-Chen Hu received his Ph.D. degree in Computer Science and Information Engineering from the Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan in 1999. Dr. Hu is currently an assistant professor in the Department of Computer Science and Information Engineering, Providence University, Sha-Lu, Taiwan. He is a member of the SPIE society and a member of the IEEE society. He is also a member of the Phi Tau Phi Society of the Republic of China. His research interests include image and data compression, information hiding, and image processing.     

Hiding a halftone secret image in two camouflaged halftone images

In this paper, we shall propose a method to hide a halftone secret image into two other camouflaged halftone images. In our method, we adjust the gray-level image pixel value to fit the pixel values of the secret image and two camouflaged images. Then, we use the halftone technique to transform the secret image into a secret halftone image. After that, we make two camouflaged halftone images at the same time out of the two camouflaged images and the secret halftone image. After overlaying the two camouflaged halftone images, the secret halftone image can be revealed by using our eyes. The experimental results included in this paper show that our method is very practicable. The text was submitted by the authors in English. Wei-Liang Tai received his BS degree in Computer Science in 2002 from Tamkang University, Tamsui, Taiwan, and his MS degree in Computer Science and Information Engineering in 2004 from National Chung Cheng University, Chiayi, Taiwan. He is currently a PhD student of Computer Science and Information Engineering at National Chung Cheng University. His research fields are image hiding, digital watermarking, and image compression. Chi-Shiang Chan received his BS degree in Computer Science in 1999 from National Cheng Chi University, Taipei, Taiwan, and his MS degree in Computer Science and Information Engineering in 2001 from National Chung Cheng University, Chiayi, Taiwan. He is currently a PhD student of Computer Science and Information Engineering at National Chung Cheng University. His research fields are image hiding and image compression. Chin-Chen Chang received his BS degree in Applied Mathematics in 1977 and his MS degree in Computer and Decision Sciences in 1979, both from National Tsing Hua University, Hsinchu, Taiwan. He received his PhD in Computer Engineering in 1982 from National Chiao Tung University, Hsinchu, Taiwan. During the academic years of 1980–1983, he was on the faculty of the Department of Computer Engineering at National Chiao Tung University. From 1983–1989, he was on the faculty of the Institute of Applied Mathematics, National Chung Hsing University, Taichung, Taiwan. From 1989 to 2004, he has worked as a professor in the Institute of Computer Science and Information Engineering at National Chung Cheng University, Chiayi, Taiwan. Since 2005, he has worked as a professor in the Department of Information Engineering and Computer Science at Feng Chia University, Taichung, Taiwan. Dr. Chang is a fellow of the IEEE, a fellow of the IEE, and a member of the Chinese Language Computer Society, the Chinese Institute of Engineers of the Republic of China, and the Phi Tau Phi Society of the Republic of China. His research interests include computer cryptography, data engineering, and image compression.     

On semantic resolution with lemmaizing and contraction and a formal treatment of caching

Reducing redundancy in search has been a major concern for automated deduction. Subgoal-reduction strategies, such as those based on model elimination and implemented in Prolog technology theorem provers, prevent redundant search by usinglemmaizing andcaching, whereas contraction-based strategies prevent redundant search by usingcontraction rules, such assubsumption. In this work we show that lemmaizing and contraction can coexist in the framework ofsemantic resolution. On the lemmaizing side, we define two meta-level inference rules for lemmaizing in semantic resolution, one producing unit lemmas and one producing non-unit lemmas, and we prove their soundness. Rules for lemmaizing are meta-rules because they use global knowledge about the derivation, e.g. ancestry relations, in order to derive lemmas. Our meta-rules for lemmaizing generalize to semantic resolution the rules for lemmaizing in model elimination. On the contraction side, we give contraction rules for semantic strategies, and we define apurity deletion rule for first-order clauses that preserves completeness. While lemmaizing generalizes success caching of model elimination, purity deletion echoes failure caching. Thus, our approach integrates features of backward and forward reasoning. We also discuss the relevance of our work to logic programming. Supported in part by the National Science Foundation with grant CCR-94-08667 and CCR-97-01508. Supported in part by grant NSC 86-2213-E-002-047 and NSC 87-2213-E-002-029 of the National Science Council of the Republic of China. Maria Paola Bonacina, Ph.D.: She is on the faculty of the Department of Computer Science of the University of Iowa. She received a laurea (1986) and a doctorate in informatics from the Universita degli Studi di Milano, and a Ph.D. in computer science from the State University of New York at Stony Brook (1992). She was awarded fellowships by the Universita degli Studi di Milano, the European Union and the General Electric Foundation. The unifying theme of her research is automated theorem proving. Her research areas include distributed automated deduction, the theory of search and strategy analysis, completion-based theorem proving, category theory for computer science, term rewriting systems, logic programming, and manyvalued logic. Jieh Hsiang, Ph.D.: He is a Professor of Computer Science at the National Taiwan University and is also the Director of the Center of Excellence for Research in Computer Systems of the National Taiwan University. Professor Hsiang is known for work in term rewriting systems and automated deduction. His other research interests include logic programming, programming logics, computer viruses, and intelligent agents. Recently he has also become interested in the digitization of Taiwanese and Chinese historical records and heritage. Professor Hsiang received a B.S. degree in mathematics from National Taiwan University in 1976 and a Ph.D. degree in computer science from the University of Illinois at Urbana-Champaign in 1982. Before returning to Taiwan in 1993, he was a Professor of Computer Science at the State University of New York st Stony Brook.     

