Scalable Gamma-Driven Multilayer Network for Brain Workload Detection Through Functional Near-Infrared Spectroscopy

Wu, Edmond Q.; Tang, Zhi-Ri; Yao, Yuxuan; Qiu, Xuyi; Deng, Ping-Yu; Xiong, Pengwen; Song, Aiguo; Zhu, Limin; Zhou, MengChu

doi:10.1109/tcyb.2021.3116964

Cited by 15 publications

(4 citation statements)

References 53 publications

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“…e biggest advantage of the neural network [16,17] is that it can automatically adjust the weights through changes in the environment, thereby achieving the purpose of its own adaptability. e input layer, hidden layer, and output layer make up the bulk of a BP neural network; the hidden layer may consist of one or more layers.…”

Section: Realization Process Of Bp Neural Network Algorithmmentioning

confidence: 99%

[Retracted] Correlation Analysis between Emotion Control and Professional Self‐Efficacy of Singing Artists Based on Multidimensional Environment

Liu

2022

Journal of Environmental and Public Health

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The tertiary industry occupies a large area in China’s economic system, and it plays an important function in the growth of China’s economic development. It is of positive significance to study the relationship between emotional labor and occupational self-efficacy of singing artists in the tertiary industry. This paper mainly studies the correlation between the emotional labor of singing artists and their professional self-efficacy and analyzes the strength of the correlation. This paper selects 150 singing art personnel in the singing art association in city A to conduct a questionnaire survey and conducts data processing on the questionnaire. This paper explores the influencing factors of emotional labor and four dimensions of occupational self-efficacy. This paper firstly analyzes the differences of the influencing factors of emotional labor and then tests the interaction of the different factors selected. It then conducts a significant test on the four dimensions of professional self-efficacy and finally studies the correlation between the two based on the previous analysis results. This paper concludes that there is a highly significant relationship between the emotional labor and professional ego efficacy of singing artists. And the correlation coefficient and determination coefficient are 0.293 and 0.087, respectively. It shows that 8.7% of the total variance in occupational self-efficacy variables can be explained by emotional labor. There was no significant correlation between surface acting and occupational self-efficacy. Deep acting has the greatest correlation with the physical and mental efficacy dimension of occupational self-efficacy, with a correlation coefficient of 0.391. There were significant correlations between natural performance and the four dimensions of occupational self-efficacy. The highest value is interpersonal efficacy, which is 0.337. The research conclusions of this paper have certain reference value for exploring the relationship between emotional labor and professional self-efficacy of singing artists.

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Section: Realization Process Of Bp Neural Network Algorithmmentioning

confidence: 99%

[Retracted] Correlation Analysis between Emotion Control and Professional Self‐Efficacy of Singing Artists Based on Multidimensional Environment

Liu

2022

Journal of Environmental and Public Health

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“…It is characterized by sports competitions and is a social sports activity with the main goal of giving full play to the spirit of sports competition based on sports rules. At present, artificial intelligence [ 3 , 4 ] is widely used in competitive sports and has penetrated into all aspects of competitive sports, such as athlete quality testing, competitive sports training, action analysis and tactical modelling, auxiliary referees, and intelligent referees.…”

Section: The Application Of Artificial Intelligence In Sportsmentioning

confidence: 99%

Application and Prospect Analysis of Artificial Intelligence in the Field of Physical Education

Wu-jun

2022

Computational Intelligence and Neuroscience

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The development of AI technology has a significant impact on every sector of business. Artificial intelligence uses this technology to reduce the amount of work required, duplicate work, and increase the accuracy of work by modelling human behaviour and thought. On the basis of a thorough analysis of artificial intelligence technology, the technology is applied to teaching, specialised training, and specialised testing in response to the current issues in the field of physical education and the business that can be improved through auxiliary tools. The paper discusses how artificial intelligence technology can be used in physical education. After that, it examines how physical education is currently taught in classrooms and discusses how artificial intelligence is affecting this field. Following a thorough demonstration of the aforementioned material, the commonly used artificial intelligence technologies are introduced in turn, along with the methodology used in physical education. The use of computer models in physical education is then explained, and future analysis is conducted on the basis of this information.

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“…The objects of Formulas ( 5 )∼( 8 ) are multilayer deep networks, which are trained on continuous real values. In other words, the simple overlapping of RBM networks constitutes a multilayer deep structure [ 19 ]. Deeper training model's visible layers are represented by the training results of simple RBM network model data.…”

Section: Construction Of a New Type Of International Relationsmentioning

confidence: 99%

[Retracted] Big Data Analysis of Benign Interaction of Great Power Relations and New International Relations Based on Deep Learning

2022

Journal of Environmental and Public Health

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The development of a new type of international relations is the advancement and improvement of diplomatic thinking among contemporary nations. It also serves as a crucial yardstick for assessing the future global pattern and the direction of order changes. Proper interaction between major powers can foster the growth of new international relations and has a significant impact on advancing global cooperation and the promotion of human peace. The goal of this essay is to examine how friendly interactions between major powers have affected the development of new international relations. A deep learning network model is presented for this purpose. The deep learning model was used to identify the emotions of the survey results, analyze each person’s emotional tendencies, and summarize and compare the data. Relevant questionnaire surveys were conducted using the online questionnaire survey method on individuals in various countries. The survey results in this paper demonstrate that 96.5 percent of Chinese, 89.3 percent of Russians, and 81.6 percent of Americans support friendly relations between major nations. Only a very small percentage of the investigators supported hostile relations, with their support being 1.06 percent, 3.11 percent, and 2.94 percent, respectively. Therefore, creating a win-win partnership between major powers is exactly what the people of all nations are calling for. In contrast to the past, it is no longer hostile and violent. People anticipate that more great powers will coexist peacefully.

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Scalable Gamma-Driven Multilayer Network for Brain Workload Detection Through Functional Near-Infrared Spectroscopy

Cited by 15 publications

References 53 publications

[Retracted] Correlation Analysis between Emotion Control and Professional Self‐Efficacy of Singing Artists Based on Multidimensional Environment

[Retracted] Correlation Analysis between Emotion Control and Professional Self‐Efficacy of Singing Artists Based on Multidimensional Environment

Application and Prospect Analysis of Artificial Intelligence in the Field of Physical Education

[Retracted] Big Data Analysis of Benign Interaction of Great Power Relations and New International Relations Based on Deep Learning

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