Institution
Nanjing University of Aeronautics and Astronautics
Education•Nanjing, China•
About: Nanjing University of Aeronautics and Astronautics is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Computer science & Microstructure. The organization has 33704 authors who have published 37321 publications receiving 438855 citations. The organization is also known as: Nanjing College of Aviation Industry & Nanjing Aeronautical Institute.
Papers published on a yearly basis
Papers
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TL;DR: Based on the stiffness degradation rule of composites, a phenomenological fatigue damage model is presented in this article, which contains two material parameters, i.e., the fatigue life of materials and inversely proportional to the fatigue loading level.
136 citations
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TL;DR: This work extracts the events from Web news and the users' sentiments from social media, and investigates their joint impacts on the stock price movements via a coupled matrix and tensor factorization framework.
Abstract: Traditional stock market prediction approaches commonly utilize the historical price-related data of the stocks to forecast their future trends. As the Web information grows, recently some works try to explore financial news to improve the prediction. Effective indicators, e.g., the events related to the stocks and the people’s sentiments toward the market and stocks, have been proved to play important roles in the stocks’ volatility, and are extracted to feed into the prediction models for improving the prediction accuracy. However, a major limitation of previous methods is that the indicators are obtained from only a single source whose reliability might be low, or from several data sources but their interactions and correlations among the multi-sourced data are largely ignored. In this work, we extract the events from Web news and the users’ sentiments from social media, and investigate their joint impacts on the stock price movements via a coupled matrix and tensor factorization framework. Specifically, a tensor is firstly constructed to fuse heterogeneous data and capture the intrinsic relations among the events and the investors’ sentiments. Due to the sparsity of the tensor, two auxiliary matrices, the stock quantitative feature matrix and the stock correlation matrix, are constructed and incorporated to assist the tensor decomposition. The intuition behind is that stocks that are highly correlated with each other tend to be affected by the same event. Thus, instead of conducting each stock prediction task separately and independently, we predict multiple correlated stocks simultaneously through their commonalities, which are enabled via sharing the collaboratively factorized low rank matrices between matrices and the tensor. Evaluations on the China A-share stock data and the HK stock data in the year 2015 demonstrate the effectiveness of the proposed model.
136 citations
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TL;DR: In this article, coal fly ash with size of 74 μm and sulfuric acid with concentration of 50% are mixed in pressure reaction kettle to react for 4 h at 180°C.
136 citations
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TL;DR: In this article, the effect of the size of the dimples on friction under line contact condition was investigated on a brass disk sliding against a stationary cylindrical surface of bearing roller.
136 citations
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TL;DR: The phase and morphology of as-synthesized RGO-Ni composites are characterized by XRD, Raman, FESEM and TEM in this paper, which shows that Ni nanoparticles with a diameter around 20nm are grown densely and uniformly on the RGO sheets.
136 citations
Authors
Showing all 34050 results
Name | H-index | Papers | Citations |
---|---|---|---|
Chao Zhang | 127 | 3119 | 84711 |
Guoxiu Wang | 117 | 654 | 46145 |
Zhongfan Liu | 115 | 743 | 49364 |
Xiaoming Li | 113 | 1932 | 72445 |
Wei Liu | 102 | 2927 | 65228 |
Shihua Li | 101 | 616 | 35335 |
Junjie Zhu | 100 | 719 | 46374 |
Lei Wang | 95 | 1486 | 44636 |
Gui-Rong Liu | 95 | 595 | 36641 |
Yongyao Xia | 95 | 389 | 30430 |
Haibo Zeng | 94 | 604 | 39226 |
Wei Zhou | 93 | 1640 | 39772 |
Xiaogang Zhang | 91 | 448 | 30136 |
Wei Chen | 90 | 938 | 35799 |
Xihong Lu | 88 | 337 | 29367 |