ARMiner: A Data Mining Tool Based on Association Rules

In this paper,ARM iner,a data mining tool based on association rules,is introduced.Beginning with the system architecture,the characteristics and functions are discussed in details,including data transfer,concept hierarchy generalization,mining rules with negative items and the re-development of the system.An example of the tool‘s application is also shown.Finally,Some issues for future research are presented.     

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.     

A New Algorithm for Generalized Optimal Discriminant Vectors

A study has been conducted on the algorithm of solving generalized optimal set of discriminant vectors in this paper.This paper proposes an analytical algorithm of solving generalized optimal set of discriminant vectors theoretically for the first time.A lot of computation time can be saved because all the generalized optimal ests of discriminant vectors can be obtained simultaneously with the proposed algorithm,while it needs no iterative operations .The proposed algorithm can yield a much higher recognition rate.Furthermore,the proposed algorithm overcomes the shortcomings of conventional human face recognition algorithms which were effective for small sample size problems only.These statements are supported by the numerical simulation experiments on facial database of ORL.     

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.     

A Model for Slicing JAVA Programs Hierarchically

Program slicing can be effectively used to debug, test, analyze, understand and maintain objectoriented software. In this paper, a new slicing model is proposed to slice Java programs based on their inherent hierarchical feature. The main idea of hierarchical slicing is to slice programs in a stepwise way, from package level, to class level, method level, and finally up to statement level. The stepwise slicing algorithm and the related graph reachability algorithms are presented, the architecture of the Java program Analyzing TOol (JATO) based on hierarchical slicing model is provided, the applications and a small case study are also discussed.     

An Algebraic Hardware/Software Partitioning Algorithm

Hardware and software co-design is a design technique which delivers computer systems comprising hardware and software components.A critical phase of the co-design process is to decompose a program into hardware and software .This paper proposes an algebraic partitioning algorithm whose correctness is verified in program algebra.The authors inroduce a program analysis phase before program partitioning and deveop a collection of syntax-based splitting rules.The former provides the information for moving operations from software to hardware and reducing the interaction between compoents,and th latter supports a compositional approach to program partitioning.     

Improving WCET by applying worst-case path optimizations

It is advantageous to perform compiler optimizations that attempt to lower the worst-case execution time (WCET) of an embedded application since tasks with lower WCETs are easier to schedule and more likely to meet their deadlines. Compiler writers in recent years have used profile information to detect the frequently executed paths in a program and there has been considerable effort to develop compiler optimizations to improve these paths in order to reduce the average-case execution time (ACET). In this paper, we describe an approach to reduce the WCET by adapting and applying optimizations designed for frequent paths to the worst-case (WC) paths in an application. Instead of profiling to find the frequent paths, our WCET path optimization uses feedback from a timing analyzer to detect the WC paths in a function. Since these path-based optimizations may increase code size, the subsequent effects on the WCET due to these optimizations are measured to ensure that the worst-case path optimizations actually improve the WCET before committing to a code size increase. We evaluate these WC path optimizations and present results showing the decrease in WCET versus the increase in code size. A preliminary version of this paper entitled “Improving WCET by optimizing worst-case paths” appeared in the 2005 Real-Time and Embedded Technology and Applications Symposium. Wankang Zhao received his PhD in Computer Science from Florida State University in 2005. He was an associate professor in Nanjin University of Post and Telecommunications. He is currently working for Datamaxx Corporation. William Kreahling received his PhD in Computer Science from Florida State University in 2005. He is currently an assistant professor in the Math and Computer Science department at Western Carolina University. His research interests include compilers, computer architecture and parallel computing. David Whalley received his PhD in CS from the University of Virginia in 1990. He is currently the E.P. Miles professor and chair of the Computer Science department at Florida State University. His research interests include low-level compiler optimizations, tools for supporting the development and maintenance of compilers, program performance evaluation tools, predicting execution time, computer architecture, and embedded systems. Some of the techniques that he developed for new compiler optimizations and diagnostic tools are currently being applied in industrial and academic compilers. His research is currently supported by the National Science Foundation. More information about his background and research can be found on his home page, http://www.cs.fsu.edu/∼whalley. Dr. Whalley is a member of the IEEE Computer Society and the Association for Computing Machinery. Chris Healy earned a PhD in computer science from Florida State University in 1999, and is currently an associate professor of computer science at Furman University. His research interests include static and parametric timing analysis, real-time and embedded systems, compilers and computer architecture. He is committed to research experiences for undergraduate students, and his work has been supported by funding from the National Science Foundation. He is a member of ACM and the IEEE Computer Society. Frank Mueller is an Associate Professor in Computer Science and a member of the Centers for Embedded Systems Research (CESR) and High Performance Simulations (CHiPS) at North Carolina State University. Previously, he held positions at Lawrence Livermore National Laboratory and Humboldt University Berlin, Germany. He received his Ph.D. from Florida State University in 1994. He has published papers in the areas of embedded and real-time systems, compilers and parallel and distributed systems. He is a founding member of the ACM SIGBED board and the steering committee chair of the ACM SIGPLAN LCTES conference. He is a member of the ACM, ACM SIGPLAN, ACM SIGBED and the IEEE Computer Society. He is a recipient of an NSF Career Award.     

