scholarly journals An Empirical Study on the Countermeasures of Implementing 5G Multimedia Network Technology in College Education

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Ke Li ◽  
Sang-Bing Tsai
Keyword(s):  
Physical Education ◽  
Heterogeneous Network ◽  
Evaluation System ◽  
Evaluation Process ◽  
Representation Learning ◽  
Attention Mechanism ◽  
Teaching Model ◽  
Education Evaluation ◽  
Network Representation ◽  
Multimedia Network

Aiming at the problem of 5G multimedia heterogeneous multimodal network representation learning, this paper proposes a collaborative multimodal heterogeneous network representation learning method based on attention mechanism. This method learns different representations for nodes based on heterogeneous network structure information and multimodal content and designs an attention mechanism to learn weights for different representations to fuse them to obtain robust node representations. Combining the general process of exploring the college physical education model and the characteristics of the multimedia network classroom environment, this article constructs the process of exploring the college physical education teaching model of the multimedia network classroom. Through the research and practice of the inquiry college physical education teaching model in the multimedia network classroom, it is verified that the implementation of the inquiry college physical education teaching in the multimedia network classroom can effectively influence and increase the students’ interest in learning and stimulate the students’ inner learning motivation. Through the guidance and training of teachers, a variety of disciplines can be used to carry out college physical education in multimedia network classrooms, so that the integration between courses can be truly realized, with the aim that all courses can share the excellent results brought by the development of modern education technology. More educators understand, accept, and participate in the practice of college physical education based on multimedia network classrooms and better serve the education of college physical education. The construction of the college physical education evaluation system should be combined with the characteristics of the 5G multimedia network era. The evaluation process includes data collection, data analysis, result output, and result feedback. Each link is an indispensable part of the college physical education evaluation process. Based on the relevant knowledge of the 5G multimedia network, the evaluation indicators determined in this study can basically reflect the various elements of the physical education process in colleges and universities. The distribution of index weight coefficients is more scientific and reasonable. Compared with the current system, the college physical education evaluation system constructed by exploration has a certain degree of objectivity and scientificity. Therefore, it is feasible to apply the 5G multimedia network to the evaluation of college physical education.

scholarly journals The Status Quo and Improvement Methods of College Physical Education Evaluation

2020 ◽  
Vol 9 (7) ◽  
pp. 125
Author(s):  
Wenhua Li
Keyword(s):  
Physical Education ◽  
Evaluation System ◽  
Status Quo ◽  
Teaching Evaluation ◽  
Education Evaluation ◽  
Teaching Tasks ◽  
The Status ◽  
Improvement Measures ◽  
Education Goals ◽  
Education Process

In the process of college physical education, teaching evaluation is one of the very important teaching tasks. Through a scientific and complete teaching evaluation system, the physical education process can be optimized to a certain extent, and the effective realization of physical education goals can be promoted to improve the college The quality and efficiency of physical education. This article first analyzes the status quo of college physical education evaluation, and then proposes some optimization and improvement measures for the problems found, hoping to improve the college physical education evaluation system and enhance the comprehensive ability of students.

scholarly journals Um metamodelo para elaboração, aplicação e análise de autoavaliações institucionais em conformidade com o SINAES

2019 ◽  
Vol 1 (44) ◽  
pp. 122
Author(s):  
Giuseppe Anthony Nascimento de Lima ◽  
Thalles Henrique Do Nascimento Araújo ◽  
Luciano Ferreira de Azevedo ◽  
Francisco Fernandes de Araújo Neto
Keyword(s):  
Higher Education ◽  
Data Analysis ◽  
Diagnostic Criteria ◽  
Evaluation System ◽  
Evaluation Process ◽  
Education Evaluation ◽  
Self Evaluation ◽  
Software Interface ◽  
Quantitative Metrics ◽  
Evaluative Processes

