bluuebunny/crossref_metadata_2025_split huggingface dataset:
A BOW-Based Sentence Embedding Method for Chinese Event Identification
Authors: Gao Lizheng , Zhou Gang , Luo Junyong 
Published: April 2020

Abstract
Event extraction is an important branch of information extraction. It involves two challenging issues: event identification and argument identification. Most approaches of event identification are trigger-based, which suffer a lot from sample imbalance, word ambiguity, low scalability, etc. To solve these problems, we attempt to explore sentence-based event identification, whose main issue is sentence representation. With the success of word embedding, it has attracted much attention to generate semantic embeddings of sentences. In this paper, we propose a simple BOW-based sentence embedding method to represent event sentences for Chinese event identification. We compute embeddings on the dependency tree and map different relations to simple arithmetic operations. We evaluate our method with a dataset of Chinese event identification and compare the result with other BOW-based methods. The results show that our approach significantly outperforms other BOW-based methods.
Application of D2D Communication System Based on Android and JXTA on the Internet of Vehicles
Authors: Lunyuan Cao 
Published: April 2020

Abstract
This paper introduces the development prospect of the Internet of vehicles. By combining D2D technology with cellular networks, the problem of the increasingly scarce spectrum resources of traditional cellular networks is solved. D2D Communication System based on Android and JXTA is realized by designing network topology and network settings, peer discovery and instant messaging modules and applied on the Internet of Vehicles to achieve an intelligent transportation system with high security and reliability.
Study on the knowledge dissemination efficiency and influence factors of electronic technology journals community based on the DEA-Tobit method
Authors: Peng Huiling , Qu Hui , Li Ping 
Published: April 2020

Abstract
[Research objective] The construction of the journal community as the key content of the development of electronic technology, is of great practical significance to research knowledge production and dissemination efficiency of the journal community.[Research methods and data sources] This paper, by using DEA-Tobit model and in combination with the Chinese S&T Journal Citation Reports (Expanded Edition), focuses on the evaluation of the knowledge dissemination efficiency of electronic technology journal communities from the perspective of knowledge exchange, and demonstrates and studies the factors that affect the knowledge dissemination efficiency of journal communities.[Conclusion](1) Generally speaking, there is still 31% optimization space for the knowledge dissemination performance of the electronic technology journal community, and the low scale efficiency value has a large impact on it. (2) Journals such as Electronic Products, Light & Lighting, Journal of University of Electronic Science and Technology of China, and Journal of Chinese Electron Microscopy Society have relatively high knowledge transmission efficiency, and the value of technical efficiency, pure technical efficiency, and scale efficiency of those journals are equal to 1. (3) The academic quality of journal papers is the key variable to influence the electronic technical journal community knowledge dissemination efficiency; the duration of the journal and the economic status of the journal location are also positive factors affecting the effectiveness of journal knowledge dissemination; factors such as the degree of journal cooperation, the internationalization level of journals, and the institutional distribution of journal articles have a limited impact on the effectiveness of knowledge dissemination in the journal community. In addition, in view of the lower time-sensitive of the electronic technology literature, the overall influence of the novelty of the literature used by authors, which is measured by “cited half-life”, on the performance of knowledge exchange is quite different from expectations.
Image Processing of Large-Scale Pollution on Water
Authors: Zhao Qianqian 
Published: April 2020

Abstract
In order to improve the monitoring of water surface environment, the image processing of large-scale water pollution is proposed. First, UAV was used to take aerial photos of the area to be cleaned on the water, and the obtained image was preprocessed with saturation enhancement, etc. Then the image was segmented into image segmentation or edge detection to distinguish the foreground from the background. This experiment used three widely used segmentation methods to process the selected aerial image. The three methods are: threshold segmentation, region-based segmentation and morphological gradient detection.
Research on Intelligent Signal Timing Model Optimization Based on Deep Learning Thought
Authors: Zhang Xin , Song Yinghua , Liu Dan 
Published: April 2020

Abstract
Aiming at the problem of traffic congestion and traffic jams at intersections, this paper proposes an optimized control system for automatic timing of traffic lights.Based on big data and deep learning ideas, the number of vehicles parked at intersections in a signal cycle and the signal cycle time are used to calculate the number of vehicles parked at intersections in the next cycle. According to the number of vehicles parked, the green time of the signal light is obtained, and an optimization model of the signal light is established.The model aims to maximize the traffic capacity at the intersection and minimize the delay time.Finally, the model is simulated by python, and the obtained data is compared with the data under the control of traditional signal lights.
Detection of Man-made objects along the High-speed Railway Based on High Resolution Remote Sensing Images
Authors: Feng Boqing , Wang Yaoyao , Gao Fan , Tan Qulin , Jiang Lili , Hu Jiping , Wang Yingjie 
Published: April 2020

