bluuebunny/crossref_metadata_2025_split huggingface dataset:
Based on the construction of financial management information platform of colleges and universities in 5G environment——Take Guangzhou Nanyang Polytechnic Vocational College as an example
Authors: Li Meiling 
Published: August 2020

Abstract
With the rapid development of wireless technology, mobile communication service has experienced the development from voice service to mobile broadband data service, mobile communication network has gradually evolved from 3G, 4G to 5G, namely the fifth generation of mobile communication network.With the advent of 5G technology, the new generation of information technology has accelerated the reform of higher education system, and the construction of an information platform for financial management in colleges and universities has become an important research topic for the information construction and financial work in colleges and universities.Under the background of “Internet +", the construction target of “financial management informatization platform” from the construction stage of “smart campus” is being promoted to the informatization application service of “smart campus” and “Internet of Things +", and the development of financial management informatization in colleges and universities is changing from business process-oriented to service informatization.Financial resources are transformed from digitization to digitization, and the integration, analysis and utilization of data are emphasized to provide personalized services. The main network scenarios of 5G can be summarized as continuous wide area coverage, high capacity of hot spots, large connection with low power consumption and high reliability with low delay. Now that 5G technology is on the way, in the connected society of the future, everyone and everything will be connected to each other, thus achieving the so-called “Internet of everything”.
In this paper, using the method of literature research, field survey and data analysis of guangzhou nanyang technological vocational college financial management informationization development research and analysis, combining the present situation of the financial management informatization, with the help of a financial management concepts and network information technology, knowledge, financial software system using financial management information platform for the school financial management software for scientific and standardized management, based on a student online payment platform, financial reimbursement platform, campus all-in-one-card platform, improve the service efficiency of funds, the school to further enhance the level of school financial management.
Research on the application of WeChat mobile learning platform in ideological and political course teaching in universities
Authors: Yan li 
Published: August 2020

Abstract
With the rapid popularization of personal mobile devices (such as mobile phones, tablets, etc.) and the mobile Internet, learning can take place anytime and anywhere and is no longer limited by time and space. The effective use of mobile technology for learning is mobile learning.Current, WeChat platform with the rapid development of the public will WeChat tentacles extend to mobile learning areas, the former because of its ease of operation, the diversity of interactivity, content delivery precision, and access to information in the sexual and other unique advantages, in the field of education in colleges and universities in the rapid rise, became popular with the teachers and students in the course of mobile learning platform, not only for college students to provide a convenient, simple, cheap and efficient mobile learning applications, also for the innovative development of colleges and universities education courses provides the high quality network carrier.Therefore, to explore the intrinsic educational value and learning support function of WeChat mobile learning platform and apply it effectively to ideological and political course teaching in colleges and universities has increasingly become an important topic of widespread concern for front-line teachers, experts and scholars.Based on marxist communication theory, ideological and political course teaching process theory and constructivism learning theory, this study aims to improve the effectiveness of ideological and political course teaching in colleges and universities, and conducts theoretical research and practical exploration closely around the issue of “how to use WeChat mobile learning platform to assist ideological and political course teaching”.
Research and application of Improved snake algorithm in Boundary detection of Core CT image
Authors: Sun Wenhua , Zhang Wei 
Published: August 2020

Abstract
With the continuous refinement of oilfield development, computed tomography (CT) scanning technology has gradually become an important means to study the core microstructure, through the analysis of core CT image to obtain the core structure information. Active contour model (snake algorithm model) has been widely used in medical image segmentation. Considering the great similarity between core CT image and medical CT image of petroleum geology department, this paper attempts to improve the traditional snake algorithm model. The experimental results show that the improved algorithm has achieved good results in the boundary extraction of core CT sequence image.
Research on the Quality Evaluation Strategy of Multi-source Heterogeneous Aggregation Data
Authors: Zhan Gaofeng , Jiang Yong , Wang Xiaofeng , Zhao Yuyang , Zhao Tong 
Published: August 2020

Abstract
In the era of big data, the application of multi-source heterogeneous aggregation data is more and more extensive. If the quality of aggregation data is uneven, it will bring a lot of troubles to the subsequent data mining, and then lead to inaccurate decision-making. A comprehensive quality evaluation method for aggregation data is proposed in this paper, based on factor analysis and multivariate variance analysis which is from the perspective of multivariate statistical inference. The case study shows that the method proposed in this paper is feasible and adaptive for the long-term evaluation of the quality of multi-source heterogeneous aggregation data.
Route Mining from Satellite-AIS Data Using Density-based Clustering Algorithm
Authors: Yitao Wang , Lei Yang , Xin Song 
Published: August 2020

