bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the comprehensive evaluation method of college students’ achievements based on multi-view RSR
Authors: Ao Xiqin , He Aixiang 
Published: August 2020

Abstract
In view of the problems and shortcomings of the current college students’ achievements evaluation methods, a multi-view rank sum ratio(RSR) comprehensive evaluation method of students’ achievements was proposed. The method integrated the two factors of curriculum importance and students’ learning ability when determining the weight. Then combined with the RSR ranking method, the comprehensive evaluation ranking of students’ achievements was carried out. This method overcomes the subjectivity of weight setting and maximally reflects the integrity of information. Finally, through the empirical analysis, the method was compared with the average score method and intellectual education evaluation method, and the effectiveness of the method was verified through the ranking results comparison.
Producer-consumer Model Based Thread Pool Design
Authors: Wang Liangzhou , Wang Chaobin 
Published: August 2020

Abstract
The concurrency of the server has a crucial impact on the efficiency of processing requests on the server side, so the thread pool technology has been widely applied to the server. Different thread pools play an important role in improving the performance of highly concurrent servers. This article first introduces socket technology, thread pools, etc., which are high-concurrency server development technologies in Linux systems, then proposes a thread pool model based on the producer consumer model, and gives key codes. Finally, the performance is compared through experiments . Experimental results show that lightweight servers can achieve higher concurrency by using this thread pool model.
Research on Stock Returns Forecast of the Four Major Banks Based on ARMA and GARCH Model
Authors: Hu Yuanwei , Tao Zheng , Xing Dongao , Pan Ziyi , Zhao Junyi , Chen Xiaoling 
Published: August 2020

Abstract
This paper uses the prediction method of time series analysis to fit and predict the stock daily logarithmic return series of the four major banks. The ARMA model and the GARCH model are constructed and compared empirically. The results show that the GARCH model is better than that of the ARMA model in the fitting effect. In the prediction effect, The ARMA model is the best, followed by the GARCH model.
Skew-normal median regression model with applications
Authors: Cao Xingyun , Wang Gege , Wu Liucang 
Published: August 2020

AbstractSkewed/asymmetrical data often appear in many research fields such as finance, economy, climate science, environmental science, engineering technology, social sciences and biomedicine. Little research has been carried out to establish median regression model to investigate the influence of some covariates on distributional characteristics. Since the median can capture the “medium” level of the skewed data, the main objective of this paper is to construct the median regression model for the analysis of skew-normal data. We develop an expectation-maximization (EM) algorithm facilitated by Newton-Raphson algorithm to estimate the regression coefficients and parameters. The proposed methods are evaluated by some Monte Carlo simulations and are illustrated by a real data analysis.
Analysis of Convertible Bond Investment Value
Authors: Liu Zhaoyang 
Published: August 2020

Abstract
During the vigorous development of convertible bonds in China, it has become a hot investment product recently. This paper introduces the investment methods and risks of convertible bonds to investors with various risk tolerance through the explanation of the background and important clauses. Convertible bonds, as a combination of creditor’s rights and options, can be said to be applicable to all kinds of investors at the same time. Investors with low risk tolerance can obtain fixed income regardless of market conditions under the condition that they have stable and low-risk coupon rate as guarantee. Investors with high risk tolerance can obtain returns with greater risks and greater returns through stock conversion under the same stable fixed income background. Under the protection of many important clauses (the specific clauses are as follows), the interests of various types of investors are stabilized. At the same time, this paper also puts forward several investment suggestions according to the risks of convertible bonds.
Population and Cultural Disasters Caused by Sea Level Rise Based on Regression Model
Authors: Wang Jiapan , Gao Yi , Lin Haoqi 
Published: August 2020

Abstract
With the worsening environment, more people become EDPs since their homeland become inhabitable. Leaving the place they once called home, their rights may not be guaranteed. Meanwhile, their unique culture are also facing the edge of extinction. To determine the scope of the issue, we discuss the number of people at risk and specify the cultural loss. When predicting EDP population, we start by using the regression model to predict the trend of sea level rise due to the greenhouse effect and find out by 2120, the world’s average sea level will probably rise by 60mm. Considering the effect of greenhouse gas makes this model more persuasive than if we only use sea level data to predict. Then, we build a spherical cap model to resemble to geographical features of tropical islands. It greatly simplifies the complexity of island topography and extends our prospective from a few islands to the whole world. With the help of the spherical cap model, on conservative estimate, the current number of EDP is about 67 million; by 2050, the potential EDPs will reach 130 million and over 400,000 square kilometers of land will be submerged. In the aspect of culture, with island residents becoming refugees, the potential lost of religious rituals, folk stories, traditional techniques, intangible arts and unique languages lead to the huge loss of cultural heritage.
Towards Student Learning Ability Estimation and Truth Discovery in Japanese Online Course
Authors: Han Lanling , Liu Yanwei , Shi Chunhui , Bi Yang , Yu Liang , Shen Hua 
Published: August 2020

