The Research on Optimization of Badminton Sport Competition Environment-Hawkeye Instant Replay

Xiaofeng Su, Pingping Liu and Li Guo

Abstract: With the development of badminton games, both fans and athletes are all put forward higher requirements for fair judgment. However, it is difficult to solve all disputes fairly due to the limitation of human vision. Therefore, the introduction of Hawkeye is the key to solve above problems. This paper is divided into three parts; the first part introduces the working principle of Hawkeye briefly, and the necessity of introducing Hawkeye technology. The second part mainly discusses the current problems existing in Hawkeye. The last part makes suggestions to solve the problem existing in badminton sport. Finally, we can draw the conclusion that Hawkeye technology will be more widely used in sports field. Meanwhile, with the maturation of Hawk-Eye technology, this technology will certainly achieve very well application in other sports.

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Research on Key Technologies of Music Data Management Based on Graph

Yutong Liu

Abstract: Considering the deficiencies of existing music data models and queiy languages, this paper presents a graph-based music data model named Gra-MM to model music data with complicated relationships. The definition of model’s logical data structure and algebraic operations are given. Then based on Gra-MM, this paper present a music data query language called Gra-MQL, giving the BNF syntax in the language. Gra-MQL can handle the complicated relationships among music data well, and also has the ability to query music by meta data as well as music content data, which meets the demands of various users and overcomes the shortcomings of traditional graph query languages which do not have adequate expressive power when dealing with data that have complicated relationships and don’t have the ability to query music based on music content data.

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A Performance Prediction to Shanghai Disneyland Resort: Multiple Regression Analysis Based on the Experiences of Hong Kong Disneyland

Haotian Deng, Xianshu Wang, Junyuan Xiang, Yueqi Zhang, Xin Tian, and Delin Yang

Abstract: Prediction on a newly-established tourist site or commercial property is usually difficult due to the lack of historical data and the problem of finding a similar comparison counterpart. Shanghai Disneyland Resort is openning soon and has attracted huge attention from general public, however question remains as to the performance of it. This article starts from the historical data of Hong Kong Disneyland, by exerting multiple regression analysis with conparison method, then derives highly fitting models on telling the vistor consumption amount and visior flow volume which are the key factors for our further prediction on the income statement of Shnghai Disneyland Resort. To give extented application, our disccusion of Shanghai Disneyland Resort provides a new train of thought of prediciting a newly-established tourist site or commercial property.

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QSAR Study of 2,4-diaminopyrimidine Derivatives as GHS-R Antagonists by HM and GEP

Fucheng Song, Lianhua Cui, Jinmei Piao, Hongzong Si and Honglin Zhai

Abstract: Two-dimensional quantitative structure–activity relationship studies were performed on a series of 2,4-diaminopyrimidine derivatives as the inhibitors of growth hormone secretagogue receptor, and to gain insights into the structural determinants. The heuristic method was used to explore the descriptors responsible for bioactivity and gain a best linear model with R² 0.74 in CODESSA software. Gene expression programming method produced a nonlinear quantitative model that R² 0.80 for training set, and R+ 0.72 for test set. This paper provides new instruction for effective drug designing and screening in the future.

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