scholarly journals Research on the Evaluation and Optimization Method of the Impact of Chorus Education on University Culture Based on Coevolution Model in the Background of Artificial Intelligence

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Qingna Lin ◽  
Lizheng Zhuo
Keyword(s):  
Artificial Intelligence ◽  
Evaluation System ◽  
Quantitative Methods ◽  
Comprehensive Evaluation ◽  
Colleges And Universities ◽  
Practical Significance ◽  
University Culture ◽  
Research Perspectives ◽  
Artificial Intelligence Technology ◽  
The Impact

The development of artificial intelligence technology is a field where all walks of life need to carry out in-depth research in the future, and the introduction of artificial intelligence technology in the field of university evaluation has become an inevitable trend. Through the collection and collation of the literature at home and abroad, the influence of chorus education on college culture in China has long remained in qualitative and experiential judgment and the significance and value of chorus education to colleges and universities are relatively single. Therefore, it is of great innovative value and practical significance to establish a scientific, systematic, and comprehensive evaluation mechanism for the impact of chorus education on university culture and to scientifically analyze key issues, establish evaluation criteria, and inject new research perspectives into the promotion of chorus education in colleges and universities in China, combining with the mature coevolution theoretical model of management science. It is of great innovative value and significance to combine the DEMATEL research method with the current practice of promoting chorus education in China’s colleges and universities and to systematically and comprehensively construct the evaluation system and research paradigm in line with chorus education by using the qualitative and quantitative methods.

Intelligent Evaluation System of Animation Works Based on ELP

2013 ◽  
Vol 756-759 ◽  
pp. 2416-2421
Author(s):  
Jun Li Zhao
Keyword(s):  
Artificial Intelligence ◽  
Digital Media ◽  
Evaluation System ◽  
Comprehensive Evaluation ◽  
Qualitative Evaluation ◽  
Fuzzy Comprehensive Evaluation ◽  
Teachers And Students ◽  
Artificial Intelligence Technology ◽  
E Learning

In digital media area, exchange and evaluation of the animation works has become a prominent problem. In this paper, we develop an intelligent evaluation system of animation works based on E-learning portfolio, which can record students animation works and learning files in digitized form. It achieves a combination of quantitative evaluation and qualitative evaluation using fuzzy comprehensive evaluation and artificial intelligence technology. It can not only generate the scores, but also generate remarks automatically. This will facilitate teachers and students to exchange and evaluate animation works, and improve the quality of evaluation.

Research on the framework of university ideological and political education management system based on artificial intelligence

2021 ◽  
pp. 1-10
Author(s):  
Xuying Sun ◽  
Yu Zhang
Keyword(s):  
Artificial Intelligence ◽  
Political Theory ◽  
Outlier Detection ◽  
Management System ◽  
Detection Algorithm ◽  
Colleges And Universities ◽  
Ideological And Political Education ◽  
Political Education ◽  
Data Simulation ◽  
Artificial Intelligence Technology

The importance of the management of ideological and political theory courses in colleges and universities is objective to the importance of ideological and political theory courses. At present, the management of ideological and political theory courses in colleges and universities has big problems in both macro and micro aspects. This paper combines artificial intelligence technology to build an intelligent management system for ideological and political education in colleges and universities based on artificial intelligence, and conducts classroom supervision through intelligent recognition of student status. The KNN outlier detection algorithm based on KD-Tree is proposed to extract the state information of class students. Through data simulation, it can be known that the KD-KNN outlier detection algorithm proposed in this paper significantly improves the efficiency of the algorithm while ensuring the accuracy of the KNN algorithm classification. Through experimental research, it can be seen that the construction of this system not only clarifies the direction of management from a macro perspective, but also reveals specific methods of management from a micro perspective, and to a certain extent effectively solves the problems in the management of ideological and political theory courses in colleges and universities.