An integrated edge detection method using mathematical morphology

This paper presents an edge detection method based on mathematical morphology. The proposed scheme consists of four steps: preprocessing, edge extraction, edge decision, and postprocessing. In the preprocessing step, a morphological central transformation is applied to remove noise. In the edge extraction and decision steps, a morphological edge extractor is designed to estimate the edge information of an image, and an edge decision criterion is followed to determine whether a pixel is an edge or not. In the postprocessing step, the morphological hit-or-miss transformation is utilized to improve the correctness of the detected edges. It is proved theoretically for the correctness and effectiveness for detecting ideal edges. Experimental results show that the proposed method works well on both artificial and real images. The text was submitted by the authors in English. Chin-Pan Huang was born in 1959 in Taiwan, Republic of China. He received the B.S. and M.S. degrees in electrical engineering from Chung Cheng Institute of Technology, Taiwan, in 1981 and in 1985, respectively. In 1996, he received the Ph.D. degree in electrical engineering from the University of Pittsburgh in the United States. From 1996 to 2002, he was an associate scientist of the Electronic System Division in Chung Shan Institute of Science and Technology. He then joined the Department of Computer and Communication Engineering at Ming Chuan University in August 2002 and is currently an assistant professor there. His recent research interests include data compression, computer vision, digital image processing, and pattern recognition. Ran-Zan Wang was born in 1972 in Fukien, Republic of China. He received his B.S. degree in computer engineering and science in 1994 and M.S. degree in electrical engineering and computer science in 1996, both from Yuan-Ze University. In 2001, he received his Ph.D. degree in computer and information science from National Chiao Tung University. In 2001–2002, he was an assistant professor at the Department of Computer Engineering at the Van Nung Institute of Technology. He joined the Department of Computer and Communication Engineering at Ming Chuan University in August 2002 and is currently an assistant professor there. His recent research interests include data hiding and digital watermarking, image processing, and pattern recognition. Dr. Wang is a member of the Phi Tau Phi Scholastic Honor Society.     

Linear logic for deductive databases

This paper deals with deductive databases in linear logic. The semantics of queries, views, constraints, and (view) updates are defineddeclaratively in linear logic. In constrast to classical logic, we can formalise non-shared view, transition constraints, and (view) updates easily. Various proof search strategies are presented along with an algorithm for query evaluation from a bottom-up direction. An additional advantage is that the associated meaning of a given relation can be defined in terms of the validity of a legal update in a given relation. We also defined formally the update principles and showed the correctness of the update translation algorithms. In this approach, we provide virtual view updates along with real view updates, and view DELETIONs are special cases of view REPLACEMENTs. This permits three transactional view update operations (INSERTION, DELETION, REPLACEMENT) in comparison to only (INSERTION, DELETION) in most existing systems. Dong-Tsan Lee, Ph.D.: He is a computer scientist in the Department of Computer Science at University of Western Australia, Perth, Western Australia, Australia. He received the B.S. and M.S. degrees from the Department of Computer Science at National Chiao-Tung University, Taiwan, in 1983 and 1985, respectively, and earned the Ph.D. degree from the Department of Computer Science at University of Western Australia. His research interests include database and artificial intelligence, linear logic, and real-time software engineering. Chin-Ping Tsang, Ph.D.: He is currently an associate professor in the Department of Computer Science at University of Western Australia, Perth, Western Australia, Australia. He received the Ph.D. degree from the University of Western Australia. He was the head of the Department of Computer Science at the University of Western Australia from 1994 to 1997. His research interests include artificial intelligence, non-classicial logic and neural nets.     

