bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Application of Cloud Computing in Government Management
Authors: Zhang Hua 
Published: March 2020

Abstract
Nowadays, the realization of government functions has been more and more inseparable from the network, at the same time, the public also hope the government to provide more and more convenient and fast related services, interactive functions can also advance with The Times. At the same time, the government wants to make public services more efficient. In the context of big data and cloud computing, the openness and sharing of government-owned data has an extremely important impact on the society. In the process of government management, the traditional management way already can’t adapt to the needs of a large number of data exchange, but now the government management slightly to the research of innovative technology still lags behind, the rise of cloud computing provides a new way for the government management innovation, this article to introduce the cloud computing government management for research purposes, to provide a new way for the government management reform.
Vulnerability Mining Technology Based on Genetic Algorithm and Model Constraint
Authors: Ren Tianyu , Wang Xiaohu , Li Qun , Wang Chao , Dong Jiahan , Guo Guangxin 
Published: March 2020

Abstract
The Internet brings people so much convenience, but also with a variety of viruses, network attacks and other security issues. Vulnerability mining technology is the core technology to solve the security of application software. According to different test objects, it can be divided into source-oriented vulnerability mining technology and binary code vulnerability mining technology. In recent years, software vulnerability mining technology still has many defects, involving dynamic tracking, symbol execution, path constraint collection and solutions. The purpose of this paper is to enable people to safely and safely use the Internet, maintaining the security of network application software has become the core issue of network security. In this paper, by introducing the improved genetic algorithm, the STP solver in KLEE and the improved genetic algorithm and model constraints are implemented to solve the nonlinear constraints in parallel. The solution module of genetic algorithm and model constraint is designed, and the parallel solution module in KLEE and the abstract resolution layer of KQuery are implemented. Finally, the parallel solution module is called by KLEE to generate test cases. The results show that the improved genetic algorithm can solve the nonlinear constraint conditions that cannot be solved in the original model, and generate test cases that can cover the path of the nonlinear constraint conditions, effectively improving the test cover path and test efficiency. Finally, the improved genetic algorithm constraint model is applied to memory leak detection.
Research on Value Assessment of Scientific and Technological Enterprises Based on BP Neural Network
Authors: Li Ximei 
Published: March 2020

Abstract
At present, in the research of the value evaluation of science and technology enterprises, most scholars adopt market method, income method, real option method and other basic research methods. These commonly used methods have some limitations in the application of evaluation. Therefore, from the perspective of BP neural network, the author discusses the applicability and validity of BP neural network in evaluating the value of scientific and technological enterprises, and provides a reference for relevant investment decision makers of scientific and technological enterprises.
Optimization of Road Safety Assessment Algorithm for Automatic Driving Vehicle
Authors: Long Qiong , Duan Xian-Li 
Published: March 2020

Abstract
Autonomous vehicles (self driving automobile), also known as driverless vehicle, computer-driven vehicle, or wheel mobile robot, is a kind of intelligent vehicle which realizes driverless through computer system. In the 20th century, it has a history of several decades, and in the beginning of the 21st century, it shows a trend of close to practicality. Autonomous Vehicles rely on the cooperation of artificial intelligence, visual computing, radar, monitoring devices and global positioning system, so that computers can automatically and safely operate motor vehicles without any active human operation.
Study and application of numerical simulation method for welding process based on Marc
Authors: Gao Qihan 
Published: March 2020

Abstract
The bridge and shipbuilding industry have been troubled by the issues of increased production costs and delays due to the welding residual stress and deformation. It is of great practical significance to study welding residual stress and deformation. In this paper, the FEM software Marc is used to carry out numerical simulation of plate pass welding, and the welding temperature field and residual stress distribution after welding are obtained. The simulation calculation results are qualitatively analyzed.
Research on Computer-aided Translation Technology on the Background of Information Age
Authors: Cheng Xiaoxiao 
Published: March 2020

Abstract
The rapid development of science and technology has brought a strong impact on people’s traditional habits, among which there is no lack of subversive impact. Even in language communication, the progress of computer technology has been involved and achieved a place. Although computer-aided translation software cannot replace translators to complete translation work independently, it plays an important role in translation work. It not only greatly simplifies the work of translators, lightens the burden for translators, improves their work efficiency, but also helps translators to make faster progress in translation, which can be described as half the result. Through the discussion of the help of computer translation technology, computer aided translation software and computer translation software to translators in translation and learning, as well as the application of computer aided translation technology, the author studies the computer aided translation technology in the background of information age.
The Development of IoT Technology in the Field of Intelligent Building
Authors: Wang Xin 
Published: March 2020

