42292334
An Initial Framework for Collaboration-Based Component Selection
14600536
An Approach to Provisioning E-Commerce Applications with Commercial Components
Component-based development is a trend towards building e-commerce applications. However, commercial components are rarely used during the development. The reason is that existing approaches to selecting and composing components suffer from the problem that the components retrieved usually do not exactly fit with other components in the system being developed. While formal methods can be used to describe and check semantic characteristics to better match components, there are practical limitations which restrict their adoption. We have proposed a framework to support a semantic description and selection of components. We used Simple Component Interface Language (SCIL) to describe user requirements and pre-built components from the current component sources. Specifications in SCIL can be translated to a variety of models including those that have a formal basis. In this paper, we perform a case study of searching commercial components for a generic e-commerce application. We specify the commercial components in SCIL and use two specific tools: jMocha and Alloy Analyser to identify the correct components that suit a particular task
14258683
A framework for checking behavioral compatibility for component selection
Component selection and composition are the main issues in component-based development (CBD). Existing approaches suffer from the problem that the components retrieved usually do not exactly fit with other components in the system being developed. While formal methods can be used to describe and check semantic characteristics to better match components, there are practical limitations which restrict their adoption. In this paper, we propose a framework to support a semantic description and selection of components. Towards this we first introduce a Simple Component Interface Language (SCIL). SCIL files can be translated to a variety of models including those that have a formal basis. We report our experience with two specific tools, viz., Reactive Modules and Alloy with a view to using tools based on formal methods but without exposing the details of the tools
8890864
Improving Error Tolerance for Multithreaded Register Files
Chip multithreaded computing is exposed to the dual challenges of increasing system complexity and error sensitivity. It is critical to develop effective solutions that achieve better error tolerance without inducing performance degradation. In this paper, we propose a new error-tolerant memory design based on a unique computing phenomenon referred to as the dynamic multithreading redundancy (DMR). The proposed technique exploits the interplay between the concurrent threads for runtime error control. We also present two DMR enhancements, immediate write-back and self-recovery, to address the error accumulation effect. A multithreaded register file was implemented to demonstrate the proposed DMR technique. Simulation results on the SPEC CPU2000 benchmarks demonstrate significant overhead reduction in performance and energy efficiency related to error recovery. In addition, the proposed technique features good scalability with respect to the instruction-level and thread-level parallelism for next-generation processor design, where the soft error problem is expected to get worse due to technology scaling and architecture-affecting trends.
1037558
PhoenixG: a unified management framework for industrial information grid
The industrial information grid is a special kind of system, the users of which exclusively own geographically distributed computing resources for business service, and try to maintain the lowest total cost of ownership while guaranteeing quality of service. In this paper, we classify the industrial information grid as an extension to grid problem; develop a unified management framework for new management paradigm, which supports the distribution of administration labor and collaboration of system administrator at different locations; propose a self-organizing algorithm, which supports the initial establishment, daily management and exception processing of industrial information grid. Finally, we evaluate the performance of system management, and analyze the management overhead with this new management paradigm.
21334257
Feature Extraction Based on the Independent Component Analysis for Text Classification
The independent component analysis (ICA) is a very popular algorithm used in the blind source separation and it has been widely used in many other fields. In this paper, the ICA is applied to text classification. We try to combine the traditional feature selection methods with ICA technology to improve the text classification performance by extracting Independent features. Further, a series of comparison experiments have been performed. The experiment results have shown that the ICA technology can indeed help to improve the classification performance and the combined method has showed the clear advantages.
41493711
Car Plate Localization Using Modified PCNN in Complicated Environment
Car plate Localization, which remains a difficult problem under complicated environment, is the key problem in many traffic related applications. In this paper we describe a new method based on modified Pulse Coupled Neural Network (PCNN) with adaptive threshold, which can capture relatively complete objects in human perception. After inverse filtering, PCNN processing is applied to produce a firing time sequence image. Then car plates' position and rotated angle can be extracted from the firing image. Experiment results show that the correct car plate locating rate reaches 98%, which is higher than other Localization methods on the same image database.
23743946
Automatic pectoral muscle boundary detection in mammograms based on Markov chain and active contour model
Automatic pectoral muscle removal on medio-lateral oblique (MLO) view of mammogram is an essential step for many mammographic processing algorithms. However, it is still a very difficult task since the sizes, the shapes and the intensity contrasts of pectoral muscles change greatly from one MLO view to another. In this paper, we propose a novel method based on a discrete time Markov chain (DTMC) and an active contour model to automatically detect the pectoral muscle boundary. DTMC is used to model two important characteristics of the pectoral muscle edge, i.e., continuity and uncertainty. After obtaining a rough boundary, an active contour model is applied to refine the detection results. The experimental results on images from the Digital Database for Screening Mammography (DDSM) showed that our method can overcome many limitations of existing algorithms. The false positive (FP) and false negative (FN) pixel percentages are less than 5% in 77.5% mammograms. The detection precision of 91% meets the clinical requirement.