Abstract
Automatic Identification System (AIS) provides a large number of vessel navigation data for Marine traffic research. In this paper, we proposed a route mining method based on satellite AIS. The method includes data preprocessing, structure similarity calculation, clustering and route extraction. The validity of the route mining method was verified by satellite AIS data from seas near Australia and Warrior Strait. This method is helpful to understand Marine traffic pattern. It provides reliable basis for route planning and lay a foundation for ship abnormal behavior detection.
Research on Improving the Quality of Online Teaching Based on Big Data under the COVID-19 Coronavirus Epidemic
Authors: Su Bowen , Hu Qiliang 
Published: August 2020

Abstract
In 2020, the global COVID-19 outbreak came out of the blue and caught people and businesses by surprise, including the education sector. In order to ensure the “suspension of classes”, schools at all levels in China implement online teaching. How to ensure the quality of online teaching is an important issue. Based on the big data of online teaching, it is of great practical significance to analyze the factors affecting the quality of online teaching, so as to improve the path of improving the quality of online teaching. With the help of big data analysis, the index system of online teaching quality improvement is constructed and applied. Through questionnaire survey and SPSS software analysis, it can be concluded that the teaching quality of online teaching can be improved from three aspects: the behavior level of school, the learning level of students and the behavior level. Therefore, the following Suggestions are put forward: improve the hardware environment, perfect the teaching organization, strengthen the teaching supervision, strengthen students’ mastery of knowledge and skills, strengthen students’ active inspection and team learning. It is hoped that the implementation of such recommendations will further improve the quality of online teaching in the context of COVID-19.
Conceptual Housing and Housing Prices: An Empirical Study Based on Micro-big Data of Hangzhou Newly-built Housing Market
Authors: Lian Yukun , Li Shuyuan , Wen Haizhen 
Published: August 2020

Abstract
With the fierce competition in the market and the improvement of residents’ consumption concepts, a multitude of new concept products have emerged in the real estate market, including green housing, education housing, subway housing, and park housing. However, the existing research does not fully explain how these housing concept labels affect the housing price. This study takes Hangzhou as an example, collects a total of 36,907 transaction data of new housing districts in 2016, and constructs a hedonic price model to analyze the influence of four housing concept labels, namely green housing, education housing, subway housing, and park housing, on housing prices. The empirical results show that the impact of diverse types of concept labels on housing prices is heterogeneous. In addition to education housing, the impact of green housing, subway housing, and park housing on housing prices is significant and positive, which can bring an 8.2%, 3.0 %, and 4.1% price increase.
Public Opinion Guidance with New Government Media In the Age of Big Data
Authors: Ji Yunqing 
Published: August 2020

Abstract
The Internet has changed the way of people’s life, meanwhile, the emergence of new media is changing people’s habit of reading news and getting information. Recently, in order to take use of the new media platform to guide the network public opinion, The government gradually increased the construction of new government media. This paper aim to study the new characteristics of public opinion in new media age, analyzes the problems of the new government media in the public opinion guiding, and also put forward some optimization strategies.
Demographic Structure and Household Tourism Decisisions Based on Microdata
Authors: Jiang Zhiping , Zhang Jiping 
Published: August 2020

Abstract
Due to the differences of demographic structure, household tourism preference and travel choice behavior are more microcosmic. Based on a large nationwide sample of micro-household survey data, some mathematical models are used to empirically study the influence of demographic structure on the decision-making behavior of household tourism in China. Our research shows that the relationship between the proportion of the elderly in a family and the tourism decision of the family is not always a inverse proportion, which only exists in the non-elderly families with younger heads.However, for the elderly families with older heads, the proportion of the elderly population is a positive factor to promote the increase of household tourism intention and tourism expenditure. It shows that the aging of the population has not only brought challenges to China’s tourism industry, but also brought opportunities for sustainable development.
Research on Export Efficiency Measurement and Influencing Factors of the Pearl River Delta Urban Agglomeration
Authors: Wu Yan , Li Minyi 
Published: August 2020

Abstract
This paper firstly analyses the export situation of the Pearl River Delta urban agglomeration in the past 10 years, and then uses the DEA model and panel data model to analyse export efficiency measurement and influencing factors of Pearl River Delta urban agglomeration. Finally, it proposes countermeasures to promote the improvement of the export efficiency of the Pearl River Delta urban agglomeration.
Research on Massive News Events Evolution Prediction Based on Improved PrefixSpan Algorithm
Authors: Wang Biao , Dai Xiao , Yang Jing , Li Shun 
Published: August 2020

