Background Of Big Data Research Articles

The Rationale of Physical Education and Aesthetics in the Context of Big Data and the Value and Significance of its Implementation in Colleges and Universities

Abstract This paper first takes the deep learning theory as the basis of the thesis of sports and aesthetic education, constructs the flipped classroom teaching model of sports and aesthetic education based on the theory, and introduces the Bayesian estimation theory and the structural equation model to apply it to sports and aesthetic education. Secondly, the research object and method are selected for the flipped classroom teaching model of physical education and aesthetic education, and the teaching process of the flipped classroom experiment and the assumptions related to students’ learning satisfaction are given. Finally, the application value of physical education and aesthetics in colleges and universities is analyzed through the convergence of path coefficients in Bayesian structural equation modeling and hypothesis testing. When the number of iterations reaches 100*103 times, the H6-H11 path coefficient convergence value interval is [-22.5, 14.2]. The convergence interval fluctuates a lot and shows a more unstable trend than the H1-H5 path coefficient. Students learning satisfaction will have a direct effect on their aesthetic ability and improve their aesthetic awareness, and the path coefficients are 0.629 and 0.524, respectively. Deep learning theory based on sports and aesthetics in colleges and universities under the background of big data can improve students’ learning satisfaction and then promote the enhancement of students’ aesthetic ability and aesthetic awareness.

External communication of Chinese traditional culture under the background of big data

Traditional culture is a symbol of a country’s existence and history. The external dissemination of traditional culture is the key to expanding the country’s influence and enhancing the country’s international image. The external dissemination of culture also poses a potential impact on the country’s economy and development. In the context of the information age, the dissemination of Chinese traditional culture is attached great importance. The culture of the Forbidden City, from self-construction to borrowing, from online to offline all-media communication channels, unique and novel cultural and creative products and a young brand image provide it with a unique means of communication. The dissemination of the Forbidden City culture is of positive significance to the demonstration of cultural confidence and the innovation and development of culture, and it can be used as a typical case of the dissemination of Chinese traditional culture. Big data technology analyzes the research object through the process of data collection, data screening and data processing, combined with various data analysis tools, and the ultimate goal is to obtain favorable results for the analyst based on the analysis. The use of big data technology in cultural communication research has gradually become the focus of current scholars. This paper takes the Forbidden City culture as the research object, analyzes the current situation of the foreign communication of the traditional culture of the Forbidden City, puts forward the dilemma of the current external communication of Chinese traditional culture based on the current situation, summarizes the problems and reasons of traditional cultural communication, and designs corresponding solutions combined with big data technology. Through the data simulation of Chinese traditional cultural communication using big data solutions, it is found that the demand satisfaction, cultural benefits after cultural communication, and the direction of cultural influence have all improved after analyzing the user’s individual needs combined with big data technology.

Cost control problems and countermeasures of e-commerce enterprises under the background of big data and Internet of Things

The scale of e-commerce in China continues to expand, and it has a relatively good development prospect. However, there are many problems in cost control in the development of e-commerce in our country. E-commerce companies have many problems in terms of promotion costs, warehousing costs, and operating costs. Although predecessors have made great achievements in this field and helped e-commerce companies solve problems related to cost control, there are still many problems in e-commerce companies. Question. This article starts with big data and Internet of Things technology, and focuses on storage costs and transportation costs to solve the problems of cost control in e-commerce companies. The problems existing in the development of e-commerce enterprises are: (1) The cost control system is not mature enough, the business scope is not clear, the cost control lacks innovative awareness, the logistics cost remains high, and the logistics management model is unreasonable. In order to solve these problems, we built a transportation cost optimization model and an operation cost optimization model based on big data and Internet of Things technology. Transportation cost and operation cost are two important components of the cost of e-commerce enterprises in my country. The model has been verified to effectively reduce transportation costs and operating costs, which is of great significance to reducing the cost of e-commerce enterprises in my country, can solve the problems of e-commerce enterprise development, and promote the development of e-commerce in my country. Finally, according to the model constructed by the questionnaire survey and the article, we put forward corresponding suggestions (1) optimize customer relationship, improve the enterprise model (2) promote enterprise innovation, and promote the transformation of marketing costs (3) improve the degree of informatization of e-commerce enterprises.

Teaching Reform of Finance Major Course under the Background of Big Data --Take International Finance as an Example

With the deepening of economic and financial globalization and integration, many economic and financial departments need a large number of high-quality application-oriented professionals who are familiar with financial theory and financial practice. Under the background of big data, the universality and comprehensiveness, theoretical and practical, epochal and forward-looking of financial professional courses are increasingly prominent. These characteristics need rich data, charts to illustrate and demonstrate, must rely on the network and big data platform, in order to achieve good teaching effect. Therefore, in order to achieve the expected teaching objectives, teaching methods must be reformed and various teaching methods and forms should be adopted flexibly in the teaching process of finance major.

