9510053
DXEC: integrating database, XML and email for collaboration
This paper introduces DXEC, a database, XML and email enabled framework for better collaborative work. The framework use emails as the main collaboration medium, which are mainly generated automatically by OA applications and groupware systems. But instead of using them naively, each email in the system are wrapped in a XML envelop, which provides superior searching and filtering ability. Emails are stored in a XML enable database, and a XML filter engine is used to filter the incoming messages and disseminate them to relevant audiences. User profile in XPath, which can be specified by hand and refined through feedbacks, are used by the filter engine to ensure everyone received only interested messages. In this paper, we present the architecture of DXEC and introduce major components and important algorithms. We also demonstrate its use in software development process.
8340253
UGE4B: An Universal Grid Environment for Bioinformatics Research
Recent years, grid technology has been used widely in the fields of scientific research. In this paper, we present a universal grid environment for bioinformatics research (UGE4B). Although there have been several similar projects successfully constructed in the world, we need to meet some unique requirements from bioinformatics research in China. UGE4B consists of 6 components, including portal, task management, data management, information server, security and computing node. As a national-wide bioinformatics research platform, UGE4B is built through interconnecting multiple sub grids provided by each bioinformatics institutes. Besides provides a universal portal to end users for bioinformatics computing and data accessing, UGE4B also supported some special bioinformatics applications
5747087
Efficient Processing of Warping Time Series Join of Motion Capture Data
Discovering non-trivial matching subsequences from two time series is very useful in synthesizing novel time series. This can be applied to applications such as motion synthesis where smooth and natural motion sequences are often required to be generated from existing motion sequences. We first address this problem by defining it as a problem of l-e-join over two time series. Given two time series, the goal of l-e-join is to find those non-trivial matching subsequences by detecting maximal l-connections from the e-matching matrix of the two time series. Given a querying motion sequence, the l-e-join can be applied to retrieve all connectable motion sequences from a database of motion sequences. To support efficient l-e-join of time series, we propose a two-step filter-and-refine algorithm, called Warping Time Series Join (WTSJ) algorithm. The filtering step serves to prune those sparse regions of the e-matching matrix where there are no maximal l-connections without incurring costly computation. The refinement step serves to detect closed l-connections within regions that cannot be pruned by the filtering step. To speed up the computation of e-matching matrix, we propose a block-based time series summarization method, based on which the block-wise e-matching matrix is first computed. Lots of pairwise distance computation of elements can then be avoided by applying the filtering algorithm on the block-wise e-matching matrix.Extensive experiments on l-e-join of motion capture sequences are conducted. The results confirm the efficiency and effectiveness of our proposed algorithm in processing l-e-join of motion capture time series.
8051159
A Web-based Framework For On-line Collaborative Learning
This paper presents a framework for design of online courses and collaborative learning based on Web technologies. It provides the following features: construction of structured learning materials in a distributed environment; personalization of course contents in the run-time that adapts to the progress of individual students; it can supply relevant Web resources to the students by analyzing the learning history dynamically; students in a group could exchange their learning experiences and discover relevant knowledge via the communication channels provided by the framework. The proposed techniques could be deployed to a variety of online computer-assisted modules to improve the effectiveness of Web-based e-learning
26669443
Bottom-up discovery of frequent rooted unordered subtrees
In the past decade, XML has emerged as the standard language for information exchanging over the Internet. Due to its tree-structure paradigm, XML is superior for its capability of storing, querying, and manipulating complex data. Therefore, discovering frequent tree patterns over tree-structured data has become an interesting topic for XML data management. In this paper, we propose a tree mining algorithm, named BUXMiner, for finding a special class of frequent trees, called rooted unordered trees, from a tree-structured database. BUXMiner employs an efficient bottom-up approach to enumerate all candidate trees over a compact global tree guide and computes the frequent trees based on the tree guide. In addition to BUXMiner, we also propose a mining approach called BUMXMiner to discover the maximal frequent rooted unordered trees. We compare BUXMiner with previous tree-structure mining algorithms, namely XQPMinerTID and FastXMiner, which were also proposed to discover rooted unordered trees. The experimental results show that our algorithm outperforms XQPMinerTID and FastXMiner in terms of efficiency. The performance results from real-world applications also indicate the usefulness of our proposed tree mining algorithms in a variety of web applications, such as analysis of web page access patterns and mining frequent XML query patterns for caching.
