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
2937871
Improving XML Querying with Maximal Frequent Query Patterns
Querying on XML data is a computational-expensive process due to the complex nature of both the XML data and the query. In this paper, we propose an approach to expedite XML query processing by caching the results of a specific class of queries, namely the maximal frequent queries. We mine the maximal frequent query patterns from user-issued queries and cache the results of such queries. We propose a recursive algorithm for query processing using the cached query results. Query rewriting is employed to deal with four kinds of similar queries namely exact matching, exact containment, semantic matching and semantic containment. We perform experiments on the XMARK datasets and show that the proposed methods are both effective and efficient in improving the performance of XML queries.
15964720
A Network Access Control Architecture Using State-Transfer-Based Dynamic Policy
The access control architecture using state-transfer-based dynamic policy is proposed to make access control more flexible and dynamic. This architecture can dynamically change the policy according to a state-transfer composed of a previous state and a current state. It can indicate the tendency of the system by using both previous and current information in order to decide a more appropriate policy to the current system and future condition. And there are two steps in this dynamic policy method, one is deciding a partial-state and the other one is deciding a state, two dynamic policy decision layers are included into this architecture in order to manage these two steps
37239622
Classifying Motion Time Series Using Neural Networks
This paper proposes an effective time-series classification model based on the Neural Networks. Classification under this model consists of three phases, namely data preprocessing, training, and testing. The main contributions of the paper are described as following: We propose a feature extraction algorithm, which involves computation of finite difference of sequences, for preprocessing. We employ two different types of Neural Networks for training and testing. The results of the experiments on real univariate motion capture data and synthetic data show that our approach is effective in providing good performance in terms of accuracy. It is therefore a promising method for classifying time-series, in particular for univariate human motion capture data.
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
15894335
An adaptive load balancing framework for parallel database systems based on collaborative agents
Load balancing is a key technique in parallel computer supported collaborative work (CSCW) systems, parallel database system and P2P system for instance, to boost performance and improve scalability. In order to reduce total cost of ownership (TCO), adaptive/self-tuning administration techniques are gradually and extensively expected in the cyberspace. In parallel database systems, adaptive load balancing techniques are proposed to face the change in data storage patterns and access patterns in a dynamic real environment. The techniques utilized in both shared-nothing and shared-disk parallel database systems are discussed, and a general flexible framework based on collaborative agents is studied to support these techniques in both architectures. The framework supports two kinds of load balancing - one is passively executing query statements balancedly, and the other one is proactively adjusting data placement and task execution scheme, by means of data and task migration, whenever load unbalance is detected. Three categories of agents, scheduling agents, monitoring agents and task agents, are identified in the framework. The collaboration protocols and scheduling algorithms to support adaptive load balancing are described. The framework also applies to other parallel systems such as P2P systems and shared file processing systems due to their underlying commonness.
472296
A Fast Center of Mass Estimation Algorithm for Coordinates of IR Markers
For the binocular vision system based on light-weighted passive IR reflective markers and IR LED array PCB board, which is used to measure the 3-D motion parameters of rocket motor, the most important issue is determining the coordinates of infrared markers. In order to solve this problem, a fast center of mass estimation algorithm was proposed in this paper. The new algorithm segments the infrared image by self-adapting thresholding method firstly, and then calculating the center of mass of infrared markers by improved statistical averaging technique. A comparison was made between the newly developed algorithm and other algorithms such as traditional statistical averaging, FFT and least-squares method. The result indicates that the new algorithm is more suited for high-speed motion analysis because of high accuracy and faster processing speed. Tests performed on real-world images show that the algorithm can greatly improve the speed of the calculation and ensure the demand of precision on the basis of the better image segmentation result and improved statistical averaging technique.
13259771
Deploying HEP Applications on Multiple Grid Infrastructures
High energy physics (HEP) experiments are facing unprecedented challenges to deal with huge volumes of data. Grid is the excellent technology for it. However, Incompatibility of a variety of grid middewares is an obstacle to exploit the resources on multiple grid infrastructures. This paper firstly introduces HEP experiments and HEP grid, and then reviews the solutions for grid interoperability and interoperations. Because current HEP applications are tightly with gLite middleware, this paper highlights a gateway approach to interoperate with gLite and described it in detail. Direct access to gLite storage system is very important, and a dedicated tool for HEP data sharing is then proposed and implemented. Finally, the implementation of the interoperability of GOS and gLite is introduced.
10468118
Graphic sequences with a realization containing a generalized friendship graph
Gould, Jacobson and Lehel [R.J. Gould, M.S. Jacobson, J. Lehel, Potentially G-graphical degree sequences, in: Y. Alavi, et al. (Eds.), Combinatorics, Graph Theory and Algorithms, vol. I, New Issues Press, Kalamazoo, MI, 1999, pp. 451-460] considered a variation of the classical Turan-type extremal problems as follows: for any simple graph H, determine the smallest even integer @s(H,n) such that every n-term graphic sequence @p=(d"1,d"2,...,d"n) with term sum @s(@p)=d"1+d"2+...+d"n>=@s(H,n) has a realization G containing H as a subgraph. Let F"t","r","k denote the generalized friendship graph on kt-kr+r vertices, that is, the graph of k copies of K"t meeting in a common r set, where K"t is the complete graph on t vertices and 0@?r@?t. In this paper, we determine @s(F"t","r","k,n) for k>=2, t>=3, 1@?r@?t-2 and n sufficiently large.
7188468
GPGPU supported cooperative acceleration in molecular dynamics
Molecular dynamics simulations have become a significant computational approach to study complicated physical phenomena at the atomic level. Nevertheless, accurate simulations are limited in size and timescale by the available computing resources, which make the simulations very time-consuming. This consequentially leads to tremendous computational requirements. Therefore, the need for speeding up this process is crucial. In this paper, we present a novel implementation to accelerate molecular dynamics simulations with GPGPU (General Purpose Graphics Processing Unit). Our goal is to reduce the total computational time of MD simulations at a very high performance/cost ratio with the introduction of the GPGPU algorithm. This is motivated by their enhanced programmability, attractive cost/performance ratio and incredible growth in speed. To demonstrate that GPGPUs already provide an inexpensive alternative to scientific applications, we have used AMD's Brook+ streaming programming environment to implement a new parallel algorithm. Our experimental results show the novel approach achieves speedup by the factor of fifteen compared to the corresponding sequential implementation.
21571419
N-distinguishing Tests for Enhanced Defect Diagnosis
Diagnostic ATPG has traditionally been used to generate test patterns that distinguish pairs of modeled faults. In this work, we investigate the use of n-distinguishing test sets, which distinguish pairs of single stuck-at faults n times, to enhance the probability of distinguishing unmodeled defects. The basis for the use of n-distinguishing test sets to enhance defect diagnosis is similar to that for using n-detection test sets to improve the detection of unmodeled defects. We use a heuristic to target a subset of fault pairs for n-distinguishing in order to improve the efficacy of the patterns generated for aiding diagnosis. Experimental results on the larger ISCAS benchmark circuits are presented to demonstrate the improvements in defect diagnostic resolution due to the use of n-distinguishing test sets. We use randomly selected resistive bridges to represent unmodeled defects. The experimental results also show that the coverage of unmodeled defects by n-distinguishing test sets is similar to that by n-detection test sets even though the number of n-distinguishing tests is typically smaller. This suggests the possibility of using n-distinguishing test sets in place of n-detection test sets in manufacturing test.