Abstract
This paper focuses on an important task in online courses, which is to estimate student learning ability from students’ answering records. The challenge of this task is to automatically estimate the learning ability for students and infer the true answer for each question without any supervision. Most of the existing methods solve these challenges by designing an optimization objective function. However, these approaches ignore the characteristics of students from different groups. Intuitively, outstanding students always provide correct answers and should be assigned higher weights compared with ordinary students. Based on this intuition, this paper proposes a new optimization framework by dividing students into two groups: an authoritative group and an ordinary group. The losses of the objective are from both authoritative students and ordinary students. Through optimizing both losses simultaneously, the proposed model can automatically estimate learning ability for authoritative students and ordinary students and infer the right answer for each question. Two experiments conducted on two datasets show that the proposed model outperforms state-of-the-art baselines.
Research On Optimal Search Efficiency Of Rocket Wreckage Based On UAV
Authors: Zhang Wei , Yao Shengsheng , Wang Qiang , Zhong When an , Wang Yuchao 
Published: August 2020

Abstract
In order to improve the efficiency of UAV search for debris targets in the area of debris. The paper discusses the relationship between the flight altitude, photoelectric turret parameters, searching area and resolution of UAV. Then discusses the characteristics of rocket debris distribution based on historical debris distribution data.by building the model of UAV operating area and regularities of debris distribution,this paper calculate the probability of finding the debris targets in one flight with optimal searching method by Monte Carlo calculation method.this method has high practical value for using UAV to search rocket debris.
Analysis and design of intelligent environmental protection IOT system architecture based on GIS
Authors: Min Huang 
Published: August 2020

Abstract
With the third great change of the world’s information industry, IOT will open an information age of interconnection of all things. The environmental protection Internet of things combines the traditional environmental protection industry with the Internet of things technology, realizes the practice of environmental protection informatization, is conducive to the construction of an all-round environmental protection governance system, speeds up the process of China’s environmental protection informatization, and promotes the rapid transition from “digital environmental protection” to “intelligent environmental protection”. With the continuous progress of cloud computing, big data and other cutting-edge technologies, environmental protection Internet of things has begun to integrate these technologies to better meet the needs of the public. In this paper, through the analysis and research of the application example of environmental protection Internet of things, summarizes the overall architecture of intelligent Internet of things system based on GIS for environmental protection. The overall architecture of the intelligent Internet of things system can be divided into four levels: field equipment, transmission network, IOT equipment management platform, environmental protection big data analysis and application platform. Using the IOT system architecture to design the IOT system platform can solve the repeated construction of infrastructure and software application system in the field of environmental protection, improve the traditional environmental governance mode and meet the public’s right to know the environmental conditions. People can understand the real-time environmental information through mobile terminals or environmental protection cloud platform, and enterprises that cause pollution can use the network Anonymous reporting is carried out so that the public can participate in the national cause of ecological environment governance.
Design of a WeChat Mobile Learning Platform for Multi-modal Language Learning and its Application
Authors: Lei Qian-qian , Liu Hai-yang 
Published: August 2020

Abstract
To follow the increasingly popularity of MALL (Mobile Assisted Language Learning) in the mobile multi-media era, the study probes into the design of a multi-modal language mobile learning platform supported by WeChat. The study also practically applies the platform to an English course for mobile learning and analyses the learning results with the quasi experimental research method. The experiment shows that the platform can effectively improve learners’ language ability, especially listening, writing and speaking skills.
Research on Baidu Street View Road Crack Information Extraction Based on Deep Learning Method
Authors: Zhang Min , Liu Yang , Luo Shaohua , Gao Siyan 
Published: August 2020

Abstract
Rapid and effective identification and extraction of road cracks has always been a major difficulty in road detection and maintenance. This paper applies the Deeplabv3 + model to road crack extraction, and proposes a new joint identification method for road cracks based on open network data and open source convolutional neural network. Based on the semantic segmentation theory and Deeplabv3+ neural network, this method uses baidu street view map as the training data set. By adjusting the proportion weight of road cracks and background, the training network model can quickly and accurately identify road cracks. Experimental results show that this method has achieved a good effect on crack segmentation: Mean Intersection over Union(MIOU) of this method is more than 70%, and the processing speed is 1 second/sheet, which is better than FCN algorithm.The results of road crack information extraction are similar to those of manual interpretation, which indicates that this method is feasible for quality evaluation of municipal roads.
Empirical Research on Youth National Security Cognition Level Based on Cloud Model
Authors: Fan Jiangyan , Zhang Hongbing , Liu Ying 
Published: August 2020