Abstract
This paper describes the existing concepts of IoT and briefly explains author’s understanding of IoT. Based on characteristics of intelligent building technology in the era of IoT and its effect on the field of intelligent building, on the basis of a brief description of the current situation of IoT developing in China, it explains the application and development of IoT technology in the field of intelligent building, indicating IoT Technology has a huge developing opportunity in the field of intelligent building, and the time of IoT has reached.
Study on Fault Diagnosis Model of Electric Vehicle based on Learning Algorithm
Authors: Luo Hao 
Published: March 2020

Abstract
As a complex system composed of a variety of mechanical and electrical equipment, the fault of electric vehicle is also complex and diverse. The fault causes of electric vehicles have the characteristics of fuzziness or randomness. As an important part of the electric vehicle, the power battery pack is one of the main fault sources of the electric vehicle, and it is also the focus of fault diagnosis. Therefore, this paper first analyzes the battery fault of electric vehicle, and then introduces the knowledge base and classification method of fault diagnosis model, and finally studies the fault diagnosis model and algorithm of electric vehicle based on decision tree.
Research on New and Old Kinetic Energy Conversion Dynamic Factors Based on Cloud Computing-Big Data Service Enterprises
Authors: Geng Xize 
Published: March 2020

Abstract
In China, the “New and Old Kinetic Energy Conversion” was proposed as the latest national development idea, and it was quickly concerned by relevant researchers. Cloud computing - Big data service enterprises, as a representative of new technology innovation enterprise, have become the leading force to promote the new and old kinetic energy conversion. In this paper, the deep dynamic sources of the two kinetic energy conversions are analyzed in details, and the new and old kinetic energy conversion dynamics are subdivided from the national, industrial and enterprise levels. On the basis of the prior research, this paper combines the actual situation of cloud computing-big data enterprises, and finally determines 68 dynamics factors of new kinetic energy replaces traditional kinetic energy of cloud computing-big data service enterprises based on three levels and eight categories.
Analysis of Charging Strategy of Electric Vehicle Battery-bsse on the Operation Mode of Power Exchange
Authors: Li Jun 
Published: March 2020

Abstract
With the increasingly urgent demand for environmental protection, electric vehicle as a non-polluting means of transportation is becoming more and more popular, and has become the focus of research. This paper first analyzes the current demand of electric vehicle for power exchange, then introduces the operating cost of electric vehicle for power station, and finally analyzes and discusses the battery charging strategy in the power station.
Construction of “Audio-Visual Japanese” Digital Course Based on “General Education Curriculum” Cloud Platform
Authors: Chen Yingchao , Duan Hongfang 
Published: March 2020

Abstract
In this paper, the development of new textbooks is taken as the first step, the modern information technology is used to establish a multidimensional stereoscopic teaching mode of “Cloud platform-assisted learning + students’ autonomous learning”, which has effectively improved the teaching effect of the Japanese audio-visual course. This paper is aimed to explore new ideas for building the digital course of “Audio-Visual Japanese’ based on the General Education Curriculum” cloud platform, to improve students’ Japanese listening and speaking skills effectively, and provide a reference for practical teaching and research in this field.
Analysis on the Cooperation Mode of Robot “Industry College” Based on School-Enterprise Integration
Authors: Tian Jia , Fang Jian 
Published: March 2020

Abstract
The “1+1” school-running model of the Robot Industry College integrates vocational and technical teachers’ colleges with high-quality enterprise resources, giving full play to the advantages of both schools and enterprises, and will train more qualified personnel. This article starts with the cooperation goal and cooperation content, and imagines the cooperation mode of the Robot Industry College.
Design of Logistics Information Management System Based on Information Technology
Authors: Zhang Hongquan 
Published: March 2020

