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2,381 results on '"Zhang, Hong-yu"'

2. ShizishanGPT: An Agricultural Large Language Model Integrating Tools and Resources

Author

Yang, Shuting, Liu, Zehui, Mayer, Wolfgang, Ding, Ningpei, Wang, Ying, Huang, Yu, Wu, Pengfei, Li, Wanli, Li, Lin, Zhang, Hong-Yu, Feng, Zaiwen, Goos, Gerhard, Series 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, Barhamgi, Mahmoud, editor, Wang, Hua, editor, and Wang, Xin, editor

Published
2025
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7. Causal Intervention for Measuring Confidence in Drug-Target Interaction Prediction

Author

Ye, Wenting, Li, Chen, Xie, Yang, Zhang, Wen, Zhang, Hong-Yu, Wang, Bowen, Cheng, Debo, and Feng, Zaiwen

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Machine Learning
Abstract

Identifying and discovering drug-target interactions(DTIs) are vital steps in drug discovery and development. They play a crucial role in assisting scientists in finding new drugs and accelerating the drug development process. Recently, knowledge graph and knowledge graph embedding (KGE) models have made rapid advancements and demonstrated impressive performance in drug discovery. However, such models lack authenticity and accuracy in drug target identification, leading to an increased misjudgment rate and reduced drug development efficiency. To address these issues, we focus on the problem of drug-target interactions, with knowledge mapping as the core technology. Specifically, a causal intervention-based confidence measure is employed to assess the triplet score to improve the accuracy of the drug-target interaction prediction model. Experimental results demonstrate that the developed confidence measurement method based on causal intervention can significantly enhance the accuracy of DTI link prediction, particularly for high-precision models. The predicted results are more valuable in guiding the design and development of subsequent drug development experiments, thereby significantly improving the efficiency of drug development.

Published
2023

8. BPCE: A Prototype for Co-Evolution between Business Process Variants through Configurable Process Model

Author

Liu, Linyue, Guo, Xi, Ouyang, Chun, Hung, Patrick C. K., Zhang, Hong-Yu, He, Keqing, Mo, Chen, and Feng, Zaiwen

Subjects
Computer Science - Software Engineering, 68N99, D.2.2
Abstract

With the continuous development of business process management technology, the increasing business process models are usually owned by large enterprises. In large enterprises, different stakeholders may modify the same business process model. In order to better manage the changeability of processes, they adopt configurable business process models to manage process variants. However, the process variants will vary with the change in enterprise business demands. Therefore, it is necessary to explore the co-evolution of the process variants so as to effectively manage the business process family. To this end, a novel framework for co-evolution between business process variants through a configurable process model is proposed in this work. First, the mapping relationship between process variants and configurable models is standardized in this study. A series of change operations and change propagation operations between process variants and configurable models are further defined for achieving propagation. Then, an overall algorithm is proposed for achieving co-evolution of process variants. Next, a prototype is developed for managing change synchronization between process variants and configurable process models. Finally, the effectiveness and efficiency of our proposed process change propagation method are verified based on experiments on two business process datasets. The experimental results show that our approach implements the co-evolution of process variants with high accuracy and efficiency., Comment: 18 pages , 11 figures

Published
2023

9. SGMFQP:An Ontology-based Swine Gut Microbiota Federated Query Platform

Author

Wang, Ying, Jiang, Qin, Geng, Yilin, Hu, Yuren, Tang, Yue, Li, Jixiang, Zhang, Junmei, Mayer, Wolfgang, Liu, Shanmei, Zhang, Hong-Yu, Yan, Xianghua, and Feng, Zaiwen

Subjects
Computer Science - Databases, Quantitative Biology - Quantitative Methods
Abstract

Gut microbiota plays a crucial role in modulating pig development and health, and gut microbiota characteristics are associated with differences in feed efficiency. To answer open questions in feed efficiency analysis, biologists seek to retrieve information across multiple heterogeneous data sources. However, this is error-prone and time-consuming work since the queries can involve a sequence of multiple sub-queries over several databases. We present an implementation of an ontology-based Swine Gut Microbiota Federated Query Platform (SGMFQP) that provides a convenient, automated, and efficient query service about swine feeding and gut microbiota. The system is constructed based on a domain-specific Swine Gut Microbiota Ontology (SGMO), which facilitates the construction of queries independent of the actual organization of the data in the individual sources. This process is supported by a template-based query interface. A Datalog+-based federated query engine transforms the queries into sub-queries tailored for each individual data source, and an automated workflow orchestration mechanism executes the queries in each source database and consolidates the results. The efficiency of the system is demonstrated on several swine feeding scenarios.

Published
2023

24. A Reinforcement Learning-Based Approach for Continuous Knowledge Graph Construction

Author

Luo, Jiao, Zhang, Yitao, Wang, Ying, Mayer, Wolfgang, Ding, Ningpei, Li, Xiaoxia, Quan, Yuan, Cheng, Debo, Zhang, Hong-Yu, Feng, Zaiwen, 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, Jin, Zhi, editor, Jiang, Yuncheng, editor, Buchmann, Robert Andrei, editor, Bi, Yaxin, editor, Ghiran, Ana-Maria, editor, and Ma, Wenjun, editor

Published
2023
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27. A life-threatening bleeding prediction model for immune thrombocytopenia based on personalized machine learning: a nationwide prospective cohort study

Author

An, Zhuo-Yu, Wu, Ye-Jun, Hou, Yu, Mei, Heng, Nong, Wei-Xia, Li, Wen-Qian, Zhou, Hu, Feng, Ru, Shen, Jian-Ping, Peng, Jun, Zhou, Hai, Liu, Yi, Song, Yong-Ping, Yang, Lin-Hua, Fang, Mei-Yun, Li, Jian-Yong, Cheng, Yun-Feng, Liu, Peng, Xu, Ya-Jing, Wang, Zhao, Luo, Yi, Cai, Zhen, Liu, Hui, Wang, Jing-Wen, Li, Juan, Zhang, Xi, Sun, Zi-Min, Zhu, Xiao-Yu, Wang, Xin, Fu, Rong, Huang, Liang, Wang, Shao-Yuan, Yang, Tong-Hua, Su, Li-Ping, Ma, Liang-Ming, Chen, Xie-Qun, Liu, Dai-Hong, Yao, Hong-Xia, Feng, Jia, Zhang, Hong-Yu, Jiang, Ming, Zhou, Ze-Ping, Wang, Wen-Sheng, Shen, Xu-Liang, Baima, Yangjin, Li, Yue-Ying, Wang, Qian-Fei, Huang, Qiu-Sha, Fu, Hai-Xia, Zhu, Xiao-Lu, He, Yun, Jiang, Qian, Jiang, Hao, Lu, Jin, Zhao, Xiang-Yu, Chang, Ying-Jun, Wu, Tao, Pan, Yao-Zhu, Qiu, Lin, Gao, Da, Jin, A-Rong, Li, Wei, Gao, Su-Jun, Zhang, Lei, Hou, Ming, Huang, Xiao-Jun, and Zhang, Xiao-Hui

Published
2023
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44. High reliable gas sensor based on crystal-facet regulated α-Fe2O3 nanocrystals for rapid detection of exhaled acetone.

Author

Hu, Jin-Yong, Lei, Hong, Zhang, Hong-Yu, Xue, Xiong-Xiong, Wang, Xin-Peng, Wang, Cong-Hui, and Zhang, Yong

Abstract

Copyright of Rare Metals is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2024
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