bluuebunny/crossref_metadata_2025_split huggingface dataset:
Historical Opportunity and Structural Transformation of Sports Industry Development under the Background of New Information Technology
Authors: Deng Chenliang , Tang Zhaohua 
Published: July 2020

Abstract
Based on the analysis of the status quo of the development of sports industry, this paper studies the development opportunities and structural changes of sports industry under the background of new information technology. Objective to explore the development opportunities and structural transformation of sports industry under the background of new information technology, broaden the research field of sports industry, and provide references for the development planning or policy formulation of sports industry. According to this study, the current development status of sports industry is not optimistic, which is mainly reflected in the weak willingness of sports consumption, the shortage of sports venues and facilities, the lack of talents in sports industry, and the lack of in-depth integration with new information technology. Under the background of new information technology, the development opportunities of sports industry are mainly reflected in three aspects, that is, new information technology promotes sports industry to seize opportunities and expand markets, innovate the operation mode and operation mode of sports industry, and change the service platform and service system of sports industry. The structural transformation of the development of sports industry is reflected in the new competition system, new technology system, new consumption structure and new business trend. In the context of new information technology, it is necessary to analyze the opportunities and challenges faced by the sports industry more deeply, put forward more specific operational development countermeasures, and build a new sports industry development ecosystem and business model, in order to promote its sound development.
Cultivation Strategy of College Students’ Craftsman Spirit from the Perspective of Artificial Intelligence
Authors: Luo Qinglan , Wang Chunyan , Zhao Ying 
Published: July 2020

Abstract
With the continuous deepening of artificial intelligence in education informatization, the transformation of education methods and learning methods under various new technologies has great prospects for promoting the research and application of personalized and deep learning in the AI environment. This article mainly studies the cultivation strategy of college students’ craftsman spirit in the perspective of artificial intelligence. Based on the current situation of digital literacy, achievement gaps, and outdated knowledge, this article explores new methods suitable for the new environment, such as role change, innovative education, integration of multiple learning methods, and creation of new learning spaces. The further development of higher education in the context of artificial intelligence provides exploration and discovery to serve the future of students. The experimental analysis of this article found that the correlation coefficients of the factors of the scale were between 0.394 and 0.618, which were basically at a moderate level and basically met the requirements of 0.10 to 0.60. At the same time, the correlation between the factors and the total score of the questionnaire was between 0.724 and 0.833. Meet the requirements. The cultivation of craftsman spirit meets the needs of colleges and universities to cultivate new talents, and provides theoretical support for colleges and universities to carry out spiritual and cultural education.
Innovative Research on Smart Service System of Self-Driving Tour Based on 5G Technology
Authors: Wang Jing 
Published: July 2020

Abstract
With the advent of 5G commercial era, self-driving tour are supposed to greet new developing opportunities as a new-coming sightseeing method. Via combing the composition and existing problems of self-driving tour service system, to transform the traditional self-driving tour service system under the support of 5G technology is put forward. Regarding the self-driving information service as the core, the 5G technology is applied in order to build an information service cloud platform linking self-driving tour service system and self-driving tourists, as well as VR, AI, unmanned driving, intelligent search, intelligent positioning and other science and technology are utilized to the self-driving tour service system, which jointly structure self-driving tour smart service system, so as to satisfy the service needs of self-driving tourists and initiate the new chapter of self-driving development.
High-Speed Maglev Train Battery Design Considering of the Position of Assist Stop Areas
Authors: Tian Yi , Geng Shuheng , Hou Shengjie , Lyu Xinnan , Wang Suoping 
Published: July 2020

Abstract
With the increase of the operation speed in the high-speed maglev railway system, the distance between the assist stop areas can be increased. To ensure the safe operation between the two assist stop areas, the capacity of the onboard storage battery in maglev trains shall be redesigned. This paper derives the distance between the assist stop areas in different operation speed, which generate the speed curves for calculating the minimum battery capacity required for operation. We analysed the capacity requirements of the maglev battery at the different commercial operation and maintenance operation speed, as well as the impact of the battery capacity to the location design of the assist stop area, which can provide the guidance to the design of the onboard battery capacity in high-speed maglev train.
Implementation and Optimization of Particle Effects based on Unreal Engine 4
Authors: Zhang Juan 
Published: July 2020