Abstract
The condition along the high-speed railway is very important for the safe operation. In the paper, man-made objects along the high-speed railway are used as detecting targets. The paper analyses the existing forms of hidden dangers which are caused by man-made objects along the high-speed railway and what harms they could bring to operation of the high-speed railway. The method of detecting man-made objects along the high-speed railway based on high resolution remote sensing images is studied using remote sensing image classification. According to the established method which is suitable for detecting man-made objects along the high-speed railway, firstly detecting and extracting man-made objects along the high-speed railway, and improving classification accuracy by GIS vector data. Then, using the method to detect man-made objects along the Xuzhou section of Beijing-Shanghai high-speed railway based on GF-3. The results show that there is hidden danger of the plastic house, which proves the effectiveness and practical significance of the method.
Determination of Maintenance Time of Radar Seeker Based on ABC Method
Authors: Jiong Yue , Weimin Lv 
Published: April 2020

Abstract
According to the health state grade classification standard of seeker and the corresponding performance state description, the health state grade corresponding to the predicted value of performance index parameters of transmitter and antenna servo mechanism is evaluated. As a result, the health status grade of the seeker system is obtained. In order to determine the maintenance time of the seeker more accurately, the comprehensive performance index of the seeker in the stage of “deterioration” is divided by the application of ABC analysis rule. Finally, the best maintenance time of seeker is determined by calculation.
Design of Real Time Communication Software Based on ReWorks Operating System
Authors: Zhang Jianwei , Tian Xingke , Man Yi 
Published: April 2020

Abstract
This paper briefly introduces the functions and characteristics of the embedded operating system ReWorks. Aiming at the design requirement of real-time communication software, the task mechanism of ReWorks operating system is analyzed, the design process of real-time communication software is given, and the software development and debugging process using ReDe integrated environment under ReWorks environment is introduced. The data transmission and communication of the vehicle information system are realized.
Business Steward: Definition, Mode and Influence
Authors: Qi Kailong 
Published: April 2020

Abstract
This thesis firstly puts forward the concept and definition of business steward, who is professional service staff to help employers and customers manage business. Similar to the “intelligent +” transformation of traditional retail, catering and manufacturing industries and so on by AI technology, AI technology will eventually transform the steward industry in business management - traditional business staff. Business stewards serve employers and customers to complete business stewardship business such as business management, wealth appreciation, asset management, happy life and so on mainly through artificial intelligence, intelligent machine, search engine, cloud computing, o2o, big data evaluation, LBS, social network, mobile Internet and other comprehensive tools. From the perspective of practical activities of business steward mode innovation, its main modes are classified into four types: independent professional business steward company, business steward in subdivided industries, generalized business steward crowdsourcing organization, and intelligent AI business steward. The industry influence of business steward consists in sharing outsourcing service-oriented business services, excellent loyal and stable business stewards, and business stewards of “buyer type interest representatives”, which can solve the problem of skill training for managers, reduce the cost of employment management and tax, and meet the business requirements of public business management. In the future, the intelligent business steward will make huge impact on the business economy of China and the world in terms of business management, improving work efficiency and promoting the development of science, technology and culture.
Research on Feature Extraction Method of Geometric Image Recognition
Authors: Chen Na , Zheng Gang , Wu Chunqiong 
Published: April 2020

Abstract
The existing image recognition feature extraction technology cannot effectively transmit the image information if the extracted features are not complete, sufficient and inaccurate. It will have an impact on image processing, such as reducing the accuracy and efficiency of subsequent image recognition and image tracking. At the same time, the existing technology for image processing destroys the topological structure between image pixels, and the process is complicated in the calculation of high-dimensional data space. Therefore, this paper proposes a method and steps of feature extraction for collective image recognition, and makes relevant supplementary explanation and analysis.
Facial Landmark Detection Experiment
Authors: Su Yanzhe 
Published: April 2020

Abstract
Facial landmark detection or face alignment is an important problem in computer vision. Different types of methods have been proposed to target this problem, with their advantages and disadvan- tages. This paper classified the past methods into three categories, briefly compared them, then attempted to reimplementing part of a recent work. Experiments were done with a common, current dataset to compare the method with other methods.
Research on Image Recognition of Power Inspection Robot Based on Improved YOLOv3 Model
Authors: Xiong Wei , Yang Sha , Zhang Zhao , Chen Liang , Huang Shuxin 
Published: April 2020