<p>The legislation that establishes the National Higher Education Evaluation System (SINAES) states that the institutional self-evaluation process in Brazilian Higher Education Institutions (BHEI) must be made periodically and compulsorily. However, the legislation, regulamentation and technical notes do not have a toolset (evaluative instrumentation, quality and quantitative metrics, diagnostic criteria, etc.) for conception, application and data analysis in self-evaluative processes. Among the various techniques and instruments used by many BHEI, this research tried to collect the most productive and efficient ones which were compatible with SINAES so as to obtain a metamodel able to guide the assembling and management of computerized internal institutional evaluations, in which software interface prototyping techniques were employed for its validation.</p>

scholarly journals Facing Big Data Information Fusion and Data Mining Technology to Construct College Physical Education Teaching Evaluation System

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Yong-tong Ma
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Physical Education ◽  
Information Fusion ◽  
Teaching Methods ◽  
Evaluation System ◽  
Evaluation Process ◽  
Teaching Evaluation ◽  
Evaluation Index ◽  
Mining Technology

The purpose is to enrich the evaluation system of physical education (PE) teaching in colleges and universities and to improve PE teaching methods and improve teaching quality. Based on big data information fusion and data mining technology, firstly, the related theories of teaching evaluation are analyzed and expounded, as well as the characteristics and principles of the construction of college PE teaching evaluation system. Secondly, from the perspective of evaluation index system of sports teachers’ teaching and students’ sports teaching, the content and evaluation index of college sports teaching evaluation are analyzed under the background of big data information fusion and data mining by questionnaire survey. Combined with model test, the results show that traditional college sports teacher pays more attention to the design and teaching methods of PE and ignore the learning process of students. The evaluation process of PE ignores the individual differences of students, the feedback method lacks openness, and the evaluation process is isolated. Based on the big data technology and teaching evaluation theory, the evaluation index is designed for PE teaching in colleges and universities. The average value of the first layer indexes is above 4, and the coefficient of variation is less than 0.2, which can basically reflect the content of PE teaching evaluation and provide some reference for the research of PE teaching evaluation.

A Survey on Heterogeneous Network Representation Learning

2021 ◽  
pp. 107936
Author(s):  
Yu Xie ◽  
Bin Yu ◽  
Shengze Lv ◽  
Chen Zhang ◽  
Guodong Wang ◽  
...  
Keyword(s):  
Heterogeneous Network ◽  
Representation Learning ◽  
Network Representation

scholarly journals A Semantic Aware Meta-Path Model for Heterogeneous Network Representation Learning

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 220274-220284
Author(s):  
Yiping Yang ◽  
Zhongwang Fu ◽  
Adnan Iftekhar ◽  
Xiaohui Cui
Keyword(s):  
Heterogeneous Network ◽  
Representation Learning ◽  
Path Model ◽  
Network Representation ◽  
Meta Path

A Drug Target Interaction Prediction Based on LINE-RF Learning

2020 ◽  
Vol 15 (7) ◽  
pp. 750-757
Author(s):  
Jihong Wang ◽  
Yue Shi ◽  
Xiaodan Wang ◽  
Huiyou Chang
Keyword(s):  
Network Topology ◽  
Drug Target ◽  
Large Scale ◽  
Representation Learning ◽  
New Drugs ◽  
Combination Method ◽  
Learning Methods ◽  
Network Representation ◽  
On Line ◽  
Clinical Experiments

Background: At present, using computer methods to predict drug-target interactions (DTIs) is a very important step in the discovery of new drugs and drug relocation processes. The potential DTIs identified by machine learning methods can provide guidance in biochemical or clinical experiments. Objective: The goal of this article is to combine the latest network representation learning methods for drug-target prediction research, improve model prediction capabilities, and promote new drug development. Methods: We use large-scale information network embedding (LINE) method to extract network topology features of drugs, targets, diseases, etc., integrate features obtained from heterogeneous networks, construct binary classification samples, and use random forest (RF) method to predict DTIs. Results: The experiments in this paper compare the common classifiers of RF, LR, and SVM, as well as the typical network representation learning methods of LINE, Node2Vec, and DeepWalk. It can be seen that the combined method LINE-RF achieves the best results, reaching an AUC of 0.9349 and an AUPR of 0.9016. Conclusion: The learning method based on LINE network can effectively learn drugs, targets, diseases and other hidden features from the network topology. The combination of features learned through multiple networks can enhance the expression ability. RF is an effective method of supervised learning. Therefore, the Line-RF combination method is a widely applicable method.

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