Application of Python Software Environment for Analyzing the Systems of Quality Management with the Use of Machine Teaching Methods

Dzedik, Valentin A.; Chigirinskaya, Natalia V.

doi:10.1007/978-3-319-90835-9_67

Cited by 2 publications

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“…Outsourcing in all considered cases provides a balance of corporate social responsibility, economic efficiency of the business, and its digital competitiveness (Dzedik and Chigirinskaya, 2019 ). In the first case, business communication with customers can be carried out on the terms of outsourcing (Li et al, 2022 ).…”

Section: Literature Reviewmentioning

confidence: 99%

“Smart” outsourcing in support of the humanization of entrepreneurship in the artificial intelligence economy

Matytsin

Dzedik

Makeeva

et al. 2023

Humanit Soc Sci Commun

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The article focuses on the problem of optimizing human resource management with systematic coverage of economic efficiency and corporate social responsibility. The purpose of the article is to study the role of outsourcing in the humanization of entrepreneurship in the AI economy. The potential of outsourcing in the field of entrepreneurship development in the AI economy is justified through econometric modeling using the regression analysis method on the example of companies from the “Global-500” in 2022. Promising directions for the development of “smart” outsourcing in support of the humanization of entrepreneurship in the economy using the method of comparative analysis are determined through the identification of its advantages in comparison with traditional outsourcing for the humanization of entrepreneurship. Using the case study method, successful examples of the use of “smart” outsourcing in various business operations of entrepreneurship are systematized. The key conclusion is that in the AI economy, the humanization of entrepreneurship can be provided with the help of “smart” outsourcing, which is more preferable than traditional outsourcing due to its increased flexibility, rationality, and efficiency. The theoretical significance lies in clarifying the specifics of outsourcing in the AI economy, as well as in justifying the preference for “smart” outsourcing and in providing a scientific methodology for its implementation. The practical significance is connected with the fact that the proposed practical recommendations on the implementation of “smart” outsourcing allow to improve the efficiency of entrepreneurial activity and strengthen the resilience of businesses to economic crises, supporting economic growth through “smart” outsourcing.

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Section: Literature Reviewmentioning

confidence: 99%

“Smart” outsourcing in support of the humanization of entrepreneurship in the artificial intelligence economy

Matytsin

Dzedik

Makeeva

et al. 2023

Humanit Soc Sci Commun

Self Cite

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“…It can be seen that, at home and abroad, the teaching quality of preschool teachers has received wide attention from the society. In terms of the evaluation of teaching quality, scholars have conducted research from multiple aspects and make the evaluation of teaching quality more standardized and professional [16][17][18][19][20][21]. Burle et al [22] mentioned that the United States has established quite a few educational evaluation centers and some universities have set up educational evaluation courses.…”

Section: Introductionmentioning

confidence: 99%

A Teaching Quality Evaluation Model for Preschool Teachers Based on Deep Learning

Wang

Liu

2021

Int. J. Emerg. Technol. Learn.

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Developed countries regard preschool education as an important starting point and foundation for elite training. In recent years, preschool education has also attracted a growing attention in developing countries like China. Considering the significance of the teaching quality of preschool teachers to lifelong academic achievement, this paper designs a teaching quality evaluation model for preschool teachers based on deep learning. Firstly, a progressive system with a hierarchical structure was developed for the relevant evaluation indices. Then, the fuzzy comprehensive evaluation of each index layer and evaluation criterion was determined by the principle of fuzzy relationship synthesis. Finally, an evaluation prediction model was established based on extreme gradient boosting (XGBoost) algorithm and technology services’ ResNet (TS-ResNet), and proved effective and accurate through experiments. The research results provide a reference for the application of the proposed model in other evaluation prediction scenarios.

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Application of Python Software Environment for Analyzing the Systems of Quality Management with the Use of Machine Teaching Methods

Cited by 2 publications

References 0 publications

“Smart” outsourcing in support of the humanization of entrepreneurship in the artificial intelligence economy

“Smart” outsourcing in support of the humanization of entrepreneurship in the artificial intelligence economy

A Teaching Quality Evaluation Model for Preschool Teachers Based on Deep Learning

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