bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research and design of system security based on .NET frame
Authors: Zhou Jing , Guan Yurong , Zhou Fei 
Published: November 2019

Abstract
For using the .NET framework model of Web application system for Web development to some security problems in the analysis and discussion, this paper put forward some security prevention programs, though. The .NET framework system itself has some security protection mechanism, but users in developing Web mode when the application is to avoid safe hidden trouble, should be more reliable in every link of security Settings.
Exploration of Modular Teaching Model for Environmental Art Design Specialty in Information Age
Authors: Zhe Zhang , Wang Qinghai , Xing Yadan 
Published: November 2019

Abstract
In the information age, the current teaching situation of environmental art design is not optimistic. There are many reasons for this phenomenon. In addition to the traditional inherent factors, the more important thing is that there is no basic teaching evaluation system and teaching model reference in environmental art design education. Based on the characteristics of the information age, this paper studies and establishes new rules of teaching design of environmental art design, and designs a teaching model of environmental art design.
Research on Topic Mining Algorithm Based on Deep Learning Extension
Authors: Yang Fuqiang , Zhao Xuechen , Zhang Maohong 
Published: November 2019

Abstract
This paper proposes a new algorithm that can consider both keywords and time of occurrence. Firstly, after the data is preprocessed, the LDA model of the theme event set is established, and the set of subject words is generated as the description mark of the event. The semantic and temporal similarity between the event keywords are calculated by the DTW algorithm to obtain the corresponding similarity matrix. Finally, the collaborative training method is used to iteratively generate the final feature vector and complete the event selection. The simulation results show that the proposed algorithm has higher accuracy and higher efficiency than previous algorithms.
Research on equipment life cycle information management
Authors: Qi Jiandong , Qi Jiandong 
Published: November 2019

Abstract
At the beginning of this century, with the rapid development of information technology and the high technology of weapons and equipment, the traditional management model can no longer meet the current and future development needs of equipment construction. It is urgent to establish an information management system to improve the life cycle of equipment. This paper explores the life cycle information management model of equipment from many perspectives and levels, such as equipment management at home and abroad, equipment information management analysis, basic principles of equipment information management construction, system technology platform, system development and so on.
Application of Improved Non-local Mean Filtering Algorithm in Detection of Oil and Gas Wells
Authors: Cuan Ying , Wang Sijie , Han Jiaxin 
Published: November 2019

Abstract
As the oil and gas exploration in most parts of China has entered into the middle and late stages, the aging and wear problems of mining equipment have become increasingly prominent. In the process of visual image acquisition of oil and gas well casing damage, due to the influence of the complex environment of light and dust, the image data source noise is serious, and the image recognition model has low accuracy. This paper improves the neighbourhood filtering algorithm block search process with the ant colony pheromone correlation theory, optimizes the block matching process with the Pearson algorithm, and eventually applies the optimized non-local mean filtering algorithm to the oil and gas well casing damage visual detection process. The experimental results show that the improved non-local mean filtering algorithm has a significant impact on the adaptability and effectiveness of the noise reduction effect.
Research Progress in Image Denoising Algorithms Based on Deep Learning
Authors: Ruikai Cai 
Published: November 2019

Abstract
Images constitute the main source of information to people. Digital images are vital means of obtaining, processing, analyzing, and sharing information in the era of information. Now they have been deeply incorporated into every aspect of people’s production and life, generating considerable social and economic benefits. Thus improving the quality of images and reducing the negative impact of image noises to subsequent image processing have been two important research topics. Image processing technology has been combined with such research fields as cognitive psychology, machine learning, machine vision, and deep learning in recent years, which lead to an unprecedented development level and breakthroughs. Therefore, the study of image denoising technology has profound theoretical significance and promising prospects in practical application. The paper mainly discusses the development course of applying deep learning technology to the image denoising field. Meanwhile, it introduces various classical denoising algorithms and focuses on the thoughts, advantages, and disadvantages of each algorithm. Furthermore, it discusses the challenges faced by deep learning in the denoising field and puts forward possible solutions.
Research on key technologies of intelligent agriculture under 5G environment
Authors: Meng Hainie , cheng Yunli 
Published: November 2019

Abstract
The application of agricultural Internet of things technology is the need of modern agriculture development, and also is an important sign of the future agricultural development level, which will be the direction of future agricultural development. The core technology of intelligent management is to adopt the methods of automation and information. In order to achieve accurate agricultural automation control and facilitate the information and intellectualization of management, it is necessary to develop intelligent agriculture with Internet of things, intelligent perception, intelligent control and cloud platform technology as the core.
Coordination and Optimization of Urban Traffic Control and Path Guidance Based on Multi-Agent
Authors: Wang ZhengQin 
Published: November 2019

