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The Research Article (RA) is an important and challenging academic genre as it contains multiple parts such as introduction, methodology, results, analysis/discussion of findings, and conclusion. Each part contains one or more subgenres. Hence, although essential for teaching, learning and applications, genre-based analysis of the RA is generally considered to be very difficult in nature because of...
The academic Abstract genre is one of the most important parts of a research paper because it is viewed at first by readers. When well written, it enables them to quickly and accurately identify the main ideas and contributions of the work presented. Hence writing an abstract is the most difficult part. Poorly written abstracts can affect negatively the significance and understanding of the paper...
In this paper, a new model based on variational level set method for segmenting multiphase images is proposed. Its energy functional is based on the level set functions and the regional characteristics functions. It can deal with changes in curves' topology and be extended to multiphase image segmentation models which are based on other schemes for region competition as well. The gradient flow of...
The fine-grained access control approaches in DBMSs should satisfy soundness property which requires the answer of a query returned by the approach under the control of fine-grained access control is consistent with the answer when there is no fine-grained access control. However, existing techniques cannot guarantee soundness property for all SQL queries. Therefore, for an approach, there is a practical...
This paper designs an experiment to analyze different EEG patterns while subjects are listening to different language songs. In the process of experiment, the subjects listen to multi-section songs. Every two songs have the same rhythm and only the lyrics are different, one in Chinese and the other in Japanese. The songs are sung by one singer and the Chinese subject dont know Japanese at all. At...
Developing tools for monitoring the correlations among thousands of financial data streams in an online fashion can be interesting and useful work. We aimed to find highly correlative financial data streams in local patterns. A novel distance metric function slope duration distance (SDD) is proposed, which is compatible with the characteristics of actual financial data streams. Moreover, a model monitoring...
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