bluuebunny/crossref_metadata_2025_split huggingface dataset:
A New Reversible Database Watermarking Approach with Ant Colony Optimization Algorithm
Authors: Lian Junyao 
Published: August 2020

Abstract
In many fields such as medicine, science, transportation, it is often necessary to maintain the real-time information, and the data in the centralized database that saves data in these fields is distributed to various clients. On the insecure public Internet, there are distributed databases stored in data centers. Sharing may create risks, such as unauthorized copies, changes to data, and distribution of data to unauthorized persons for reuse. Many database watermarking methods have been proposed to protect digital rights. In order to reduce watermark distortion and increase watermark capacity, people pay more and more attention to the optimization of watermark technology. This paper proposes a method of embedding differential expansion watermarking (DEW) based on ant colony algorithm (ACO) in relational database. This method uses a secure hash algorithm for grouping, increasing the privacy of watermark embedding. The ant colony algorithm performs the optimization operation, finds the best attribute columns for embedding the watermark in the subgroup, and finally uses the differential expansion technology to embed the watermark. Experimental results show that compared with similar works reported in the literature, the reversible watermarking method based on ant colony algorithm database proposed in this paper not only increases the watermarking capacity, but also improves the robustness against various types of attacks.
A Structural Equation Model Study on the Cognitive Factors of Irony Processing
Authors: Ran LI , Shide LI 
Published: August 2020

Abstract
Irony processing has always been a hot issue in experimental pragmatics. Existing studies have found out many cognitive factors contributing irony processing with unique paths and contribution rate of their own. Structural equation model can clearly demonstrate the exact path and contribution rate of each factor to irony processing, namely the need for cognition, empathy ability, sarcasm preference and working memory capacity. Three offline questionnaires on the need for cognition, empathy ability and sarcasm preference and two online tests of working memory capacity and irony processing have been conducted. Two hypotheses are verified through hierarchical linear modeling and structural equation modeling. Statistic results show that the four cognitive factors all exert positive effect on irony processing, with sarcasm preference exerting a direct effect while the need for cognition showing an indirect effect through the mediation of working memory capacity and empathy ability respectively, which is of great significance to the teaching of linguistics and rhetorics.
Study on Security Countermeasures of Cross-border E-Commerce Payment Risk
Authors: Lei Wang 
Published: August 2020

Abstract
China has now fully entered the era of Internet +, cross-border e-commerce has achieved stable development. If we want to promote the sustainable development of cross-border e-commerce, we must constantly improve and optimize the existing payment mode of cross-border e-commerce. This paper analyzes this, analyzes the payment risk of cross-border e-commerce, and puts forward targeted security countermeasures to lay a good foundation for the stable development of cross-border e-commerce.
The national economic growth rate has a clear downward trend, many businesses in the operation and development process, gradually looking for new channels to achieve business development and development. Cross-border e-commerce is in this context put forward a new business channel, its overall development speed is relatively fast. According to relevant statistics and survey results, China’s entire cross-border e-commerce transactions reached 6.7 trillion yuan in 2016, an increase of 22.2 percent over the same period last year. At the same time, imports of e-commerce transactions also reached 1.2 trillion yuan, a year-on-year growth rate of 33.3%. It can be seen from this that the overall development situation of cross-border e-commerce is generally good in the process of modern society development. But to achieve stable and sustainable development, we must ensure that there are corresponding supporting services to support, the most important point is cross-border payment. Only by ensuring the perfection and optimization of cross-border payment mode can we promote the stable and sustainable development of cross-border e-commerce.
ARIMA Based on Linear Interpolation for SO2 Monitoring Data’s Calibration
Authors: Xu Yan , Xu Enhua 
Published: August 2020

Abstract
Linear interpolation filling the missing values could be effectively solved the problem of data missing and improved the effect of the addictive model of ARIMA and multivariate linear regression. The addictive calibration model by ARIMA and Multiple linear regression for SO2 was reconstructed based on linear interpolation filling. The error analysis showed that the accuracy of SO2 was improved. The prediction effect was also improved by considering the interaction effect.
Controlling Shareholder’s Share Pledge, Earnings Management and Audit Decision—Based on Regression Method in Statistics
Authors: Zhao Minshu , Yuan Fangying 
Published: August 2020

