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9 articles
Research Article
An Empirical Study for Enhanced Software Defect Prediction Using a Learning-Based Framework
Kamal Bashir, Tianrui Li, Chubato Wondaferaw Yohannese
Pages: 282 - 298
The object of software defect prediction (SDP) is to identify defect-prone modules. This is achieved through constructing prediction models using datasets obtained by mining software historical depositories. However, data mined from these depositories are often associated with high dimensionality, class...
Research Article
A Validation Approach for Ontology-Based Real-time DBMS
Wided Ben Abid, Mohamed Ben Ahmed Mhiri, Malek Ben Salem, Emna Bouazizi, Faiez Gargouri
Pages: 311 - 317
Real-time DBMS (DataBase Management Systems) are an appropriate storage system under real-time constraints. However real-time DBMS do not implement inference or reasoning mechanisms. Ontologies on the other hand allow these mechanisms by creating formal representations of concepts, properties and relationships...
Research Article
A New Rewarding Mechanism for Branching Heuristic in SAT Solvers
Wenjing Chang, Yang Xu, Shuwei Chen
Pages: 334 - 341
Decision heuristic strategy can be viewed as one of the most central features of state-of-the-art conflict-driven clause-learning SAT solvers. Variable state independent decaying sum (VSIDS) still is the dominant branching heuristics because of its low cost. VSIDS consists of a rewarding mechanism for...
Research Article
A New Algorithm of Mining High Utility Sequential Pattern in Streaming Data
Huijun Tang, Yangguang Liu, Le Wang
Pages: 342 - 350
High utility sequential pattern (HUSP) mining has emerged as a novel topic in data mining, its computational complexity increases compared to frequent sequences mining and high utility itemsets mining. A number of algorithms have been proposed to solve such problem, but they mainly focus on mining HUSP...
Research Article
Multimodal Emotion Recognition Method Based on Convolutional Auto-Encoder
Jian Zhou, Xianwei Wei, Chunling Cheng, Qidong Yang, Qun Li
Pages: 351 - 358
Emotion recognition is of great significance to computational intelligence systems. In order to improve the accuracy of emotion recognition, electroencephalogram (EEG) signals and external physiological (EP) signals are adopted due to their perfect performance in reflecting the slight variations of emotions,...
Research Article
Further Complete Solutions to Four Open Problems on Filter of Logical Algebras
Wei Wang, Pengxi Yang, Yang Xu
Pages: 359 - 366
This paper focuses on the investigation of filters of pseudo BCK-algebra and BL-algebra, important and popular generic commutative and non-commutative logical algebras. By characterizing Boolean filter and implicative filter in pseudo BCK-algebra, the essential equivalent relation between these two filters...
Research Article
A New Edge Detection Method Based on Global Evaluation Using Supervised Classification Algorithms
Pablo A. Flores-Vidal, Guillermo Villarino, Daniel Gómez, Javier Montero
Pages: 367 - 378
Traditionally, the last step of edge detection algorithms, which is called scaling-evaluation, produces the final output classifying each pixel as edge or nonedge. This last step is usually done based on local evaluation methods. The local evaluation makes this classification based on measures obtained...
Research Article
Fusion of Measures for Image Segmentation Evaluation
Macmillan Simfukwe, Bo Peng, Tianrui Li
Pages: 379 - 386
Image segmentation is an important task in image processing. However, no universally accepted quality scheme exists for evaluating the performance of various segmentation algorithms or just different parameterizations of the same algorithm. In this paper, an extension of a fusion-based framework for...
Research Article
Enactment of Ensemble Learning for Review Spam Detection on Selected Features
Faisal Khurshid, Yan Zhu, Zhuang Xu, Mushtaq Ahmad, Muqeet Ahmad
Pages: 387 - 394
In the ongoing era of flourishing e-commerce, people prefer online purchasing products and services to save time. These online purchase decisions are mostly influenced by the reviews/opinions of others who already have experienced them. Malicious users use this experience sharing to promote or degrade...