S-Club: an overlay-based efficient service discovery mechanism in CROWN Grid

Information service plays a key role in grid system, handles resource discovery and management process. Employing existing information service architectures suffers from poor scalability, long search response time, and large traffic overhead. In this paper, we propose a service club mechanism, called S-Club, for efficient service discovery. In S-Club, an overlay based on existing Grid Information Service (GIS) mesh network of CROWN is built, so that GISs are organized as service clubs. Each club serves for a certain type of service while each GIS may join one or more clubs. S-Club is adopted in our CROWN Grid and the performance of S-Club is evaluated by comprehensive simulations. The results show that S-Club scheme significantly improves search performance and outperforms existing approaches. Chunming Hu is a research staff in the Institute of Advanced Computing Technology at the School of Computer Science and Engineering, Beihang University, Beijing, China. He received his B.E. and M.E. in Department of Computer Science and Engineering in Beihang University. He received the Ph.D. degree in School of Computer Science and Engineering of Beihang University, Beijing, China, 2005. His research interests include peer-to-peer and grid computing; distributed systems and software architectures. Yanmin Zhu is a Ph.D. candidate in the Department of Computer Science, Hong Kong University of Science and Technology. He received his B.S. degree in computer science from Xi’an Jiaotong University, Xi’an, China, in 2002. His research interests include grid computing, peer-to-peer networking, pervasive computing and sensor networks. He is a member of the IEEE and the IEEE Computer Society. Jinpeng Huai is a Professor and Vice President of Beihang University. He serves on the Steering Committee for Advanced Computing Technology Subject, the National High-Tech Program (863) as Chief Scientist. He is a member of the Consulting Committee of the Central Government’s Information Office, and Chairman of the Expert Committee in both the National e-Government Engineering Taskforce and the National e-Government Standard office. Dr. Huai and his colleagues are leading the key projects in e-Science of the National Science Foundation of China (NSFC) and Sino-UK. He has authored over 100 papers. His research interests include middleware, peer-to-peer (P2P), grid computing, trustworthiness and security. Yunhao Liu received his B.S. degree in Automation Department from Tsinghua University, China, in 1995, and an M.A. degree in Beijing Foreign Studies University, China, in 1997, and an M.S. and a Ph.D. degree in computer science and engineering at Michigan State University in 2003 and 2004, respectively. He is now an assistant professor in the Department of Computer Science and Engineering at Hong Kong University of Science and Technology. His research interests include peer-to-peer computing, pervasive computing, distributed systems, network security, grid computing, and high-speed networking. He is a senior member of the IEEE Computer Society. Lionel M. Ni is chair professor and head of the Computer Science and Engineering Department at Hong Kong University of Science and Technology. Lionel M. Ni received the Ph.D. degree in electrical and computer engineering from Purdue University, West Lafayette, Indiana, in 1980. He was a professor of computer science and engineering at Michigan State University from 1981 to 2003, where he received the Distinguished Faculty Award in 1994. His research interests include parallel architectures, distributed systems, high-speed networks, and pervasive computing. A fellow of the IEEE and the IEEE Computer Society, he has chaired many professional conferences and has received a number of awards for authoring outstanding papers.     

Adaptive group scheduling mechanism using mobile agents in peer-to-peer grid computing environment

Peer-to-peer grid computing is an attractive computing paradigm for high throughput applications. However, both volatility due to the autonomy of volunteers (i.e., resource providers) and the heterogeneous properties of volunteers are challenging problems in the scheduling procedure. Therefore, it is necessary to develop a scheduling mechanism that adapts to a dynamic peer-to-peer grid computing environment. In this paper, we propose a Mobile Agent based Adaptive Group Scheduling Mechanism (MAAGSM). The MAAGSM classifies and constructs volunteer groups to perform a scheduling mechanism according to the properties of volunteers such as volunteer autonomy failures, volunteer availability, and volunteering service time. In addition, the MAAGSM exploits a mobile agent technology to adaptively conduct various scheduling, fault tolerance, and replication algorithms suitable for each volunteer group. Furthermore, we demonstrate that the MAAGSM improves performance by evaluating the scheduling mechanism in Korea@Home. SungJin Choi is a Ph.D. student in the Department of Computer Science and Engineering at Korea University. His research interests include mobile agent, peer-to-peer computing, grid computing, and distributed systems. Mr. Choi received a M.S. in computer science from Korea University. He is a student member of the IEEE. MaengSoon Baik is a senior research member at the SAMSUNG SDS Research & Develop Center. His research interests include mobile agent, grid computing, server virtualization, storage virtualization, and utility computing. Dr. Baik received a Ph.D. in computer science from Korea University. JoonMin Gil is a professor in the Department of Computer Science Education at Catholic University of Daegu, Korea. His recent research interests include grid computing, distributed and parallel computing, Internet computing, P2P networks, and wireless networks. Dr. Gil received his Ph.D. in computer science from Korea University. He is a member of the IEEE and the IEICE. SoonYoung Jung is a professor in the Department of Computer Science Education at Korea University. His research interests include grid computing, web-based education systems, database systems, knowledge management systems, and mobile computing. Dr. Jung received his Ph.D. in computer science from Korea University. ChongSun Hwang is a professor in the Department of Computer Science and Engineering at Korea University. His research interests include distributed systems, distributed algorithms, and mobile computing. Dr. Hwang received a Ph.D. in statistics and computer science from the University of Georgia.     

Fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers

In this paper, we present a new method for fuzzy risk analysis based on the ranking of generalized trapezoidal fuzzy numbers. The proposed method considers the centroid points and the standard deviations of generalized trapezoidal fuzzy numbers for ranking generalized trapezoidal fuzzy numbers. We also use an example to compare the ranking results of the proposed method with the existing centroid-index ranking methods. The proposed ranking method can overcome the drawbacks of the existing centroid-index ranking methods. Based on the proposed ranking method, we also present an algorithm to deal with fuzzy risk analysis problems. The proposed fuzzy risk analysis algorithm can overcome the drawbacks of the one we presented in [7]. Shi-Jay Chen was born in 1972, in Taipei, Taiwan, Republic of China. He received the B.S. degree in information management from the Kaohsiung Polytechnic Institute, Kaohsiung, Taiwan, and the M.S. degree in information management from the Chaoyang University of Technology, Taichung, Taiwan, in 1997 and 1999, respectively. He received the Ph.D. degree at the Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, in October 2004. His research interests include fuzzy systems, multicriteria fuzzy decisionmaking, and artificial intelligence. Shyi-Ming Chen was born on January 16, 1960, in Taipei, Taiwan, Republic of China. He received the Ph.D. degree in Electrical Engineering from National Taiwan University, Taipei, Taiwan, in June 1991. From August 1987 to July 1989 and from August 1990 to July 1991, he was with the Department of Electronic Engineering, Fu-Jen University, Taipei, Taiwan. From August 1991 to July 1996, he was an Associate Professor in the Department of Computer and Information Science, National Chiao Tung University, Hsinchu, Taiwan. From August 1996 to July 1998, he was a Professor in the Department of Computer and Information Science, National Chiao Tung University, Hsinchu, Taiwan. From August 1998 to July 2001, he was a Professor in the Department of Electronic Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan. Since August 2001, he has been a Professor in the Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan. He was a Visiting Scholar in the Department of Electrical Engineering and Computer Science, University of California, Berkeley, in 1999. He was a Visiting Scholar in the Institute of Information Science, Academia Sinica, Republic of China, in 2003. He has published more than 250 papers in referred journals, conference proceedings and book chapters. His research interests include fuzzy systems, information retrieval, knowledge-based systems, artificial intelligence, neural networks, data mining, and genetic algorithms. Dr. Chen has received several honors and awards, including the 1994 Outstanding Paper Award o f the Journal of Information and Education, the 1995 Outstanding Paper Award of the Computer Society of the Republic of China, the 1995 and 1996 Acer Dragon Thesis Awards for Outstanding M.S. Thesis Supervision, the 1995 Xerox Foundation Award for Outstanding M.S. Thesis Supervision, the 1996 Chinese Institute of Electrical Engineering Award for Outstanding M.S. Thesis Supervision, the 1997 National Science Council Award, Republic of China, for Outstanding Undergraduate Student's Project Supervision, the 1997 Outstanding Youth Electrical Engineer Award of the Chinese Institute of Electrical Engineering, Republic of China, the Best Paper Award of the 1999 National Computer Symposium, Republic of China, the 1999 Outstanding Paper Award of the Computer Society of the Republic of China, the 2001 Institute of Information and Computing Machinery Thesis Award for Outstanding M.S. Thesis Supervision, the 2001 Outstanding Talented Person Award, Republic of China, for the contributions in Information Technology, the 2002 Institute of information and Computing Machinery Thesis Award for Outstanding M.S. Thesis Supervision, the Outstanding Electrical Engineering Professor Award granted by the Chinese Institute of Electrical Engineering (CIEE), Republic of China, the 2002 Chinese Fuzzy Systems Association Best Thesis Award for Outstanding M.S. Thesis Supervision, the 2003 Outstanding Paper Award of the Technological and Vocational Education Society, Republic of China, the 2003 Acer Dragon Thesis Award for Outstanding Ph.D. Dissertation Supervision, the 2005 “Operations Research Society of Taiwan” Award for Outstanding M.S. Thesis Supervision, the 2005 Acer Dragon Thesis Award for Outstanding Ph.D. Dissertation Supervision, the 2005 Taiwan Fuzzy Systems Association Award for Outstanding Ph.D. Dissertation Supervision, and the 2006 “Operations Research Society of Taiwan” Award for Outstanding M.S. Thesis Supervision. Dr. Chen is currently the President of the Taiwanese Association for Artificial Intelligence (TAAI). He is a Senior Member of the IEEE, a member of the ACM, the International Fuzzy Systems Association (IFSA), and the Phi Tau Phi Scholastic Honor Society. He was an administrative committee member of the Chinese Fuzzy Systems Association (CFSA) from 1998 to 2004. He is an Associate Editor of the IEEE Transactions on Systems, Man, and Cybernetics - Part C, an Associate Editor of the IEEE Computational Intelligence Magazine, an Associate Editor of the Journal of Intelligent & Fuzzy Systems, an Editorial Board Member of the International Journal of Applied Intelligence, an Editor of the New Mathematics and Natural Computation Journal, an Associate Editor of the International Journal of Fuzzy Systems, an Editorial Board Member of the International Journal of Information and Communication Technology, an Editorial Board Member of the WSEAS Transactions on Systems, an Editor of the Journal of Advanced Computational Intelligence and Intelligent Informatics, an Associate Editor of the WSEAS Transactions on Computers, an Editorial Board Member of the International Journal of Computational Intelligence and Applications, an Editorial Board Member of the Advances in Fuzzy Sets and Systems Journal, an Editor of the International Journal of Soft Computing, an Editor of the Asian Journal of Information Technology, an Editorial Board Member of the International Journal of Intelligence Systems Technologies and Applications, an Editor of the Asian Journal of Information Management, an Associate Editor of the International Journal of Innovative Computing, Information and Control, and an Editorial Board Member of the International Journal of Computer Applications in Technology. He was an Editor of the Journal of the Chinese Grey System Association from 1998 to 2003. He is listed in International Who's Who of Professionals, Marquis Who's Who in the World, and Marquis Who's Who in Science and Engineering.     

