A General Probability Formula of the Number of Location Areas Boundaries Crossed by a Mobile Between Two Successive Call Arrivals

Mobility management is a challenging topic in mobile computing environment. Studying the situation of mobiles crossing the boundaries of location areas is significant for evaluating the costs and performances of various location management strategies. Hitherto, several formulae were derived to describe the probability of the number of location areas' boundaries crossed by a mobile. Some of them were widely used in analyzing the costs and performances of mobility management strategies. Utilizing the density evolution method of vector Markov processes, we propose a general probability formula of the number of location areas' boundaries crossed by a mobile between two successive calls. Fortunately, several widely-used formulae are special cases of the proposed formula.     

SmallWorld Model-Based Polylogarithmic Routing Using Mobile Nodes

The use of mobile nodes to improve network system performance has drawn considerable attention recently. The movement-assisted model considers mobility as a desirable feature,where routing is based on the store-carry-forward paradigm with random or controlled movement of resource rich mobile nodes.The application of such a model has been used in several emerging networks,including mobile ad hoc networks(MANETs),wireless sensor networks(WSNs),and delay tolerant networks(DTNs).It is well known that mobility increases the capacity of MANETs by reducing the number of relays for routing,prolonging the lifespan of WSNs by using mobile nodes in place of bottleneck static sensors,and ensuring network connectivity in DTNs using mobile nodes to connect different parts of a disconnected network.Trajectory planning and the coordination of mobile nodes are two important design issues aiming to optimize or balance several measures, including delay,average number of relays,and moving distance.In this paper,we propose a new controlled mobility model with an expected polylogarithmic number of relays to achieve a good balance among several contradictory goals,including delay,the number of relays,and moving distance.The model is based on the small-world model where each static node has"short"link connections to its nearest neighbors and"long"link connections to other nodes following a certain probability distribution.Short links are regular wireless connections whereas long links are implemented using mobile nodes.Various issues are considered,including trade-offs between delay and average number of relays,selection of the number of mobile nodes,and selection of the number of long links.The effectiveness of the proposed model is evaluated analytically as well as through simulation.     

Approximate K-Median of Location Streams with Redundancy and Inconsistency

Data streams produced by positioning systems such as Global Positioning System (GPS) or RFID readers can be considered as location streams[12]. Location streams are usually generated in a distributed fashion by a large scale distributed system covering a wide range of areas. Computing on distributed location streams is both practically useful and theoretically challenging. The results of computation could be used to schedule the traffic in a metropolis to avoid traffic jam, dispatch taxis to serve the passengers more quickly and display the current position of goods in supply chain management, etc. Since location streams are usually generated with very high rate in uncertain ways over hostile environments, the collected updates of location are probably redundant and inconsistent in a wide positioning system. To process distributed location streams with redundancy and inconsistency, this paper proposes a novel method based on min-wise hash. With this method, redundant updates of distributed location streams can be effiectively filtered out, while the true location could be derived from inconsistent ones. Consequently, globally uniform samples can be obtained. Based on the uniform samples, an algorithm for computing the approximate k-median of huge number of moving objects is presented in this paper. Furthermore, it is demonstrated that sketch-based methods are not necessarily effiective in processing location streams with redundancy and inconsistency. In addition to theoretical analysis, some extensive experiments are conducted to validate the efficiency and effiectiveness of the proposed approach.     

A Fast Defects Location Method in ICT Images Based on Block Fractal Dimension

Non-destructive testing(NDT) has been widely used in many fields, we can easily see it is being used in shipbuilding, aerospace, weapons manufacturing and so on. ICT is one of the best non destructive testing methods currently, but it has not been used widely, because it requires much compute and costs much time. Defect location is one of the most important processing steps in the digital image analysis. Defect location would correspondingly reduce the time spent in the testing. We may only require locating the defects in some case. So, we divide the CT images into several little blocks which the square is equal, and then calculate the fractal on each block. By determining the value and connected region number of the fractal dimension, we can locate defects of the image. The results show that the block fractal dimension is a useful and time-saving defect location method.     