Abstract
This article uses 2009-2019 Shanghai and Shenzhen A-share listed companies as a sample to study the impact of listed companies’ equity pledge behaviour on auditors’ decision-making. The empirical results show that if there is a pledge of large shareholder equity, the audit pricing will be higher than when it does not exist. At the same time, the greater the proportion of pledged equity is, the higher the audit pricing accordingly is. The study finds that the equity pledge behaviour would make auditors more likely to issue non-standard audit opinions. The state-owned nature has a positive regulating effect on the relationship between equity pledge and audit opinion. But it has a negative regulating effect on the relationship between equity pledge and audit pricing. In the study of the mechanism of action, it is found that the equity pledge affects the auditor’s decision-making by affecting the level of earnings management. The research in this article provides a reference for listed companies, auditor firms and regulatory authorities.
Data Diven Based Extraction and Recognition of Space Target’s Radar Micromotion Features
Authors: Guo Wenbo , Zhu Jubo , Wang Zelong , Liu Jiying , Yu Qi 
Published: August 2020

Abstract
The micromotion features of the space target is an important information source of radar target recognition. Multiple micromotions due to certain complex features can further characterize the specific targets and then improve the accuracy of the target recognition. With regard to the extraction and recognition of space target complex micromotion features, the data-driven method was used to conduct effective extraction and training recognition. On the one hand, the EMD method was used to effectively separate the complex micromotion components of the space target, and then the motion parameters of the target are estimated with high precision. On the other hand, we take the motion parameters of the target in various forms of micromotion as input and learn typical object movement characteristics by a machine learning algorithm, thus improve the precision and accuracy of target detection. The simulation results show that EMD method can accurately extract various motion parameters of space complex micromotion targets, and the neural network model can complete the target classification and recognition task with high accuracy.
Analysis of Relationship Between Hot News and Stock Market——Based on LDA Model and Event Study
Authors: Liu Chanyuan 
Published: August 2020

Abstract
This paper clustered the document of news released by major mainstream media outlets in November 2019 through LDA topic model and finds out the hot topic this month through the probability distributions between the topics and within the words. Then we backtracked on the topic and find the initial occurrence of the news, then categorized the news according to the status of the facts reported in the news. Then we carried on the research through using the constituent stock of concept stock in this model to report the event in a short-term event study, which finally find the breaking news could cause the related module in the short-term abnormal return while the continuing news would not do. It means that breaking news could allow media report to keep pace with market reactions, which the continuing news cannot promised. Investors will not be affected by continuing media reports on investment judgment as they have received relevant information in advance.
The Applicable Conditions of Incentive Contract for Knowledge Sharing in Industrial Construction Supply Chain Based on Evolutionary Game Theory
Authors: Qiao Shi , Wang Qiankun , Guo Zeng , Shen Chuxiong , Xu Wei 
Published: August 2020

AbstractKnowledge sharing is fundamental for improving knowledge system of industrial construction, and incentive contract is considered important means to promote knowledge sharing. This study aims to analyze the applicable conditions of incentive contract for knowledge sharing and provide guidance for core enterprises to formulate incentive contracts to promote knowledge sharing between member enterprises. Based on evolutionary game theory, an incentive model of knowledge sharing is developed. By solving the model, it is shown that the preconditions for applying incentive contract in industrial construction supply chain are that output capacity of knowledge sharing is higher than the cost, and incentive coefficient is more than the ratio of costs to outputs; and if knowledge sharing is implemented in industrial construction supply chain, the conditions should be satisfied, which are that the output capacity of knowledge sharing is higher than the sum of cost and risk, and the incentive intensity is higher than the ratio of the sum of cost and risk to the output capacity. These conclusions help us to formulate reasonable incentive mechanism.
Forecasting the Exchange Rate for USD to RMB using RNN and SVM
Authors: Liao Ruofan , Boonyakunakorn Petchaluck , Harnpornchai Napat , Sriboonchitta Songsak 
Published: August 2020

Abstract
One of the most important mechanisms supporting world trade is the exchange rate. Depreciation or appreciation of any currency, especially those main currencies such as US dollar, Pound sterling, Renminbi, could greatly affect international trade leading to greater impact to businesses and people’s wellbeing. Recently, researchers have been exploring the use of machine learning techniques to forecast time series data in the financial area. This paper will use machine learning techniques, namely Recurrent Neural Network (RNN), Support Vector Machine (SVM), and a traditional model, namely the ARIMA model which is selected as a benchmark. The result shows that RNN has the best performance compared with both SVM and ARIMA. This paper aims to forecast the exchange rate for USD to RMB, which could give the involved country, institution or people the foresight of the situation and prepare for risk.
Performance Analysis and Optimization of Spaceborne Multi-baseline InSAR Systems
Authors: Wang Yilin , Tan Xintong , Zhu Jubo , Liu Jiying 
Published: August 2020