DEEPFAKE AS A PHENOMENON OF POLITICAL COMMUNICATION

2021 ◽  
Vol 27 (6) ◽  
pp. 101-106
Author(s):  
М. Falaleev ◽  
◽  
N. Sitdikova ◽  
Е. Nechay ◽  
◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Political Communication ◽  
Political Discourse ◽  
Rapid Development ◽  
Theoretical Data ◽  
Practical Significance ◽  
Subject Field ◽  
Learning Programs ◽  
Definition Of ◽  
The Impact

The development of digital technologies, coupled with progress in the development of self-learning programs based on AI (Artificial Intelligence), has obvious advantages in improving the effectiveness of information impact on people around the world. During the 2010s, researchers have documented trends in the use of artificial intelligence for the construction and distribution of media content to indirectly manipulate political discourse at the national and global levels. Special interest in the context of this issue is how the rapid development of AI technologies affects political communication. The object of consideration within the framework of this article is the deepfake technology. Based on this, as a subject, the authors define deepfake as a phenomenon of modern political communication. Accordingly, the purpose of the study is to describe and predict the impact of deepfake technology on political communication at the global and national levels. The paper presents the definition of deepfake, assesses its characteristics depending on the methods and purposes of its distribution, and analyzes the prospects for using this tool to influence political discourse in modern Russia. To study the subject field of the research, methods of systematizing theoretical data, classification, analysis of a set of factors and forecasting have been applied. The practical significance of the work is presented by the authors’ definition and typology of the phenomenon of deepfake and describes its significance as a factor of political communication on the example of a particular country. The results of the work will be useful for researchers studying the problems of digitalization of the media space and modern means of disinformation in politics, both at the local and global levels

scholarly journals Urban living environment assessment index system based on psychological security

2019 ◽  
Author(s):  
Xia Huiyi ◽  
◽  
Nankai Xia ◽  
Liu Liu ◽  
◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Collection ◽  
Urban Environment ◽  
Evaluation System ◽  
Living Environment ◽  
Mobile Internet ◽  
Practical Significance ◽  
Human Beings ◽  
Urban Living

With the development of urbanization and the continuous development, construction and renewal of the city, the living environment of human beings has also undergone tremendous changes, such as residential community environment and service facilities, urban roads and street spaces, and urban public service formats. And the layout of the facilities, etc., and these are the real needs of people in urban life, but the characteristics of these needs or their problems will inevitably have a certain impact on the user's psychological feelings, thus affecting people's use needs. Then, studying the ways in which urban residents perceive changes in the living environment and how they perceive changes in psychology and emotions will have practical significance and can effectively assist urban management and builders to optimize the living environment of residents. This is also the long-term. One of the topics of greatest interest to urban researchers since then. In the theory of demand hierarchy proposed by American psychologist Abraham Maslow, safety is the basic requirement second only to physiological needs. So safety, especially psychological security, has become one of the basic needs of people in the urban environment. People's perception of the psychological security of the urban environment is also one of the most important indicators in urban environmental assessment. In the past, due to the influence of technical means, the study of urban environmental psychological security often relied on the limited investigation of a small number of respondents. Low-density data is difficult to measure the perceptual results of universality. With the leaping development of the mobile Internet, Internet image data has grown geometrically over time. And with the development of artificial intelligence technology in recent years, image recognition and perception analysis based on machine learning has become possible. The maturity of these technical conditions provides a basis for the study of the urban renewal index evaluation system based on psychological security. In addition to the existing urban visual street furniture data obtained through urban big data collection combined with artificial intelligence image analysis, this paper also proposes a large number of urban living environment psychological assessment data collection strategies. These data are derived from crowdsourcing, and the collection method is limited by the development of cost and technology. At present, the psychological security preference of a large number of users on urban street images is collected by forced selection method, and then obtained by statistical data fitting to obtain urban environmental psychology. Security sense training set. In the future, when the conditions are mature, the brainwave feedback data in the virtual reality scene can be used to carry out the machine learning of psychological security, so as to improve the accuracy of the psychological security data.