116588251
On-line evolutionary exponential family mixture
This paper deals with evolutionary clustering, which refers to the problem of clustering data with distribution drifting along time. Starting from a density estimation view to clustering problems, we propose two general on-line frameworks. In the first framework, i.e., historical data dependent (HDD), current model distribution is designed to approximate both current and historical data distributions. In the second framework, i.e., historical model dependent (HMD), current model distribution is designed to approximate both current data distribution and historical model distribution. Both frameworks are based on the general exponential family mixture (EFM) model. As a result, all conventional clustering algorithms based on EFMs can be extended to evolutionary setting under the two frameworks. Empirical results validate the two frameworks.
7606399
A fuzzy image metric with application to fractal coding
Image quality assessment is an important issue addressed in various image processing applications such as image/video compression and image reconstruction. The peak signal-to-noise ratio (PSNR) with the L(2)-metric is commonly used in objective image quality assessment. However, the measure does not agree very well with the human visual perception in many cases. A fuzzy image metric (FIM) is defined based on Sugeno's (1977) fuzzy integral. This new objective image metric, which is to some extent a proper evaluation from the viewpoint of the judgment procedure, is closely approximates the subjective mean opinion score (MOS) with a correlation coefficient of about 0.94, as compared to 0.82 obtained using the PSNR. Compared to the L(2)-metric, we demonstrate that a better performance can be achieved in fractal coding by using the proposed FIM.
13807032
Coordinating Agents in Shop Floor Environments From a Dynamic Systems Perspective
In this paper, we address agent coordination from a dynamic systems perspective and propose a dynamic coordination model, which is inspired by biological metabolic systems. A new coordination mechanism through dynamic local adjustment (CDLA) is presented, and coordination is achieved when every agent utilizes explicitly the global system dynamics and performs iteratively a dynamic local adjustment procedure. The CDLA mechanism is investigated in an example multiagent shop floor system. The results show that the example manufacturing process is well-coordinated and the coordination approach is practically applicable and effective
15925751
SpMT WaveCache: Exploiting Thread-Level Parallelism in WaveScalar
Speculative Multithreading (SpMT) increases the performance by means of executing multiple threads speculatively to exploit thread-level parallelism. By combining software and hardware approaches, we have improved the capabilities of previous WaveScalar ISA on the basis of Transactional Memory system for the WaveCache Architecture. Threads are extracted at the course of static compiling, and speculatively executed as a thread-level transaction that is supported by extra hardware components, such as Thread-Context-Table (TCT) and Thread-Memory-History (TMH). We have evaluated the SpMT WaveCache with 6 real benchmarks from SPEC, Mediabench and Mibench. On the whole, the SpMT WaveCache outperforms superscalar architecture ranging from 2X to 3X, and great performance gains are achieved over original WaveCache and Transactional WaveCache as well.
537363
Change propagation algorithm in a unified feature modeling scheme
Product lifecycle stages are inter-related and mutually constraining. Due to the sequential nature of the product development processes, some constraints or conflicts may emerge in a later stage and require modifications to the decisions made in earlier stages. The iterations between stages are hence unavoidable and must be managed carefully to maintain the consistency, integrity and validity of product information models. Due to the inter- or intra-stage relations, a chain of changes is very likely to occur as the consequence of an initial change. Modeling and maintaining these relations are important in collaborative engineering to evolve the state of the whole product model in a consistent manner. This paper introduces a new method of modeling associative engineering relations in a unified feature modeling scheme and elaborates a change propagation algorithm for the information consistency control among multiple applications of product lifecycle stages. The algorithm is established on a JTMS-based dependency network. Two case studies are used to illustrate the proposed dependency network and change propagation algorithm.
40279092
An Audio Feature Extraction Method Taking Class Information into Account
An inverter ballast for fluorescent lamps utilizing a resonant circuit coupled to the lamp and operated from a source of DC power through transistors. The transistors are controlled by a sensing means in the resonant loop which insures that the transistor switch at zero current. Furthermore, the coupling means for the load controls a source of heater voltage to the anodes of the fluorescent light which operate at very low current, an antisaturation circuit made up of separate windings are on the current transformer and connected to the switching transistor bases and through diodes to the power supply to prevent "shoot through" current in the transistors. An autotransformer is used as a high leakage reactance transformer; and a circuit is provided to prevent overload of the resonant circuit in case of lamp failure. Shoot through currents are prevented, and overload of the resonant circuit is prevented, and an autotransformer coupling of the resonant circuit to the load is used.