Retracted: The Development Path and Data Mining Mode of Rural Tourism under the Background of Big Data

Retracted: The Development Path and Data Mining Mode of Rural Tourism under the Background of Big Data

Retracted: Application of Swarm Intelligence Optimization Algorithm in Logistics Delivery Path Optimization under the Background of Big Data

Retracted: Application of Swarm Intelligence Optimization Algorithm in Logistics Delivery Path Optimization under the Background of Big Data

Retracted: The Cultivation of Cross-Cultural Communicative Competence in English Teaching under the Background of Artificial Intelligence and Big Data

Retracted: The Cultivation of Cross-Cultural Communicative Competence in English Teaching under the Background of Artificial Intelligence and Big Data

Systematic intelligent analysis tools and practices for the management and control of power grid transmission channels under the background of big data

Systematic intelligent analysis tools and practices for the management and control of power grid transmission channels under the background of big data

Exploration and Research on Cultivating Social Work Talents in Universities under the Background of Big Data

Exploration and Research on Cultivating Social Work Talents in Universities under the Background of Big Data

Research on the Informationization Management and Practice Path of Higher Education Teaching under the Background of Big Data

Research on the Informationization Management and Practice Path of Higher Education Teaching under the Background of Big Data

Retracted: Research on the Social Security and Elderly Care System under the Background of Big Data

Retracted: Research on the Social Security and Elderly Care System under the Background of Big Data

Research on the Era Value and Communication Path of Human Destiny Community and Socialist Core Values in the Context of Big Data

Abstract This paper analyzes the socialist core values and explores the contemporary characteristics and values of socialist core values under the background of big data. On this basis, in order to better practice the socialist core values, through the communication path of big data, combined with the belief propagation algorithm and the association effect, it constructs a node influence propagation NIP model based on the improvement of knowledge graph to realize the propagation of socialist core values. At the same time, the algorithm constructed in this paper is subjected to performance verification experiments, and the effect of socialist core value dissemination and the value of the times are explored. The results show that the influence range of the national level and the individual level are roughly the same as 1200 and 1190, respectively, both slightly higher than the individual influence range of 1000, and the propagation time of the state, society and individual is within 150s, 200s and 300s respectively. Resistance to Western ideology rose by 0.13, the deepening of socialist theory grew by 0.09, and the process of constructing a world value system increased by 0.06. Based on this paper, the study of the value of time and the path of dissemination has a positive impact on the development of socialism.

Research on the Teaching Reform of Physical Education Combined with Civic and Political Education in the New Era under the Background of Big Data

Abstract This paper researches the teaching reform of the integration of sports and civic politics in the new era, and the addition of sports elements in civic politics education can achieve the mutual integration of the two. A personalized Civic and Political teaching model is constructed by combining the attention mechanism based on a recurrent neural network. Based on the personalized teaching model, a model of students’ academic ability in Civics and Politics is established. The EERNN model predicts the next Civics and Politics test scores and assists teachers in proactively intervening. The path of sports Civics integration is proposed from three aspects: increasing the implementation of sports Civics education, improving the awareness of Civics education of physical education teachers, and supervising the integration of students’ sports Civics thinking. Set up an experiment that compares the cognition of students in the experimental and control classes on health indicators and Civics elements. Analyze the student’s learning behaviors and the results after using the personalized recommendation Civics teaching model. The results of the experiment show that the students’ Civics elements of the seven dimensions improved after the experiment, respectively, by 3.05, 2.17, 3.79, 2.16, 2.67, 3.24, and 2.77. The Civics scores of the students in the experimental class increased from 113.89 to 123.48. The personalized learning model effectively enhanced the effectiveness of students’ civics learning.

