21318621
Design and implementation of a computational grid for bioinformatics
The popular technologies, Internet computing and grid technologies promise to change the way we tackle complex problems. They enable large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. And harnessing these new technologies effectively transforms scientific disciplines ranging from high-energy physics to the life sciences. The computational analysis of biological sequences is a kind of computation driven science. Cause the biology data growing quickly and these databases are heterogeneous. We can use the grid system sharing and integrating the heterogeneous biology database. As we know, bioinformatics tools can speed up analysis the large-scale sequence data, especially about sequence alignment and analysis. The FASTA is a tool for aligning multiple protein or nucleotide sequences. These two bioinformatics software, which we used is a distributed and parallel version. The software uses a message-passing library called MPI (message passing interface) and runs on distributed workstation clusters as well as on traditional parallel computers. A grid computing environment is proposed and constructed on multiple Linux PC clusters by using globus toolkit (GT) and SUN grid engine (SGE). The experimental results and performances of the bioinformatics tool using on grid system are also presented.
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.
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.
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.
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.
16561888
Learning to predict train wheel failures
This paper describes a successful but challenging application of data mining in the railway industry. The objective is to optimize maintenance and operation of trains through prognostics of wheel failures. In addition to reducing maintenance costs, the proposed technology will help improve railway safety and augment throughput. Building on established techniques from data mining and machine learning, we present a methodology to learn models to predict train wheel failures from readily available operational and maintenance data. This methodology addresses various data mining tasks such as automatic labeling, feature extraction, model building, model fusion, and evaluation. After a detailed description of the methodology, we report results from large-scale experiments. These results clearly show the great potential of this innovative application of data mining in the railway industry.
15185752
Specifying distributed multi-agent systems in chemical reaction metaphor
This paper presents an application of Chemical Reaction Metaphor (CRM) in distributed multi-agent systems (MAS). The suitability of using CRM to model multi-agent systems is justified by CRM's capacity in specifying dynamic features of multi-agent systems. A case study in an agent-based e-learning system (course material updating) demonstrates how the CRM based language, Gamma, can be used to specify the architectures of multi-agent systems. The effectiveness of specifying multi-agent systems in CRM from the view point of software engineering is further justified by introducing a transformational method for implementing the specified multi-agent systems. A computation model with a tree-structured architecture is proposed to base the design of the specified multi-agent system during the implementation phase. A module language based on the computation model is introduced as an intermediate language to facilitate the translation of the specification of multi-agent systems. The multicast networking technology pragmatizes the implementation of communications and synchronization among distributed agents. The paper also discusses the feasibility of implementing an automatic translation from the Gamma specification to a program in the module language.
2577694
Efficient acoustic index for music retrieval with various degrees of similarity
Content-based music retrieval research has mostly focused on symbolic data rather than acoustical data. Given that there are no general-purpose transcription algorithms that can convert acoustical data into musical scores, new methods are needed to do music retrieval on acoustical data. In this paper, we review some existing methods on contentbased music retrieval, discuss different definitions of music similarity, and present a new framework to perform music indexing and retrieval. The framework is based on an earlier prototype we developed, with significant improvements.In our framework known as MACSIS, each audio file is broken down into small segments and converted into feature vectors. All vectors are stored in a high-dimensional indexing structure called LSH, a probabilistic indexing scheme that makes use of multiple hashing instances in parallel. At retrieval time, small segments of audio matches are retrieved from the index and pieced together using the Hough Transform technique, and results are used as the basis to rank candidate matches.
17968973
Authoring Cases from Free-Text Maintenance Data
Automatically authoring or acquiring cases in the case-based reasoning (CBR) systems is recognized as a bottleneck issue that can determine whether a CBR system will be successful or not. In order to reduce human effort required for authoring the cases, we propose a framework for authoring the case from the unstructured, free-text, historic maintenance data by applying natural language processing technology. This paper provides an overview of the proposed framework, and outlines its implementation, an automated case creation system for the Integrated Diagnostic System. Some experimental results for testing the framework are also presented.
14016299
Building Parallel Corpora by Automatic Title Alignment
Cross-lingual semantic interoperability has drawn significant research attention recently, as the number of digital libraries in non-English languages has grown exponentially. Cross-lingual information retrieval (CLIR) across different European languages, such as English, Spanish and French, has been widely explored, but CLIR across European and Oriental languages is still at the initial stages. To cross the language boundary, a corpus-based approach shows promise of overcoming the limitations of knowledge-based and controlled vocabulary approaches. However, collecting parallel corpora between European and Oriental languages is not an easy task. Length-based and text-based approaches are two major approaches to align parallel documents. In this paper, we investigate several techniques using these approaches, and compare their performance in aligning English and Chinese titles of parallel documents available on the Web.