bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of Big Data Technology in Innovation of College Students’ Education Management
Authors: Ren Yaqiong 
Published: October 2020

Abstract
Innovation of College Students’ education management has always been an important part of university education management. Compared with the previous education management mode, now it cannot be better applied to the current new era, the management of college students is facing new challenges and opportunities, so we should actively seek innovation and breakthrough in the education management mode. Now is the era of Internet big data, teaching management work also conforms to the development of the times, actively learn big data technology, and introduce it into the management and innovation of college students. In view of the current situation of College Students’ education management in China, this paper studies the application of big data technology in the innovation of College Students’ education management. This paper compares the application of big data technology in different schools and different groups of users, discusses and analyzes the results, and puts forward the application and improvement strategies of big data technology in the innovation of College Students’ education management, which provides technical support for the development of College Students’ education management.
Research on Joint Optimization of Edge Computer Offload Strategy and Wireless Resource Allocation
Authors: Wang HuiNan , Liu JiaYi , Zhang JianMin 
Published: October 2020

Abstract
To solve the problem that users cannot use network resources efficiently, based on mobile edge computer network architecture,in a resource-constrained system, an energy-efficient offload strategy and a wireless resource joint optimization algorithm (EEJS) are proposed to achieve a balance between user diversity and MS diversity.
Big Data in Preschool Dance Multimedia Teaching Dance Posture Correction
Authors: Wang Li Li 
Published: October 2020

Abstract
With the explosive growth of data and the enhancement of data openness, big data is quietly changing our daily work and life. This article mainly studies the application of big data in preschool dance multimedia teaching dance posture correction. Using a small sample control method, the body characteristics of the research subject were measured before the experiment and used as the index before the measurement; after 8 weeks of learning, the measurement was performed again and used as the index after the measurement. Then, the principle of feature plane similarity matching is used to analyze the motion posture. The experiment found that after 8 weeks of multimedia correction training, mild pelvic backwards accounted for 75% and moderate 22.2%. The results show that big data plays a technical support role in the correction of dance posture in preschool dance multimedia teaching.
Design and Research on Digital Business Platform of Enterprise Project Management System Based on Information Technology
Authors: Zhe Wang , Shu LiBao , Shen Chen , Da ZhaoHong 
Published: October 2020

Abstract
Although the traditional digital business platform of enterprise project management system has a complete set of design and research scheme, it cannot meet the new requirements of the new era for enterprise level project management system digital business platform. Therefore, in order to improve the design and research level of enterprise project management system digital business platform, this paper puts forward the method of integrating information technology and enterprise level project management system digital business platform design and research. Based on the analysis of the design and research status of enterprise project management system digital business platform, combined with the current new requirements for enterprise level project management system digital business platform, a set of design and research scheme that is most suitable for enterprise level project management system digital business platform is formulated. Through the analysis and research, it is found that the method proposed in this paper has important practical significance for the design and research of enterprise project management system digital business platform.
Current Situation and Development Trend of Electrical Automation Engineering Control System
Authors: Xie Guokun 
Published: October 2020

Abstract
Nowadays, with the rapid development of science and technology, more and more factories and enterprises are also growing. In order to obtain more profits, these factories and enterprises need to reduce their production costs, which make the improvement and development of automatic control technology on the agenda. The automatic control system can reduce the production cost and system operation cost to a great extent. This kind of automatic control system not only promotes the progress of social economy, but also reduces the possibility of accidents, which greatly guarantees people’s life safety. Therefore, this paper analyzes and discusses the current situation and future development trend of electrical automation engineering control system. Firstly, the composition of electrical automation engineering control system is introduced and explained. Then, this paper analyzes which fields this control system has been applied in our country and the specific benefits it brings. Finally, it forecasts its future development and gives relevant suggestions. The results show that the workers have a positive attitude towards the electrical automation engineering control system, and the electrical automation engineering control system can reduce the cost of the factory and improve the income.
Evaluation Model of Soccer Training Technology Based on Artificial Intelligence
Authors: Yang Yongzhi 
Published: October 2020