Abstract
The wide application of virtual reality and augmented reality makes the engine of developing virtual reality develop towards more realistic rendering, more convenient operation and better performance. In the realization of virtual reality scene, the three-dimensional particle effects play an excellent performance, and enhance the immersion of the experiencer. However, the production and optimization of three-dimensional particle effects have always been a complicated task for developers. Based on the visual blueprint script of Unreal Engine 4 and the modular particle editor, the author elaborates the method of making particle effects in detail, calculates the cost of particle system in real time by using the console of Unreal Engine 4, and then analyses the reasons that affect the performance of particle effects according to the data. Three methods, GPU launcher, material instruction reduction and LOD application, are used to optimize the performance of particle effects, and data are used to show the results of optimization.
Spatiotemporal Analysis of Air Pollutant Concentrations in Major Transportation Hubs of Kunming : A Case Study of Dongfeng East Road Station
Authors: Wang Yifu , Yuan Lei 
Published: July 2020

Abstract
The rapid development of industrialization and the continuous acceleration of the urbanization process have continuously improved the quality of life of the people, but at the same time brought important environmental problems such as air pollution and climate change that humans have to face today. In this paper, the meteorological data of Dongfeng East Road Station in Kunming is taken as the research object, and the Spark platform is used to quickly and effectively analyze the air pollution data of Dongfeng East Road Station. Through analysis and research on the air pollution-related conditions of major transportation hubs in Kunming in recent years, the results show that the concentration of air pollutants at Dongfeng East Road Station in Kunming has a relatively obvious downward trend, especially the significant decline in SO2 and CO. As far as air quality is concerned, the air quality in some areas of Kunming continues to improve.
Test and Analysis of Characteristics of Safe Driving Speed on Typical Ice-snow Road
Authors: Meng Enjie , Wang Bing , Wei Ji’ao , Liu Haoran , Zhao Kuo , Hu Ze 
Published: July 2020

Abstract
When a motor vehicle driver encounters ice-snow road on low-grade road, it is easy to cause traffic incidents or even accidents because it is difficult to autonomously control the safe speed, which is a hot and difficult problem in the cold areas of northern China; At present, there is little research on the characteristics of safe driving speed on different types of ice-snow roads at home and abroad. In this paper, six types of typical ice-snow roads, such as fresh snow, snowboards, semi-melted snowboards, ice boards, semi-melted snowboards, and “black ice” (snow-covered ice), were constructed to test the safe driving speed and its corresponding main factors, and the data was processed to explore the safe driving speed on different types of ice-snow roads and its relationship with the main influencing factors; this study has practical significance for guiding drivers to autonomously control safe vehicle speed on ice-snow road, and also provides reference for the development of intelligent transportation technologies such as speed guidance, dynamic speed limit and autonomous driving.
Design Traffic Signal Node Based on Edge Computing
Authors: Yang Jinyan 
Published: July 2020

Abstract
With the development of economy, the traffic jams are more and more serious. The traditional timing traffic signal can’t make full use of the road traffic resources. In order to solve this problems, an edge computing intelligent traffic light node is proposed, video target detection, artificial intelligence and other new technologies are used to realize the effective control of intersection signals, so as to optimize pedestrian traffic, vehicle delay, traffic capacity and parking times. The simulation results show that this method can greatly improve the traffic efficiency and reduce the waiting time of the intersection during normal times. It can effectively delay the peak period and shorten the peak period.
Remote Sensing Dynamic Monitoring on the Land Destruction and Recovery of Green Mines
Authors: Yao Weiling , Yang Jinzhong , An Na , Li Li , Sun Yaqin , Chen Dong 
Published: July 2020

Abstract
The construction of green mine is the only way to promote ecological civilization and realize the harmonious development of man and nature. This paper introduces the methods and steps of using remote sensing technology to carry out dynamic monitoring on green mines, and summarizes the main monitoring elements of green mine environment, and analyse the status quo and dynamic changes of land destruction and recovery of green mines according to the monitoring results. On the whole, the land recovery rate of green mines is low in China, and the level of land recovery is uneven in different regions, mines and minerals. The result shows a tendency that the land occupation of green mines has changed from the extension of the land destruction in the early stage to the recovery of the stock mining land. The main recovery modes of green mine include prevention engineering, ecological protection engineering, functional restoration and reconstruction, land reclamation, soil restoration and so on. It is necessary to strengthen the application of radar data to monitor mining subsidence area and the application of hyperspectral data to enhance the monitoring of mine recovery effect.
Survey of Methods for Data-Scarce Processing Based on Mechanism Model
Authors: Wang Guobo , Ma Minglu , Xu Liansheng 
Published: July 2020

