bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design of remote monitoring system for tablet coating equipment
Authors: Zhang Heling , Yu Ying , Zhang Kang 
Published: September 2020

Abstract
Through the design of single-chip microcomputer control system, this paper makes full use of automatic control technology, computer technology, communication technology, network technology, instrument technology and software technology. Fuzzy control is used to realize production process automation. In the process of drug coating, the particle shape, particle moisture and spray gun mouth condition in the pot of the coating machine were detected on-line, and the control methods of air volume, steam volume and drug liquid volume needed in the production process were studied.
PID control realization of drying system of the finishing line based on MCGS and PLC
Authors: Zhang Junyan 
Published: September 2020

Abstract
In order to achieve the temperature control accuracy of the finishing line drying system, a PID control system based on MCGS and PLC is proposed. Using MCGS configuration software to edit the touch screen picture, Siemens PLC hardware configuration and programming, PID control algorithm to realize the conversion of analog and digital quantity, as well as the communication design between the upper computer (PC) and PLC and touch screen. Through the practical verification of assembly and debuggin, the control of the given value ± 5 °C of the drying system temperature of the finish line is realized.
Establishment of taxi priority scheme model based on priority queuing system
Authors: Su Youkang 
Published: September 2020

Abstract
With the continuous development of China’s economy, the construction of civil aviation engineering has become a major topic in China. Once again, there is a great lack of research on how to give passengers priority to return to the airport. Based on the analysis data of three representative airport passengers taking taxis, this paper establishes the priority scheme model based on the priority queuing system. Finally, by establishing the “priority function” model and quantifing the priority index, a feasible “priority” arrangement scheme is obtained. It is found that the professionalism, taxi drivers who have carried long-distance passengers are more likely to gain more profits by staying in the urban area, and the taxi drivers who have carried passengers for a short distance back to the airport to continue carrying passengers may reduce the time cost consumption Through the guidance and feasibility evaluation of how to give priority to taxi drivers based on the mathematical model, it can help the airport management department to formulate the optimization scheme scientifically and effectively, improve the working enthusiasm of taxi drivers and the travel efficiency of passengers, which has certain guiding significance for the scientific and efficient management of the airport.
Application analysis of machine learning in fault diagnosis: A bibliometric analysis
Authors: Tu Wenyan , Fang Ji , He Yihua , Huang Jin 
Published: September 2020

Abstract
This article to analyze the application of machine learning in fault diagnosis by using bibliometrics, co-citation network analysis and cluster analysis methods. The analysis found that in the application research of machine learning in fault diagnosis, China has the largest number of published papers and cited papers, among which IEEE access is the most published journal, MECHANICAL SYSTEMS AND SIGNAL PROCESSING is the most cited journal,followed by the United States and India. Using document co-citation relationship analysis, a set of key documents in this field was identified., Currently, the important algorithms fault diagnosis include support vector data description method, transfer learning algorithm, convolutional neural network algorithm, natural inspired optimization algorithm, bayesian network, wavelet packet decomposition algorithm, fuzzy logic algorithm and so on. All of them are clustered according to keywords, and their application fields include acoustic emission and fault diagnosis of doubly-fed induction generators.
A VFDT algorithm optimization and application thereof in data stream classification
Authors: Jia Shuangying 
Published: September 2020

Abstract
Data stream mining is a new technology for dynamically extracting feature patterns from data streams. Its core technology is data stream mining algorithms. Data stream mining algorithms are divided into clustering and classification algorithms. In data stream classification algorithms, VFDT (The Concept-adapting Very Fast Decision Tree algorithm is an effective classification decision tree algorithm. The algorithm dynamically constructs a decision tree based on the improvement of the Hoefdding tree. With the inflow of data, new branches are continuously added and outdated Branch. However, the algorithm has the problem of concept drift, and some nodes may no longer meet the Hoefdding bound, which affects the classification mining effect. This paper proposes an optimization algorithm (VFDT), which reduces the impact of concept drift and network noise by adding sliding window technology and fuzzy technology to the VFDT classification mining algorithm. Experimental results show that the algorithm can effectively improve the accuracy of stream data classification mining. Reduce classification errors.
Performance degradation analysis of reliability growth of airborne power supply based on logistic regression
Authors: Zhang Jie , Li Ningzhou , Wei Xiaojuan 
Published: September 2020