Finite-horizon scheduling of radar dwells with online template construction

Timing constraints for radar tasks are usually specified in terms of the minimum and maximum temporal distance between successive radar dwells. We utilize the idea of feasible intervals for dealing with the temporal distance constraints. In order to increase the freedom that the scheduler can offer a high-level resource manager, we introduce a technique for nesting and interleaving dwells online while accounting for the energy constraint that radar systems need to satisfy. Further, in radar systems, the task set changes frequently and we advocate the use of finite horizon scheduling in order to avoid the pessimism inherent in schedulers that assume a task will execute forever. The combination of feasible intervals and online dwell packing allows modular schedule updates whereby portions of a schedule can be altered without affecting the entire schedule, hence reducing the complexity of the scheduler. Through extensive simulations we validate our claims of providing greater scheduling flexibility without compromising on performance when compared with earlier work based on templates constructed offline. We also evaluate the impact of two parameters in our scheduling approach: the template length (or the extent of dwell nesting and interleaving) and the length of the finite horizon. Sathish Gopalakrishnan is a visting scholar in the Department of Computer Science, University of Illinois at Urbana-Champaign, where he defended his Ph.D. thesis in December 2005. He received an M.S. in Applied Mathematics from the University of Illinois in 2004 and a B.E. in Computer Science and Engineering from the University of Madras in 1999. Sathish’s research interests concern real-time and embedded systems, and the design of large-scale reliable systems. He received the best student paper award for his work on radar dwell scheduling at the Real-Time Systems Symposium 2004. Marco Caccamo graduated in computer engineering from the University of Pisa in 1997 and received the Ph.D. degree in computer engineering from the Scuola Superiore S. Anna in 2002. He is an Assistant Professor of the Department of Computer Science at the University of Illinois. His research interests include real-time operating systems, real-time scheduling and resource management, wireless sensor networks, and quality of service control in next generation digital infrastructures. He is recipient of the NSF CAREER Award (2003). He is a member of ACM and IEEE. Chi-Sheng Shih is currently an assistant professor at the Graduate Institute of Networking and Multimedia and Department of Computer Science and Information Engineering at National Taiwan University since February 2004. He received the B.S. in Engineering Science and M.S. in Computer Science from National Cheng Kung University in 1993 and 1995, respectively. In 2003, he received his Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign. His main research interests are embedded systems, hardware/software codesign, real-time systems, and database systems. Specifically, his main research interests focus on real-time operating systems, real-time scheduling theory, embedded software, and software/hardware co-design for system-on-a-chip. Chang-Gun Lee received the B.S., M.S. and Ph.D. degrees in computer engineering from Seoul National University, Korea, in 1991, 1993 and 1998, respectively. He is currently an Assistant Professor in the Department of Electrical Engineering, Ohio State University, Columbus. Previously, he was a Research Scientist in the Department of Computer Science, University of Illinois at Urbana-Champaign from March 2000 to July 2002 and a Research Engineer in the Advanced Telecomm. Research Lab., LG Information & Communications, Ltd. from March 1998 to February 2000. His current research interests include real-time systems, complex embedded systems, QoS management, and wireless ad-hoc networks. Chang-Gun Lee is a member of the IEEE Computer Society. Lui Sha graduated with the Ph.D. degree from Carnegie-Mellon University in 1985. He was a Member and then a Senior Member of Technical Staff at Software Engineering Institute (SEI) from 1986 to 1998. Since Fall 1998, he has been a Professor of Computer Science at the University of Illinois at Urbana Champaign, and a Visiting Scientist of the SEI. He was the Chair of IEEE Real Time Systems Technical Committee from 1999 to 2000, and has served on its Executive Committee since 2001. He was a member of National Academy of Science’s study group on Software Dependability and Certification from 2004 to 2005, and is an IEEE Distinguished Visitor (2005 to 2007). Lui Sha is a Fellow of the IEEE and the ACM.     

Preference update for e-commerce applications: Model,language, and processing

It is likely that customers issue requests based on out-of-date information in e-commerce application systems. Hence, the transaction failure rates would increase greatly. In this paper, we present a preference update model to address this problem. A preference update is an extended SQL update statement where a user can request the desired number of target data items by specifying multiple preferences. Moreover, the preference update allows easy extraction of criteria from a set of concurrent requests and, hence, optimal decisions for the data assignments can be made. We propose a group evaluation strategy for preference update processing in a multidatabase environment. The experimental results show that the group evaluation can effectively increase the customer satisfaction level with acceptable cost. Peng Li is the Chief Software Architect of didiom LLC. Before that, he was a visiting assistant professor of computer science department in Western Kentucky University. He received his Ph.D. degree of computer science from the University of Texas at Dallas. He also holds a B.Sc. and M.S. in Computer Science from the Renmin University of China. His research interests include database systems, database security, transaction processing, distributed and Internet computer and E-commerce. Manghui Tu received a Bachelor degree of Science from Wuhan University, P.R. China in 1996, and a Master Degree in Computer Science from the University of Texas at Dallas 2001. He is currently working toward the PhD degree in the Department of Computer Science at the University of Texas at Dallas. Mr. Tu’s research interests include distributed systems, grid computing, information security, mobile computing, and scientific computing. His PhD research work focus on the data management in secure and high performance data grid. He is a student member of the IEEE. I-Ling Yen received her BS degree from Tsing-Hua University, Taiwan, and her MS and PhD degrees in Computer Science from the University of Houston. She is currently an Associate Professor of Computer Science at the University of Texas at Dallas. Dr. Yen’s research interests include fault-tolerant computing, security systems and algorithms, distributed systems, Internet technologies, E-commerce, and self-stabilizing systems. She had published over 100 technical papers in these research areas and received many research awards from NSF, DOD, NASA, and several industry companies. She has served as Program Committee member for many conferences and Program Chair/Co-Chair for the IEEE Symposium on Application-Specific Software and System Engineering & Technology, IEEE High Assurance Systems Engineering Symposium, IEEE International Computer Software and Applications Conference, and IEEE International Symposium on Autonomous Decentralized Systems. She is a member of the IEEE. Zhonghang Xia received the B.S. degree in applied mathematics from Dalian University of Technology in 1990, the M.S. degree in Operations Research from Qufu Normal University in 1993, and the Ph.D. degree in computer science from the University of Texas at Dallas in 2004. He is now an assistant professor in the Department of Computer Science, Western Kentucky University, Bowling Green, KY. His research interests are in the area of multimedia computing and networking, distributed systems, and data mining.     

