45464184
Chemical Reaction Metaphor in Distributed Learning Environments
This paper presents an application of Chemical Reaction Metaphor (CRM) in agent-based distributed learning systems. The suitability of using CRM to model multi-agent systems is justified by CRM’s capacity in catching dynamic features of multi-agent systems in an e-learning environment. A case study in course material updating demonstrates how the CRM based language, Gamma language, can be used to specify the architecture of the learning environment. Finally, a discussion on the implementation of Gamma language in a distributed system is given.
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.
15205794
Specification of Multi-Agent Systems in the Gamma Language
The suitability of using chemical reaction metaphor (CRM) to model multi-agent systems (MASs) is justified by CRM's capacity in specifying dynamic features of multi-agent systems. This paper presents a case study that demonstrates the applications of CRM in specifying multi-agent systems. The case study is the specification of a navigation training system. Given the dynamic and concurrent nature of multi-agent systems, we find that the chemical reaction metaphor provides a mechanism for describing the overall architecture of the distributed multi-agent systems precisely and concisely, while giving the design of the real system a solid starting point and allowing step-by-step refinement of the system using transformational methods
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.
14699908
Performance Analysis of Applying Replica Selection Technology for Data Grid Environments
The Data Grid enables the sharing, selection, and connection of a wide variety of geographically distributed computational and storage resources for solving large-scale data intensive scientific applications. Such technology efficiently manage and transfer terabytes or even petabytes of data for data-intensive, high-performance computing applications in wide-area, distributed computing environments. Replica selection process allows an application to choose a replica from replica catalog, based on its performance and data access features. In this paper, we build a Grid environment based on three existing PC Cluster environments and perform performance analysis of data transfers using GridFTP protocol over these systems. In addition, based on experimental results, it is proposed a cost model to pick the best replica, in real and dynamic network situations.
39381350
Performance-Based Workload Distribution on Grid Environments
Imbalanced workload-distribution can significantly degrade performance of grid computing environments. In the past, the theory of divisible load has been widely investigated in static heterogeneous systems. However, it has not been widely applied to grid environments, which are characterized by heterogeneous resources and dynamic environments. In this paper, we propose a performance-based approach to workload distribution for master-slave types of applications on grids. Furthermore, applications with irregular workloads are addressed. We implemented three kinds of applications and conducted experimentations on our grid test-beds. Experimental results show that this approach performs more efficiently than conventional schemes. Consequently, we claim that dynamic workload distribution can benefit applications on grid environments.
636423
Visualization of large category map for Internet browsing
Information overload is a critical problem in World Wide Web. Category map developed based on Kohonen's self-organizing map (SOM) has been proven to be a promising browsing tool for the Web. The SOM algorithm automatically categorizes a large Internet information space into manageable sub-spaces. It compresses and transforms a complex information space into a two-dimensional graphical representation. Such graphical representation provides a user-friendly interface for users to explore the automatically generated mental model. However, as the amount of information increases, it is expected to increase the size of the category map accordingly in order to accommodate the important concepts in the information space. It results in increasing of visual load of the category map. Large pool of information is packed closely together on a limited size of displaying window, where local details are difficult to be clearly seen. In this paper, we propose the fisheye views and fractal views to support the visualization of category map. Fisheye views are developed based on the distortion approach while fractal views are developed based on the information reduction approach. The purpose of fisheye views are to enlarge the regions of interest and diminish the regions that are further away while maintaining the global structure. On the other hand, fractal views are an approximation mechanism to abstract complex objects and control the amount of information to be displayed. We have developed a prototype system and conducted a user evaluation to investigate the performance of fisheye views and fractal views. The results show that both fisheye views and fractal views significantly increase the effectiveness of visualizing category map. In addition, fractal views are significantly better than fisheye views but the combination of fractal views and fisheye views do not increase the performance compared to each individual technique.
16872458
Decision tree construction for data mining on grid computing environments
In this paper, the authors presented the grid-based decision tree architecture, with the intention of applying it to both parallel and sequential algorithms. Also, it is shown that, based on the scope and model of data mining applied in the grid environment as well as user equivalent perspective, grid roles can be categorized into three types. It was aimed, through these definitions, to help software developers define clear system processes and differentiate the application scope for software applications. To fulfill the architecture, an existing parallel decision tree algorithm was first applied (the SPRINT algorithm) to the grid environment. The performance and differences in many other areas are compared using datasets of different sizes. The experimental results will be used for future reference and further development.
14819907
Precise RSSI with High Process Variation Tolerance
A receiving signal strength indicator (RSSI) built with transconductance amplifiers is presented. The RSSI achieves high tolerance to process variations by utilizing the unique nature of branch currents in a transconductance amplifier. These branch currents are used to implement a current-mode rectifier and amplitude clipping circuit that are tolerant of process variations. An on-chip offset control loop permits the entire RSSI to be realized with only one external component. In 0.18 mum CMOS with a 1.8V supply, the RSSI draws 2.5mA and provides 80dB of offset suppression and more than 70dB of log-linear range with less than +/-2dB error due to process variation.