scholarly journals EMPIRICAL STUDY ON REFORM AND INNOVATION OF TAX LAW TALENT TRAINING MODE IN UNIVERSITIES IN THE CONTEXT OF INTERNET PLUS

2021 ◽  
Author(s):  
QUAN TAO
Keyword(s):  
Industrial Structure ◽  
Knowledge Society ◽  
Principal Component ◽  
Chinese Higher Education ◽  
Tax Law ◽  
System Reform ◽  
Economic Market ◽  
Training Mode ◽  
New Form ◽  
Reform And Innovation

With the continuous development of Internet plus information technology and the continuous changes of the economic market environment, the traditional tax law talent training mode can no longer meet the new standards and requirements. In this context, this paper studies the reform and innovation of tax law talent training mode in universities, first it reviews the literature, then points out the relevant significance, and applies the principal component analysis method for analysis, and finally puts forward the relevant measures. Internet plus is the new form of Internet development under the innovation, and it is the new form of economic and social development promoted by the evolution of the Internet form promoted by innovation of knowledge society. The combination of Internet plus tax law talent cultivation and innovation mechanism is conducive to promoting the national tax system reform and upgrading of industrial structure, and promoting the continuous evolution of economic form, thereby promoting the vitality of social economic entities, and providing a broad platform for reform, innovation and development[1]. Under the background of Internet plus, Chinese higher education needs to train more talents for tax law practice suitable for economic development, and promote reform and innovation of tax law teaching mode and personnel training mechanism.

scholarly journals Prediction of China’s Energy Consumption Based on Robust Principal Component Analysis and PSO-LSSVM Optimized by the Tabu Search Algorithm

Energies ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 196 ◽  
Author(s):  
Lihui Zhang ◽  
Riletu Ge ◽  
Jianxue Chai
Keyword(s):  
Principal Component Analysis ◽  
Energy Consumption ◽  
Tabu Search ◽  
Industrial Structure ◽  
Principal Component ◽  
Component Analysis ◽  
Support Vector ◽  
Forecasting Model ◽  
Robust Principal Component Analysis ◽  
Consumption Structure

China’s energy consumption issues are closely associated with global climate issues, and the scale of energy consumption, peak energy consumption, and consumption investment are all the focus of national attention. In order to forecast the amount of energy consumption of China accurately, this article selected GDP, population, industrial structure and energy consumption structure, energy intensity, total imports and exports, fixed asset investment, energy efficiency, urbanization, the level of consumption, and fixed investment in the energy industry as a preliminary set of factors; Secondly, we corrected the traditional principal component analysis (PCA) algorithm from the perspective of eliminating “bad points” and then judged a “bad spot” sample based on signal reconstruction ideas. Based on the above content, we put forward a robust principal component analysis (RPCA) algorithm and chose the first five principal components as main factors affecting energy consumption, including: GDP, population, industrial structure and energy consumption structure, urbanization; Then, we applied the Tabu search (TS) algorithm to the least square to support vector machine (LSSVM) optimized by the particle swarm optimization (PSO) algorithm to forecast China’s energy consumption. We collected data from 1996 to 2010 as a training set and from 2010 to 2016 as the test set. For easy comparison, the sample data was input into the LSSVM algorithm and the PSO-LSSVM algorithm at the same time. We used statistical indicators including goodness of fit determination coefficient (R2), the root means square error (RMSE), and the mean radial error (MRE) to compare the training results of the three forecasting models, which demonstrated that the proposed TS-PSO-LSSVM forecasting model had higher prediction accuracy, generalization ability, and higher training speed. Finally, the TS-PSO-LSSVM forecasting model was applied to forecast the energy consumption of China from 2017 to 2030. According to predictions, we found that China shows a gradual increase in energy consumption trends from 2017 to 2030 and will breakthrough 6000 million tons in 2030. However, the growth rate is gradually tightening and China’s energy consumption economy will transfer to a state of diminishing returns around 2026, which guides China to put more emphasis on the field of energy investment.

On the Way to Smart Education and Urban Society

2019 ◽  
pp. 1-11
Author(s):  
Linda Daniela ◽  
Kwok Tai Chui ◽  
Anna Visvizi ◽  
Miltiades D. Lytras
Keyword(s):  
Quantitative Data ◽  
Knowledge Society ◽  
Descriptive Analysis ◽  
Urban Society ◽  
Future Directions ◽  
Aggregated Data ◽  
Research Article ◽  
Smart Education ◽  
New Form ◽  
Emerging Topics

This chapter summarizes the development and transformation of the International Journal of Knowledge Society Research (IJKSR) into a new form called the International Journal of Smart Education and Urban Society (IJSEUS). In the chapter, there is used literature review methodology to analyze the 199 articles published in 32 issues from 2010 to 2017. The obtained results allow us to ascertain what were the emerging topics published in the journal, which types of research article are published more often, and which countries are represented. The aggregated data also allow us to identify future directions in developing a journal and promoting its visibility and citation. The descriptive analysis method was adopted for data analysis, the quantitative data were compiled using Excel software, and the content analysis was done descriptively by defining the research categories.