Abstract
YOLO series models are widely used in power inspections, but they are prone to miss inspections for small targets and diverse targets. In response to this defect, an improved network model of YOLOv3-g suitable for GPU cores and an improved network model of YOLOv3 mini suitable for CPU cores are proposed. By reducing the number of small and medium-scale targets, the number of convolution kernels is increased, and the small and medium-scale targets are increased. The intensity of feature extraction reduces the amount of network calculations and better solves the problem of inaccurate detection and recognition of small targets in electric robot scenes.
Research on VisualInspection System of Waterproof Breathable Membrane Based on HALCON
Authors: Peng Qingfeng , Yang Shifeng 
Published: April 2020

Abstract
Aiming at the needs for high-efficiency, high-precision and stable detection of waterproof and breathable membranes, a waterproof and breathable membrane quality detection system with burrs, filaments, spots and uniformity as the detection indicatorshas been designed based on HALCON. The upper computer system is developed based on C#and the lower computer is developed based on PLC. The upper computer system analyzes and processes the images collected by the industrial camera, which is the core of the entire detection system. The lower computer communicates with the upper computer through industrial Ethernet, and sends motion instructions to the servo system through the Ethernet bus. Tests show that the system can perform high-efficiency, high-precision and stable detection of the quality of waterproof and breathable membranes.
Tactile Guidance System for the Blind Based on Digital Image Processing
Authors: Tang Wenyuan 
Published: April 2020

Abstract
Science and technology are making earth-shaking changes in our daily lives, and as a special group, blind people should enjoy the fruits of technological progress. Since the traditional blind guiding device can only give rough information about the distance and orientation of the obstacle, the user obtains too little information, and there is still too much unknown fear during the traveling. The guiding effect is not great. Therefore, after considering the physical and psychological needs of the blind, this paper designs a system of tactile perception imaging instead of vision. The system collects obstacle information through the camera, performs digital image processing, and then displays it on the tactile imager through special encoding processing. Through the sense of touch, the blind person processes the tactile information into image information through the brain, thereby obtaining the size, shape and position information of the obstacle, and then forming a more concrete understanding of the obstacle, so that the blind can perfectly avoid the obstacle.
Research Of The Blind Equalization Technology In The Non-Cooperative Communication Receiving System
Authors: Yan Ming , Wu Caifeng , Liu Yang , Xie Zhiyuan , Zhu Qinghao 
Published: April 2020

Abstract
Convergence rate and steady-state mean square error are the main parameters to evaluate the performance of blind equalization algorithm. In order to improve the blind equalization performance of non-cooperative communication reception under multipath fading channel, a modified super-exponential iterative blind equalization algorithm is adopted, which converges faster than the traditional constant modulus algorithm and achieves the same steady-state mean square error. Aiming at the MPSK non-cooperative signal with unknown modulation order, a two-mode blind equalization method based on fractional interval is proposed. The method makes full use of the robustness and fast convergence of the super-exponential iterative algorithm, and combines the low steady-state mean square error of the recursive least squares algorithm. The effectiveness of the method is proved by simulation and experiment.
Automatic scoring method of English composition based on language depth perception
Authors: Dan Tang , Yu Sun 
Published: April 2020

Abstract
AutomatedEssaySystem (AES) refers to a system for evaluating and rating compositions by using techniques in the fields of statistics, natural language processing and linguistics. The selection of composition features is one of the key issues in the study of automatic composition scoring. This paper abstracts the features of language sense from the depth of language perception, which makes up for the shortcomings of the automatic scoring system of shallow features (such as vocabulary difficulty, grammar, etc.). The features of language sense are mainly the similarity of keywords extracted from the first and last paragraphs of a composition by rake algorithm, the similarity of texts calculated by cosine similarity to the context content of a composition and the similarity detection of composition language materials by automata. Finally, from the three aspects of correlation, error and overall accuracy, it analyzes whether the deep-seated language features improved the scoring ability of AES system. The experimental results show that the added depth perception features enhance the language ability of automatic scoring and are closer to manual scoring.
Topological Data Analysis of Customer Relationship
Authors: Lu Yutao 
Published: April 2020