An instance-based learning approach based on grey relational structure

In instance-based learning, the ‘nearness’ between two instances—used for pattern classification—is generally determined by some similarity functions, such as the Euclidean or Value Difference Metric (VDM). However, Euclidean-like similarity functions are normally only suitable for domains with numeric attributes. The VDM metrics are mainly applicable to domains with symbolic attributes, and their complexity increases with the number of classes in a specific application domain. This paper proposes an instance-based learning approach to alleviate these shortcomings. Grey relational analysis is used to precisely describe the entire relational structure of all instances in a specific domain. By using the grey relational structure, new instances can be classified with high accuracy. Moreover, the total number of classes in a specific domain does not affect the complexity of the proposed approach. Forty classification problems are used for performance comparison. Experimental results show that the proposed approach yields higher performance over other methods that adopt one of the above similarity functions or both. Meanwhile, the proposed method can yield higher performance, compared to some other classification algorithms. Chi-Chun Huang is currently Assistant Professor in the Department of Information Management at National Kaohsiung Marine University, Kaohsiung, Taiwan. He received the Ph.D. degree from the Department of Electronic Engineering at National Taiwan University of Science and Technology in 2003. His research includes intelligent Internet systems, grey theory, machine learning, neural networks and pattern recognition. Hahn-Ming Lee is currently Professor in the Department of Computer Science and Information Engineering at National Taiwan University of Science and Technology, Taipei, Taiwan. He received the B.S. degree and Ph.D. degree from the Department of Computer Science and Information Engineering at National Taiwan University in 1984 and 1991, respectively. His research interests include, intelligent Internet systems, fuzzy computing, neural networks and machine learning. He is a member of IEEE, TAAI, CFSA and IICM.     

A Prolog simulator for deterministic P systems with active membranes

In this paper we propose a new way to represent P systems with active membranes based on Logic Programming techniques. This representation allows us to express the set of rules and the configuration of the P system in each step of the evolution as literals of an appropriate language of first order logic. We provide a Prolog program to simulate, the evolution of these P systems and present some auxiliary tools to simulate the evolution of a P system with active membranes using 2-division which solves the SAT problem following the techniques presented in Reference.¹⁰ Andrés Cordón-Franco: He is a member of the Department of Computer Science and Artificial Intelligence at the University of Sevilla (Spain). He is also a member of the research group on Natural Computing of the University of Seville. His research interest includes Mathematical Logic, Logic in Computer Science, and Membrane Computing, both from a theoretical and from a practical (software implementation) point of view. Miguel A. Gutiérrez-Naranjo: He is an assistant professor in the Computer Science and Artificial Intelligence Department at University of Sevilla, Spain. He is also a member of the Research Group on Natural Computing of the University of Seville. His research interest includes Machine Learning, Logic Programming and Membrane Computing, both from a theoretical and a practical point of view. Mario J. Pérez-Jiménez, Ph.D.: He is professor of Department of Computer Science and Artificial Intelligence at University of Seville, where he is the head of the Group of Research on Natural Computing, He has published 8 books of Mathematics and Computation, and more than 90 scientific articles in prestigious scientific journals. He is member of European Molecular Computing Consortium. Fernando Sancho-Caparrini: He is a member of the Department of Computer Science and Artificial Intelligence at the University of Sevilla (Spain). He is also a member of the research group on Natural Computing of the University of Seville. His research interest includes Complex Systems, DNA Computing, Logic in Computer Science, and Membrane Computing, both from a theoretical and from a practical point of view.     

Behavioural notions for elementary net systems

We study the relationships between a number of behavioural notions that have arisen in the theory of distributed computing. In order to sharpen the under-standing of these relationships we apply the chosen behavioural notions to a basic net-theoretic model of distributed systems called elementary net systems. The behavioural notions that are considered here are trace languages, non-sequential processes, unfoldings and event structures. The relationships between these notions are brought out in the process of establishing that for each elementary net system, the trace language representation of its behaviour agrees in a strong way with the event structure representation of its behaviour. M. Nielsen received a Master of Science degree in mathematics and computer science in 1973, and a Ph.D. degree in computer science in 1976 both from Aarhus University, Denmark. He has held academic positions at Department of Computer Science, Aarhus University, Denmark since 1976, and was visiting researcher at Computer Science Department, University of Edinburgh, U.K., 1977–79, and Computer Laboratory, Cambridge University, U.K., 1986. His research interest is in the theory of distributed computing. Grzegorz Rozenberg received a master of engineering degree from the Department of Electronics (section computers) of the Technical University of Warsaw in 1964 and a Ph.D. in mathematics from the Institute of Mathematics of the Polish Academy of Science in 1968. He has held acdeemic positions at the Institute of Mathematics of the Polish Academy of Science, the Department of Mathematics of Utrecht University, the Department of Computer Science at SUNY at Buffalo, and the Department of Mathematics of the University of Antwerp. He is currently Professor at the Department of Computer Science of Leiden University and Adjoint Professor at the Department of Computer Science of the University of Colorado at Boulder. His research interests include formal languages and automata theory, theory of graph transformations, and theory of concurrent systems. He is currently President of the European Association for Theoretical Computer Science (EATCS). P.S. Thiagarajan received the Bachelor of Technology degree from the Indian Institute of Technology, Madras, India in 1970. He was awarded the Ph.D. degree by Rice University, Houston Texas, U.S.A, in 1973. He has been a Research Associate at the Massachusetts Institute of Technology, Cambridge a Staff Scientist at the Geosellschaft für Mathematik und Datenverarbeitung, St. Augustin, a Lektor at Århus University, Århus and an Associate Professor at the Institute of Mathematical Sciences, Madras. He is currently a Professor at the School of Mathematics, SPIC Science Foundation, Madras. He research intest is in the theory of distributed computing.     