A Positive and Comparative Study on Industrial Structure Transformation Capacity of Provincial Level Divisions in China

2013 ◽  
Vol 807-809 ◽  
pp. 1780-1786
Author(s):  
Xi Ping Pan ◽  
Jing Hua Sha ◽  
Yan Shuang She
Keyword(s):  
Principal Component Analysis ◽  
Comparative Analysis ◽  
Industrial Structure ◽  
Principal Component ◽  
Industry Structure ◽  
Structure Transformation ◽  
The West ◽  
Industrial Transformation ◽  
Provincial Level ◽  
Industrial Economics

Most urban planning policies are affected by the industrial structure. This paper gave a positive and comparative analysis on the industrial structure transformation ability and transformation direction of the thirty-one provincial level divisions in China by using principal component analysis, based on theories of regional economic development and industrial economics. The results show that Beijing, Shanghai, Guangdong, Jiangsu, Zhejiang and Shandong have strong industrial structure transformation ability and the industrial transformation direction is in the tertiary industry except for Guangdong, Jiangsu and Shandong. The industrial structure transformation ability over the thirty-one regions exhibits a decreasing trend from the eastern coastal area to the west inland. The sequence of industry structure transformation direction is from the first industry to the second and then to the tertiary for China.

scholarly journals Multiple Measures are Needed to Quantify Training Loads in Professional Rugby League

2017 ◽  
Vol 38 (10) ◽  
pp. 735-740 ◽  
Author(s):  
Daniel Weaving ◽  
Ben Jones ◽  
Phil Marshall ◽  
Kevin Till ◽  
Grant Abt
Keyword(s):  
Principal Component Analysis ◽  
Principal Components ◽  
High Speed ◽  
Perceived Exertion ◽  
Principal Component ◽  
Component Analysis ◽  
Rugby League ◽  
Training Load ◽  
Rating Of Perceived Exertion ◽  
Training Mode

AbstractThis study aims to investigate the effect of training mode (conditioning and skills) on multivariate training load relationships in professional rugby league via principal component analysis. Four measures of training load (internal: heart rate exertion index, session rating of perceived exertion; external: PlayerLoad™, individualised high-speed distance) were collected from 23 professional male rugby league players over the course of one 12 wk preseason period. Training was categorised by mode (skills or conditioning) and then subjected to a principal component analysis. Extraction criteria were set at an eigenvalue of greater than 1. Modes that extracted more than 1 principal component were subject to a varimax rotation. Skills extracted 1 principal component, explaining 57% of the variance. Conditioning extracted 2 principal components (1st: internal; 2nd: external), explaining 85% of the variance. The presence of multiple training load dimensions (principal components) during conditioning training provides further evidence of the influence of training mode on the ability of individual measures of external or internal training load to capture training variance. Consequently, a combination of internal and external training-load measures is required during certain training modes.

Education and Teaching Methods of Full-Time Engineering Professional Master

2014 ◽  
Vol 971-973 ◽  
pp. 2579-2582
Author(s):  
Ping Cao ◽  
Yong Gang Yan ◽  
Qi Jun Chen
Keyword(s):  
Graduate Education ◽  
Teaching Methods ◽  
Research Training ◽  
Full Time ◽  
Training Method ◽  
Master Degree ◽  
Initial Stage ◽  
Training Mode ◽  
New Form

As a new form of graduate education, full-time professional master degree of Shandong Jianzhu University is in the initial stage, so it is necessary to study the training objectives, curriculum and teaching methods of professional master systematically. The paper describes the characteristics of professional master's education of the engineering and introduces the training method of professional master of engineering on the basis of research, training mode and other aspects in detail, and then states the curriculum composed of several aspects, including degree courses, non-degree courses and compulsory part. Finally, the paper explores the education and teaching methods of engineering professional master.

scholarly journals Sustainable development based on structural transformation in Southeast China

2020 ◽  
Author(s):  
Meiping Liu
Keyword(s):  
Economic System ◽  
Structural Adjustment ◽  
Industrial Structure ◽  
Transition Period ◽  
Rapid Development ◽  
Subsequent Development ◽  
System Reform ◽  
Quality Development ◽  
High Quality ◽  
Southeast China

China has developed into a highly diversified economy. Southeast China is one important region with rapid economic development and generally considered to contain Zhejiang, Fujian and Guangdong. The rapid development of Southeast China under structural adjustment is an exploration of the development of the forefront of China's reform and opening up. Structural adjustment is a major theoretical and practical improvement. Through the academic exploration of the current industrial structure transformation and upgrading, this paper deepens the understanding of Southeast China's high-quality development and helps to promote the construction of the modern economic system. Based on the exploration of the characteristics of the transition period of economic construction. This paper examines the characteristics and advantages of Southeast China's high-quality development and the challenges that may be faced in subsequent development. This paper makes recommendations for economic system reform and government services.

scholarly journals Analysis of Factors Influencing the Coordinated Development of New Urbanization with Green and Low Carbon under the Ecological Perspective - Taking Heilongjiang Province as an Example

2018 ◽  
Vol 53 ◽  
pp. 04048
Author(s):  
Youjun Li ◽  
Wei Li
Keyword(s):  
Industrial Structure ◽  
Principal Component ◽  
Ecological Perspective ◽  
Heilongjiang Province ◽  
Low Carbon ◽  
Coordinated Development ◽  
Green Development ◽  
New Type ◽  
Countermeasures And Suggestions ◽  
New Urbanization

Under the ecological perspective, the new type of urbanization, green and low-carbon coordinated development is a powerful engine for economic development. Based on the analysis of the existing results of the new urbanization green development and low-carbon development factors, a new index system of influencing factors for the coordinated development of green and low-carbon urbanization was constructed. And then concludes the results of the analysis by using the relevant statistical data of Heilongjiang Province from 2007 to 2017, using the principal component analysis method and using SPSS statistical software. Finally, puts forward some relevant countermeasures and suggestions on scientific and technological innovation, the industrial structure and cultural education, etc.

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