Abstract
The spaceborne interferometric synthetic aperture radar (InSAR) technique has become a useful tool to obtain the surface elevation or deformation. The multi-baseline InSAR technique is capable of fusing data from multiple channels for interferometric processing and improving the accuracy of elevation estimation of the observed scenes. In this paper, we study the joint distribution to statistically characterize the interferometric phases of multi-baseline InSAR. The baseline parameters are sought based on the second-order moment of the interferometric phase joint probability density function (PDF). The study done in this thesis provides a basis for the design of parameters for multi-baseline interferometric systems.
Keyword-aware Route Search for Various User Requests
Authors: Wang Shuang , Zhang Qiaoqiao , Wang Yinzhe , Zheng Xueliang 
Published: August 2020

Abstract
With the popularity of smart mobile devices and social network, there are numerous location-based data with semantic information. This paper proposes a new route search algorithm which can learn from users’ historical record to meet different requests from various users. In this algorithm, point matching and candidate route generation should be done firstly. Secondly, the ranking scores of candidate routes are calculated. Also, the distance of routes is considered in this part. For users’ requests, it is calculated by users’ historical record including keyword record and distance record. Keyword record represents users’ requests for keywords, and it is comprised of queried record and selected record. Distance record represents users’ tolerance of route distance. Finally, route suggestions are given to users after calculation. Meanwhile, the record is updated after users’ selections. At the end of the paper, the experiments are conducted on real location-based datasets, and the result of the experiments shows that the proposed algorithm demonstrates good performance for different users’ requests.
An Improved Stream Cipher Algorithm Based on NFLSR
Authors: Feng Guanghui , Zhang Chunfu 
Published: August 2020

Abstract
To overcome defects of traditional stream cryptographic algorithms based on XOR operation, this paper proposes a new stream cipher algorithm with higher security and suitability for encrypting short information, which is based upon traversal operation and zipper-like random dynamic hash mapping, has the same time and space complexity as the traditional one. It generates the key stream through an application of Nonlinear Feedback Shift Register (NLFSR) and Bits Scrambling.
Financial Risk Assessment Based on Factor Analysis Model
Authors: Han Dan , Ren Xinchang 
Published: August 2020

Abstract
Based on factor analysis,this paper establishes a financial risk assessment model at the company level,and determines the influence degree of the solvency, operation ability, profitability, development ability and the ability to obtain cash flow on the model,and collects a large amount of relevant information and data, calculates the index weight. Finally, based on the analysis of the actual situation of each real estate company in China,the SPSS software is used for empirical analysis, and divides the risk levels of these 120 real estate companies.And then we put forward corresponding suggestions.
R&D Investment, Innovation Output and Enterprise Competitiveness: A Perspective of Employee Education
Authors: Wang Liangcheng , Wang Shengkun , Peng Tao 
Published: August 2020

Abstract
The study examines whether employee education plays a role in firm’s competitiveness, particularly in innovation activities. The innovation activity has two paths: technologic output and the transformation of scientific achievements. Using the sample of 174 listed companies of top 500 companies in china, we find that innovation output and enterprise competence have significant “inverted U” relationship; constrained by efficiency in achievement transformation path, R&D investment has significant negative effect on enterprise competence. Innovation output plays a completely mediating role in the relation between R&D investment and enterprise competence. Employee education has negative regulating effect on the first path, but the study has not found significant regulating effect on achievement transformation path.
The Game Analysis of Low Carbon Supply Chain Emission Reduction Considering Channel Power under the Concern of Fairness
Authors: Wang Hongqi , Li Jing , Qiu Xingbo 
Published: August 2020

Abstract
The emission reduction strategies of different channel power structures is studied under the fair, neutral and fair concerns of manufacturers, and compares the emission reduction levels, wholesale and retail prices, and the changes and differences in the profits of supply chain members under various circumstances. The research shows that the increase of emission reduction cost factor is not conducive to the improvement of emission reduction level, price and profit. The profit level of manufacturer under the manufacturer-led structure is not conducive to the manufacturer-led structure due to other structures, but is conducive to the improvement of the profit level of manufacturer under other structures. Manufacturer’s equity concern behaviour is beneficial to the improvement of manufacturer’s utility, in which the equity concern factor should be kept at a certain level under Nash vertical structure. Equity concerns and emission reduction strategies under decentralized decision-making are not conducive to the improvement of the overall supply chain effectiveness.
Research on the Influence of Internal Control on Enterprise Credit Risk
Authors: Wang Xiaohui , Yuan Fangying 
Published: August 2020

