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Your search keyword '"Jiang, Xiaoguang"' showing total 128 results
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128 results on '"Jiang, Xiaoguang"'

1. PMPI: Patch-Based Multiplane Images for Real-Time Rendering of Neural Radiance Fields

Author

Jiang, Xiaoguang, Yang, You, Liu, Qiong, Tao, Changbiao, Liu, Qun, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Fang, Lu, editor, Pei, Jian, editor, Zhai, Guangtao, editor, and Wang, Ruiping, editor

Published
2024
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5. Identification Winding Material of Distribution Transformer Based on Multi-Information Fusion

Author

Xiong, Hu, Li, Jiayuan, Xie, Xianming, Xiang, Bin, Jiang, Xiaoguang, Zhu, Changchen, and Liu, Zhixiong

Abstract

In transformer production, some manufacturers use aluminum to impersonate copper to reduce the manufacturing cost, which is difficult to be detected and can cause significant losses to the power grid. To address the problem of non-destructive identification of winding material in distribution transformers, we propose a multi- information recognition method by fusing the harmonic resistance coefficient and the appearance parameters of the transformer, namely volume and height. Then the winding material is identified by a trained support vector machine model. The test results demonstrate that our proposed method achieves 90% recognition accuracy for copper transformers and 100% accuracy for aluminum transformers with the test samples. Additionally, the proposed non-destructive method is easier to implement than other methods in engineering.

Published
2024
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13. Chinese named entity recognition method based on multiscale feature fusion

Author

Jiang, Xiaoguang

Abstract

In response to the problems of low recognition accuracy and poor recognition efficiency in traditional methods, the paper proposes a Chinese named entity recognition method based on multiscale feature fusion. Firstly, the similarity between each word is calculated using the literal similarity algorithm to obtain synonyms of Chinese named entities. Then, the Chinese named entity features are obtained, including character features, character shape features, binary character features, and word similarity features, through multiscale feature fusion to obtain the Chinese named entity feature set. Finally, the target Chinese named entity for recognition is obtained by matching vocabulary, compressing vocabulary vectors, and integrating character vectors, and the CRF is used to implement Chinese named entity recognition. The experimental results show that the recognition time of this method is only 4.0 s, with a precision rate of up to 99.9% and a recall rate of up to 99.2%.

Published
2024
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50. Notice of Retraction: Factor weighing of computer-supported collaborative inquiry learning effect via AHP: A case approach

Author

Jiang Xiaoguang and Ju Fanghui

Subjects
Knowledge management, business.industry, Computer science, Professional learning community, Educational technology, Mathematics education, Information technology, Context (language use), Collaborative learning, business, Experiential learning, Computer technology, Learning effect
Abstract

The positive effect of information technology applying in teaching and studying process had been confirmed, therefore computer-supported pedagogy is adopted by Chinese educators, particularly in collaborative inquiry context in late years. This paper is trying to identify factors impact on students' learning effect in computer-supported collaborate inquiry context. The study was based on the questionnaire survey and in-depth interviews of Wanli University students who take learning in the context of computer-supported collaborative inquiry. Analytical Hierarchy Process model was developed by author in the research for weighing factors of learning effect base on the view of Wanli university students. The result shows in this case research that under the computer-supported collaborate inquiry context, learning contents and visual presentations was least influence the learning effect, the computer technology support and assessing process played the biggest roles on impacting the learning effectiveness.

Published
2010

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