9114568
A high-performance computational resource broker for grid computing environments
Internet computing and grid technologies promise to change the way we tackle complex problems. They will enable large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. As grid computing is becoming a reality, there is a need for managing and monitoring the available resources worldwide, as well as the need for conveying these resources to the everyday user. This paper describes a resource broker with its main function as to match the available resources to the user's needs. The use of the resource broker provides a uniform interface to access any of the available and appropriate resources using user's credentials. The resource broker runs on top of the Globus toolkit. Therefore, it provides security and current information about the available resources and serves as a link to the diverse systems available in the grid.
32464432
An Enhanced Parallel Loop Self-Scheduling Scheme for Cluster Environments
In this paper, a parallel loop self-scheduling scheme for heterogeneous PC cluster systems is proposed. Though the proposed scheme does allow users to choose parameters before the execution initialization phase, there are still weaknesses that motivate us to go further with new improvements in that scheme. For instance, a decision on a fixed and monotonous parameter can easily lead to invalid schedule by using previous input information. Thus, it is proposed in this paper a new scheme, where the scheduling parameter can be adjusted dynamically and fit into most widely available computer systems, in order to provide higher overall performance.
5672930
An e-Learning Platform Based on Grid Architecture
The overall popularity of the Internet has helped e-learning become a hot method for learning in recent years. Over the Internet, learners can freely absorb new knowledge without restrictions on time or place. Many companies have adopted e-learning to train their employees. An e-learning system can make an enterprise more competitive by increasing the knowledge of its employees. E-learning has been shown to have impressive potential in e-commerce. At present, most e-learning environment architectures use single computers or servers as their structural foundations. As soon as their work loads increase, their software and hardware must be updated or renewed. This is a big burden on organizations that lack sufficient funds. Thus, in this study we employ a kind of Grid Computing technology, called the ”Data Grid” to integrate idle computer resources in enterprises into e-learning platforms, thus eliminating the need to purchase costly high-level servers and other equipment.
7749374
A Performance-Based Approach to Dynamic Workload Distribution for Master-Slave Applications on Grid Environments
Effective workload distribution techniques can significantly reduce the total completion time of a program on grid computing environments. In this paper, we propose a dynamic performance-based workload partition approach for master-slave types of applications on grids. Furthermore, we implement two types of applications and conduct the experimentations on our grid testbed. Experimental results showed that our method could execute more efficiently than traditional schemes.
12951016
A shareable e-learning platform using data grid technology
Over the past decade, speed in the transmission of knowledge is no longer the way it used to be. Due to this influence, conventional educational methodology has also followed this trend and has gone through a momentous transformation. An excellent example is e-learning which has achieved and broken through the restrictions of time and space. In recent years it has become one of the most popular teaching methods. SCORM (Sharable Course Object Reference Model) the most popular e-learning standard has been adapted from many differing e-learning platforms. Normally, courseware meeting SCORM standards is sharable with other e-learning platforms. Most e-learning platforms however are unable to share courseware directly on the Internet. With this in mind, we have employed one type of grid computing technology called "data grid" in order to achieve this. This technology allows the integration of different SCORM platforms into a huge e-learning environment.
7849532
A Peer-to-Peer Resource Sharing System with Data Grid Technology for Mobile Devices
Increases in mobile device processing power, storage capacity, and connectivity in recent years have led to a rapid rise in mobile device use. But mobile users face challenges in making connections with other users in order to share resources. To address this issue, we propose an architecture that uses peer-to-peer protocol to establish a resource sharing platform for mobile devices, combined with a data grid to help analyze and classify resources.