Abstract
With the advancement of the times, network technology has gradually replaced manual operations; intelligent management has saved time and effort, and can ensure the efficient operation of enterprises. Information agencies We must be proficient in the application of logistics management information technology, which is also an inevitable result of the development of society to a certain historical stage. The arrival of the conference changed the face of the whole society. People have long been inseparable from smartphones and computers, and industries are increasingly dependent on information technology. As an important part of social and economic development, logistics enterprises bear the responsibility of freight transportation. Under such a development background, only by adopting scientific management methods scientifically and continuously making progress can we promote the sustainable development of enterprises. This article uses modern logistics and logistics information methods to explain the role of information technology in logistics information management. Introduce some design requirements of logistics information management system. Analyzing the problems of logistics management informatization and the reasons for the lack of modern logistics management informatization, it is concluded that logistics enterprises must pay more attention to logistics management informatization and apply it widely. Improve the relevant standards and levels of information technology, strengthen the supervision and management of information construction, and high-quality information technology.
Clustering Reduction Method Analysis of Rough Set and Decision Tree based on Weight Matrix Analysis
Authors: Wang Lan , Zhang Yi 
Published: March 2020

Abstract
Decision table is a kind of special and important knowledge representation system. In this paper, rough set theory is used to discretize data and reduce data and rules. From the definition of resolution matrix, it can be seen that the shorter the length of an item in the resolution matrix, the greater the effect of this item on classification. And the more frequently the item appears, the more important it is decision tree. Construction of decision tree is a cyclic recurrence process. The paper presents clustering reduction method analysis of rough set and decision tree based on weight matrix analysis.
Analysis of China’s Internet of Things Patents Based on Cloud Computing
Authors: Zhu Weijian , Tang Yang , Bai Dan 
Published: March 2020

Abstract
With the continuous development and progress of information technology, the Internet of Things has been practically used in many areas of people’s lives. The Internet of Things technology, as a collection of connected things, has storage and computing capabilities, which greatly meets the needs of society and people. Cloud computing is an important foundation for the long-term exhibition of the Internet of Things technology. It combines the products of parallel distributed computing technology, network storage virtualization technology, load balancing traditional computer network technology and other technologies, and its computing method is a comprehensive computing the way. This article is based on China’s cloud computing IoT patent application data as the analysis object. It conducts qualitative and quantitative analysis on patent-related trends, related technology composition, and applicant rankings. It reflects the current status of the development of IoT technology and is beneficial to domestic R & D institutions in the field of networking find research blind spots and choose appropriate research directions on their own.
Design and Implementation of Cloud Note System in University Classrooms
Authors: Guo Xin , Chen Tanglong , Wang Yongjiang , Tang You 
Published: March 2020

Abstract
In view of the disadvantages of paper notes that are not easy to save, not conducive to record, and easy to miss information, this fast personal note-taking software is designed with simple and efficient operation interface, which can cross different platforms. The system chooses B/S architecture, Spring + Mybatis framework in the background, and HTML + JS + Ajax technology in the foreground. MySql is adopted in the database to realize data storage. It mainly includes six functional modules: Notebook module, Note module, Recycle bin module, Collection module, Activity module and User module. Through the cloud note system, it is convenient for teachers to prepare lessons, record key teaching points, and collect students’ homework. Students are easy to record knowledge points in class. It can improve both work and learning efficiency.
Monitoring Data Analysis Technology of Smart Grid Based on Cloud Computing
Authors: Qiu Ziliang , Chen Rui , Yan Mengqiu 
Published: March 2020

Abstract
In the smart grid environment, the state data has the characteristics of wide area, panorama, mass and reliability. The traditional storage hardware uses disk arrays and the database management software uses the relational database system. Due to the poor system scalability, high cost and low reliability, it is difficult Adapt to requirements. Based on the above background, the purpose of this article is to study the research of cloud computing-based smart grid monitoring data analysis technology. Aiming at the problem that the power equipment condition monitoring data is getting larger and larger, and traditional storage methods cannot meet the condition monitoring big data storage problem, a cloud platform-based condition monitoring data storage system is designed. Using the distributed file system HDFS and Hbase databases to store status monitoring data, this paper designs a clustering algorithm based on the density cluster structure, DBCLustering, based on the shortcomings of traditional density clustering algorithms. This algorithm first builds the core reachability relationship of the data nodes The index structure CR-Tree is then used to extract a sorted linear table about the reachability relationship of the data. Finally, the clustering results are output according to the results of the linear table. In order to solve the problem of insufficient computing power of the stand-alone version of the algorithm, a clustering algorithm for condition monitoring data based on Spark-RDD-DBClustering algorithm is proposed. This algorithm realizes the parallel application of DBClustering algorithm under Spark platform, and improves the algorithm’s ability to process large-scale data.
Image Matching Method Based on Laplacian Feature Constrained Coupling Variance Measure
Authors: Yang Hongwei , Qi Yongfeng , Du Gang 
Published: March 2020

