Computer Aided Teaching System Based on Artificial Intelligence in Football Teaching and Training

As the world's largest sport, football has affected a wide area and a large number of participants and had a great impact on political economy and culture, which has become the best embodiment of the social function of football. Throughout the experience of football in developed countries in the world, the stable development of youth football is the best way to improve the level of football in a country, and the Chinese Football Association has invested more energy in professional leagues and national teams. The development of youth campus football is basically in a state of no management. Therefore, people gradually realize the concept that “football should serve education.” In order to solve the problem of football players' lack of exercise in multiple subjects, it is particularly important to design systems and make plans for their respective physical characteristics. After the failure of various important competitions, the Chinese national football team reflected on the specific factors of backwardness. Under today's system, no one manages the specific development of youth campus football. Especially for young people, training programs that adapt to their individual characteristics should be formulated according to their growth stage and physical characteristics. It can effectively improve the efficiency of football teaching and training (FTT) by managing football players' training information and coaches' teaching information in an intelligent and informatized way. The different sports in which athletes participate in training are identified through the motion recognition layer. The data generated during the entire exercise process, including exercise time, number of exercises, score settlement, and other data, are stored, and the data are finally uploaded to the server, to carry out scientific analysis and management and generate sports training prescriptions in line with their own characteristics. This paper proposes research methods based on the intelligent integrated system of FTT, including literature retrieval, questionnaire survey, training empirical method, comparative analysis method, interview method, and support vector machine model for action recognition, which are used in football teaching and the design experiment of the intelligent integrated system for training; the overall architecture design of the football teaching intelligent integration system and the specific design of the football teaching intelligent integration system are proposed. The experimental results of this article show that 90.70% of players like the teaching mode of intelligent FTT, and the intelligent FTT system can help improve the enthusiasm of players in training and learning.

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Predicting Ink Transfer Rate of 3D Additive Printing Using EGBO Optimized Least Squares Support Vector Machine Model

Mathematical Problems in Engineering ◽

10.1155/2020/8642430 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Shengpu Li ◽

Yize Sun

Keyword(s):

Support Vector Machine ◽

Prediction Model ◽

Least Squares ◽

Transfer Rate ◽

Coefficient Of Determination ◽

Percentage Error ◽

Support Vector ◽

Experimental Sample ◽

Machine Model ◽

Ink Transfer

Ink transfer rate (ITR) is a reference index to measure the quality of 3D additive printing. In this study, an ink transfer rate prediction model is proposed by applying the least squares support vector machine (LSSVM). In addition, enhanced garden balsam optimization (EGBO) is used for selection and optimization of hyperparameters that are embedded in the LSSVM model. 102 sets of experimental sample data have been collected from the production line to train and test the hybrid prediction model. Experimental results show that the coefficient of determination (R2) for the introduced model is equal to 0.8476, the root-mean-square error (RMSE) is 6.6 × 10 (−3), and the mean absolute percentage error (MAPE) is 1.6502 × 10 (−3) for the ink transfer rate of 3D additive printing.

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A New Efficient Filtering Model for GPS/SINS Ultratight Integration System

Mathematical Problems in Engineering ◽

10.1155/2020/9158185 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Chaochen Wang ◽

Yuming Bo ◽

Changhui Jiang

Keyword(s):

Navigation System ◽

The State ◽

Integrated System ◽

State Model ◽

Integration System ◽

Filter Model ◽

Integration Mode ◽

Measurement Vector ◽

Computation Load ◽

Vector Dimension

Global Positioning System (GPS) and strap-down inertial navigation system (SINS) are recognized as highly complementary and widely employed in the community. The GPS has the advantage of providing precise navigation solutions without divergence, but the GPS signals might be blocked and attenuated. The SINS is a totally self-contained navigation system which is hardly disturbed. The GPS/SINS integration system could utilize the advantages of both the GPS and SINS and provide more reliable navigation solutions. According to the data fusion strategies, the GPS/SINS integrated system could be divided into three different modes: loose, tight, and ultratight integration (LI, TI, and UTC). In the loose integration mode, position and velocity difference from the GPS and SINS are employed to compose measurement vector, in which the vector dimension has nothing to do with the amount of the available satellites. However, in the tight and ultratight modes, difference of pseudoranges and pseudorange rates from the GPS and SINS are employed to compose the measurement vector, in which the measurement vector dimension increases with the amount of available satellites. In addition, compared with the loose integration mode, clock bias and drift are included in the integration state model. The two characteristics magnify the computation load of the tight and ultratight modes. In this paper, a new efficient filter model was proposed and evaluated. Two schemes were included in this design for reducing the computation load. Firstly, a difference between pseudorange measurements was determined, by which clock bias and drift were excluded from the integration state model. This step reduced the dimension of the state vector. Secondly, the integration filter was divided into two subfilters: pseudorange subfilter and pseudorange rate subfilter. A federated filter was utilized to estimate the state errors optimally. In the second step, the two subfilters could run in parallel and the measurement vector was divided into two subvectors with lower dimension. A simulation implemented in MATLAB software was conducted to evaluate the performance of the new efficient integration method in UTC. The simulation results showed that the method could reduce the computation load with the navigation solutions almost unchanged.