Abstract
Modern football competition has the characteristics of fierce confrontation, long duration, intensity of the game and large amount of exercise, and has high technical and tactical requirements. Therefore, the scientific and technical ability evaluation system plays a decisive role in football. One of the key factors for the real development of Chinese football is how to train and select young football talents scientifically. In order to train football talents better, this paper combines with artificial intelligence technology to study the evaluation model of football training technology. According to the characteristics and laws of football, this paper analyzes the index composition of football competitive ability. Combined with the traditional clustering data model, a support vector machine classification algorithm is proposed to construct the evaluation model of football training technology. Finally, this paper takes a professional team and a semi-professional team as an example and adds soccer evaluation model into their daily training. The results show that the evaluation efficiency is 24.12% higher than that of traditional artificial team, which proves the feasibility of this model.
RETRACTED: The Development Space of University Art Design Education in the Era of Big Data
Authors: YanYu Xiao 
Published: October 2020

Abstract
After the arrival of the era of big data, colleges and universities of art design are also facing new challenges and opportunities. How to stand out in the fierce competition has become an important issue facing art design education. The purpose of this article is to explore the development space of art design education in colleges and universities in order to deliver a steady stream of fresh talents for national construction, market operation, and enterprise development. This article analyzes the problems and blind spots in art education by discussing the status quo of art design education in some universities in Province A. It is concluded that 73.08% of college art design education lacks standardization; 65.38% of colleges and universities emphasize on mastering technology and cultivating creativity. Targeted development strategies are provided to provide a wider space for the education of art students in order to develop our art education cause construction and improve the art talent training environment.
Research on the Technology of Intelligent Basketball Shooting Training Vehicle
Authors: Haidong Liu , Nana Li 
Published: October 2020

Abstract
The basketball training car only has the function of storing basketballs and training equipment. During training, the basketball is taken out of the training car and scattered on the ground. The athlete needs to bend down to pick up the ball for shooting training, which is not conducive to the continuity of shooting action training, and affects the intensity of shooting training and the shooting accuracy improvement. It is necessary to manually place the basketball on the swing seat, it can not be automatically served, and the function is low. Therefore, this article conducts technical research on the basketball shooting training vehicle, and sets up a telescopic motor to drive the upper tee to move up and down and other technical studies, in order to intelligently upgrade the existing shooting training vehicle, which is conducive to the continuity of shooting action training and the intensity of shooting training, can improve the fixation of the shooting hand and improve the shooting percentage.
A Brief Analysis of The Defects and Countermeasures of EVM in Project Management
Authors: Zhanli LI 
Published: October 2020

Abstract
Through calculation and induction, demonstration by example, comparative analysis and other methods, this paper draws the following conclusion: the control of project progress and cost by EVM should be evaluated with a single project as the goal, and on the premise of the timely accuracy of phase cost statistics; In the evaluation of comprehensive project progress, it should be carried out in different levels, with the evaluation of key line work as the main and non-key line work as the auxiliary; The influence of safety, quality, environment and other factors on the cost should be fully considered when evaluating the project cost.
Research on Cultural and Creative Product Design System Based on 3DP Technology
Authors: Zhao Chongli 
Published: October 2020

Abstract
With the development of the times, the progress of society, the continuous improvement of human science and technology and cultural level, more and more high-tech science and technology are constantly applied in daily life, 3DP technology as a member of many high-tech is gradually accepted by people. In this era of rapid development, the research and development of cultural and creative product design system cannot do without the help of these high-tech technologies. In order to better meet the requirements of the new era for cultural and creative product design system, this paper proposes a method to integrate 3DP technology with the research of cultural and creative product design system. Based on the analysis of the current situation of the research on the design system of cultural and creative products, the rapid prototyping technology of 3DP technology is fully used to help the designers to carry out innovative research on the design system of cultural and creative products better combined with the current new media, so as to formulate a set of development scheme of the most suitable cultural and creative product design system in the new era. It is found that the method proposed in this paper is of great significance to promote the research and development of cultural and creative product design system.
Computer Network Flow Recognition Method Based on Improved Support Vector Machine
Authors: Xiao Shoubai 
Published: October 2020

