The Experts below are selected from a list of 213 Experts worldwide ranked by ideXlab platform
Wang Changzheng - One of the best experts on this subject based on the ideXlab platform.
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since implementing student physique healthy standard the jiangsu scientific and technical university student physique situation and the countermeasure analysis
Journal of Harbin Institute of Physical Education, 2007Co-Authors: Wang ChangzhengAbstract:Through the methods of literature material,Mathematical Statistic and soon,the student implement"Student Physique Healthy Standard"to the Jiangsu scientific and technical university from 2002 to 2004 and the situation dynamic analysis and the research,finally indicated:The Jiangsu scientific and technical university student physique healthy aggregate level enhances continuously,but has the height body weight index to present to the low body weight skewers distribution,the male student overweight and obese remarkable increase,questions and so on endurance quality serious landslide.The suggestion strengthens the health education,the increase sports facilities in- vestment,enhances the student"the health first,lifelong physical culture"exercise consciousness,inside and out- side strengthened class physical training"Trinity"the organic synthesis,promotes the student good life style raise and the establishment,the optimized sports classroom practice teaching material and the content choice,the deep- ened sports education reform,strengthens the student to and the physique healthy relevance high project endurance quality exercise,effective promotion overall physique health standard enhancement.
Jianfeng Qiu - One of the best experts on this subject based on the ideXlab platform.
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precursory pattern based feature extraction techniques for earthquake prediction
IEEE Access, 2019Co-Authors: Lei Zhang, Haipeng Yang, Jianfeng QiuAbstract:Earthquake prediction is an important and complex task in the real world. Although many data mining-based methods have been proposed to solve this problem, the prediction accuracy is still far from satisfactory due to the deficiency of feature extraction techniques. To this end, in this paper, we propose a precursory pattern-based feature extraction method to enhance the performance of earthquake prediction. Especially, the raw seismic data is firstly divided into fixed day time periods, and the magnitude of the largest earthquake in each fixed time period is labeled as the main shock. The precursory pattern is a part of the seismic sequence before the main shock, on which the existing Mathematical Statistic features can be directly generated as seismic indicators. Based on these precursory pattern-based features, a simple yet effective classification and regression tree algorithm is adopted to predict the label of the main shock in a pre-defined future time period. The experimental results on two historical earthquake records of the Changding-Garze and Wudu-Mabian seismic zones of China demonstrate the effectiveness of the proposed precursory pattern-based features with the selected CART algorithm for earthquake prediction.
Huijun Li - One of the best experts on this subject based on the ideXlab platform.
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effects of filling status of cold wire on the welding process stability in twin arc integrated cold wire hybrid welding
The International Journal of Advanced Manufacturing Technology, 2016Co-Authors: T Xiang, Huijun LiAbstract:Twin-wire metal inert gas/metal active gas (MIG/MAG) arc welding is one typical type of the high-efficient welding technologies. In order to further improve the welding efficiency without increasing the welding heat input, a novel welding technology entitled twin-arc integrated cold wire hybrid welding was developed. The addition of cold wire not only increased the welding deposition rate but also improved the welding stability. In this paper, the influential mechanism of cold wire on welding stability was studied by the high-speed photography and electrical signal acquisition. It was found that the cathode spot could be stabilized on the surface of the weld pool by increasing the cold wire feed speed, which significantly improved the welding stability. The main reasons are as follows: the addition of cold wire significantly decreased the temperature of the liquid weld pool metal around the cold wire. This led to increasing the electron emission difficulty and reducing the gradient distribution of surface tension. Therefore, the cathode spot would be more likely to stabilize in the high temperature zone instead of drifting with the rear flow of the liquid weld pool metal. Besides, the cathode spot could also be stabilized because of the less dramatic fluid flow of the liquid metal. Finally, the welding stability was evaluated by a Mathematical Statistic method, which further verified that the welding stability could be improved with the increase of cold wire feed speed to a proper range.
W U Guoshun - One of the best experts on this subject based on the ideXlab platform.
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study on generation mechanism of colorimetric planar properties in colorimetric data of process printing
Journal of Computer Applications, 2008Co-Authors: W U GuoshunAbstract:It is essential to find out relatively simple and highly effective methods of color space conversion in color management. As an optical phenomenon, the presence of dot colorimetric planes of four-color halftone printing provides a relatively novel thought to study color space conversion. The validity of the plane theory was verified by the Mathematical Statistic and the bivariate regression algorithm, and the generation mechanism of the plane theory was firstly analyzed by CIE1931Yxy chromaticity system.
Deming Kong - One of the best experts on this subject based on the ideXlab platform.
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Feasibility study on prediction of gasoline octane number using NIR spectroscopy combined with manifold learning and neural network.
Spectrochimica acta. Part A Molecular and biomolecular spectroscopy, 2019Co-Authors: Shutao Wang, Shiyu Liu, Jingkun Zhang, Xiange Che, Zhifang Wang, Deming KongAbstract:Abstract Octane number is an anti-knock index of fuel gasoline, which has an important impact on the service life of engine components and the safety of vehicles. Therefore, it is a basic work involving safety to predict the gasoline octane number accurately. This work was aimed to predict the octane number of near infrared (NIR) spectroscopy by combining dimension reduction algorithm with neural network. Covariance matrix estimation (CME), known as a Mathematical Statistic tool, was applied to estimating the intrinsic dimensions of octane spectrum dataset. Landmark-Isometric feature mapping (L-Isomap), as a novel manifold learning algorithm, was used for dimensionality reduction of spectral data. A new method, beetle antennae search optimization BP neural network (BAS-BP), was proposed to realize the prediction of octane number. In order to verify the performance of CME-L-Isomap-BAS-BP model presented in this paper, it is compared with other models. The results showed that when CME-L-Isomap was combined with BAS-BP, the average recovery rate (AR), mean square error (MSE), mean absolute percentage error (MAPE), correlation coefficient (R) and running time were superior than other models. The satisfying results demonstrated that the CME-L-Isomap-BAS-BP model is more suitable for prediction of gasoline octane number.