Abstract
With the development of society, the urbanization process is accelerating, the urban population is growing rapidly, and the traffic problems are becoming more and more prominent, which seriously affects the normal operation of the city. Transportation is the lifeblood of the city. Scientific management and control is an important way to improve the efficiency of urban traffic operation, and it is also an important symbol of urban transportation modernization, informationization and intelligence. This paper aims to study the new coordinated control method of traffic signals. Different from the traditional coordinated control method of centralized control and hierarchical control, a multi-agent distributed traffic signal coordination control system is established, which distributes the main functions of signal control to Signal control agents at various intersections reduce to the complexity of the control algorithm and improve the reliability and intelligence of the system.
Research on High Accuracy Prediction of Ship Attitude Based on Improved Neural Network Method
Authors: Bu Xu , Cheng Yunli 
Published: November 2019

Abstract
In view of the difficult problem of ship attitude prediction accuracy and the features of ship attitude change, a prediction model of high accuracy of ship attitude based on the improved neural network is proposed. Firstly the data of ship attitude is collected and de-noised. Then the high accuracy approximation to the features of ship attitude changes is carried out by using the improved neural network, some defects of which are improved. Finally the simulation experiment of ship attitude prediction is conducted. The experimental results show that the improved neural network can improve the accuracy of the ship attitude prediction and overcome the disadvantages of the large errors in the other ship attitude prediction models and the advantages of the ship attitude effect are very obvious.
Towards a Smart Manufacturing Maturity Assessment Framework: A Socio-Technical Perspective
Authors: Yue Lei , Niu Pengfei , Fang Yifang , Han Zhonghua 
Published: November 2019

Abstract
Researchers of information technology (IT) have often suggested that there is no clear relevance between the IT investment and return on investment (ROI) of enterprises. This phenomenon is called “productivity paradox”. However, research on smart manufacturing capability maturity did not reflect empirically the fact that enterprises rarely benefit from information systems. Therefore, the aim of this article attempts to explore how humans and technologies are related and propose a smart manufacturing maturity assessment framework that can reveal the interaction between humans and technologies. This research addressed two questions, (a) what domains can be identified for smart manufacturing, and (b) how to harmonize all of the technical and social factors affecting maturity and benefits. A complicated concept “socio-technical system” was surveyed for interpreting how enterprises benefit from technologies. Results of this study showed a smart manufacturing maturity assessment framework from the socio-technical perspective. As an explanation, the understanding of manufacturing operations management (MOM) capability maturity model (CMM) within the framework in the case study and its results were presented. To conclude, this study may be regarded as a meta-model or reference model for specific maturity models, as well as has the merit of offering valuable insights into the maturity assessment.
Research on College English Teaching under the Background of Artificial Intelligence
Authors: Liu Ying , Liu Miao 
Published: November 2019

Abstract
The application of language service products of artificial intelligence has brought great challenges and opportunities to language teaching in colleges and universities: promoting the teaching model innovation; changing the way of students learning; changing the basic functions of teachers. The teaching mode of college English under the background of artificial intelligence should be influenced by several aspects as follows: based on artificial intelligence in college English listening teaching; college English oral teaching based on robot; based on the number of the teaching of artificial intelligence in college English writing; cloud service based artificial intelligence college English in translation teaching.
Study on the motion design and control algorithm of the tortoise robot
Authors: Wang Dongliang , Li Hui , Lin Xiaohu , Wang Mingxin , Cao Qingzhuang 
Published: November 2019

Abstract
Turtle robot is a four-legged robot based on bionic concept. There are many researches on quadruped robots in the world, and many domestic and foreign research institutions have also developed prototypes and conducted relevant researches. If the traditional control system of the quadruped robot is used, it is difficult to obtain ideal results. At the same time, the robot’s feet are easily affected by the external environment, and how to keep the robot moving in a coordinated and balanced manner makes the problem more complicated. Starting from the control problem of the four-legged robot, this paper takes the action controller of the tortoise robot as the research object, studies the control method of one leg, establishes the four-legged eight-joint control system of the tortoise robot, designs the motion and control algorithm, and uses the infrared wireless module for remote wireless control.
Pure Rolling Steering System Design and Research for Wheeled Mobile Robot
Authors: Chen Zhifa , Xie Xiaolin , Gao Feng , Liu Zhengyu , Li Yaoyu 
Published: November 2019