Abstract
In the modern society, if manufacturers want to make huge profits, they must not only control the production cost, but also classify customers and increase the loyalty of key customers. Thus, existing data analysis methods, represented by Time Series Analysis and Topological Data Analysis (TDA), have emerged at this point of time to explore customer relationships. Based on the latest research of time series analysis and TDA, application of analysis is explored in practice. The relationship between topology and datasets will be given by displaying the process of TDA. In the end, there will be a discussion about the efficiency of different approaches, the improvement of tools in this paper and their extended application. This work is intended to provide a brief introduction of TDA and other methods to help readers understand concepts easily and provide suggestions for future studies.
Privacy preservation with unequal data exchange strategy in participatory sensing*
Authors: Zhang Tianqi , Zhang Rong , Wang Jin 
Published: April 2020

Abstract
In participatory sensing, participants contribute sensing data to task center. However, the task center is not always trustworthy. It may try to profile the participants by data mining, which is a great threat to the privacy of participants. To solve this problem, three collaborative data exchange strategies are studied. Participants exchange sensing data before upload to the task center. The mixed data protect the participants’ privacy from data mining by the task center. The simulations show that the unequal data exchange strategy is more efficient than the full exchange strategy because it considers both the tradeoff between privacy preservation and the cost of data exchange.
Strengthening the construction of digital course, Promoting the innovation of teaching mode in University
Authors: Cheng Yunli , Wang Zheng qin 
Published: April 2020

Abstract
Digital resources are the necessary conditions for the implementation of educational information. Nan Yang Polytechnic insists on the development of digital curriculum resources and teaching reform, To highlight the characteristics of professional courses and skills oriented, Based on the digital campus network platform, Taking the learning activities as the main line, the development of a “dynamic” network course, The digital curriculum resources with good interactive and sustainable development have been constructed, and the representative teaching model. It can effectively improve the quality and effect of classroom teaching, and accelerate the process of digital teaching.
Meteor Shower Scale Prediction Using Random Forest Classification
Authors: Peng Bozhen , Sun Dingyi , Cui Qifei , Yin Yip Chun 
Published: April 2020

Abstract
With the development of science and technology, the aerospace industry also has been developing rapidly. At the same time, meteor showers from the universe become one of the severest threats to the increasing numbers of aero crafts in the outer space. With the advancement of computer science, we have been able to employ big data to analyze and predifct the scale of meteor showers, so as to reduce the possibility of meteor objects hitting spacecraft and provide a strong guarantee for aerospace security. The Random Forest Classification, a kind of machine learning algorithm, is used to analyze meteor showers that once visited the earth to explore the principle of meteoroid cycles and predict the scale of meteor showers that will enter the Earth. The confusion matrix and accuracy rate will be used to evaluate the performance of the machine learning model.
Research on Supply Chain Performance Management based on Big Data Application
Authors: Yao Cenglin 
Published: April 2020

Abstract
With the coming of the era of big data and the strengthening of competition among enterprises under the condition of marketization, enterprises must make full use of big data technology to improve their supply chain performance management level, so as to establish an advantageous position in the competition. This paper first introduces the theory of supply chain performance management based on big data application, then analyzes the impact of big data application on supply chain performance, and finally gives the strategies to improve the supply chain performance of enterprises.
Research on satellite urban transportation and land spatial planning in big data environment
Authors: Nan Nan , Song Li 
Published: April 2020

Abstract
With the continuous development of computer technology, big data application has become a hot research area. Big data has the ability of high-speed and accurate data analysis, which provides great help for many research work. With the help of big data technology, we can provide data reference for the spatial planning of satellite urban traffic. Satellite towns are different from ordinary cities. Satellite town refers to the small city around the big city, which is a small town that provides residence for workers in the big city who are unable to buy houses in the big city. Compared with the general large and medium-sized cities, the space planning of satellite towns is relatively simple. Therefore, the complexity of traffic structure and function area planning of satellite towns is not as complex as that of big cities. Firstly, this paper analysis the characteristics of satellite urban traffic under big data. Then, this paper analysis the spatial planning of big data land. Finally, this paper puts forward the satellite town planning mode based on the people-oriented core concept under the big data.
Analysis and Research on the Combination of Virtual Reality Technology (VR) and College Sports Training
Authors: Qingtao Zhang 
Published: April 2020

Abstract
The combination of virtual reality technology (VR) and college sports training makes college sports training continue to innovate with the help of emerging technologies and receive good results. Virtual reality technology combines traditional technology advantages in various fields with sensor technology, three-dimensional animation technology, and network communication technology. Through research and innovation, through virtual reality technology, computer communication technology is used to achieve an effective fit between sports training and virtual reality technology. It is used to improve the technical level and training quality of college athletes, give full play to their technological advantages, and contribute to the reserve of reserve talents for competitive sports in China.