Artificial intelligence with fuzzy logic system for learning management evaluation in higher educational systems

2020 ◽  
pp. 1-11
Author(s):  
ZhiYuan Lv ◽  
Hengyun Shen
Keyword(s):  
Artificial Intelligence ◽  
Mathematical Model ◽  
Fuzzy Logic ◽  
Evaluation System ◽  
Learning Experience ◽  
Training Model ◽  
Colleges And Universities ◽  
Teaching Evaluation ◽  
Higher Learning ◽  
The Mathematical Model

In this paper, the mathematical model and algorithm based on knowledge forgetting curve are studied. Through the analysis of the current mathematical modeling and application of “knowledge forgetting curve”, the artificial intelligence method of fuzzy mathematics knowledge and differential modeling is adopted. This paper puts forward the mathematical model and algorithm design of the new “knowledge forgetting curve”, which aims to improve the intelligence of the software and bring a new learning experience for the teaching evaluation of the education system in colleges and universities. The fuzzy logic theory is applied to the teaching evaluation system of higher learning pedagogy, according to pedagogy and other related theories, combined with the current teaching evaluation indicators of colleges and universities, the teaching evaluation indicators of higher learning education are set according to certain requirements. The sample wood data is divided into two parts by using the fuzzy logic principle, and the training model is obtained by training the sample data in the evaluation system, and the training model is used to intelligently evaluate and analyze the prediction data.

The effectiveness of physical education teaching in college based on Artificial intelligence methods

2020 ◽  
pp. 1-11
Author(s):  
Zihao Li ◽  
Hejin Wang
Keyword(s):  
Artificial Intelligence ◽  
Physical Education ◽  
Rapid Development ◽  
Participation Rate ◽  
Colleges And Universities ◽  
The Body ◽  
Current Status ◽  
Innovative Teaching ◽  
Artificial Intelligence Technology ◽  
Low Activity

Traditional physical education in colleges and universities is difficult to arouse students’ interest in sports, resulting in low activity participation rate and inability to exercise the body. How to effectively improve the effectiveness of physical education in colleges and universities has become one of the hot topics of most concern from all walks of life. In physical education, innovative teaching concepts and methods, teaching methods and processes, and teaching evaluation methods are all conducive to improving the classroom atmosphere of physical education and successfully improve the effectiveness of physical education. This article focuses on analyzing the current status of physical education in colleges and universities. Based on the rapid development of artificial intelligence technology, how to improve the effectiveness of physical education is studied, and an experimental method is used to compare and analyze physical education in a college. The analysis results show that artificial intelligence-based physical education can obviously improve students’ strength quality, speed quality, endurance quality, and agility quality, which provides a more important reference and reference for improving the effectiveness of college physical education.

Artificial intelligence based on effectiveness of inverted classroom teaching of college sports

2020 ◽  
pp. 1-11
Author(s):  
Jianqin Cheng ◽  
Xiaomeng Wang
Keyword(s):  
Artificial Intelligence ◽  
Physical Education ◽  
Real Time ◽  
Visual Analysis ◽  
Analytical Framework ◽  
Colleges And Universities ◽  
Classroom Teaching ◽  
Teaching Behaviors ◽  
Inverted Classroom ◽  
Artificial Intelligence Technology

This study takes the effectiveness analysis of inverted classroom teaching in colleges and universities as a breakthrough point, and combines artificial intelligence technology with the analysis method of inverted classroom teaching in colleges and universities to enrich the existing methods for analyzing, the behavior of inverted classroom teaching in colleges and universities to realize the effectiveness of inverted classroom teaching in colleges and universities analysis. This research first constructs an analytical framework for the teaching behaviors of college physical education inverted classrooms based on artificial intelligence technology, which consists of observation dimension and the evaluation dimension. In order to further test the scientifically and operability of the analytical framework, taking emotion recognition as an example, practical operations are combined with specific examples to obtain visual analysis results. This study expands the dimension and depth of analysis of the behavior of inverted sport in classroom teaching in sport inversion colleges and universities, and has obvious advantages in saving manpower and real-time visual display. Through the analysis of the effectiveness of physical education inverted classroom teaching in sports inversion colleges and universities through artificial intelligence technology, the use of technology to participate in the analysis of physical education inverted classroom teaching behaviors in sports inverted colleges and universities, shorten the evaluation time, expand the evaluation dimension, improve the evaluation efficiency, achieve real-time feedback, real-time attention to classroom effects. Effectively regulating the inverted classroom teaching behavior of college physical education can promote the cultivation of teachers’ professional abilities, scientifically and accurately improve and correct teaching problems, and improve the quality of education and teaching. Eventually, students will achieve comprehensive self-evaluation of students, and promote personalized and standardized growth of students.

Sign in / Sign up

Export Citation Format

Share Document