Abstract
In order to solve the problem of the side slip of the wheeled mobile robot adopting the steering trapezium, a novel pure rolling steering system for wheeled mobile robot is designed. It takes advantage of synchronous belt characteristic with long-distance, variable-direction and precise transmission and is equipped with a dual power differential drive axle. This paper details the design points of the whole mechanism; sets up the kinematic models of four-wheeled Ackerman steering, crab movement, and pivot turn modes; and then the steering drive control strategies of various modes of the robot is established. A prototype equipped with a control system consisting of a control center, four steering motors, two drive motors, an electromagnetic clutch and four angle sensors is constructed. Finally, the test results for pivot turn and four-wheel minimum radius steering on the hard road shows that the trajectory slip error are less than 0.2% and 1.7%, respectively. This verifies clearly the correctness and effectiveness of the proposed pure rolling steering system for wheeled mobile robot.
Analysis and forecast of special car market based on BP neural network
Authors: Liu Dengfeng , Yu Haixin , Zhang Chen 
Published: November 2019

Abstract
This paper is based on the macro environment of the special car market and its development status. Combined with relevant data, this paper forecasts the future prospects from the perspectives of the transaction scale, market recognition and the change trend of the number of special cars, we get the current situation of the car market and the future development trend. Then, the BP neural network prediction model is used to predict the demand of the special car. The grey prediction model is used to predict the number of special cars, and then the future transaction scale of the special car market is analysed. The development prospects of the special car market are analysed from the above three aspects, and the future development of the special car is predicted. It is the result that the market will increase steadily but the growth rate has slowed down, which is in line with the actual situation.
Study on the Decision of Supply Chain Considering Asymmetric Information and Quality Competition
Authors: Zhao Chao , Zhao Jing , Wu Gang , Zhang Fan 
Published: November 2019

Abstract
Product quality is a fundamental factor for supply chain to obtain a competitive advantage. This paper studies the decisions of supply chain under asymmetry information of quality effort cost, considering the quality competition of manufacturers. Transfer payment contract is introduced by comparing the Stackelberg model between symmetry information and asymmetry information. At the same time, this paper analyzes the impact of quality competition and false information strategy on supply chain quality decision. The research shows that the quality competition can improves products quality, and manufacturers tend to choose strategy of false information. Moreover, after the introduction of contract, the manufacturers will convey the true quality information and reduce the competition to optimize their own profits.
A Simplified Method for Dynamic Equation of Robot in Generalized Coordinate System
Authors: Dong Sheng , Yuan Zhaohui , Zhang Fuli 
Published: November 2019

Abstract
This paper presents a simplified method of dynamic equations in a generalized coordinate system, which decouples the relative motion of the front and back links of the robot joint, and maps generalized angular variables to the same angular datum. Because of the decoupling between absolute angle variables, the complexity of the coefficient matrix of the dynamic equation of the system is reduced, which facilitates the application of the actual series robot system. The simplified process is derived in detail, and the equivalent relation between the generalized relative coordinates and the generalized absolute coordinate dynamics is demonstrated. The relation can be extended to the dynamic equations of different generalized coordinate variables. Aimed at the problem that the quasi-input moment vectors obtained in generalized absolute coordinates cannot be directly used without considering the dynamic coupling of the whole system, the linear relationship between the input moment vectors in absolute and relative coordinates is found. In the end, a simplified example of the Euler-Lagrange dynamic equation for multi-degree-of-freedom manipulator is given. The relationship between the two input torque vectors is simulated by MATLAB and verifies that the input torque can be indirectly calculated by finding the quasi input torque under the absolute coordinates.
Research on the Influencing Factors of College Students’ Use of Online Learning Platform from the Perspective of Customer Perception
Authors: Wei Yao , Li Jinjing , He Yong 
Published: November 2019

Abstract
[Aim] With the increasing number of users of the internet learning platform, in order to explore the influence factors (perceived usefulness, perceived ease of use, and the learning environment) of the internet learning platform from the perspective of customer perception, the impact of college students using the internet learning platform is the learning platform provides corresponding guidance. [Method] Based on the data of college students’ questionnaires, this research integrated technology acceptance model (TAM) model with customer perception theory to construct the structural equation model to evaluate the impact of perceived ease of use, and learning environment on college students’ use of online learning platform. [Conclusion] The study found that factors of the internet learning platform including perceived usefulness, perceived ease of use, and the learning environment of college students would have a significant impact on its use.
Research on Informatization of Hidden Danger Investigation and Management in Modern Cigarette Factory
Authors: Fang Wang , Xiaoyong Shi , Zheng Qiao 
Published: November 2019