Problem Analysis and Legal Protection of the Exercise of Teachers’ Educational Disciplinary Rights Based on the Background of Big Data

Abstract The right of education and discipline is an important way of school education and teaching management, teachers to fulfill the teaching and educating people, the implementation of the fundamental task of moral education. This paper firstly discusses the dilemma of exercising the right to discipline teachers in education, and also analyzes the legal nature of the right to discipline in education and the impact on the emotional performance of teachers and students in the process of exercising the right. Secondly, cochlear filtering combined with CNN and LSTM network is introduced to extract the speech characteristics of teachers in the process of exercising the right of education and discipline, and a hybrid neural network model is used to realize the recognition and prediction of students’ auditory emotions. Finally, in order to verify the effectiveness of the method of this paper, experimental test analysis was carried out, and a comprehensive rule of law guarantee proposal was given in the process of exercising the right of teachers’ educational discipline. The results show that the maximum value of the intensity of the teacher’s speech signal after processing using the cochlear filter is 78.28dB, and the difference with the original signal is only 0.32%. The accuracy of recognizing students’ auditory emotions reached 90.48% after over 50 iterations. Under the background of big data, the right to discipline teachers in education needs to be analyzed with the help of technology for the data analysis of the appropriateness of exercise, and it is united in a number of aspects, such as strengthening the legislation, standardizing the implementation, strengthening the supervision, and perfecting the relief, as a way to help the comprehensive rule of law operation of the right to discipline teachers in education.

Strategies for Monitoring and Managing Online Public Opinion in Universities Under the Background of Big Data

<p>In response to the issue of some keywords not being logged in or having inaccurate semantics in current public opinion monitoring, this article uses an improved word segmentation method to extract semantic features. In response to the current issue of unable to control the emotional direction of public opinion comments in public opinion analysis, an emotion analysis model Bi_GRU is proposed for sentiment analysis. Finally, using students’ commonly used Weibo as a verification scenario, sensitive information such as “food safety” and “campus bullying” is screened to control the emotional direction of college students. The final proof is that the method proposed in this article can effectively supervise public opinion in a centralized environment and provide effective means for student management. </p> <p> </p>

大数据背景下西部地区高校科技创新效率提升研究

With the advent of the big data era, data has become an important resource to promote social progress and development. The western region has rich scientific and technological resources and educational resources, but compared with the eastern region, there is still a certain gap in its scientific and technological innovation ability and efficiency. By establishing the evaluation index system of the efficiency of science and technology innovation in universities under the background of big data, this paper analyzes the problems of improving the efficiency of science and technology innovation in western China, and puts forward the strategy of improving the efficiency of science and technology innovation in western China based on the innovation ecological mechanism. The research shows that the evaluation of scientific and technological innovation efficiency in universities in western China focuses on input and output indicators, and the establishment of an innovation ecological mechanism with internal improvement, external support, collaborative quality improvement and cooperative interconnection will promote the improvement of the efficiency of scientific and technological innovation. The research results provide theoretical basis and practical guidance for the improvement of scientific and technological innovation efficiency in universities in western China.

Retracted: Analysis of the Needs of English-Chinese Translation Courses and Research on Teaching Strategies under the Background of Wireless Communication and Big Data

Retracted: Analysis of the Needs of English-Chinese Translation Courses and Research on Teaching Strategies under the Background of Wireless Communication and Big Data

Research on the Application of Chinese Cultural Elements in Product Packaging Design under the Background of Big Data

Abstract The K-means color extraction method based on clustering is used to extract Chinese cultural color elements in this paper, and they are intelligently laid out to design product packaging colors. In the processing of graphic elements, a SIFT-based algorithm is used to match the feature points, and the Chinese cultural graphic elements are aligned to design the graphics of product packaging. To investigate the extraction and application effects of color elements and graphic elements, a validation test was conducted on this basis. The results show that the overall effect value of traditional packaging color design is between [0.6, 0.7], the overall effect value of intelligent packaging design based on Chinese cultural elements is between [0.88,0.96], and the overall effect of the application of graphic elements of Chinese culture to product packaging design is high, with a difference of about 0.1 from the expected effect. Based on this study is able to apply the elements of Chinese culture to product packaging design.

Big data background of county-level media “mobility” pressure cracking strategy

Abstract The construction of county-level integrated media is facing a communication dilemma, and it must alter the way and method of communication by using big data. In this paper, under the background of big data, the basic metric features of the users of integrated media communication are calculated by name similarity, one-hot coding features, following rate, etc., which are combined with the pixel statistical characteristics and avatar personality features to build a user portrait of integrated media communication. Taking the user’s profile as the anchor point of communication, the CD-VAE model is used to predict and analyze the early communication of integrated media content. Through case studies, the current characteristics of county-level integrated media and the trend of primary and secondary dissemination are examined. The first and second newspapers were distributed 278 times and 251 times, respectively, with a conversion rate of 12.61%. The primary and secondary dissemination of Jitterbug reached 303 and 284 times, respectively, as media in the era of mobile Internet. The use of big data technology can effectively analyze the development pain points of county-level integrated media.

Research on the Construction and Application of Agricultural Informatization under the Background of Big Data

Research on the Construction and Application of Agricultural Informatization under the Background of Big Data