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Liu F.,Nanjing Southeast University | Li B.,Key Laboratory of Computer Network and Information Integration Southeast University
SEKE 2011 - Proceedings of the 23rd International Conference on Software Engineering and Knowledge Engineering

This paper gives a novel method of investigating flow-sensitive pointer analysis for multithreaded program based on petri net. The method mainly borrows causal data flow analysis idea from Azadeh Farzan. Petri net is used to describe control flow structure of multithreaded program. And pointer points-to information is propagated along causal dependencies of events in the partial order execution of petri net. The problem of pointer analysis is reduced to the coverability problem on the petri net. Source

Li Y.,Nanjing Southeast University | Li Y.,Chuzhou University | Li Y.,Key Laboratory of Computer Network and Information Integration Southeast University | Wang T.,Chuzhou University | And 2 more authors.

Owing to the geometric distortions of the X-ray images, C-arm CT (computed tomography) imaging system usually suffers from adverse effects. To overcome the difficulties, an integrated approach has been put forward to correct distorted X-ray images in the paper. The approach firstly uses OTSU algorithm and morphological open operation to extract the control points coordinates in the distorted X-ray images. To obtain more coordinates and improve the correction precision, least squares is used to fit the polynomial passing by the extracted points. More coordinates are calculated by using the fitted polynomial. Then, a biharmonic spline surface is interpolated by the extracted and calculated coordinates. Finally, the distorted X-ray images are corrected by using the interpolated biharmonic spline surface. Experiment on the acquired distorted X-ray images demonstrates that the proposed approach can effectively correct the distorted X-ray images. A comparison with classical approaches further shows that the approach proposed in the paper performs better in visual effects and correction accuracy. © 2015 Elsevier GmbH. Source

Liu Q.,Nanjing Southeast University | Liu Q.,Key Laboratory of Computer Network and Information Integration Southeast University | Gao Z.,Nanjing Southeast University | Gao Z.,Key Laboratory of Computer Network and Information Integration Southeast University | And 2 more authors.
Knowledge-Based Systems

Opinion target extraction, also called aspect extraction, aims to extract fine-grained opinion targets from opinion texts, such as customer reviews of products and services. This task is important because opinions without targets are of limited use. It is one of the core tasks of the popular aspect-oriented opinion mining, and is also among the most challenging tasks tackled by opinion mining researchers. Previous work has shown that the syntactic-based approach, which employs extraction rules about grammar dependency relations between opinion words and aspects (or targets), performs quite well. This approach is highly desirable in practice because it is unsupervised and domain independent. The problem of this approach is that the extraction rules should be carefully selected and tuned manually so as not to produce too many errors. Although it is easy to evaluate the accuracy of each rule automatically, it is not easy to select a set of rules that produces the best overall result due to the overlapping coverage of the rules. In this paper, we propose two approaches to select an effective set of rules. The first approach employs a greedy algorithm, and the second one employs a local search algorithm, specifically, simulated annealing. Our experiment results show that the proposed approaches can select a subset of a given rule set to achieve significantly better results than the full rule set and the existing state-of-the-art CRF-based supervised method. © 2016. Source

Wang Z.,Northeastern University China | Zhao Y.,Northeastern University China | Zhao Y.,Key Laboratory of Computer Network and Information Integration Southeast University | Wang G.,Northeastern University China | Cheng Y.,Northeastern University China
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Discriminative subgraph mining from a large collection of graph objects is a crucial problem for graph classification. Several main memory-based approaches have been proposed to mine discriminative subgraphs, but they always lack scalability and are not suitable for large-scale graph databases. Based on theMapReduce model, we propose an efficient method, MRGAGC, to process discriminative subgraph mining. MRGAGC employs the iterative MapReduce framework to mine discriminative subgraphs. Each map step applies the evolutionary computation and three evolutionary strategies to generate a set of locally optimal discriminative subgraphs, and the reduce step aggregates all the discriminative subgraphs and outputs the result. The iteration loop terminates until the stopping condition threshold is met. In the end, we employ subgraph coverage rules to build graph classifiers using the discriminative subgraphs mined by MRGAGC. Extensive experimental results on both real and synthetic datasets show that MRGAGC obviously outperforms the other approaches in terms of both classification accuracy and runtime efficiency. © Springer International Publishing Switzerland 2015. Source

Tao C.,Nanjing Southeast University | Tao C.,Key Laboratory of Computer Network and Information Integration Southeast University | Tao C.,San Jose State University | Li B.,Nanjing Southeast University | And 2 more authors.
Journal of Software

Today, component-based software engineering has been widely used in software construction to reduce project cost and speed up software development cycle. Due to software changes in new release or update of components, regression testing is needed to assure system quality. When changes made to a component, the component could be affected, moreover, the changes could bring impacts on the entire system. We firstly identify diverse changes made to components and system based on models, then perform change impact analysis, and finally refresh regression test suite using a state-based testing practice. Related existing research did not address the issue of systematic regression testing of component-based software, especially at system level. The paper also reports a case study based on a realistic component-based software system using a, which shows that the approach is feasible and effective. © 2013 ACADEMY PUBLISHER. Source

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