16831415
Automatic construction of English/Chinese parallel corpora
As the demand for global information increases significantly, multilingual corpora has become a valuable linguistic resource for applications to cross-lingual information retrieval and natural language processing. In order to cross the boundaries that exist between different languages, dictionaries are the most typical tools. However, the general-purpose dictionary is less sensitive in both genre and domain. It is also impractical to manually construct tailored bilingual dictionaries or sophisticated multilingual thesauri for large applications. Corpus-based approaches, which do not have the limitation of dictionaries, provide a statistical translation model with which to cross the language boundary. There are many domain-specific parallel or comparable corpora that are employed in machine translation and cross-lingual information retrieval. Most of these are corpora between Indo-European languages, such as English/French and English/Spanish. The Asian/Indo-European corpus, especially English/Chinese corpus, is relatively sparse. The objective of the present research is to construct English/ Chinese parallel corpus automatically from the World Wide Web. In this paper, an alignment method is presented which is based on dynamic programming to identify the one-to-one Chinese and English title pairs. The method includes alignment at title level, word level and character level. The longest common subsequence (LCS) is applied to find the most reliable Chinese translation of an English word. As one word for a language may translate into two or more words repetitively in another language, the edit operation, deletion, is used to resolve redundancy. A score function is then proposed to determine the optimal title pairs. Experiments have been conducted to investigate the performance of the proposed method using the daily press release articles by the Hong Kong SAR government as the test bed. The precision of the result is 0.998 while the recall is 0.806. The release articles and speech articles, published by Hongkong & Shanghai Banking Corporation Limited, are also used to test our method, the precision is 1.00, and the recall is 0.948.
788951
An enzyme mechanism language for the mathematical modeling of metabolic pathways
MOTIVATION
As a first step toward the elucidation of the systems biology of complex biological systems, it was our goal to mathematically model common enzyme catalytic and regulatory mechanisms that repeatedly appear in biological processes such as signal transduction and metabolic pathways.


RESULTS
We describe kMech, a Cellerator language extension that describes a suite of enzyme mechanisms. Each enzyme mechanism is parsed by kMech into a set of fundamental association-dissociation reactions that are translated by Cellerator into ordinary differential equations that are numerically solved by Mathematica. In addition, we present methods that use commonly available kinetic measurements to estimate rate constants required to solve these differential equations.
3116757
Intellectual Property Protection for Electronic Commerce Applications
Online content distribution businesses require methods to protect the intellectual property of distributed content. Intellectual property protection is a mechanism to protect the rights of ownership of original work so that no one can use the rights-protected work in any way without seeking permission for the use and, if necessary, paying the rights owners a royalty for the use. Digital watermarking is the core technology in electronic rights protection. However, research addressing the concerns of businesses about intellectual property protection schemes through watermarking is scarce. In this paper, we address these concerns by first introducing watermark design patterns (WDPs) for electronic commerce applications, then presenting problems of copyright protection using watermarking, and finally presenting management concerns. A WDP is defined as the requirements of a digital watermark for a particular type of distributed media content under the protection of its intellectual property. This paper introduces four WDPs for four types of media data - video, image, audio, and text and they are denoted as WDPvideo, WDPimage, WDPaudio and WDPtext respectively. The four WDPs are derived from the characteristics of watermarking techniques and the properties of a distributor’s web site. In our study, the proposed WDPs are used to relate the digital watermarking techniques to electronic commerce applications, and their relationships are presented graphically. The relationship diagram can facilitate electronic commerce application developers to select appropriate digital watermarking techniques and off-the-shelf systems for intellectual property protection on their web sites.
1218659
Efficient discovery of error-tolerant frequent itemsets in high dimensions
We present a generalization of frequent itemsets allowing for the notion of errors in the itemset definition. We motivate the problem and present an efficient algorithm that identifies error-tolerant frequent clusters of items in transactional data (customer-purchase data, web browsing data, text, etc.). The algorithm exploits sparseness of the underlying data to find large groups of items that are correlated over database records (rows). The notion of transaction coverage allows us to extend the algorithm and view it as a fast clustering algorithm for discovering segments of similar transactions in binary sparse data. We evaluate the new algorithm on three real-world applications: clustering high-dimensional data, query selectivity estimation and collaborative filtering. Results show that the algorithm consistently uncovers structure in large sparse databases that other traditional clustering algorithms fail to find.
818365
Effects of luminance quantization error on color image processing
A common approach to color image processing is to apply monochrome techniques to the quantized intensity component. However, the quantization error in the intermediate intensity image propagates to the final processed image. This can lead to significant distortion, depending on the input RGB values and on the particular image processing function being applied. A theoretical analysis of the worst-case quantization error is presented. Experimental results with histogram equalization demonstrate how the histogram resolution affects the performance.