Abstract
The Internet reports massive news event every day. Sequential pattern mining is adopted to study the timing relationship between news event, which can provide reference for the development or prediction of news events. With its advantages in performance and efficiency, PrefixSpan often becomes preferred algorithm in the field of sequence pattern mining. But unfortunately, because of the large amount of news and the long time span between some news events, the event sequences is long and dense, which results many subsequences in the frequent pattern and reduces the algorithm performance. In this paper, we propose an improved PrefixSpan algorithm by integrate subsequences of the supersequences in the frequent pattern and introduce news event weight in the pruning step of the PrefixSpan algorithm. Experiment results show that without affecting expression ability of frequent patterns, the improved PrefixSpan algorithm increases the efficiency by about 20 times as before and eliminates about 10% of the redundant subsequences to get a more concise frequent patterns set.
RETRACTED: Study in the Big Data Talent Training Oriented Reform of Information Management and Information System Major under the Management Category
Authors: Hou Ke , Guo Mingcheng , Li Xinhao 
Published: August 2020

Abstract
With the coming Big Data era, the curriculum system of the Information Management and Information System (IMIS for short) Major under the Management Category cannot meet the needs of modern society for talents. Many universities have taken many measures to deal with this situation, which means creating the Big Data Major among current majors or directly replacing the IMIS Major under the Management Category under the Management Category with the Big Data Major. In this paper, the overview of IMIS Major under the Management Category is introduced firstly, and then its problems in the Big Data era are analyzed. By referencing to relevant research results, the current situation and trend of IMIS Major under the Management Category reform under the Management Category is studied. Finally, our solution is put forwarded.
An Improved ORB Feature Extraction Algorithm
Authors: Geng Chuanping , Yang Junjie , Lin Jinchen , Yu Ting , Shi Kexin 
Published: August 2020

Abstract
In this paper, an improved ORB feature extraction algorithm is proposed to solve the insufficient detection effect of the traditional ORB algorithm on the image edges as well as the low actual extraction of feature points. First, the image pyramid layering was established, and then on basis of the improved oFAST12-20 corner point algorithm, the method with a setting dynamic threshold, according to the idea of adaptive threshold, was proposed to extract feature points, and the candidate set of feature points was obtained. Then, Harris algorithm was used to calculate the response value of each candidate point, and the response value was sorted from high to low. Finally, the top 80% of the feature points with high response value were extracted as the most important feature points. The experimental results show that the improved oFAST algorithm improved the extraction rate of feature points and reduces the algorithm time compared with the traditional ORB corner detection.
RSS Ranging Algorithm Based on Kalman Filtering Combined BP Neural Network
Authors: Zhou Yuanyang , Liu Yang , Wang Pengfei 
Published: August 2020

Abstract
Accurate distance estimation is an important prerequisite for positioning using wireless sensor networks (WSN). However, the path loss model (PLM) cannot accurately express the relationship between distance and received signal strength (RSS), because of the complexity of the indoor environment. Therefore, this paper proposes an improved Kalman filter as the RSS preprocessing method to make up for the defects of PLM. The improved algorithm uses BP neural network to correct the Kalman filter error, improve the filtering performance, and use the compensated RSS for PLM-based ranging. The experiment shows that the proposed method has better ranging accuracy than the method based on Kalman filtering. And the average is 0.29m, which has dropped by 0.61m.
Analysis of the Impacts of Urban Public Transport on the Housing Price in Hangzhou, China
Authors: Wei Feiyang , Zhang Donglin , Wen Haizhen 
Published: August 2020

Abstract
With the rapid increase of urban population, housing demand is gradually increasing, and traffic congestion is becoming more and more serious. People are increasingly concerned about the relationship between housing and public transportation. Hence, studying the impact of public transport on housing prices will be conducive to promoting the coordinated development of urban public transport and urban social economy. Taking Hangzhou, China as a case city, this study selected 477 residential districts and their surrounding comprehensive public transport characteristics to construct the hedonic price model, and further quantitatively analyses the impact of urban public transport on housing prices. The empirical results showed that most of the public transport characteristics produce significant premium capacity to the housing market. The ranking of the premium capacity from high to low is the distance between the community to the subway station, the speed of nearby roads, and the number of public bicycle stations. In addition, a few public transport characteristics, such as the number of bus and water bus stops, have no significant impact on housing prices. This research can serve as a theoretical basis for government departments to carry out urban planning and real estate enterprises to make decisions.
Design and Implementation of Intelligent Library System Based on Big data
Authors: Peng Zhibin , Chen Yuefeng , Luo Xiaoying , Fan Rui , Meng JiaHui 
Published: August 2020