Abstract
Computer network traffic recognition based on improved support vector machine is a defect of current mainstream network traffic algorithm, designed a network traffic prediction algorithm based on improved support vector machine. This paper mainly introduces the computer network traffic identification method based on improved support vector machine. This article mainly analyzes the related content of network traffic prediction, including the linear and nonlinear characteristics of network traffic, the theoretical basis of network traffic prediction and the method of obtaining traffic data. This paper studies support vector machine theory and least square support vector machine, and proposes an improved algorithm for least square support vector machine. The purpose of this article is to design a network traffic identification and analysis system. On the one hand, by monitoring the network traffic, we will be able to grasp the operation of the entire network in real time;on the other hand, the system statistically analyzes the results of different stages, We have a more comprehensive understanding of the operational efficiency of network resources, network performance and the rationality of network configuration. The experimental results in this paper show that the recognition efficiency of traffic based on the improved support vector machine method has been significantly improved. Under this method, the security problem of traffic has been increased by 14%, and the efficiency of traffic has been increased by 24%. The improved support vector machine will be the future computer network The development trend of traffic identification direction.
Application of big data technology in smart Tourism
Authors: Chen Nan 
Published: October 2020

Abstract
With the improvement of information technology, big data thinking has penetrated into all aspects of our social life and business fields. With the development of economy, tourism has become the pillar industry of the national economy. In order to speed up the development of tourism industry, many provinces and regions in China also follow the pace of big data era and make full use of big data technology to develop smart tourism.In today’s information age, big data technology has important application value and significance for the development of smart tourism. Based on this, this study aims to study the application of big data technology in smart tourism. This paper mainly uses data mining technology and Bayesian network model analysis technology to analyze the big data of travel ticket data of smart tourism as an example to study the application of big data technology in smart tourism. It is found that the Bayesian network model can be used to predict the future trend of air ticket price changes by using the data of a certain period of time in the past, and the prediction accuracy rate is more than 80%, which is more accurate than the traditional neural network model data analysis technology. In addition, big data technologies such as data mining have been widely used in smart tourism, which greatly improves the intelligent degree of tourism industry, and has important significance for the development of smart tourism.
Design and Research of Private Book Sharing System Based on Sharing Economy Model
Authors: Luo Cheng , Chen Ying 
Published: October 2020

Abstract
Based on the current situation, from the perspective of the sharing economy, it adds a lot of convenience to daily life. When accessing information or resources, the content that people want can be obtained quickly and easily through the Internet. At present, it has a great impact on the traditional private book system. The purpose of this paper is to study the design and research of the private library sharing system under the sharing economy in the current information age. The research method adopted in this paper is to first build a shared cloud platform, and build a private book platform by using RFID; CAN bus technology; network communication protocol and other research methods. Finally, the literature research method is used to understand the domestic plan for the construction of a private book function sharing system and the use of network surveys to analyze the resource utilization rate of domestic private libraries, which provides powerful data for the modern shared economy model of private book sharing systems. stand by. Experimental research results show that by creating a shared platform, more idle resources can be used more effectively to meet people’s more diverse needs. In addition, the establishment of a shared platform helps to establish and improve the supervision and management mechanism.
Grade Prediction Model Based on DeepCycle Neural Network Classification Algorithm
Authors: Mao Yuanfu , Sun Xiaoying 
Published: October 2020

Abstract
There are many factors affecting students’ grades, which make the prediction of students’ grades present high dimensional and nonlinear characteristics. Therefore, the traditional method has a large error in the prediction results, which is difficult to meet the practical needs. With the rapid development of artificial neural network (Ann), the deep cycle neural network algorithm based on Ann provides a new approach for student achievement prediction. In order to further improve the accuracy of student achievement prediction, this paper proposes a performance prediction model based on deep cycle neural network algorithm. First, principal component analysis is used for data dimensionality reduction processing of the established student writing evaluation system, and the first five principal components are extracted. Then, these principal components are taken as the input of the neural network to construct a three-layer neural network prediction model. The experimental results show that, compared with the single RBF neural network and BP neural network, the prediction model under deep cycle neural network is simple in structure, fast in convergence and 21.6% higher in prediction accuracy, which verifies the effectiveness of the model proposed in this paper.
Sentiment Mining Analysis of Fuzzy Evaluation Comment Data Based on the Structure of Similar Deep Learning
Authors: jiang Haifu 
Published: October 2020