Methodological Approaches to Development and Implementation of Multi-agents Investment DSS Using JADE Platform

In these latter days software agents are used for the development and implementation of intellectual decision support systems. In order to implement intelligence in a system some or several dozen of software agents are used and the made system becomes multi-agent. For the development of these systems a set of methodologies, i.e., the sequence of consequent steps of analysis, designing and implementation, is offered. The carried out analysis of the methodologies showed that as a rule they are limited by the spectrum of their pending problem （within the pales of the requirements of specific applied task, within the pales of the possibilities of technical implementation） or within the pales of amount of detail. The variety of methodologies is influenced by the fact that for the development of these systems the requirements and attitudes are offered by the specialists of related spheres such as software, numeral intellect engineers. In the course of the development of hardware and software appeared possibilities to implement mobile multi-agents systems, however, there is no one united mobile multi-agent systems design methodology, whereas existing systems are underdeveloped and their number is small. In this article we introduce the course of the designing of an intellectual real time multi-agent investment management decision support information system adapting and combining some methodologies where the choice to use either communicating or mobile agents is the question of rather technical implementation than methodological. In the article we introduce two ways of system implementation by JADE platform： the first one-using communicating agents, and the second one-using mobile agents.     

Modular supervisory control for multi-floor manufacturing processes

Due to space availability limitations and high land costs, there is an increasing development of multi-floor manufacturing (MFM) systems in urban and industrial areas. The problem of coordination in a multi-floor manufacturing process, in the Ramadge Wonham framework, is introduced. The manufacturing chain of each floor and the elevator system are modeled in the form of finite deterministic automata. The models of the multi-floor manufacturing process are parametric with respect to the number of floors and the number of manufacturing machines on each floor. The coordination desired performance is formulated in the form of desired regular languages in analytic forms. The languages are realized by appropriate supervisors in the form of finite deterministic automata. The models of the supervisors are also parametric with respect to the number of floors and the number of manufacturing machines on each floor. The total control of the coordination of the multi-floor manufacturing process is accomplished via a modular supervisory control architecture. The complexity of the supervisors as well as the complexity of the total modular supervisory architecture are determined in analytic forms with respect to the number of floors and the number of manufacturing machines on each floor. The special case of a two floor manufacturing process is presented as an illustrative example.     

The number of spanning trees in a new lexicographic product of graphs

The problem of counting the number of spanning trees is an old topic in graph theory with important applications to reliable network design. Usually, it is desirable to put forward a formula of the number of spanning trees for various graphs, which is not only interesting in its own right but also in practice. Since some large graphs can be composed of some existing smaller graphs by using the product of graphs, the number of spanning trees of such large graph is also closely related to that of the corresponding smaller ones. In this article, we establish a formula for the number of spanning trees in the lexicographic product of two graphs, in which one graph is an arbitrary graph G and the other is a complete multipartite graph. The results extend some of the previous work, which is closely related to the number of vertices and Lapalacian eigenvalues of smaller graphs only.     

A cost effective fault-tolerant scheme for RAIDs

The rapid progress in mass storage technology has made it possible for designers to implement large data storage systems for a variety of applications.One of the efficient ways to build large storage systems is to use RAIDs only when one error occurs .But in large RAIDs systems ,the fault probability will increase when the number of disks increases ,and the use of disks with big storage capacity will cause the recovering time to prolong,thus the probability of the second disk‘‘‘‘‘‘‘‘s fault will incerease Therefore,it is necessary to develop methods to recover data when two or more errors have occurred In this paper,a fault tolerant scheme is proposed based on extended Reed-Solomon code,a recovery procedure is designed to correct up to two errors which is implemented by software and hardware together,and the scheme is verified by computer simulation,In this scheme,only two redundant disks are used to recover up to two disks‘‘‘‘‘‘‘‘ fault .The encoding and decoding methods,and the implementation based on software and hardware are described.The application of the scheme in software RAIDs that are builit in cluster computers are also described .Compared with the existing methods such as EVENODD and DH ,the proposed scheme has distinct improvement in implementation and redundancy.     

