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.     

BCL—3：Aigh Performance Basic Communication Protocol for Commodity Superserver DAWNING—3000

This paper introduces the design and implemetation of BCL-3,a high performance low-level communication software running on a cluster of SMPs(CLUMPS) called DAWNING-3000,BCL-3 provides flexible and sufficient functionality to fulfill the communication requirements of fundamental system software developed for DAWNING-3000 while guaranteeing security,scalability,and reliability,Important features of BCL-3 are presented in the paper,including special support for SMP and heterogeneous network environment,semiuser-level communication,reliable and ordered data transfer and scalable flow control,The performance evaluation of BCL-3 over Myrinet is also given.     

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 .     

A Personalized Information Dissemination System Based on How—Net

The information dissemination model is becoming increasingly important in wide-area information systems,In this model,a user subscribes to an information dissemination service by submitting profiles that describe his interests.There have been several simple kinds of information dissemination services on the Internet such as mailing list,but the problem is that it provides a crude granularity of interest matching.A user whose information need does not exactly match certain lists will either receive too many irrelevant or too few relevant messages.This paper presents a personalized information dissemination model based on HowNet,which uses a Concept Network-Views(CN-V) model to support information filtering,user‘s interests modeling and information recommendation.A Concept Network is constructed upon the user‘s profiles and the content of documents,which describes concepts and their relations in the content and assigns different weights to these concepts.Usually the Concept Network is not well arranged,from which it is hard to find some useful realtions.so several views from are extracted it to represent the important relations explicitly.     

Digital Image Watermarking Based on Discrete Wavelet Transform

This paper aims at digital watermark which is a new popular research topic recently,presents some methods to embed digital watermark based on modifying frequency coefficients in discrete wavelet transform(DWT) domian,Fist,the,the present progress of digital watermark is briefly introduced;after that,starting from Pitas‘s method and discarding his pseudo random number method,the authors use a digital image scrambling technology as preprocessing for digital watermarking ,Then the authors discuss how to embed a 1-bit digital image as watermark in frequency domain.Finally another digital watermarking method is given in which3-D DWT is used to transform a given digtial image .Based on the experimental results ,it is shown that the proposed methods are robust to a large extent.     

OpenMP on Networks of Workstations for Software DSMs

This paper describes the implementation of a sizable subset of OpenMP on networks of workstations(NOWs) and the source-to-source OpenMP complier(AutoPar） is used for the JIAJIA home-based shared virtual memory system (SVM).The paper suggests some simple modifications and extensions to the OpenMP standard for the difference between SVM and SMP(symmetric multi processor),at which the OpenMP specification is aimed.The OpenMP translator is based on an automatic paralleization compiler,so it is possible to check the correctness of the semantics of OpenMP programs which is not required in an OpenMP-compliant implementation AutoPar is measured for five applications including both programs from NAS Parallel Benchmarks and real applications on a cluster of eight Pentium Ⅱ PCs connected by a 100 Mbps switched Eternet.The evaluation shows that the parallelization by annotaing OpenMPdirectives is simple and the performance of generatd JIAJIA code is still acceptable on NOWs.     

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.     

Dyanmic Data Prefetching in Home—Based Software DSMs

A major overhead in software DSM(Distributed Shared Memory)is the cost of remote memory accesses necessitated by the protocol as well as induced by false sharing.This paper introduces a dynamic prefetching method implemented in the JIAJIA software DSM to reduce system overhead caused by remote accesses.The prefetching method records the interleaving string of INV(invalidation)and GETP (getting a remote page)operations for each cached page and analyzes the periodicity of the string when a page is invalidated on a lock or barrier.A prefetching request is issued after the lock or barrier if the periodicity analysis indicates that GETP will be the next operation in the string.Multiple prefetching requests are merged into the same message if they are to the same host,Performance evaluation with eight well-accepted benchmarks in a cluster of sixteen PowerPC workstations shows that the prefetching scheme can significantly reduce the page fault overhead and as a result achieves a performance increase of 15%-20% in three benchmarks and around 8%-10% in another three.The average extra traffic caused by useless prefetches is only 7%-13% in the evaluation.     