Abstract
In most traditional library management systems, readers have to find their interest books through the name or search approximate content from library, which results in wasting time. With the help of big data technology, we construct the intelligent library system using SSM framework and Hadoop framework. A recommendation approach combined co-filtering with content-based recommendations, is introduced to make better recommend efficiency. The system has the intelligent ability of self-learning. For historical lending books data, it uses the Spark MLlib machine learning algorithm library to build clustering or classification models. On the other hand, the system uses Kafka and SparkStreaming to process real-time data. System simulation shows that it has high recommendation accuracy and good timeliness.
Analysis of the application trend of big data in power industry
Authors: Zhang Qian , Xia Liyu , Feng Wangren 
Published: August 2020

Abstract
With the permeate of new forms of digital economy into various fields of social development, the application of big data has become a driving force for innovation, transformation and upgrading in all walks of life. Internet enterprises and traditional power grid enterprises are actively exploring the innovation of big data application scenarios, which relevant data analysis ideas and methods are worth to learn.
Research on the Influencing Factors of Collaborative Innovation of Science and Technology in the Pearl River Delta Urban Agglomeration
Authors: Wu Yan , Wu Yating 
Published: August 2020

Abstract
This paper has measured the level of collaborative innovation of science and technology in the Pearl River Delta urban agglomeration from 2010 to 2018 by using the DEA-Malmquist index model. The empirical results show that the overall level of technological collaboration and innovation in the Pearl River Delta urban agglomeration is relatively high. The pure technical efficiency value of the Pearl River Delta urban agglomeration has hit its peak. In terms of its scale efficiency, that of Zhuhai and Jiangmen still has room for improvement, while that of other cities has reached the optimal level. Then, through the establishment of a panel data model of the Pearl River Delta urban agglomeration from 2009 to 2018, the influencing factors of technology collaborative innovation in the Pearl River Delta urban agglomeration was analyzed. Finally, this proposal was made.
An Empirical Analysis of Student Satisfaction in Practical Teaching––Research Based on Structural Equation Model
Authors: Huang Wenyan , Jin Wei 
Published: August 2020

Abstract
Since the middle of the last century, so far, practical teaching has been the focus of vocational education in our country[1]. This paper compares other practical teaching models at home and abroad, based on the two courses of “Real Estate Operation and Management” and “Curriculum Design” in the civil engineering major of our school, and discusses the satisfaction of the curriculum theory and practical teaching model. This paper mainly adopts the satisfaction model proposed by American scholars, combined with the data collected by the questionnaire survey, constructs the student satisfaction model of the practical teaching link, and obtains the linear path coefficient of the student’s practical teaching satisfaction and the student’s satisfaction index for the practical teaching link, so as to improve reform measures such as the assessment system, and improve the level of practical teaching, and ensure the effectiveness of practical ability training.
Music Data Mining Based on MusicXML
Authors: Chen Gen-Fang 
Published: August 2020

Abstract
In this paper, we use the music resources of the Internet to analyze and mine the data of MusicXML file. First, the structure of MusicXML file is introduced briefly, then the data source is explained, then the database is established by MySQL and PHP, and finally the data is analyzed by MATLAB. The experimental results show that the music group is centered on the group of small characters in which the center C is located, showing normal distribution, while the music group is centered on the group of small characters in G, showing normal distribution.
Fuzzy Matter-element Analysis Model of IP-influence Based on EFA-Euclid Approach Degree
Authors: Zhang Wenjing , Li Bo , Chai Jianping 
Published: August 2020

Abstract
With the rise of Intellectual Property (IP) films, IP influence has become one of the important criterias to consider whether an IP film has development value[1]. The influence of the IP films is a fuzzy concept, and its evaluation is not only affected by a variety of factors(both qualitative and quantitative indicators), but also has the problem of incompatible of single indicator evaluation. Based on the actual situation of China’s IP film market and the characteristics of literary works IP, this paper constructs an evaluation index system of the influence of IP films. On the basis of fuzzy matter-element analysis theory, the exploratory factor analysis is introduced into the weight calculation, and combined with the Euclid approach degree, the fuzzy matter-element model based on EFA-Euclid Approach Degree is established, which sorts the IP influence according to the size of the relative paste progress, and the evaluation result is more objective and reasonable. This model ranks IP influence according to the relative approach degree, and the evaluation results are more objective and reasonable.