Abstract
With the improvement of reliability design of nonlinear airborne power supply system, it is more difficult to analyze the performance degradation of components under lean failure data in reliability growth test. In this paper, a state space model of performance degradation was established for nonlinear airborne power system, and the method of performance degradation modeling and analysis was studied by using nonlinear logistic regression process. Taking electrical, mechanical and thermal stress as characteristic failure loads, a nonlinear logistic regression analysis model was established to describe the performance degradation under comprehensive stress. The state of the degradation space is divided by the Markov distance, and the performance degradation trajectory is transformed into the degradation state space by using the maximum likelihood model and correlation degree model of observed variables, the degradation space trajectory of the performance of the characteristic parameters under multi-input variables is obtained. The correctness and validity of the nonlinear logistic regression model and the degradation process analysis method are verified by the test on the brushless motor reliability test platform.
Construction and empirical study of the evaluation index system for high-quality development of marine economy in Guangdong Province based on five new development concepts
Authors: Xiao Jianhua , Hu Duanmei 
Published: September 2020

Abstract
The ocean is a strategic place for high-quality development. In-depth evaluation of the quality of Marine economic development is of great guiding significance for implementing the five new development concepts and promoting the sustainable and healthy development of Marine economy. On the basis of introducing the connotation of high-quality development of Marine economy and the five new development concepts, it tried to construct an evaluation index system for the high-quality development of the Marine economy that includes 12 evaluation dimensions and 12 indicators. The results show that: from the overall level of high-quality development of Marine economy, the high-quality development of Marine economy in Guangdong province shows a steady upward trend. The index weight of green development is the largest, which has the greatest impact on the high-quality development of Guangdong’s Marine economy. Based on the implementation of the five development concepts, the paper puts forward the countermeasures and suggestions for the high-quality development of Marine economy in Guangdong province.
Based on point-to-point network extended credit authentication model
Authors: Ma Jianyao , Wen Zhanjie 
Published: September 2020

Abstract
Research shows that P2P technology exist many problems about reliability in the Internet credit industry. It has become particularly important to ensure the reliability of users and improve the success rate of transactions. In this paper, the traditional trust identification model is improved, and the P2P business transaction is integrated into the credit identification model as a dynamic indicator. -On this basis, a block chain is constructed with credit recognition model as intelligent contract. Through the block chain network based on the credit identification model, the credit value of each user will be dynamically evaluated. The block chain network will ensure the credibility of the dynamic indicators of transactions, so as to ensure the reliability of the customer credit value evaluation. Therefore, a quantitative standard that both parties can trust can be established. Without the guarantee of the third party, both sides of P2P transaction can define the trustworthiness of the transaction parties. That guarantees the reliability of the transaction.
A cognitive analysis of an English reading test through the G-DINA model
Authors: Zhao Haizhen , Wang Weize , Huang Yuyuan 
Published: September 2020

Abstract
The development of language testing calls for more in-depth diagnostic information of language skills to provide targeted feedback for test developers and test takers as well. Cognitive diagnostic assessment is capable of evaluating language skills (cognitive attributes) involved in a language test and assessing the cognitive features of test takers. Therefore, the introduction of cognitive diagnostic assessment to language testing is of great significance. The study is aimed to make a cognitive analysis of an English reading test for first-year college students through a cognitive diagnostic model named G-DINA. Through the feedback information of cognitive analysis, the study is expected to provide scientific and targeted feedback for students and teachers, helping to improve language testing, teaching and learning.
Under the background of data science, construct the higher education quality evaluation system of civilian-run regular universities in Hubei Province based on the Analytic Hierarchy Process (AHP)
Authors: Zuo Zongwen , Wang Xiao , Wang Xian 
Published: September 2020

Abstract
This paper takes the CIPP evaluation mode as the connotation to promote the modernization of university governance ability under the background of national governance modernization, with Hubei Province as an example for the investigation. This paper constructs the indicator system framework from three dimensions of input quality, process quality and output quality of universities. Through the calculation of indicator weights and scientific assignment by analytic hierarchy process (AHP), a set of applicable and operable complete evaluation indicator system is formed, which can be used to evaluate the higher education quality and help the governance modernization of civilian-run universities.
Forecast of China’s average annual economic growth rate based on BP neural network
Authors: Hu Xuanyu 
Published: September 2020

Abstract
With the continuous development of China’s economy, the influence of financial factors on China’s economy continues to deepen. In recent years, economic development has been more stable, and the average annual growth rate has slowed down. However, the impact of financial factors of China is mostly qualitative analysis, and only few reasonable mathematical models are used in this field. This paper uses BP neural network to establish a nonlinear model of China’s annual economic growth rate and financial factors to analyze the current average annual economic growth rate, which provides effective guidance for China’s future development strategy.
Analysis of lung cancer morbidity and mortality based on particle swarm optimization
Authors: Li Naiwei , Cheng Ziyi , Woo Youngmin , Ha Jongmyung , Kim Andre 
Published: September 2020