Automatic Segmentation of News Items Based on Video and Audio Features

The automatic segmentation of news items is a key for implementing the automatic cataloging system of news video.This paper presents an approach which manages audio and video feature infomation to automatically segment news items.The integration of audio and visual analyses can overcome the weakness of the approach using only image analysis techniques.It makes the approach more adaptable to various situations of news items.The proposed approach detects silence segments in accompanying audio,and integrates them with shot segmentation results,as ewll as anchor shot detection results,to determine the boundaries among news items,Expeimental results show that the integration of audio and video features is an effective approach to solving the problem of automatic segmentation of news items.     

An Efficient VLSI Architecture for Motion Compensation of AVS HDTV Decoder

In the part 2 of advanced Audio Video coding Standard （AVS-P2）, many efficient coding tools are adopted in motion compensation, such as new motion vector prediction, symmetric matching, quarter precision interpolation, etc. However, these new features enormously increase the computational complexity and the memory bandwidth requirement, which make motion compensation a difficult component in the implementation of the AVS HDTV decoder. This paper proposes an efficient motion compensation architecture for AVS-P2 video standard up to the Level 6.2 of the Jizhun Profile. It has a macroblock-level pipelined structure which consists of MV predictor unit, reference fetch unit and pixel interpolation unit. The proposed architecture exploits the parallelism in the AVS motion compensation algorithm to accelerate the speed of operations and uses the dedicated design to optimize the memory access. And it has been integrated in a prototype chip which is fabricated with TSMC 0.18-#m CMOS technology, and the experimental results show that this architecture can achieve the real time AVS-P2 decoding for the HDTV 1080i （1920 - 1088 4 ： 2 ： 0 60field/s） video. The efficient design can work at the frequency of 148.5MHz and the total gate count is about 225K.     

Leakage current estimation of CMOS circuit with stack effect

Leakage current of CMOS circuit increases dramatically with the technology scaling down and has become a critical issue of high performance system. Subthreshold, gate and reverse biased junction band-to-band tunneling (BTBT) leakages are considered three main determinants of total leakage current. Up to now, how to accurately estimate leakage current of large-scale circuits within endurable time remains unsolved, even though accurate leakage models have been widely discussed. In this paper, the authors first dip into the stack effect of CMOS technology and propose a new simple gate-level leakage current model. Then, a table-lookup based total leakage current simulator is built up according to the model. To validate the simulator, accurate leakage current is simulated at circuit level using popular simulator HSPICE for comparison. Some further studies such as maximum leakage current estimation, minimum leakage current generation and a high-level average leakage current macromodel are introduced in detail. Experiments on ISCAS85 and ISCAS89 benchmarks demonstrate that the two proposed leakage current estimation methods are very accurate and efficient.     

Test Resource Partitioning Based on Efficient Response Compaction for Test Time and Tester Channels Reduction

This paper presents a test resource partitioning technique based on an efficient response compaction design called quotient compactor(q-Compactor). Because q-Compactor is a single-output compactor, high compaction ratios can be obtained even for chips with a small number of outputs. Some theorems for the design of q-Compactor are presented to achieve full diagnostic ability, minimize error cancellation and handle unknown bits in the outputs of the circuit under test (CUT). The q-Compactor can also be moved to the load-board, so as to compact the output response of the CUT even during functional testing. Therefore, the number of tester channels required to test the chip is significantly reduced. The experimental results on the ISCAS ‘89 benchmark circuits and an MPEG 2 decoder SoC show that the proposed compactionscheme is very efficient.     

Hybrid Broadcast for the Video-on-Demand Service

Multicast offers an efficient means of distributing video contents/programs to multiple clients by batching their requests and then having them share a server‘s video stream.Batching customers‘ requests is either client-initiated or server-initiated.Most anvanced client-initiated video multicasts are implemented by patching.Periodic broadcast,a typical server-initiated approach,can be entirety-based or segment-based.This paper focuses on the performance of the VoD service for popular videos.First,we analyze the limitation of conventional patching when the customer request rate is high.Then,By combining the advantages of each of the two broadcast schemes,we propose a hybrid broadcast scheme for popular videos ,which not only lowers the serviec latency but also improves clients‘ interactivity by using an active buffering technique ,This is shown to be a good compromise for both lowering service latency and improving the VCR-like interactivity.     