Abstract
Due to the imbalance in global economic development, the lack of response data is a prominent shortcoming in information concerning many river basins. The uncertainties incurred by data scarcity reduce the reliability of the simulation results of river basins and pose difficulties in the simulation of non-point source pollution and maritime search and rescue, which in turn affects the environment of the basin. Based on a simulation conducted using the mechanism model in the context of a lack of response data from rivers, this paper analyses a variety of methods of data processing in case of missing data. In the era of big data, this paper provides a variety means of using data-scarce simulation methods as an effective reference for simulations of water quality.
Applied Research of Internet of Things Technology in Agricultural Greenhouse
Authors: Wang Shuanghu , Yin Hongxu , Zhang Wei , Zhao Jingtao , Liang Shun 
Published: July 2020

Abstract
The application of the Internet of Things technology to agricultural electrification production, especially agricultural greenhouse cultivation, can greatly improve the quality of agricultural products. This article summarizes the application technology of the Internet of Things technology in five aspects of agricultural greenhouse insulation, electric rolling shutters, electric drainage and irrigation, electric supplementary light and electric ventilation. Deep integration with agricultural production to improve agricultural planting benefits.
Design and Implementation of Visualized and Rule Based Integrated Primary Equipment Overhaul Management System Build on Dcloud
Authors: Wang Yuesong , Gu Yeqing , Shi Jianhua 
Published: July 2020

Abstract
The systems are deployed at all levels of dispatching organizations which are connected by microservices. In this paper we introduced unified equipment model to achieve show overhaul plans on geographic information system map. Balancing and scheduling overhaul plans by build a rule based expert library. Information exchange and workflow pushing achieved by introducing data exchange service and workflow pushing service which registered on service bus provide by Dcloud, with help of the service the information could be shared among all levels of dispatching organizations, the workflow could be ran more smoothly. The system also provides a collaboration planning platform which is used for make the processing of workflow more efficient. This system is a powerful technique support for continuous protection of the safe operation of the power grid.
A Ship Draft Line Detection Method Based on Image Processing and Deep Learning
Authors: Wang Zhong , Shi Peibei , Wu Chao 
Published: July 2020

Abstract
The traditional ship draft detection method mainly adopts the method of the human eye observation, which has the problems of large precision error and slow detection speed. Aiming at this problem, this paper proposes a ship draft line detection method based on image processing and deep learning. The color image is first transformed into a grayscale image, and the corner detection is carried out by Harris operator. Contour map is obtained using Canny operator for edge detection, and line segment detection is performed using Hough algorithm. The water surface is determined by calculating the lowest position of the corner point. Then the grayscale image is binarized to increase the contrast of the image, the digital area is determined by the corner positions of the highest and lowest points, and finally the convolutional neural network is used to perform character recognition and calculate the draft of the ship. Tested on videos of various scenes, the error of the proposed method is less than 1cm.
A Study of Community Surveillance System Improvement based on ResNet Person Re-identification
Authors: Gu Xinyi , Qu Chengzhang 
Published: July 2020

Abstract
Most existing community surveillance systems rely on face recognition to identify pedestrian. The face image captured by community surveillance camera are not always clear enough. Thus, Person re-identification (ReID) imply critical applications in surveillance as it has more image information of pedestrian. In this paper, we refine a ResNet50 based reID model which only adds a Linear layer, a Batch Norm layer and a reLU layer in front of the classifier. The refined model is simple to build on the surveillance system, and we have tested in our demo surveillance system and Market1501 data-set. The experiment result shows it can work well on real-time. On Market1501, our results are competitive that rank-1=0.875000, rank-5=0.944477, and mAP=0.706647 since its low complexity. Our demo community surveillance system shows the refined ReID model is competent and practical for identification tasks.
An Online Calibration and Detection Method for Inertial Equipment on Aircraft
Authors: Song W Y , Wu X H , Wang J , Sun Y G , Fang Y 
Published: July 2020

Abstract
At present, the calibration and detection for inertial equipment on aircraft generally need to disassemble the inertial equipment from the aircraft, and it is inconvenient to use this method to maintain the inertial equipment. An online calibration and detection method is proposed in the paper, which is able to obtain the detection indexes by combining the vertical and rotary motion of the launching vehicle. The indexes contain the zero drift indexes, the scale factor nonlinear indexes and the attitude angle error indexes of the gyro and accelerometer. By judging if these indexes are within the threshold range of requirements, we can determine whether the inertial equipment perform well. Using the designed limit index as the calibration parameter, the simulation experiment of shooting is carried out to verify the effectiveness of the designed method. The simulation results show that the miss distance meets the design requirements within the limit index range. The designed algorithm can directly detect the inertial equipment online, avoiding the repeated disassembly and assembly problems caused by the traditional detection methods, and reducing the test and maintenance costs.
SLAM System Based on Tightly Coupled Visual-inertial
Authors: Chen Zhang , Mei Wang , Yunlei Yu , Yongyun Gao 
Published: July 2020

