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Using Clustering algorithm to improve the effectiveness of test case prioritization has been well recognized by many researchers. Software fault prediction has been one of the active parts of software engineering, but to date, there are few test cases prioritization technique using fault prediction. We conjecture that if the code has a fault-proneness, the test cases covering the code will findfault...
Using Clustering algorithm to improve the effectiveness of test case prioritization has been well recognized by many researchers. Software fault prediction has been one of the active parts of software engineering, but to date, there are few test cases prioritization technique using fault prediction. We conjecture that if the code has a fault-proneness, the test cases covering the code will find fault...
Experimenting in computer science course is challenging due to the limitation of site, equipment and special experiment tools. In this paper, based on the analysis of the experiments features of computer science curricula, such as, Principle of Computer Organization, Digital Image Process, Digital Signal Process etc., we design two kinds of virtual lab platforms and develop corresponding virtual lab...
In this paper, we propose an Activity-List based Nested Partitions algorithm for solving the Resource-Constrained Project Scheduling Problem(RCPSP). This algorithm is based on traditional Serial Scheduling scheme (SSS) and partitions the feasible solution space which is formulated by activity-lists into subregions by the nested partitions approach. We also utilize Double Justification as local search...
Image retargeting addresses the problem of adapting images to display on devices with small sizes and different aspect ratios. A fisheye warping method for image retargeting is presented in this paper. Our method emphasizes important aspects of images without completely discarding the remaining parts and can solve the multi-focus problem. We have designed and implemented two fisheye transformation...
Population statistic and forecast is important basis that government establishes correlative policy, population's all characteristic has strong non-linear speciality because of all kinds of effects. A cross validation optimized parameter least support vector machine method of population statistic and forecast is presented aiming at bad precision and lack of rationality of all approximate model at...
Based on the linear regressive model of support vector machines, iterative re-weighted least squares of the support vector machines for signal spectral analysis is introduced by virtue of abstract expressions of cost functions, and the uniform mathematical analytical expression of support vector machine for solving the problem of signal spectral analysis is obtained. And a new method is presented...
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