Abstract
Focusing on the development level, existing problems and cultivation path of the overall national security concept of young people has become an urgent issue of the times. In order to evaluate the national security cognition level of young people, this paper constructs a systematic evaluation system and improves the existing evaluation methods. Based on fuzzy comprehensive evaluation, grey relational analysis and the TOPSIS, a combined evaluation model based on cloud model is constructed, which takes into account the fuzziness and randomness in the evaluation process. Through the analysis of the examples and the verification of the mean square error, this new evaluation method has obvious superiority over the traditional evaluation method. The results show that the current national security awareness of young people is relatively weak, and the overall level of awareness is at a moderately low level.
The Application of Geographical Analysis in Serial Crimes
Authors: Xin Wang , Xinshe Qi , Guo Li , GaoCuicui  , Na Wang , Ruiping Huang , Rong Liu 
Published: August 2020

Abstract
In this paper, we use bayes’ theorem to generate two mathematical models for a series of crimes. This series of crimes is a dynamic process, so we regard it as JTC model. In this model, there are some major factors, such as the individual’s vulnerability to crime, the attractiveness of the place of the crime and the utilization of the crime from the place of origin to the place of destination. We combine the bayesian theorem with the JTC model to obtain the mathematical model of geographical distribution. We made full use of the model to predict the location of the next perpetrator in the series.
Research on Electronic Product Storage Reliability Based on Similar Product Prediction
Authors: Cui Zenghui , Xuan Zhaolong , Li Tianpeng , Yang Qingxi 
Published: August 2020

Abstract
For the long-term storage of some electronic products, the life value of the electronic product is calculated in combination with the non-work failure rate model, and the life value is applied to the similar product prediction method to obtain information about the storage reliability of the electronic product . The calculation process of the non-work failure rate model and the prediction method of similar products is introduced, and the application examples are used to verify, reduce the error when using the entire system life information for estimation, and improve the accuracy of storage reliability.
Research on Tourism Question Answering System Based on Xi’an Tourism Knowledge Graph
Authors: Yang Lu , Cao Han , Hao Fei , Zhang WeiZhen , Ahmad Muhib 
Published: August 2020

Abstract
Question answering (QA) system provides a direct, efficient and accurate way for people to obtain information. At present, open domain QA systems such as Siri and Cortana are widely used in the general field, but they cannot meet the demand of some professional fields. This paper focuses on the background and needs of QA in the tourism field, researching the relevant technologies required for the implementation of QA system, and finally completes the construction of QA system based on the knowledge graph of tourism. The main research contents of this paper are as follows: 1.An algorithm to identify the tourism entities in questions is proposed according to the characteristics of the tourism entities. 2. Referring to the ideas of Liu et al., a convolutional neural network (CNN) model is introduced into attribute linking, but in order to improve the accuracy of attribute linking, we move the similarity calculation of questions and attributes from the outside of the model to the input layer of the model, and also introduce Attention mechanism. Integrate the technology of each module to design and implement a QA system for tourism. We experiment with the system on the constructed Xi’an tourism knowledge graph, and the results prove that the system we designed can answer the natural language questions raised by users about tourism.
Research and Application of High-Performance Data Storage and Transmission Technology in Microservice Environment
Authors: Li Kunying , Ding Yu , Shi Ying , Wang Liling , Zhen Zebing 
Published: August 2020

Abstract
With the development of the Internet, various types of application systems are emerging, which brings more and more server access, more and more content, and more and more strong interaction between users and the system. The new generation of microservice software development framework brings great pressure for data transmission and storage. In order to improve the stability of data storage and read and write speed. This paper proposes a cache service architecture designed by sentinel mode. Redis is used as the core intermediary layer of high-performance storage to solve the lightweight and high concurrent data, and multiple linear regression analysis is used to determine those data that need asynchronous transmission and heavyweight transmission with RabbitMQ message queue for transmission. Finally, it realizes the efficient storage, expansion and effective and timely information communication of data in the whole microservice environment.
A Financial Fraud Detection Model Based on Organizational Impression Management Strategy
Authors: Zhang Jie , Yao Jianrong , Wang Lu , Chen Yuangao , Pan Yanqin 
Published: August 2020