Fast evaluation of Bounded Slice-line Grid

Bounded Slice-line Grid (BSG) is an elegant representation of block placement, because it is very intuitionistic and has the advantage of handling various placement constraints. However, BSG has attracted little attention because its evaluation is very time-consuming. This paper proposes a simple algorithm independent of the BSG size to evaluate the BSG representation in O(nloglogn) time, where n is the number of blocks. In the algorithm, the BSG-rooms are assigned with integral coordinates firstly, and then a linear sorting algorithm is applied on the BSG-rooms where blocks are assigned to compute two block sequences, from which the block placement can be obtained in O(n log logn) time. As a consequence, the evaluation of the BSG is completed in O(nloglogn) time, where n is the number of blocks. The proposed algorithm is much faster than the previous graph-based O(n^2) algorithm. The experimental results demonstrate the efficiency of the algorithm.     

Privacy preservation for data cubes

A range query finds the aggregated values over all selected cells of an online analytical processing (OLAP) data cube where the selection is specified by the ranges of contiguous values for each dimension. An important issue in reality is how to preserve the confidential information in individual data cells while still providing an accurate estimation of the original aggregated values for range queries. In this paper, we propose an effective solution, called the zero-sum method, to this problem. We derive theoretical formulas to analyse the performance of our method. Empirical experiments are also carried out by using analytical processing benchmark (APB) dataset from the OLAP Council. Various parameters, such as the privacy factor and the accuracy factor, have been considered and tested in the experiments. Finally, our experimental results show that there is a trade-off between privacy preservation and range query accuracy, and the zero-sum method has fulfilled three design goals: security, accuracy, and accessibility. Sam Y. Sung is an Associate Professor in the Department of Computer Science, School of Computing, National University of Singapore. He received a B.Sc. from the National Taiwan University in 1973, the M.Sc. and Ph.D. in computer science from the University of Minnesota in 1977 and 1983, respectively. He was with the University of Oklahoma and University of Memphis in the United States before joining the National University of Singapore. His research interests include information retrieval, data mining, pictorial databases and mobile computing. He has published more than 80 papers in various conferences and journals, including IEEE Transaction on Software Engineering, IEEE Transaction on Knowledge & Data Engineering, etc. Yao Liu received the B.E. degree in computer science and technology from Peking University in 1996 and the MS. degree from the Software Institute of the Chinese Science Academy in 1999. Currently, she is a Ph.D. candidate in the Department of Computer Science at the National University of Singapore. Her research interests include data warehousing, database security, data mining and high-speed networking. Hui Xiong received the B.E. degree in Automation from the University of Science and Technology of China, Hefei, China, in 1995, the M.S. degree in Computer Science from the National University of Singapore, Singapore, in 2000, and the Ph.D. degree in Computer Science from the University of Minnesota, Minneapolis, MN, USA, in 2005. He is currently an Assistant Professor of Computer Information Systems in the Management Science & Information Systems Department at Rutgers University, NJ, USA. His research interests include data mining, databases, and statistical computing with applications in bioinformatics, database security, and self-managing systems. He is a member of the IEEE Computer Society and the ACM. Peter A. Ng is currently the Chairperson and Professor of Computer Science at the University of Texas—Pan American. He received his Ph.D. from the University of Texas–Austin in 1974. Previously, he had served as the Vice President at the Fudan International Institute for Information Science and Technology, Shanghai, China, from 1999 to 2002, and the Executive Director for the Global e-Learning Project at the University of Nebraska at Omaha, 2000–2003. He was appointed as an Advisory Professor of Computer Science at Fudan University, Shanghai, China in 1999. His recent research focuses on document and information-based processing, retrieval and management. He has published many journal and conference articles in this area. He had served as the Editor-in-Chief for the Journal on Systems Integration (1991–2001) and as Advisory Editor for the Data and Knowledge Engineering Journal since 1989.     