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Introduction of New Forms of Education in Modern Higher and Vocational Education and Training

International Journal of Higher Education ◽

10.5430/ijhe.v9n7p107 ◽

2020 ◽

Vol 9 (7) ◽

pp. 107

Author(s):

Liudmyla I. Berezovska ◽

Galyna D. Kondratska ◽

Anna A. Zarytska ◽

Kateryna S. Volkova ◽

Taras M. Matsevko

Keyword(s):

Higher Education ◽

Vocational Education ◽

Education System ◽

Comparative Method ◽

Developed Countries ◽

Education And Training ◽

Educational Process ◽

Vocational Education And Training ◽

National Education ◽

And Training

This article sets sights on highlighting the effectiveness and efficiency of higher and vocational education and training, as well as exploring ways to address and implement the current reform agenda in the field. The research was conducted on the basis of a generalizing and comparative method, to identify the problems and development of vocational and higher education. Within the framework of the conducted research the current state of vocational and higher education has been characterized; the features of online learning at leading universities and its advantages has been clarified; the prospects of introduction of continuity of education have been studied, for the development of personality abilities, taking into account changes in society in the context of improvement of the system of vocational and higher education caused by the European integration process of education; directions for the development of vocational and higher education as part of the national education system and society in general have been outlined. It is determined, that at the present stage the domestic education system should be improved and transferred to an innovative way of development in accordance with developed countries. In the near future, such modern forms of education as: distance education, dual education, continuing vocational education and others, should be improved and implemented into the educational process.

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An Improved Whale Algorithm for Support Vector Machine Prediction of Photovoltaic Power Generation

Symmetry ◽

10.3390/sym13020212 ◽

2021 ◽

Vol 13 (2) ◽

pp. 212

Author(s):

Yu-Wei Liu ◽

Huan Feng ◽

Heng-Yi Li ◽

Ling-Ling Li

Keyword(s):

Support Vector Machine ◽

Prediction Model ◽

Output Power ◽

Input Data ◽

Support Vector Machine Model ◽

Weather Conditions ◽

Clean Energy ◽

Support Vector ◽

Machine Model ◽

Photovoltaic Power

Accurate prediction of photovoltaic power is conducive to the application of clean energy and sustainable development. An improved whale algorithm is proposed to optimize the Support Vector Machine model. The characteristic of the model is that it needs less training data to symmetrically adapt to the prediction conditions of different weather, and has high prediction accuracy in different weather conditions. This study aims to (1) select light intensity, ambient temperature and relative humidity, which are strictly related to photovoltaic output power as the input data; (2) apply wavelet soft threshold denoising to preprocess input data to reduce the noise contained in input data to symmetrically enhance the adaptability of the prediction model in different weather conditions; (3) improve the whale algorithm by using tent chaotic mapping, nonlinear disturbance and differential evolution algorithm; (4) apply the improved whale algorithm to optimize the Support Vector Machine model in order to improve the prediction accuracy of the prediction model. The experiment proves that the short-term prediction model of photovoltaic power based on symmetry concept achieves ideal accuracy in different weather. The systematic method for output power prediction of renewable energy is conductive to reducing the workload of predicting the output power and to promoting the application of clean energy and sustainable development.

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Reference intervals for 26 common biochemical analytes in term neonates in Jilin Province, China

BMC Pediatrics ◽

10.1186/s12887-021-02565-8 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Kaijin Wang ◽

Xuetong Zhu ◽

Qi Zhou ◽

Jiancheng Xu

Keyword(s):

Lactate Dehydrogenase ◽

Clinical Decision Making ◽

Reference Intervals ◽

Individual Characteristics ◽

Integrated System ◽

Delivery Mode ◽

Related Factor ◽

Term Neonates ◽

Age Related ◽

Laboratory Test Results

Abstract Background Biochemical analytes provide information for neonatal disease management and therapy, and population-based reference intervals (RIs) are essential to accurately interpret laboratory test results. This study aimed to establish local RIs for biochemical assays in term neonates. Methods A total of 195 healthy term neonates from birth to 3rd day were recruited as reference individuals prospectively. Analytes of 26 common biochemistries were measured using the VITROS 5600 Integrated System. The 3-level nested ANOVA was performed to assess the need for partitioning RIs of each analyte, and RIs were derived by a nonparametric method or robust method. Multiple regression analysis was used to evaluate specific correlations between the analytes and individual characteristics including age, gender, gestational age, birthweight and delivery mode. Results There were no between-sex differences in all analytes, whereas there were significant between-day-age differences in 6 analytes. Small between-delivery-mode differences were observed in the results for potassium, phosphorus, and urea. The major related factor of most analytes was postnatal age. During the first 3 days, values of iron, lipids and lipoproteins increased; creatinine, urea, uric acid, creatine kinase and lactate dehydrogenase decreased; other analytes showed slight changes or relatively stable trends. Reference limits of some analytes, particularly lactate dehydrogenase and alkaline phosphatase, were significantly different from adult and pediatric groups. Conclusions RIs of 26 common biochemical analytes are established for term neonates aged 0 to 3 days in northeast China. Additionally, it is suggested that age-related changes should be valued in the clinical decision-making process for newborns.

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