Abstract
As an important part of the development strategy of cigarette enterprises, safety production management is an important guarantee to realize the operation target of cigarette factory and improve the economic benefit of enterprises, among which, hidden danger investigation and management are the most important means and methods. Especially when the industry is striving to achieve “Implementing the New Concept of Development, Go Up to a New Level of Cigarettes”, hidden danger investigation is not tolerated in the slightest carelessness. This paper expounds the improvement of enterprise safety management efficiency and the role of security hidden danger analysis and decision-making by realizing informatization of hidden danger investigation and management in cigarette enterprises. This paper also discusses the infrastructure of system construction, the principles and promotion strategy to be noted in the process of implementation.
Bayesian Network-based GF-City Metropolitan Zone Modelling: an Approach Based on Location Quotient Resource Impulse Response Principle
Authors: Ma Chaoping , You Yucong , Yi Luxia 
Published: November 2019

Abstract
Based on the evolution phenomenon and law of “location quotient”, this paper has studied the mapping relationship between image recognition of GF-City metropolitan area and the impulse response of local industrial resources. Based on the “location quotient” method, the level of local industry specialization in Foshan city was analysed, with the aid of VAR model. With the help of economic logic reasoning method, the VAR regression equation model improved design pattern analysis method was extracted in terms of the typical local industry semantics; a Bayesian network-based VAR model GF-City metropolitan area local industrial resources was constructed together with the impulse response network model. Based on the image recognition evaluation experiment of GF-City metropolitan area, the network combined Bayesian scoring function and search algorithm to carry out learning reasoning, and thus divided into local industrial grammar sub-network, image vocabulary sub-network and mapping relationship sub-network by modularization. According to the trend of node and conditional probability distribution, the image lexical structure and morphological organization characteristics were analysed, and the impulsive local industry resource impulse response knowledge rules were subsequently mined and characterized. Consequently, an example analysis proved the validity and applicability of the modelling method for the knowledge acquisition of the “location quotient” resource impulse response, so as to further analyse and perfect the rapid development of Foshan City with the drive of “GF-City metropolitan area” in the background of GHM Greater Bay Area.
Design and implementation of elderly assistant & custody system based on Kinect and Gizwits
Authors: Yan Ran , Zhang Haoyu 
Published: November 2019

Abstract
Since most of the traditional elderly assistant system cannot achieve remote control and send immediate notifications to their families when falling of the elderly occurs, a somatosensory interactive and remote controllable elderly assistant & custody system is designed and realized based on Kinect and Gizwits in this paper. Old people’s falling can be detected via the depth images and skeleton information captured by Kinect sensor and notified to their family members through web service. Remote control of the simulated smart home appliance through the mobile APP can be achieved via Data Points set in Gizwits cloud platform. Because of the remote control of the domestic appliance and accurate identification of falling-down action, the presented system can provide the elderly people with great convenience and ensure their living safety.
Application of Gait Recognition Technology in Badminton Action Analysis
Authors: Li Yunwei , Jiang Shiwei 
Published: November 2019

Abstract
In order to improve the quality of teaching, achieve better training results and achieve excellent results in athletics competitions, it is especially important to carry out the analysis of badminton routine teaching and athletic competitions. Gait recognition technology is identified by the individual’s unique biological characteristics. With the improvement of computer performance, under the background of the rapid development of big data and artificial intelligence, the video data of badminton is collected by deploying high-performance camera. Video image segmentation, preprocessing, feature extraction, get the badminton player’s three-dimensional gait characteristics data. Using the acquired gait data as a sample, a gait-based machine learning model is constructed, and the sample data is trained. Finally, identification information of badminton players is automatically identified, which facilitates the comparison and analysis of different athletes’ movement data.
Research on Readers’ Behavior of College Libraries Based on Data Mining Technology
Authors: Hu Jianfei , Tang Jinling , Zhang Bin 
Published: November 2019

Abstract
College libraries produce a large amount of book circulation data every day. In addition to recording readers’ personal information, these data are generally used for routine business statistics. Their potential use value is far from being fully tapped and utilized. A careful study of readers’ long-term borrowing history data reveals that there is a certain correlation between readers’ borrowing behavior and books, between different disciplines and between different types of readers and borrowing books. Digging out the correlation between these data is conducive to the rational allocation of resources and improving the utilization of resources. It can also improve the library’s service level. Based on the author’s learning and practical experience, this paper first analyzed the necessity of applying data mining technology to library and then discussed the basic techniques of data mining. The article proposed the basic steps of applying data mining to digital library systems and finally studied The application of data mining technology in the analysis of library readers’ borrowing behavior.