Improving Software Quality Prediction by Noise Filtering Techniques

Accuracy of machine learners is affected by quality of the data the learners are induced on. In this paper, quality of the training dataset is improved by removing instances detected as noisy by the Partitioning Filter. The fit dataset is first split into subsets, and different base learners are induced on each of these splits. The predictions are combined in such a way that an instance is identified as noisy if it is misclassified by a certain number of base learners. Two versions of the Partitioning Filter are used： Multiple-Partitioning Filter and Iterative-Partitioning Filter. The number of instances removed by the filters is tuned by the voting scheme of the filter and the number of iterations. The primary aim of this study is to compare the predictive performances of the final models built on the filtered and the un-filtered training datasets. A case study of software measurement data of a high assurance software project is performed. It is shown that predictive performances of models built on the filtered fit datasets and evaluated on a noisy test dataset are generally better than those built on the noisy （un-filtered） fit dataset. However, predictive performance based on certain aggressive filters is affected by presence of noise in the evaluation dataset.     

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.     

Anti-aliased rendering of water surface

Water surface is one of the most important components of landscape scenes. When rendering spacious water surface such as that of the lakes and reservoirs, aliasing and/or moiré artifacts frequently occur in the regious far from the viewpoint. This is because water surface consists of stochastic water waves which are usually modeled by periodic bump mapping. The incident rays on the water surface are actually scattered by the bumped waves, and the reflected rays at each sample point are distributed in a solid angle. To get rid of the artifacts of moiré pattern, we estimate this solid angle of reflected rays and trace these rays. An image-based accelerating method is adopted so that the contribution of each reflected ray can be quickly obtained without elaborate intersection calculation. We also demonstrate anti-aliased shadows of sunlight and skylight on the water surface. Both the rendered images and animations show excellent effects on the water surface of a reservoir. The first, third and fifth co-authors were partially supported by the National Natural Science Foundation of China (Grant Nos. 60021201 and 60373035), Key Research Project of Ministry of Education (Grant No.01094) and the National Grand Fundamental Research 973 Program of China (Grant No.2002CB312102). Xue-Ying Qin is an associated professor of State Key Laboratory of CAD&CG, Zhejiang University. She received her Ph.D. degree from Hiroshima University in 2001, B.S. and M.S. degrees in Mathematics from Peking University in 1988 and from Zhejiang University in 1991, respectively. Her research interests include computer graphics, visions and image processing. Eihachiro Nakamae is currently Chairman of Sanei Co. He was granted the title of emeritus professor from both Hiroshima University and Hiroshima Institute of Technology. He was appointed as a researcher associate at Hiroshima University in 1956, a professor from 1968 to 1992 and an associated researcher at Clarkson College of Technology, Potsdam, N.Y., from 1973 to 1974. He was a professor at Hiroshima Prefectural University from 1992 to 1995 and a professor at Hiroshima Institute of Technology from a996 to the end of March 1999. He received his B.E., M.E., and Ph.D. degrees in electrical engineering in 1954, 1956, and 1967 from Waseda University. His research interests include computer graphics, image processing and electric machinery. He is a member of IEEE, ACM, CGS, Eurographics, IEE of Japan, and IPS of Japan. Wei Hua received his Ph.D. degree in applied mathematics from Zhejiang University in 2002. He joined the CAD&CG State Key Lab in 2002. His main interests include real-time simulation and rendering, virtual reality and software engineering. Yasuo Nagai is now an associate professor of Hiroshima Institute of Technology. He was appointed a researcher associate at Hiroshima Institute of Technology in 1965, and an associate professor in 1984. His research interests include computer graphics and image processing. He is a member of IEE, IEICE, IPSJ, and ITE of Japan. Qun-Sheng Peng was born in 1947. He received his Ph.D. degree in computer science from the University of East Anglia, U.K., in 1983. He is a professor and his research interests include computer graphics, computer animation, virtual reality, and point-based modeling and rendering.     

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.     