From Active to Passive—Progress in Testing Internet Routing Protocols

Routing protocols play an important role in the Internet and the test requirements are running up.To test routing protocols more efficiently,several enhancing techniques are applied in the protocol integrated test system described in this paper.The Implementation Under Test is modeled as a black box with windows.The test system is endowed with multiple channels and multiple ports to test distributed protocols.The test suite and other related aspects are also extended.Meanwhile,the passive testing is introduced to test,analyze and manage routing protocols in the production field,which is able to perform the conformance test,the interoperability test and the performance test.The state machine of peer sessions is tested with the state synchronization algorithm,and the routing information manipulation and other operations are checked and analyzed with the methods like the topology analysis and the internal process simulation,With both the active testing and the passive testing,the routing protool test is going further and more thoroughly and helps a lot in the developmnt of routers。     

Recent Progress on Selected Topics in Database Research ——-A Report by Nine Young Chinese Researchers Working in the United States

The study on database technologies, or more generally, the technologies of data and information management, is an important and active research field. Recently, many exciting results have been reported. In this fast growing field, Chinese researchers play more and more active roles. Research papers from Chinese scholars, both in China and abroad,appear in prestigious academic forums.In this paper,we, nine young Chinese researchers working in the United States, present concise surveys and report our recent progress on the selected fields that we are working on.Although the paper covers only a small number of topics and the selection of the topics is far from balanced, we hope that such an effort would attract more and more researchers,especially those in China,to enter the frontiers of database research and promote collaborations. For the obvious reason, the authors are listed alphabetically, while the sections are arranged in the order of the author list.     

Hiding collaborative recommendation association rules

The concept of Privacy-Preserving has recently been proposed in response to the concerns of preserving personal or sensible information derived from data mining algorithms. For example, through data mining, sensible information such as private information or patterns may be inferred from non-sensible information or unclassified data. There have been two types of privacy concerning data mining. Output privacy tries to hide the mining results by minimally altering the data. Input privacy tries to manipulate the data so that the mining result is not affected or minimally affected. For output privacy in hiding association rules, current approaches require hidden rules or patterns to be given in advance [10, 18–21, 24, 27]. This selection of rules would require data mining process to be executed first. Based on the discovered rules and privacy requirements, hidden rules or patterns are then selected manually. However, for some applications, we are interested in hiding certain constrained classes of association rules such as collaborative recommendation association rules [15, 22]. To hide such rules, the pre-process of finding these hidden rules can be integrated into the hiding process as long as the recommended items are given. In this work, we propose two algorithms, DCIS (Decrease Confidence by Increase Support) and DCDS (Decrease Confidence by Decrease Support), to automatically hiding collaborative recommendation association rules without pre-mining and selection of hidden rules. Examples illustrating the proposed algorithms are given. Numerical simulations are performed to show the various effects of the algorithms. Recommendations of appropriate usage of the proposed algorithms based on the characteristics of databases are reported. Leon Wang received his Ph.D. in Applied Mathematics from State University of New York at Stony Brook in 1984. From 1984 to 1987, he was an assistant professor in mathematics at University of New Haven, Connecticut, USA. From 1987 to 1994, he joined New York Institute of Technology as a research associate in the Electromagnetic Lab and assistant/associate professor in the Department of Computer Science. From 1994 to 2001, he joined I-Shou University in Taiwan as associate professor in the Department of Information Management. In 1996, he was the Director of Computing Center. From 1997 to 2000, he was the Chairman of Department of Information Management. In 2001, he was Professor and director of Library, all in I-Shou University. In 2002, he was Associate Professor and Chairman in Information Management at National University of Kaohsiung, Taiwan. In 2003, he rejoined New York Institute of Technology. Dr.Wang has published 33 journal papers, 102 conference papers, and 5 book chapters, in the areas of data mining, machine learning, expert systems, and fuzzy databases, etc. Dr. Wang is a member of IEEE, Chinese Fuzzy System Association Taiwan, Chinese Computer Association, and Chinese Information Management Association. Ayat Jafari received the Ph.D. degree from City University of New York. He has conducted considerable research in the areas of Computer Communication Networks, Local Area Networks, and Computer Network Security, and published many technical articles. His interests and expertise are in the area of Computer Networks, Signal Processing, and Digital Communications. He is currently the Chairman of the Computer Science and Electrical Engineering Department of New York Institute of Technology. Tzung-Pei Hong received his B.S. degree in chemical engineering from National Taiwan University in 1985, and his Ph.D. degree in computer science and information engineering from National Chiao-Tung University in 1992. He was a faculty at the Department of Computer Science in Chung-Hua Polytechnic Institute from 1992 to 1994, and at the Department of Information Management in I-Shou University from 1994 to 2001. He was in charge of the whole computerization and library planning for National University of Kaohsiung in Preparation from 1997 to 2000, and served as the first director of the library and computer center in National University of Kaohsiung from 2000 to 2001 and as the Dean of Academic Affairs from 2003 to 2006. He is currently a professor at the Department of Electrical Engineering and at the Department of Computer Science and Information Engineering. His current research interests include machine learning, data mining, soft computing, management information systems, and www applications. Springer     

HarkMan—A Vocabulary-Independent Keyword Spotter for Spontaneons Chinese Speech

In this paper,a noverl technique adopted in HarkMan is introduced.HarkMan is a keywore-spotter designed to automatically spot the given words of a vocabulary-independent task in unconstrained Chinese telephone speech.The speaking manner and the number of keywords are not limited.This paper focuses on the novel technique which addresses acoustic modeling,keyword spotting network,search strategies,robustness,and rejection.The underlying technologies used in HarkMan given in this paper are useful not only for keyword spotting but also for continuous speech recognition.The system has achieved a figure-of-merit value over 90%.