Sun Jinhua

Xiamen University of Technology

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Qingsong Wang

University of Science and Technology of China

Qiangling Duan

University of Science and Technology of China

Qiang Ding

China Automotive Technology and Research Center

Yu Wang

Beihang University

Jie Ji

University of Science and Technology of China

Xiangyang Wang

Shanghai University

Jiang Lin

Zhongshan Hospital

Kun Yang

China Jiliang University

Zihe Gao

University of Pennsylvania

Jiabao Wang

Chinese Academy of Tropical Agricultural Sciences

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Chinese Academy of Sciences

University of Science and Technology of China

Xiamen University of Technology

Shanghai Jiao Tong University

Chinese Academy of Tropical Agricultural Sciences

University of Chinese Academy of Sciences

Ministry of Agriculture and Rural Affairs

Xiamen University

Environment and Plant Protection Research Institute

Shanghai University

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エネルギー消費弾性制御下における地域エネルギーセキュリティの動的評価【JST・京大機械翻訳】

Anquan Yu Huanjing Xuebao (2016)

Hu Jian Sun Jinhua

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ベタインの生物学的機能とブタ肉質の改善におけるその応用【JST・京大機械翻訳】

Dongbei Nongye Daxue Xuebao (2016)

Zhang Jing Sun Jinhua Song Wentao Sun Yuecheng Anshan Shan

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省汚染源モニタリング情報公開状況評価指標システムの研究【JST・京大機械翻訳】

Huanjing Gongcheng Jishu Xuebao (2016)

Baiyin Liu Sun Jinhua Liu Xiao-fu Xu Chao Chen Yunwei

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Strategy on the Perfection of Stock Option Incentive and Corporate Governance

Sun Jinhua

The theoretical foundation of Executive Stock Option is agent theory and human capital theory. The widespread practice of ESO in the western countries provides an evidence for its effectiveness as an incentive mechanism. Introduction of ESO into Chinese corporate governance will facilitate in the regulation and normalization of managers' market and capital market. For the purpose of creating a healthy internal and external environment for the functioning of ESO, we must, in the course of practicing ESO, regulate in compliance with laws the sources of options, granting of options, determination of the striking prices, the volume of options, the length of maturity and other systematic institutions.

Perfection

Stock options

Normalization

Stock (firearms)

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位相解の曖昧さに基づく簡略化対角相互作用計算法【JST・京大機械翻訳】

Dianzi Xuebao (2016)

Sun Jinhua Zhongyang Yu Xuemin Duan

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ガラスファサードの熱性能に及ぼす火災位置の影響【Powered by NICT】

Applied Thermal Engineering (2016)

Yu Wang Qingsong Wang Sun Jinhua He Linghui K M Liew

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Additive rule of real and reciprocal space topologies at disclinations

arXiv (Cornell University) (2022)

Qinghua He Sun Jinhua Hai-Yao Deng Katsunori Wakabayashi Feng Liu

Topological materials are renowned for their ability to harbor states localized at their peripheries, such as surfaces, edges, and corners. Accompanying these states, fractional charges appear on peripheral unit cells. Recently, topologically bound states and fractional charges at disclinations of crystalline defects have been theoretically predicted. This so-called bulk-disclination correspondence has been experimentally confirmed in artificial crystalline structures, such as microwave-circuit arrays and photonic crystals. Here, we demonstrate an additive rule between the real-space topological invariant $\mathbf{s}$ (related to the Burgers vector $\mathbf{B}$) and the reciprocal-space topological invariant $\mathbf{p}$ (vectored Zak's phase of bulk wave functions). The bound states and fractional charges concur at a disclination center only if $\mathbf{s}+\mathbf{p}/2π$ is topologically nontrivial; otherwise, no bound state forms even if fractional charges are trapped. Besides the dissociation of fractional charges from bound states, the additive rule also dictates the existence of half-bound states extending over only half of a sample and ultra-stable bound states protected by both real-space and reciprocal-space topologies. Our results add another dimension to the ongoing study of topological matter and may germinate interesting applications.

Disclination

10.48550/arxiv.2202.09560

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スタック効果により誘起された空気流による火炎の偏向特性【Powered by NICT】

International Journal of Thermal Sciences (2017)

Jie Ji Man Li Shi Wenxi Zihe Gao Sun Jinhua

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Application of Grey-Markov Model in Forecasting Fire Accidents

Procedia Engineering (2011)

Zhanli Mao Sun Jinhua

Fire accidents are influenced by many complex factors, and it has the characteristic of both randomicity and fluctuation, so a new forecasting model (Grey-Markov model) was established in order to forecast fire accidents effectively in this paper, which has the merits of both GM (1, 1) forecast model and Markov chain forecast model, it can reduce random fluctuation of accident data affecting forecasting precision and develop the application scope of Grey forecast. Finally, an example was analyzed, the results show that Grey-Markov model proposed in this paper has a higher forecast precision and excellent applicability.

Scope (computer science)

10.1016/j.proeng.2011.04.663

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Light-efficient channel attention in convolutional neural networks for tic recognition in the children with tic disorders

Frontiers in Computational Neuroscience (2022)

Fudi Geng Qiang Ding Wanyu Wu Xiangyang Wang Yanping Li

Tic is a combination of a series of static facial and limb movements over a certain period in some children. However, due to the scarcity of tic disorder (TD) datasets, the existing work on tic recognition using deep learning does not work well. It is that spatial complexity and time-domain variability directly affect the accuracy of tic recognition. How to extract effective visual information for temporal and spatial expression and classification of tic movement is the key of tic recognition. We designed the slow-fast and light-efficient channel attention network (SFLCA-Net) to identify tic action. The whole network adopted two fast and slow branch subnetworks, and light-efficient channel attention (LCA) module, which was designed to solve the problem of insufficient complementarity of spatial-temporal channel information. The SFLCA-Net is verified on our TD dataset and the experimental results demonstrate the effectiveness of our method.

Complementarity (molecular biology)

Action Recognition

10.3389/fncom.2022.1047954

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