Extracting frequent connected subgraphs from large graph sets

Mining frequent patterns from datasets is one of the key success of data mining research. Currently,most of the studies focus on the data sets in which the elements are independent, such as the items in the marketing basket. However, the objects in the real world often have close relationship with each other. How to extract frequent patterns from these relations is the objective of this paper. The authors use graphs to model the relations, and select a simple type for analysis. Combining the graph theory and algorithms to generate frequent patterns, a new algorithm called Topology, which can mine these graphs efficiently, has been proposed.The performance of the algorithm is evaluated by doing experiments with synthetic datasets and real data. The experimental results show that Topology can do the job well. At the end of this paper, the potential improvement is mentioned.     

Segmentation of stick text based on sub connected area analysis

A new stick text segmentation method based on the sub connected area analysis is introduced in this paper.The foundation of this method is the sub connected area representation of text image that can represent all connected areas in an image efficiently.This method consists mainly of four steps:sub connected area classification,finding initial boundary following point,finding optimal segmentation point by boundary tracing,and text segmentaton.This method is similar to boundary analysis method but is more efficient than boundary analysis.     

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.     

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.     

Efficient mining of association rules by reducing the number of passes over the database

This paper introduces a new algorithm of mining association rules.The algorithm RP counts the itemsets with different sizes in the same pass of scanning over the database by dividing the database into m partitions.The total number of pa sses over the database is only(k 2m-2)/m,where k is the longest size in the itemsets.It is much less than k .     

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%.     

Real-time arithmetic unit

In this paper we discuss the paradigm of real-time processing on the lower level of computing systems. An arithmetical unit based on this principle containing addition, multiplication, division and square root operations is described. The development of the computation operators model is based on the imprecise computation paradigm and defines the concept of the adjustable calculation of a function that manages delay and the precision of the results as an inherent and parameterized characteristic. The arithmetic function design is based on well-known algorithms and offers progressive improvement in the results. Advantages in the predictability of calculations are obtained by means of processing groups of k-bits atomically and by using look-up tables. We report an evaluation of the operations in path time, delay and computation error. Finally, we present an example of our real-time architecture working in a realistic context. Higinio Mora-Mora received the BS degree in computer science engineering and the BS degree in business studies in University of Alicante, Spain, in 1996 and 1997, respectively. He received the PhD degree in computer science from the University of Alicante in 2003. Since 2002, he is a member of the faculty of the Computer Technology and Computation Department at the same university where he is currently an associate professor and researcher of Specialized Processors Architecture Laboratory. His areas of research interest include computer arithmetic and the design of floating points units and approximation algorithms related to VLSI design. Jerónimo Mora-Pascual received the BS degree in computer science engineering from University of Valencia (Spain), in 1994. Since 1994, he has been a member of the faculty of the Computer Technology and Computation department at the University of Alicante, where he is currently an associate professor. He completed his PhD in computer science at University of Alicante in 2001. He has worked on neural networks and its VLSI implementation. His current areas of research interest include the design of floating points units and its application for real-time systems and processors for geometric calculus. Juan Manuel García-Chamizo received his BS in physics at the University of Granada (Spain) in 1980, and the PhD degree in Computer Science at the University of Alicante (Spain) in 1994. He is currently a full professor and director of the Computer Technology and Computation department at the University of Alicante. His current research interests are computer vision, reconfigurable hardware, biomedical applications, computer networks and architectures and artificial neural networks. He has directed several research projects related to the above-mentioned interest areas. He is a member of a Spanish Consulting Commission on Electronics, Computer Science and Communications. He is also member and editor of some program committee conferences. Antonio Jimeno-Morenilla is associate professor in the Computer Technology and Computation department at the University of Alicante (Spain). He received his PhD from the University of Alicante in 2003. He concluded his bachelor studies at the EPFL (Ecole Polytechnique Fe’de’rale de Lausanne, Switzerland) and received his BS degree in computer science from the Polytechnical University of Valencia (Spain) in 1994. His research interests include sculptured surface manufacturing, CAD/CAM, computational geometry for design and manufacturing, rapid and virtual prototyping, 3D surface flattening, and high performance computer architectures. He has considerable experience in the development of 3D CAD systems for shoes. In particular, he has been involved in many government and industrial funded projects, most of them in collaboration with the Spanish Footwear Research Institute (INESCOP).     