Abstract
With the rapid development of the Internet, it is increasingly necessary to mine and analyze the sentiment of comment data. The purpose of this paper is to use the deep learning feature construction method to develop an effective mechanism to solve the learning problem under the imbalanced distribution of sentiment analysis of comment data, build an efficient model that can classify comments, and help the government correctly guide the people’s sentimental inclinations. This paper adopts the method of combining keyword extraction and incremental discretization through this model, extracts keywords from the comment corpus, sets up a fuzzy matrix according to the weight of the keywords, and uses incremental K-in the discretization of the fuzzy matrix. The means algorithm extracts some additional structural features as auxiliary information to increase the prediction accuracy of the network. Through experiments, it is found that the comprehensive evaluation results obtained by this method on the comment data set are only 0.02% different from the comprehensive scores of other papers, indicating that the results obtained by the model are extremely accurate. Moreover, the model is adjusted with hyperparameters, and it is compared with the text sentiment analysis model proposed in some articles in recent years. Experiments show that the review data sentiment analysis model constructed with deep learning features has a good classification effect and a wide range of applicability.
RETRACTED: Effective Ways to Cultivate the Autonomous Learning Ability of Minority College Students under the Network Big Data Environment
Authors: Sun Xiaoying , Li Liejun , Wu Xiufang 
Published: October 2020

Abstract
The era of big data provides convenience for college students to study independently. College teachers can make use of the relevant characteristics of big data to improve teaching methods, enrich teaching content and guide the independent learning of college students with scientific teaching evaluation, and explore the cultivation mode of college students’ independent learning ability. Big data in order to better research network environment of ethnic minorities is effective way to cultivate college students’ autonomous learning ability, this study in a university of ethnic minority college students as the research object, through a combination of big data technology to improve the way of the network teaching, through questionnaire as tools, supplemented by semistructured interview, investigation of ethnic minority college students’ autonomous learning ability, from the autonomous learning ability, independent learning behavior, autonomous learning psychology discusses three dimensions of ethnic minority college students’ autonomous learning situation, and discusses how to develop ethnic minority college students’ autonomous learning ability, according to the results, After combining big data teaching, the attendance rate increased by 21.7%.
The study of compression relaxation time of silicon rubber using optical method
Authors: Hidayat W , Prasetyo E , Marzuki A , Yanuar H P , Setyawan A 
Published: October 2020

Abstract
When rubber is subjected to a load, deformation will occur. Microscopically, the rubber bond structure is transformed from one equilibrium corresponds to the unloaded rubber that corresponds to the loaded rubber. As with any other transformation process, this process will take time. This paper experimentally demonstrates the relaxation time dependence on the mass of load observed at a constant temperature. The experiment was carried out by inserting the fiber sensor was into a silicon rubber bar. As the rubber bar was loaded, the intensity of light coming out of the fiber decreases exponentially with time. It is shown that the relaxation time increases with the increase of mass loaded on the fiber. By knowing this, the results of the fiber sensor can be adjusted according to the time-based review of rubber deformation.
Chemically induced demulsification of water in crude oil emulsion from East Kalimantan oil fields
Authors: Gustianthy A P , Febriantini D , Purnomo B , Muzayanha S U , Noverdi R 
Published: October 2020

Abstract
The application of demulsifiers on dewatering of crude oil emulsions from East Kalimantan oil fields is reported in this work. Two types of experiment were conducted: the bottle test in which emulsion resolution was carried out after demulsification process within the time intervals of 0, 5, 10, 15, 20, 25, 30, 40, 50, 60, 120 and 180 min at temperature of 40 °C followed by the appearance of separated aqueous layer, and identification of variety of fractions or compounds in crude oils that promote and stabilize these emulsions. Demulsification was successfully obtained by adding PT Pertamina (Persero)’s commercial demulsifier series of Pertadem B-02 and Pertadem B-06. Pertadem B-02 is the best candidate for destabilizing water in oil emulsions. The optimal percentage demulsification efficiency (DE) achieved by Pertadem B-02 was 100% with just concentration of 18 ppm for field A and 97% for field B. Moreover, demulsification activities in the water in oil emulsions by Pertadem B-02 were faster compared to Pertadem B-06. Fractions identifications showed emulsifying agents in crude oil of Field A that promote very unstable emulsions compared to crude oil of Field B from East Kalimantan.