Formal Ontology: Foundation of Domain Knowledge Sharing and Reusing

Domain analysis is the activity of identifying and representing the relevant information in a domain,so that the information can be shared and reused in similar systems.But until now,no efficient approaches are available for capturing and representing the results of domain analysis and then for sharing and reusing the domain knowledge.This paper proposes an ontology-oriented approach for formalizing the domain models.The architecture for the multiple-layer structure of the domain knowledge base is also discussed.And finally,some genetic algorithm-based methods have been given for supporting the knowledge sharing and reusing.     

Kernel Projection Algorithm for Large-Scale SVM Problems

Support Vector Machine (SVM) has become a very effective method in statistical machine learning and it has proved that training SVM is to solve Nearest Point pair Problem (NPP) between two disjoint closed convex sets.Later Keerthi pointed out that it is difficult to apply classical excellent geometric algorithms directly to SVM and so designed a new geometric algorithm for SVM.In this article,a new algorithm for geometrically solving SVM,Kernel Projection Algorithm,is presented based on the theorem on fixed-points of projection mapping.This new algorithm makes it easy to apply classical geometric algorithms to solving SVM and is more understandable than Keerthi‘s.Experiments show that the new algorithm can also handle large-scale SVM problems.Geometric algorithms for SVM,such as Keerthi‘s algorithm,require that two closed convex sets be disjoint and otherwise the algorithms are meaningless.In this article,this requirement will be guaranteed in theory be using the theoretic result on universal kernel functions.     

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 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.     

On efficiently summarizing categorical databases

Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its application to transaction or document clustering. However, most of the frequent itemset based clustering algorithms need to first mine a large intermediate set of frequent itemsets in order to identify a subset of the most promising ones that can be used for clustering. In this paper, we study how to directly find a subset of high quality frequent itemsets that can be used as a concise summary of the transaction database and to cluster the categorical data. By exploring key properties of the subset of itemsets that we are interested in, we proposed several search space pruning methods and designed an efficient algorithm called SUMMARY. Our empirical results show that SUMMARY runs very fast even when the minimum support is extremely low and scales very well with respect to the database size, and surprisingly, as a pure frequent itemset mining algorithm it is very effective in clustering the categorical data and summarizing the dense transaction databases. Jianyong Wang received the Ph.D. degree in computer science in 1999 from the Institute of Computing Technology, the Chinese Academy of Sciences. Since then, he ever worked as an assistant professor in the Department of Computer Science and Technology, Peking (Beijing) University in the areas of distributed systems and Web search engines, and visited the School of Computing Science at Simon Fraser University, the Department of Computer Science at the University of Illinois at Urbana-Champaign, and the Digital Technology Center and the Department of Computer Science at the University of Minnesota, mainly working in the area of data mining. He is currently an associate professor of the Department of Computer Science and Technology at Tsinghua University, P.R. China. George Karypis received his Ph.D. degree in computer science at the University of Minnesota and he is currently an associate professor at the Department of Computer Science and Engineering at the University of Minnesota. His research interests spans the areas of parallel algorithm design, data mining, bioinformatics, information retrieval, applications of parallel processing in scientific computing and optimization, sparse matrix computations, parallel preconditioners, and parallel programming languages and libraries. His research has resulted in the development of software libraries for serial and parallel graph partitioning (METIS and ParMETIS), hypergraph partitioning (hMETIS), for parallel Cholesky factorization (PSPASES), for collaborative filtering-based recommendation algorithms (SUGGEST), clustering high dimensional datasets (CLUTO), and finding frequent patterns in diverse datasets (PAFI). He has coauthored over ninety journal and conference papers on these topics and a book title “Introduction to Parallel Computing” (Publ. Addison Wesley, 2003, 2nd edition). In addition, he is serving on the program committees of many conferences and workshops on these topics and is an associate editor of the IEEE Transactions on Parallel and Distributed Systems.     

Blending parametric patches with subdivision surfaces

In this paper the problem of blending parametric surfaces using subdivision patches is discussed.A new approach,named removing-boundary,is presented to generate piecewise-smooth subdivision surfaces through discarding the outmost quadrilaterals of the open meshes derived by each subdivision step.Then the approach is employed both to blend parametric bicubic B-spline surfaces and to fill n-sided holes.It is easy to produce piecewise-smooth subdivision surfaces with both convex and concave corners on the boundary,and limit surfaces are guaranteed to be C^2 continuous on the boundaries except for a few singular points by the removing-boundary approach Thus the blending method is very efficient and the blending surface generated is of good effect.