Abstract
Financial fraud misleads investors into making wrong decisions based on incorrect information, especially for listed companies’ financial statements fraud. It damages investors’ interests, disturbs the economic order, and creates a crisis of trust, which is extremely harmful. Therefore, it is of great significance to build an effective financial fraud detection model for listed companies. This study uses a sample of 126 Chinese listed companies from 2013 to 2017 to examine the relationship between two organizational impression management strategies (promotion strategy and defense strategy) and financial fraud using the integrated learning methods. This study innovatively analyzes financial fraud using social media data and annual reports’ readability data as non-financial features. The results show that companies implementing the defensive/protective strategy were more likely to commit financial fraud. In addition, the average number of tables in a company’s annual report can significantly help researchers to judge fraud.
Research on Classroom Attendance System Based on Face Recognition
Authors: Pu Jingyu , Zhang Liang , Zhang Jinqian , Xue Ziwei , Zhang Xixin , Yang Jie 
Published: August 2020

Abstract
Deep learning face recognition technology has become one of the most popular technologies. The explosive growth in the use of face recognition has brought a variety of practical needs. Face recognition can be applied to identity authentication, bank security, forensic investigation, face scanning payment, access control system and so on. Existing face recognition methods have achieved remarkable results. With the continuous development of deep learning technology, many depth methods show better accuracy than human recognition. Based on the in-depth study and discussion of the deep learning method, this paper applies the theory to practice, and designs and develops a set of face recognition system for classroom attendance.
Estimation Method of Blurred Parameters in Moving Blurred Image
Authors: Zhang Guanyang , Zheng Tianxiong 
Published: August 2020

Abstract
In order to improve the quality of image restoration and remove the blur caused by motion in the image, a blurred parameter recognition algorithm with point spread function is proposed. This algorithm combines the Fourier spectrum of the image with the edge detection based on phase consistency and identifies the blurred angle by determining the direction of the edge of the center bright stripe. Then bilinear interpolation is used to generate the sub-pixel image of the spectrum, calculate the distance between the dark bands, and estimate the blurred length. Experimental results show that, compared with the traditional algorithm, the proposed method can not only obtain higher precision of blurred angle and blurred length, but also have better stability, and can correctly detect blurred parameters of blurred images with different scales and contents.
Research on Weapon Equipment Purchase Performance Evaluation Based on Support Vector Machine
Authors: Li Xiaosong , Peng Xinran , Xiao Zhenhua 
Published: August 2020

Abstract
In this paper, we present an efficient performance evaluation method of weapon equipment purchase based on support vector machine. Firstly, the concept of weapon equipment purchase performance evaluation was explained and the existing problems of weapon equipment purchase performance evaluation were analysed. Then, a 12-dimension performance evaluation indicator system was constructed (these dimensions are: budget progress, cost-benefit ratio, expenditures reduction rate, supplier satisfaction, purchaser satisfaction, customer satisfaction, purchase cycle rationality, qualification rate, price rationality, competition, success rate, and policy completeness). And lastly, a weapon equipment purchase performance evaluation model based on support vector machine was established, and a case analysis was conducted. The result provides a reference for building the indicator system and model for weapon equipment purchase performance evaluation and the research conclusion can help complete and improve the evaluation method.
The framework study on mimic defense technology in power web service system
Authors: Cai Yuxiang , Pan Dan , Wang Yiting 
Published: August 2020

Abstract
Aimed at the features of the power grid web system for the State Grid Corporation of China (SGCC), the paper analyzes the confronting security risks. A mimic defense security protection system for the power grid web application has been designed by combining the features of network attack and introducing the mimic defense core technology. The defense framework with layered ideas and dynamic heterogeneous redundancy has implemented effective protection at multiple attack phase and expanded the defense range so as to provide the security protection capacity to the power grid web application.
Fall into the trap of phishing for fools—Based on behavioral analysis of smoking and drinking
Authors: Huang Zhanbing , Gao Fangyuan , Lu Yu 
Published: August 2020

Abstract
Behavioral Economics puts forward that the weakness of human decision-making is an important cause of the vulnerability of the poor. If the external environment of decision-making is bad, it is easy to fall into the trap of “phishing for fools” set by the economic subject, which causes economic loss or psychological burden and increases the risk of returning to poverty. This paper studies whether the low-income groups are more likely to fall into the trap of “phishing for fools” and make irrational decisions based on the fact that the excessive consumption of tobacco and alcohol is harmful to their health but the consumption is increasing year by year. Based on the data on the 2015 China Health and Retirement Longitudinal Study, this paper Constructs Logit model, linear regression model and ordered Probit model to empirically analyze the important factors influencing the smoking and drinking behavior of rural residents. The results showed that, under the control of individual characteristics and regional living habits, income level had a significant impact on low-income groups’ alcohol and tobacco consumption behavior.