In this paper, we propose an efficient algorithm, NCLOSED, for mining the N k-closed itemsets with the highest supports for 1 up to a certain k max value. The algorithm adopts best-first search strategy to generate c...
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In this paper, we propose an efficient algorithm, NCLOSED, for mining the N k-closed itemsets with the highest supports for 1 up to a certain k max value. The algorithm adopts best-first search strategy to generate closed itemsets with highest remaining supports. It does not keep closed itemsets mined in main memory to ensure that they are really closed. This is because this algorithm can directly generate closed itemsets. Moreover, duplicated closed itemsets are detected and discarded from this algorithm.
The process of evaluating, classifying, and assigning bugs to programmers is a difficult and time consuming task which greatly depends on the quality of the bug report itself. It has been shown that the quality of rep...
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The process of evaluating, classifying, and assigning bugs to programmers is a difficult and time consuming task which greatly depends on the quality of the bug report itself. It has been shown that the quality of reports originating from bug trackers or ticketing systems can vary significantly. In this research, we apply information retrieval (IR) and natural language processing (NLP) techniques for mining bug repositories. We focus particularly on measuring the quality of the free form descriptions submitted as part of bug reports used by open source bug trackers. Properties of natural language influencing the report quality are automatically identified and applied as part of a classification task. The results from the automated quality assessment are used to populate and enrich our existing softwareengineering ontology to support a further analysis of the quality and maturity of bug trackers.
In this paper, we proposed an efficient algorithm, TOPK_CLOSED, for mining top-k closed itemsets. This algorithm mines top-k closed itemsets using best-first search. The closed itemsets with the highest supports are f...
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In this paper, we proposed an efficient algorithm, TOPK_CLOSED, for mining top-k closed itemsets. This algorithm mines top-k closed itemsets using best-first search. The closed itemsets with the highest supports are firstly found from this algorithm. Consequently, the method quickly finds top-k closed itemsets, which leads to an efficient pruning unnecessary itemsets and stop mining rapidly. In addition, this algorithm can generate closed itemsets without keeping candidates in main memory.
Ambiguity is a major problem of software errors because much of the requirements specification is written in a natural language format. Therefore, it is hard to identify consistencies because this format is too ambigu...
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ISBN:
(纸本)9781424439027
Ambiguity is a major problem of software errors because much of the requirements specification is written in a natural language format. Therefore, it is hard to identify consistencies because this format is too ambiguous for specification purposes. This paper aims to propose a method for handling requirement specification documents which have a similar content to each other through a hierarchical text classification. The method consists of two main processes of classification: heavy classification and light classification. The heavy classification is to classify the requirement specification documents having similar content together. Meanwhile, light classification is to elaborate specification requirement documents by using the Euclidean distance. Finally, slimming down the number of requirements specification through hierarchical text classification classifying may yield a specification which is easier to understand. That means the proposed method is more effective for reducing and handling in the requirements specification.
Microarray technology has been increasingly used in cancer research because of its potential for measuring expression levels of thousands of genes simultaneously in tissue samples. It is used to collect the informatio...
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Microarray technology has been increasingly used in cancer research because of its potential for measuring expression levels of thousands of genes simultaneously in tissue samples. It is used to collect the information from tissue samples regarding gene expression differences that could be useful for cancer classification. However, this classification task faces many challenges due to availability of a smaller number of samples compared to the huge number of genes, and many of the genes are not relevant to the classification. It has been shown that selecting a small subset of genes can lead to an improved accuracy of the classification. Hence, this paper proposes a solution to the problem of gene selection by using a multi-objective approach in genetic algorithm. This approach is experimented on two microarray data sets such as lung cancer and mixed-lineage leukemia cancer. It obtains encouraging result on those data sets as compared with an approach that uses single objective approach.
Still, requirements and software design are often confused with one another. We provide a new (partial) explanation for this phenomenon, based on the insight that representations of concepts related to requirements an...
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Still, requirements and software design are often confused with one another. We provide a new (partial) explanation for this phenomenon, based on the insight that representations of concepts related to requirements and software design, respectively, may sometimes look very similar. This does not mean, however, that the requirements and design concepts are the same. So, we should distinguish requirements from their representations and, analogously, software design from its representation. Then it is easier to clearly distinguish requirements and software design as well.
This paper presents a case study that describes TSPi teaching (introduction to the team software process) to 4th year students, grouped by teams, at the computerscience School, Polytechnic University of Madrid (UPM)....
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This paper presents a case study that describes TSPi teaching (introduction to the team software process) to 4th year students, grouped by teams, at the computerscience School, Polytechnic University of Madrid (UPM). The achievements of the teams, due to training and the use of TSPi, were analyzed and discussed. This paper briefly discusses the approach to the teaching and some of the issues that were identified. The teams collected data on the projects developed. They reviewed the schedule and quality status weekly. The metrics selected to analyze the impact on the students were: size, effort, productivity, costs and defects density. These metrics were chosen to analyze teams 'performance evolution through project development. This paper also presents a study related to the evolution of estimation, quality and productivity improvements these teams obtained. This study will prove that training in TSPi has a positive impact on getting better estimations, reducing costs, improving productivity, and decreasing defect density. Finally, the teams 'performance are analyzed.
Heterogeneous sensor networks (HSNs) with multiple sensing modalities are gaining popularity in diverse fields. Tracking is an application that can benefit from multiple sensing modalities. If a moving target emits so...
Heterogeneous sensor networks (HSNs) with multiple sensing modalities are gaining popularity in diverse fields. Tracking is an application that can benefit from multiple sensing modalities. If a moving target emits sound then both audio and video sensors can be utilized. These modalities can complement each other in the presence of high background noise that impairs the audio or visual clutter affecting the video. Audio-video tracking can also provide cues for the other modality for actuation. In this paper, we describe an approach for target tracking in urban environments utilizing an HSN of mote class devices equipped with acoustic sensor boards and embedded PCs equipped with web cameras. Our system employs a Markov Chain Monte Carlo Data Association algorithm for tracking vehicles emitting engine noise. Experimental results from a deployment in an urban environment are used to demonstrate our approach.
The aim of this panel session is to promote discussion on emergent challenges and the need for advancements in the theory, methodology, applications, education in M&S. The changing landscape in science and enginee...
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作者:
He-xuan HuAnne-lise GehinMireille BayartLanguages
Informatics Systems and Software Engineering Department Faculty of Computer Science Université des Sciences et Technologies de Lille Villeneuve d'Ascq France
This paper proposes a formal framework for reconfigurable control, based on model checking. This framework first generates a flexible model (i.e., an execution structure) according to the diagnosis, then defines a tem...
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This paper proposes a formal framework for reconfigurable control, based on model checking. This framework first generates a flexible model (i.e., an execution structure) according to the diagnosis, then defines a temporal specification language to deal with the problems due to infinite execution cycles and non-determinism, and finally provides the algorithms that will automatically verify whether the updated model satisfies the desired specification.
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