Abstract
Aiming at the problem of mobile robot positioning, IMU information is used to improve the performance of visual SLAM. Firstly, instead of the calculation of feature descriptor, LK optical flow is used in the processing of visual information, to increase the speed of feature extraction. And detectors are used to remove outliers. Secondly, the visual information and IMU information are initialized separately to obtain the camera pose and IMU pose. And then Visual-inertia joint initialization is conducted by tightly coupling of the IMU information and the visual information, to improve the calculation. Finally, the pose state estimation is achieved through back-end optimization. The validity of the proposed algorithm is verified by the experiments.
Research on Chinese Sentence Compression Automatic Evaluation Method based on Sentence Hierarchical Information Extraction
Authors: Wang ZhongXian , Du WenShuang , Ren JiaLu 
Published: July 2020

Abstract
People often feel incomprehensible and difficult to understand in the face of huge amounts of information. They instinctively produce the natural need to condense information to save time. Sentence compression technology has been born. The research on sentence compression evaluation methods has developed with the rise of sentence compression technology, and has gradually become a hot issue for sentence compression tasks. The method of sentence compression evaluation is to judge a good or bad cornerstone of compression results. influences. Under the current practical background, the performance evaluation of sentence compression mainly includes two methods: manual evaluation and automatic evaluation. The main problems encountered are: First, most of the research work uses manual evaluation indicators. The compression results under manual evaluation have high accuracy and meet the requirements. People’s daily language habits have the disadvantages of inflexibility and poor reusability. Second, there are few automatic evaluation methods for Chinese sentences, and the existing traditional automatic evaluation methods only consider the morphological similarity between the compressed sentence and the original sentence, and cannot well represent the compression effect. Based on the above practical problems, this paper proposes an automatic evaluation method for Chinese sentence compression based on sentence hierarchical information extraction. Compared with the manual evaluation method and the traditional automatic evaluation method, the Chinese sentence compression automatic evaluation method based on sentence hierarchical information extraction overcomes the disadvantages of high manual evaluation cost and low reusability. It uses the similarity of sentence hierarchical information to diversify. Ground characterization and evaluation of compression effects have significantly improved the rationality and accuracy of traditional automatic evaluation methods Introduction.
A Rapid Recognition Method for Rice False Smut based on HOG Features and SVM Classification
Authors: S Naila , JJ Yu , N Yang , H Kashif , J Tang , AY Wang 
Published: July 2020

Abstract
A rapid detection method for the detection of false smut is introduced based on HOG features and SVM classification to overcome the drawbacks of false smut detection like time wasting and inaccurate recognition. In this paper, original images of false smut used, which directly taken from the field of rice. First of all, the image false smut diseased rice acquired by image preprocessing was based on the color threshold to obtain the (ROI) region of interest from healthy and unhealthy pictures of rice. Secondly, the gamma-correction performed on the extracted ROI unhealthy and background region of healthy rice images. The HOG features extracted to form a high-dimensional HOG feature vector. Third, the PCA analysis performed on high-dimensional HOG features, and the original 1764-dimensional feature vector reduced to a two-dimensional vector that can represent most vectors to achieve the purpose of dimension reduction. Finally, the dimension-reduced HOG feature vector sent to the SVM classifier for training. The expected recognition accuracy under the binomial kernel function is 80.6%, and the actual test set recognition is 78.56%.
A Novel Sudden Fault Prediction Method Based on Hierarchical Structure with GRU Neural Network for X-ray High-voltage Power Supply
Authors: Zhang Jianlong , Li Qiao , Wang Bin , Cui Mengying 
Published: July 2020

Abstract
Considering the sudden fault feature of X-ray high-voltage power supply are mostly reflected in the high-frequency components, a hierarchical structure with time sequential neural network is proposed to predict sudden fault of X-ray high-voltage power supply in this paper. Gate recurrent unit is the basic unit of time sequential neural network. Firstly, multi-wavelet transform is used to decompose the signal of the X-ray high-voltage power signal to obtain the coefficients of each frequency band. Secondly, signal waveform reconstructed for each layer of wavelet coefficients is as the input of the gate recurrent unit network to predict signals at different frequencies. Finally, each gate recurrent unit performs multi-step prediction on the reconstructed waveform in this frequency band for sudden fault and all band prediction outputs are composed to obtain the final prediction results. The simulation experiment shows that our method has better performance than the Kalman filter, recurrent neural network and long-short term memory prediction methods, and can accurately predict sudden fault of X-ray high-voltage power supplies.