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625 results on '"Zhang, Chunying"'

51. Transcriptome-Wide Analysis of Core Transcription Factors Associated with Defense Responses in Autotetraploid versus Diploid Rice under Saline Stress and Recovery

Author

Wang, Yingkai, primary, Meng, Weilong, additional, Ye, Yan, additional, Yu, Xinfang, additional, Chen, Haiyuan, additional, Liu, Yuchen, additional, Xu, Minghong, additional, Wang, Ningning, additional, Qi, Fan, additional, Lan, Yujie, additional, Xu, Yan, additional, Ma, Jian, additional, and Zhang, Chunying, additional

Published
2023
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55. Asymmetric Ternary Spiro Phosphine Oxide Hosts for Yellow Thermally Activated Delayed Fluorescence Diodes with External Quantum Efficiency Beyond 30%

Author

Wang, Zicheng, primary, Man, Yi, additional, Zhang, Chunying, additional, Pang, Yudong, additional, Wei, Ying, additional, Zhang, Jing, additional, Shuo, Chen, additional, Duan, Chunbo, additional, Han, Chunmiao, additional, Cao, Chenhui, additional, Shui, Xinfeng, additional, and Xu, Hui, additional

Published
2023
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57. Boronotyrosine, a Borylated Amino Acid Mimetic with Enhanced Solubility, Tumor Boron Delivery, and Retention for the Re-emerging Boron Neutron Capture Therapy Field

Author

Raitano, Arthur, primary, Martin, Tioga, additional, Zhang, Chunying, additional, Malinao, Maria-Christina, additional, Capo, Linnette, additional, Ikeura, Maki, additional, Carroll, Rebecca, additional, Quintana, Jason C., additional, Dlamini, Samkeliso, additional, Kulenovic, Leila, additional, Jahanshir, Eva, additional, Kang, Sohye, additional, Morrison, Karen, additional, Torgov, Michael, additional, and Morrison, Kendall, additional

Published
2023
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58. Dynamic Three Way Decisions and Its Application Based on Two-Direction PS-Probabilistic Rough Set

Author

Zhang, Chunying, Wang, Liya, Liu, Baoxiang, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Polkowski, Lech, editor, Yao, Yiyu, editor, Artiemjew, Piotr, editor, Ciucci, Davide, editor, Liu, Dun, editor, Ślęzak, Dominik, editor, and Zielosko, Beata, editor

Published
2017
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64. Rough Control Rule Mining Model Based on Decision Interval Concept Lattice and Its Application

Author

Sun, Ailing, Zhang, Chunying, Wang, Liya, Wang, Zhijiang, Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kara, Orhun, Series editor, Liu, Ting, Series editor, Kotenko, Igor, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Chen, Wenguang, editor, Yin, Guisheng, editor, Zhao, Gansen, editor, Han, Qilong, editor, Jing, Weipeng, editor, Sun, Guanglu, editor, and Lu, Zeguang, editor

Published
2016
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67. MTTEGDM: A Moving Target Evolutionary Game Defense Model Based on Three-Way Decisions.

Author

Zhang, Zhihua, Liu, Lu, Zhang, Chunying, Ren, Jing, Ma, Jiang, Wang, Liya, and Liu, Bin

Subjects
MONTE Carlo method, HATE crimes, BIAS correction (Topology), EVOLUTIONARY models
Abstract

Aiming at the fact that the moving target defense game model fails to accurately portray attack and defense gains, resulting in bias in attack and defense games and the inability to select effective defense strategies, we construct the moving target three-way evolutionary game defense model (MTTEGDM). Firstly, the model is defined and analyzed theoretically under the premise of uncertainty and irrationality. Then, combined with the three-way decisions, the attack intention is introduced into the target network loss calculation, and a dynamic weight adjustment algorithm based on the three-way decisions is proposed to accurately characterize the attack and defense gains from a multi-attribute perspective. Finally, the evolutionary game model is used to analyze the evolution trend of the multi-stage defense strategy, so as to carry out feasible and effective defense behavior. The simulation results show that the model can accurately predict the optimal defense strategy of moving targets in different stages. Through a Monte Carlo simulation experiment, the proposed algorithm is compared with the traditional evolutionary game model, and the effectiveness and security of the proposed algorithm are verified. [ABSTRACT FROM AUTHOR]

Published
2024
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78. Three-way decision models and its optimization based on Dempster–Shafer evidence theory and rough sets

Author

Zhang, Chunying, Feng, Xiaoze, and Gao, Ruiyan

Abstract

Dempster–Shafer evidence, rough set and three-way decision are related to each other. They are all theories and methods of handling uncertain information. First, it is required to combine the Dempster–Shafer evidence with rough set theory, and the rough set theory can therefore be applied to obtain the basic probability assignment function of evidence, which allows it to be obtained more objectively. Second, the conditional probability function in the three-way decision is replaced by a value in the belief interval, and three-way decision models are established to integrate the Dempster–Shafer evidence theory with rough sets. Third, by adjusting the value of the belief factor, the decision inference rules suitable for decision-makers of different risk types are obtained. Finally, an example is provided in this case to prove the validity of this model.