Abstract
Based on the particle swarm algorithm to establish a mathematical model, this article counts the air quality index, tobacco sales, the number of cancer hospitals and the number of health personnel from 2008 to 2019, and quickly calculates the morbidity and mortality of lung cancer over the years, and uses statistics The relative error between the value and the calculated value is the evaluation standard. The result proves that the relative error between the calculated value and the statistical value of the morbidity and mortality of lung cancer is less than 10%, indicating that the calculation result of the particle swarm algorithm has good confidence.
The design and implementation of a campus web information system based on micro-service architecture
Authors: Gong Yifei , Chen Kengbin , Gu Feng , Wang Fei 
Published: September 2020

Abstract
In the development of Web information system, the traditional monolithic application architecture is simple and effective for small-scale projects. Because all business logics are combined together in those projects, secondary development and maintenance become very difficult. In recent years, there are methods to solve this problem, which are popular Web distributed architecture solution. The first step of the solution is to separate front-end and back-end of Web system and the second step is to decompose system’s services into micro-services. Micro-service architecture splits application into smaller scale services and each service completes only performs special function. Through service registration centre, micro-service architecture provides unified mechanism of service discovery and registration, it provides unified interfaces for calls from front-end through gateway technology; it protects stability and fault tolerance via back-off mechanism and circuit-breaker mechanism. We have developed a campus Web information system, which adopts two techniques, the separation of front-end and back-end and micro-service architecture By using Spring Cloud framework as back-end developing architecture, the solution of splitting application to micro-services is obtained, and then problems in monolithic application architecture are solved. The high reusability of back-end services is realized and the advantages of micro-service architecture are tested in our system.
Research overview to the quality evaluation of strong-motion observation data
Authors: Liu Yanqiong , Liu Jie 
Published: September 2020

Abstract
The quality of strong-motion observation data can directly influence the reliability of earthquake disaster prevention, seismic intensity rapid reporting, earthquake early warning and other results, so it’s of great significance to analyse and evaluate the quality of observation data. In this paper, a detailed survey is made considering the status of domestic and overseas studies on the quality of strong-motion observation data, followed by elaborations about the method and deficiencies in the quality evaluation of strong-motion data; Meanwhile, the main factors influencing the quality of strong-motion observation data are also illustrated, and indexes of quality evaluation are summarized by combining with characteristics and application objectives of strong earthquake observation data; Furthermore, this paper also provides discussions about the development trend of data quality evaluation based on the actual strong-motion observation conditions in China, and puts forward some suggestions.
Research on the change of vegetation loss and gain in Shenyang based on NDVI index
Authors: Xie Zhiwei , Ping Jiwei , Sun Lishuang , Dai Yuchen 
Published: September 2020

Abstract
Monitoring long time series of vegetation cover changes is essential to investigate the vegetation gain/loss and ecological conservation of an area. This paper first calculates and synthesizes the maximum NDVI image based on Landsat data of Google Earth Engine platform. Secondly, the vegetation cover is obtained using the dimidiate pixel model. Thirdly, the temporal and spatial trends of vegetation cover are analyzed using linear regression analysis method. Finally, with the support of random pre algorithm, the land cover types are obtained, and the gain / loss change types of vegetation are analyzed. The results show that the overall vegetation cover in Shenyang is mainly high cover. Vegetation cover change was dominated by significant gain, with minimal significant loss and an overall upward trend. Large areas of land cover in the study area were converted to vegetation, while vegetation in some areas of the district was converted to construction land.
Study on the evaluation of agricultural product logistics efficiency in Jilin province
Authors: Yu Hongshen , Zhao Lihong , Wu Maoyang 
Published: September 2020

Abstract
With a great variety of crop categories, Jilin Province is the main grain producing area in China, but agricultural product logistics is developing slowly. Based on the input-output data of agricultural product logistics in Jilin Province from 2009 to 2018, this paper conduct an empirical study on the efficiency of agricultural product logistics in Jilin Province with Deap2.1 software by means of CCR and BCC models in data envelopment analysis. The research results show that there are still some deficiencies in the investment of fixed assets and professionals etc. in agricultural product logistics in Jilin Province, and the scale effect has not yet been realized, and the overall capacity of agricultural product logistics is weak; This paper puts forward the reasonable allocation of input resources from the three levels of government, industry and logistics subjects, to improve the management level of agricultural product logistics and realize the cost reduction and efficiency increase.
Research on YOLOv3 algorithm based on darknet framework
Authors: Guo Rong , Li Shixin , Wang Kun 
Published: September 2020