Performance analysis of active schedules in identical parallel machine

Active schedule is one of the most basic and popular concepts in production scheduling research. For identical parallel machine scheduling with jobs’ dynamic arrivals, the tight performance bounds of active schedules under the measurement of four popular objectives are respectively given in this paper. Similar analysis method and conclusions can be generalized to static identical parallel machine and single machine scheduling problem.     

Realistic modeling and animation of human body based on scanned data

In this paper we propose a novel method for building animation model of real human body from surface scanned data. The human model is represented by a triangular mesh and described as a layered geometric model. The model consists of two layers: the control skeleton generating body animation from motion capture data, and the simplified surface model providing an efficient representation of the skin surface shape. The skeleton is generated automatically from surface scanned data using the feature extraction, and then a point-to-line mapping is used to map the surface model onto the underlying skeleton. The resulting model enables real-time and smooth animation by manipulation of the skeleton while maintaining the surface detail. Compared with earlier approach, the principal advantages of our approach are the automated generation of body control skeletons from the scanned data for real-time animation, and the automatic mapping and animation of the captured human surface shape. The human model constructed in this work can be used for applications of ergonomic design,garment CAD, real-time simulating humans in virtual reality environment and so on.     

Tracking clusters in evolving data streams over sliding windows

Mining data streams poses great challenges due to the limited memory availability and real-time query response requirement. Clustering an evolving data stream is especially interesting because it captures not only the changing distribution of clusters but also the evolving behaviors of individual clusters. In this paper, we present a novel method for tracking the evolution of clusters over sliding windows. In our SWClustering algorithm, we combine the exponential histogram with the temporal cluster features, propose a novel data structure, the Exponential Histogram of Cluster Features (EHCF). The exponential histogram is used to handle the in-cluster evolution, and the temporal cluster features represent the change of the cluster distribution. Our approach has several advantages over existing methods: (1) the quality of the clusters is improved because the EHCF captures the distribution of recent records precisely; (2) compared with previous methods, the mechanism employed to adaptively maintain the in-cluster synopsis can track the cluster evolution better, while consuming much less memory; (3) the EHCF provides a flexible framework for analyzing the cluster evolution and tracking a specific cluster efficiently without interfering with other clusters, thus reducing the consumption of computing resources for data stream clustering. Both the theoretical analysis and extensive experiments show the effectiveness and efficiency of the proposed method. Aoying Zhou is currently a Professor in Computer Science at Fudan University, Shanghai, P.R. China. He won his Bachelor and Master degrees in Computer Science from Sichuan University in Chengdu, Sichuan, P.R. China in 1985 and 1988, respectively, and Ph.D. degree from Fudan University in 1993. He served as the member or chair of program committee for many international conferences such as WWW, SIGMOD, VLDB, EDBT, ICDCS, ER, DASFAA, PAKDD, WAIM, and etc. His papers have been published in ACM SIGMOD, VLDB, ICDE, and several other international journals. His research interests include Data mining and knowledge discovery, XML data management, Web mining and searching, data stream analysis and processing, peer-to-peer computing. Feng Cao is currently an R&D engineer in IBM China Research Laboratories. He received a B.E. degree from Xi'an Jiao Tong University, Xi'an, P.R. China, in 2000 and an M.E. degree from Huazhong University of Science and Technology, Wuhan, P.R. China, in 2003. From October 2004 to March 2005, he worked in Fudan-NUS Competency Center for Peer-to-Peer Computing, Singapore. In 2006, he received his Ph.D. degree from Fudan University, Shanghai, P.R. China. His current research interests include data mining and data stream. Weining Qian is currently an Assistant Professor in computer science at Fudan University, Shanghai, P.R. China. He received his M.S. and Ph.D. degree in computer science from Fudan University in 2001 and 2004, respectively. He is supported by Shanghai Rising-Star Program under Grant No. 04QMX1404 and National Natural Science Foundation of China (NSFC) under Grant No. 60673134. He served as the program committee member of several international conferences, including DASFAA 2006, 2007 and 2008, APWeb/WAIM 2007, INFOSCALE 2007, and ECDM 2007. His papers have been published in ICDE, SIAM DM, and CIKM. His research interests include data stream query processing and mining, and large-scale distributed computing for database applications. Cheqing Jin is currently an Assistant Professor in Computer Science at East China University of Science and Technology. He received his Bachelor and Master degrees in Computer Science from Zhejiang University in Hangzhou, P.R. China in 1999 and 2002, respectively, and the Ph.D. degree from Fudan University, Shanghai, P.R. China. He worked as a Research Assistant at E-business Technology Institute, the Hong Kong University from December 2003 to May 2004. His current research interests include data mining and data stream.     