Published
2024
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79. Three-way clustering method for incomplete information system based on set-pair analysis

Author

Zhang, Chunying, Gao, Ruiyan, Qin, Hao, and Feng, Xiaoze

Abstract

Traditional clustering algorithms clearly assign uncertain information into a single cluster, which does not fully indicate that a cluster may not have a clear boundary. For a large number of missing data, the traditional clustering method cannot achieve a good clustering effect on these datasets. Therefore, the idea of three-way decision is introduced into the traditional k-means clustering, as a result, the knowledge of set-pair information granule be combined. This paper presents a three-way clustering method which can process missing values effectively. First, for missing values, the granularity corresponding to missing values are recorded as the degree of difference. Next, the algorithm is going to establish the distance between the samples and the clustering centers according to the set-pair theory. All samples are assigned into clusters according to the size of the distance, and the clustering results with three-way are formed, which are positive region, boundary region and negative region, which improves the structure of clustering results. The samples of positive region certainly belong to this cluster; the samples of boundary region may belong to this cluster; the samples of negative region don’t belong to this cluster; and the clustering results are represented by the three regions together. Finally, the validity of the algorithm is verified by UCI dataset great work.

Published
2024
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80. Construction and Embedding Representation of Relational Aggregation Hypergraphs in Cyber-Physical Systems

Author

Zhang, Liyan, Guo, Jingfeng, Li, Yang, Wang, Jing, Li, Shanshan, Zhang, Chunying, and Ji, Jiaqi

Abstract

With the rapid development of cyber-physical systems (CPS), constructing information systems with high-quality services has become an urgent requirement in both academia and industry. Hypergraphs are widely used in graph data analysis tasks due to their wide node-aware range and reasonable interpretability. This article proposes a model known as the relation-aggregated hypergraph neural network, which aims to better describe and apply complex structures and relationships in the physical world, thereby improving the management efficiency and service quality of service recommendation in CPS. First, explicit and implicit hyperedges are constructed based on the explicit and implicit relationships between nodes, respectively. Second, a global attention mechanism is adopted to calculate the importance between neighbor nodes that share implicit hyperedges with the current node, generating a relation-aggregated hypergraph. Finally, by weighting the generated hypergraph association matrix and passing the aggregated features through the hypergraph neural network, we obtain the embedding representation of nodes. Node classification experiments were conducted on three public network datasets, and the accuracy rates were 83.7%, 88.8%, and 84.9%, respectively, which were higher than those of the baseline model.

Published
2023
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82. Research on the Method of Hypergraph Construction of Information Systems Based on Set Pair Distance Measurement.

Author

Wang, Jing, Lan, Siwu, Li, Xiangyu, Lu, Meng, Guo, Jingfeng, Zhang, Chunying, and Liu, Bin

Subjects
INFORMATION storage & retrieval systems, K-nearest neighbor classification, RESEARCH methodology, SET theory, HYPERGRAPHS
Abstract

As a kind of special graph of structured data, a hypergraph can intuitively describe not only the higher-order relation and complex connection mode between nodes but also the implicit relation between nodes. Aiming at the limitation of traditional distance measurement in high-dimensional data, a new method of hypergraph construction based on set pair theory is proposed in this paper. By means of dividing the relationship between data attributes, the set pair connection degree between samples is calculated, and the set pair distance between samples is obtained. Then, on the basis of set pair distance, the combination technique of k-nearest neighbor and ε radius is used to construct a hypergraph, and high-dimensional expression and hypergraph clustering are demonstrated experimentally. By performing experiments on different datasets on the Kaggle open-source dataset platform, the comparison of cluster purity, the Rand coefficient, and normalized mutual information are shown to demonstrate that this distance measurement method is more effective in high-dimensional expression and exhibits a more significant performance improvement in spectral clustering. [ABSTRACT FROM AUTHOR]

Published
2023
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83. Analyst Coverage and Corporate ESG Performance.

Author

Zhang, Chunying and Wu, Xiaohui

Abstract

In recent years, environmental, social, and governance factors (ESG) have played an increasingly significant role in the practice of corporate development of widespread concern. For corporate ESG, it is still necessary to consider the factors that influence the development of corporate ESG. This paper performed fixed-effect panel model analysis to investigate the relationship between analyst coverage and corporate ESG performance using data from China's listed firms from 2011 to 2021. Our results showed that analyst coverage improves corporate ESG performance, especially the environmental (E) and social (S) dimensions, proving that analyst coverage is an important driving force behind corporate ESG engagement. The results were shown to be valid through a series of endogeneity and robustness checks. In the heterogeneity analysis, we showed that the promotion effects are more significant for state-owned firms and firms faced with greater financial constraints and higher information asymmetry. Furthermore, analyst coverage improves corporate ESG performance through the potential channels of attracting media attention and conducting site visits. Our study enriches the existing literature on the determinants of corporate ESG performance, and highlights the role analysts play in shaping corporate non-financial behavior and promoting corporate sustainable development. [ABSTRACT FROM AUTHOR]

Published
2023
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91. Algorithm Research of Top-Down Mining Maximal Frequent SubGraph Based on Tree Structure

Author

Chen, Xiao, Zhang, Chunying, Liu, Fengchun, Guo, Jingfeng, Akan, Ozgur, Series editor, Bellavista, Paolo, Series editor, Cao, Jiannong, Series editor, Dressler, Falko, Series editor, Ferrari, Domenico, Series editor, Gerla, Mario, Series editor, Kobayashi, Hisashi, Series editor, Palazzo, Sergio, Series editor, Sahni, Sartaj, Series editor, Shen, Xuemin (Sherman), Series editor, Stan, Mircea, Series editor, Xiaohua, Jia, Series editor, Zomaya, Albert, Series editor, Coulson, Geoffrey, Series editor, Sénac, Patrick, editor, Ott, Max, editor, and Seneviratne, Aruna, editor

Published
2012
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