A Novel Computer Architecture to Prevent Destruction by Viruses

In today‘s Internet computing world,illegal activities by crackers pose a serious threat to computer security.It is well known that computer viruses,Trojan horses and other intrusive programs may cause sever and often catastrophic consequences. This paper proposes a novel secure computer architecture based on security-code.Every instruction/data word is added with a security-code denoting its security level.External programs and data are automatically addoed with security-code by hadware when entering a computer system.Instruction with lower security-code cannot run or process instruction/data with higher security level.Security-code cannot be modified by normal instruction.With minor hardware overhead,then new architecture can effectively protect the main computer system from destruction or theft by intrusive programs such as computer viruses.For most PC systems it includes an increase of word-length by 1 bit on register,the memory and the hard disk.     

Provisioning QoS guarantee by multipath routing and reservation in Ad hoc networks

In this paper, a QoS multipath source routing protocol (QoS-MSR) is proposed for ad hoc networks. It can collect QoS information through route discovery mechanism of multipath source routing (MSR) and establish QoS route with reserved bandwidth. In order to reserve bandwidth efficiently, a bandwidth reservation approach called the multipath bandwidth splitting reservation (MBSR) is presented, under which the overall bandwidth request is split into several smaller bandwidth requests among multiple paths. In simulations, the anthors introduce Insignia, an in-bind signaling system that supports QoS in ad hoc networks, and extend it to multipath Insignia (M-Insignia) with QoS-MSR and MBSR. The results show that QoS-MSR routing protocol with the MBSR algorithm can improve the call admission ratio of QoS traffic, the packet delivery ratio, and the end-to-end delay of both best-effort traffic and QoS traffic. Therefore, QoS-MSR with MBSR is an efficient mechanism that supports QoS for ad hoc networks.     

Efficient Computation of k-Medians over Data Streams Under Memory Constraints

In this paper, we study the problem of efficiently computing k-medians over high-dimensional and high speed data streams. The focus of this paper is on the issue of minimizing CPU time to handle high speed data streams on top of the requirements of high accuracy and small memory. Our work is motivated by the following observation： the existing algorithms have similar approximation behaviors in practice, even though they make noticeably different worst case theoretical guarantees. The underlying reason is that in order to achieve high approximation level with the smallest possible memory, they need rather complex techniques to maintain a sketch, along time dimension, by using some existing off-line clustering algorithms. Those clustering algorithms cannot guarantee the optimal clustering result over data segments in a data stream but accumulate errors over segments, which makes most algorithms behave the same in terms of approximation level, in practice. We propose a new grid-based approach which divides the entire data set into cells （not along time dimension）. We can achieve high approximation level based on a novel concept called （1 - ε）-dominant. We further extend the method to the data stream context, by leveraging a density-based heuristic and frequent item mining techniques over data streams. We only need to apply an existing clustering once to computing k-medians, on demand, which reduces CPU time significantly. We conducted extensive experimental studies, and show that our approaches outperform other well-known approaches.     

Speech Detection in Non-Stationary Noise Based on the 1/f Process

In this paper,an effective and robust active speech detection method is proposed based on the 1/f process technique for signals under non-stationary noisy environments.The Gaussian 1/f process ,a mathematical model for statistically self-similar radom processes based on fractals,is selected to model the speech and the background noise.An optimal Bayesian two-class classifier is developed to discriminate them by their 1/f wavelet coefficients with Karhunen-Loeve-type properties.Multiple templates are trained for the speech signal,and the parameters of the background noise can be dynamically adapted in runtime to model the variation of both the speech and the noise.In our experiments,a 10-minute long speech with different types of noises ranging from 20dB to 5dB is tested using this new detection method.A high performance with over 90% detection accuracy is achieved when average SNR is about 10dB.     

Self-stabilizing depth-first token circulation on networks

Summary This paper proposes a self-stabilizing protocol which circulates a token on a connected network in nondeterministic depth-first-search order, rooted at a special node. Starting with any initial state in which the network may have no token at all or more than one token, the protocol eventually makes the system stabilize in states having exactly one circulating token. With a slight modification to the protocol —by removing nondeterminism in the search — a depth-first-search tree on the network can be constructed. The proposed protocol runs on systems that allow parallel operations. Shing-Tsaan Huang was born in Taiwan on September 4, 1949. He got his Ph.D. degree in 1985 from Department of Computer Science, University of Maryland at College Park. Before he pursued his Ph.D. degree, he had worked several years in the computer industry in Taiwan. Professor Huang is currently the chairman of the Department of Computer Science, Tsing Hua University, Taiwan, Republic of China. His research interests include interconnection networks, operating systems and distributed computing. He is a senior member of the IEEE Computer Society and a member of the Association for Computing Machinery. Nian-Shing Chen was born in Taiwan on October 21, 1961. He received his Ph.D. degree in computer science from National Tsing Hua University in 1990. Dr. Chen is currently an associate professor with the Department of Information Management at Sun Yat-Sen University of Taiwan. His research interests include distributed systems, computer networks, computer viruses and expert systems. He is a member of IEEE and Phi Tau Phi honorary society.This research is supported by National Science Council of the Republic of China under the contract NSC81-0408-E-007-05 and NSC82-0408-E-007-027