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.     

A Transactional Asynchronous Replication Scheme for Mobile Database Systems

In mobile database systems,mobility of users has a significant impact on data replication.As a result,the various replica control protocols that exist today in traditional distributed and multidatabase environments are no longer suitable To solve this problem,a new mobile database replication scheme,the Transaction-Level Result-Set Propagation(TLRSP)model,is put forward in this paper,The conflict dectction and resolution strategy based on TLRSP is discussed in detail,and the implementation algorithm is proposed,In order to compare the performance of the TLRSP model with that of other mobile replication schemes,we have developed a detailde simulation model.Experimantal results show that the TLRSP model provides an effcient support for replicated mobile database systems by reducing reprocessing overhead and maintaining database consistency.     

Handling non-canonical software requirements based on Annotated Predicate Calculus

Eliciting requirements for a proposed system inevitably involves the problem of handling undesirable information about customer's needs, including inconsistency, vagueness, redundancy, or incompleteness. We term the requirements statements involved in the undesirable information non-canonical software requirements. In this paper, we propose an approach to handling non-canonical software requirements based on Annotated Predicate Calculus (APC). Informally, by defining a special belief lattice appropriate for representing the stakeholder's belief in requirements statements, we construct a new form of APC to formalize requirements specifications. We then show how the APC can be employed to characterize non-canonical requirements. Finally, we show how the approach can be used to handle non-canonical requirements through a case study. Kedian Mu received B.Sc. degree in applied mathematics from Beijing Institute of Technology, Beijing, China, in 1997, M.Sc. degree in probability and mathematical statistics from Beijing Institute of Technology, Beijing, China, in 2000, and Ph.D. in applied mathematics from Peking University, Beijing, China, in 2003. From 2003 to 2005, he was a postdoctoral researcher at Institute of Computing Technology, Chinese Academy of Sciences, China. He is currently an assistant professor at School of Mathematical Sciences, Peking University, Beijing, China. His research interests include uncertain reasoning in artificial intelligence, knowledge engineering and science, and requirements engineering. Zhi Jin was awarded B.Sc. in computer science from Zhejiang University, Hangzhou, China, in 1984, and studied for her M.Sc. in computer science (expert system) and her Ph.D. in computer science (artificial intelligence) at National Defence University of Technology, Changsha, China. She was awarded Ph.D. in 1992. She is a senior member of China Computer Federation. She is currently a professor at Academy of Mathematics and System Sciences, Chinese Academy of Science. Her research interests include knowledge-based systems, artificial intelligence, requirements engineering, ontology engineering, etc. Her current research focuses on ontology-based requirements elicitation and analysis. She has got about 60 papers published, including co-authoring one book. Ruqian Lu is a professor of computer science of the Institute of Mathematics, Chinese Academy of Sciences. His research interests include artificial intelligence, knowledge engineering and knowledge based software engineering. He designed the “Tian Ma” software systems that have been widely applied in more than 20 fields, including the national defense and the economy. He has won two first class awards from Chinese Academy of Sciences and a National second class prize from the Ministry of Science and Technology. He has also won the sixth Hua Lookeng Prize for Mathematics. Yan Peng received B.Sc. degree in software from Jilin University, Changchun, China, in 1992. From June 2002 to December 2005, he studied for his M.E. in software engineering at College of Software Engineering, Graduate School of Chinese Academy of Sciences, Beijing, China. He was awarded M.E degree in 2006. He is currently responsible for CRM (customer relationship management) and BI (business intelligence) project in the BONG. His research interests include customer relationship management, business intelligence, data ming, software engineering and requirements engineering.     

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.