Abstract
Traffic jams and accidents occur frequently in modern cities. In the context of smart cities, intelligent transportation can be effectively controlled through target detection technology. In view of the problems of slow detection speed and low accuracy of traditional vehicle detection algorithms, a YOLOv3 algorithm based on K-means ++ is proposed. The accuracy of bounding box detection is improved by the K-means ++ algorithm. Compared with the traditional YOLOv3 detection algorithm, the improved algorithm improves the detection speed and accuracy. Experiments show that the improved algorithm has a higher recognition rate for small targets in the actual test, while reducing the false detection rate and improving the accuracy of the algorithm.
Research and design of recommendation in book circle system
Authors: Xu Hui , Ren Shanshan , Yan Jingjing , Li Zheng 
Published: September 2020

Abstract
Reading is the ladder of human progress. It is the real needs of readers to quickly find good books and needed books in this fast-paced times. It will be more enjoyable if we can find the book friends who are interlinked with each other through reading. Digital reading records the whole process of reading, which contains readers’ reading preference. In this paper, we discussed the techniques based on the data related to reading: (1) book friends are personally recommended using books as the media; (2) good books are personally recommended taking readers as media; (3) reader recommendation model and book recommendation model are built based on the relationship between “book-reader” in reading events. A reading system with such a recommendation function can make it easy for readers to find the books they want and find book friends who have sympathetic thoughts.
Research on infrared passive ranging algorithm based on unscented Kalman filter and modified spherical coordinates
Authors: Chi Y H , Hu L H , Gao X , Li S F 
Published: September 2020

Abstract
Target range detection is one of the key technologies for intelligent unmanned vehicle to work reliably and efficiently. Infrared passive ranging can estimate the relative distance information of the target in real time by measuring the angle information with noise. It has many advantages such as low cost, good real-time performance and so on, which has a good application prospect in the range detection. In this paper, the mathematical model of infrared passive ranging of intelligent unmanned vehicle based on modified spherical coordinates (MSC) is established, and the algorithm flow based on unscented Kalman filter (UKF) is given. Finally, the simulation experiment and analysis are carried out. The results show that: in the problem of target range detection of intelligent unmanned vehicle, the method adopted has high ranging accuracy and good stability.
Study of the energy band structure of xBa (Sc1/2Nb1/2)O3-(1-x)(K1/2Na1/2)NbO3 perovskite solid solution
Authors: Ye Hongjun , Xing Zhuo 
Published: September 2020

Abstract
As an important branch of the research on smart materials, the piezoelectric and ferroelectric materials play an important role in the devices with functions of sensing and energy conversion of electricity, magnetism, sound, light, force, and heat, etc., and provide a strong hardware support for the development of artificial intelligence and data science. This paper studied the properties of the potassium sodium niobate (K1/2Na1/2) NbO3-based doped solid solution, calculated the xBa(Sc1/2Nb1/2)O3-(1-x)( K1/2Na1/2)NbO3 solid solution by using the First-Principles software based on quantum mechanics, and by changing the value of x, studied the energy band structure of several doping amounts. In the end, it found that Nb4d and Sc3d electrons contributed to the valence band maximum, and had a hybrid phenomenon with O2p between the energy band -7eV to and -2eV. Also, due to the doping of the Atom B, the energy band gap changed regularly.
Spatial pattern of artificial intelligence and its influence on labor market in China
Authors: Tian Lingyue , Sui Dangchen 
Published: September 2020

Abstract
With the rapid development of artificial intelligence, the labor market is constantly impacted. In order to explore the spatial relationship of AI development in different regions and the impact of technological progress on labor market, spatial autocorrelation test and individual time fixed effect model were used. The results show that there is a significant positive spatial dependence on the development level of artificial intelligence in China’s provinces. At present, the development of artificial intelligence leads to employment polarization in the labor market of China. Therefore, promoting the balanced development of regional artificial intelligence and encouraging the horizontal transfer of labor force will alleviate the negative impact of artificial intelligence.
Study on credit risk of real estate industry based on genetic algorithm KMV model
Authors: Cheng Xusheng , Sun Ziran , Bao Weiqi 
Published: September 2020

Abstract
This paper firstly analyzes the current situation of credit risk in China’s real estate industry, and then compares the traditional and modern credit risk measurement models. On this basis, the KMV model is selected and the artificial intelligence model genetic algorithm (GA) is introduced to improve the accuracy of KMV model. Secondly, annual financial data and stock trading data of 108 real estate listed companies from 2010 to 2019 are selected for empirical research. The analysis of the total default distance between the 108 companies and the actual economic development in China proves that the results of the GA-KMV model are in good agreement with the economic development trend, indicating that the model has good applicability. Finally, some suggestions are put forward according to the empirical results.