Abstract
In order to overcome the current image matching algorithms, which mainly use the distance information between pixels to achieve feature matching, ignoring the variance information between images, resulting in more false matching in the matching results, this paper designs an image matching method based on Laplacian feature constrained coupling variance measure. Firstly, Harris operator is introduced to extract image features roughly. On the basis of rough extraction, Laplacian feature of pixels is used to optimize the extracted image features to obtain more accurate image features. Then, the gradient feature of the image is used to calculate the direction information of the image. Based on the gradient feature, the neighborhood of the feature points is established, and the Haar wavelet value in the neighborhood is obtained to obtain the feature vector. Finally, the regional variance model is used to measure the variance information of the image, and it is introduced into the process of image feature matching. The variance information is added on the basis of Euclidean distance measurement of feature points to achieve image feature matching more accurately. RANSAC method is used to purify the results of feature matching, eliminate mismatching and complete image matching. The experimental results show that compared with the existing matching algorithms, the proposed algorithm has better matching performance and higher accuracy, which accuracy maintained above 90%.
A Multi-person collaborative Simulation System for Subway Emergency Based on Virtual Reality
Authors: Jiang Tao , Qiu Yahui , Li Fang 
Published: March 2020

Abstract
In the operation of urban rail stations, joint emergency drills for different types of work are an important way to ensure the safe operation of urban rail stations. However, due to the lack of equipment and means, at present, the joint emergency drills for urban rail stations are mostly a single-person system. Based on the current status of emergency joint drills in urban rail stations, this article proposes a virtual reality-based multi-person collaborative urban rail station emergency simulation system. Construct a large-scale virtual reality scene through the viewpoint-related LOD quadtree, and use socket technology to achieve multiplayer online interaction. Finally, all models are jointly driven by Unity3d in the simulation scene. An immersive, multi-industry coordinated urban rail station emergency drill simulation system was constructed. Providing a simulation training environment similar to the actual situation for emergency trains in urban rail stations can greatly improve the shortcomings of difficult and inefficient implementation of the organization, and change the difficult situation of insufficient emergency drills for multiple types of rail stations.
Hospital Nursing Information Sharing Platform based on Improved Particle Swarm Optimization Algorithm
Authors: Xie Shiyu 
Published: March 2020

Abstract
Traditional sharing platform adopts manual input information, and the sharing process is inefficient. A hospital nursing information sharing platform based on improved particle swarm optimization algorithm is proposed. The main index structure of the patient was designed and the information input was completed. The priority random swimming data transmission algorithm is used to transfer nursing information. The information sharing mechanism of particle swarm optimization (PSO) is analyzed, and the sharing platform is designed according to the optimal position of individual particles. Experiments show that the shared platform can achieve high speed interaction of hospital nursing information.
Distributed Storage and Computing Technology in New Energy Real-time on-Board Data
Authors: Wang Yingzi , Hou Jue , Chu Sisi 
Published: March 2020

Abstract
The development and application of new energy vehicles has always been the focus of the government. As far as the users of new energy vehicles are concerned, the safety and energy-saving effects of operating conditions are of vital importance. Therefore, to fully promote the development of new energy vehicles, we must do a good job in the statistics and processing of new energy real-time vehicle data. This article focuses on the analysis of the effects of distributed storage and computing technology on real-time on-board data processing for new energy vehicles to provide solutions to the difficulties of countries and enterprises in the research and development of new energy vehicles and promote he energy saving of the state and enterprises.
Prediction of Regional Economic Trend with f Improved BP Neural Network Algorithm
Authors: Liu Anmin , Zhu Jiang , Yue Donghai , Liu Guangxin 
Published: March 2020

Abstract
Traditional BP neural network-based prediction method cannot accurately predictregional economic trend, and the operation efficiency is low. To this end, a method based on improved BP neural network algorithm is developed to predict regional economic trend. The Cobb-Douglas production function is used to select the most influential number of working people and economic investment in fixed assets, fiscal expenditure, gross foreign export value, retail sales of social consumer goods index as the sample data and normalized. The error of sample data is calculated by TangXC_BPModel model, and the the weights are modified uniformly so that and the regional economic trend is predicted accurately.