Abstract
This paper empirically tests the relationship between internal control and credit risk by taking a-share listed companies from 2014 to 2018 as samples. It is found that the quality of internal control is positively correlated with the credit risk. Further analysis shows that the five elements of internal control are significantly related to the size of credit risk, among which the internal environment, information and communication elements have a more significant impact on credit risk.
Exact analytic solutions of nonlinear equations
Authors: Zhong Baoming , Jiang Jun 
Published: August 2020

Abstract
The improved sub-equation method is used to obtain the exact analytical solution of (2 + 1) - dimensional BBM Equation. Some traveling wave solutions such as soliton solution and periodic wave solution of trigonometric function are obtained. Practice shows that the sub-equation method is widely used in nonlinear evolution equations.
Research on O3 Concentration Monitoring Data in Aircraft Cabin
Authors: Xu Enhua , Xu Yan 
Published: August 2020

Abstract
The paper explored the hourly and daily characteristics of O3 concentration monitoring data in aircraft cabin by micro air monitor, and proposed the additive model for O3 considering the influence of internal and external factors. Linear interpolation filling the missing values could effectively solve the problem of data missing and improved the effect of the addictive model of ARIMA and multiple regressions. The addictive calibration model by ARIMA and Multiple regressions for O3 was reconstructed based on linear interpolation filling. The error analysis showed that the accuracy of O3 was improved. The prediction effect was also improved by considering the interaction effect.
An Improved K-means Distributed Clustering Algorithm Based on Spark Parallel Computing Framework
Authors: Lu Xin , Lu Huanghuang , Yuan Jiao , Wang Xun 
Published: August 2020

Abstract
Traditional K-means distributed clustering algorithm has many problems in clustering big data, such as unstable clustering results, poor clustering results and low execution efficiency. In this paper, a density based initial clustering center selection method is proposed to improve the K-means distributed clustering algorithm. The algorithm uses the sample density, the distance between clusters and the cluster compact density, defines the product of the three as the difference weight density, and finds the sample point with the maximum difference weight density as the initial cluster center, so as to solve the problem of randomness and low quality of initial cluster center selection. At the same time, this paper uses spark parallel computing framework to implement the improved algorithm to further improve the processing performance of the algorithm in big data clustering.The experimental results show that the improved k-means distributed clustering algorithm based on spark parallel computing framework has higher execution efficiency, accuracy and good stability in big data clustering analysis.
Comparison of Research on Social Media in China and Foreign Countries Based on Bibliometric Analysis
Authors: Yunan Peng , Zongshui Wang , Yueyang Feng , shengqin Yang 
Published: August 2020

Abstract
This paper aims to compare the similarities and differences of Chinese and foreign research on social media. Cluster analysis, co-word analysis and social network analysis have been used to compare the research trends, content relevance and network structure of research on social media. (1) Similarities: Social media is a hot topic for scholars both in China and foreign countries; the development of social network technology leads to many new areas; social media research tends to study privacy, commerciality and service; hotspots of social media research in China and foreign countries both include social media, platform and social network. (2) Difference: Chinese research mainly focuses on big data, Wechat and Weibo, while foreign research mainly focuses on Facebook, Twitter and other kinds of social network media; Chinese research is clustered while foreign research is extensive; Chinese research pays more attention on macroscopic perspectives, such as media convergence, big data and libraries; foreign research tends to microcosmic perspectives, such as emotional analysis, crisis information dissemination, social media marketing.
Application of statistical analysis method in scale validity test
Authors: Wang Gang , Zhou Huaren , Yao Jia 
Published: August 2020

Abstract
In order to facilitate research and improve application efficiency, scales based on various functions were designed and developed. However, in the process of using the scale, people often ignore the validity of the scale for a specific purpose, resulting in the loss of significance of subsequent studies. This paper briefly introduces the application of correlation analysis and factor analysis in scale validity test, which is enlightening to improve people’s understanding of statistical analysis methods.
Value at Risk of the Exchange Rate in Southeast ASEAN-3 Based on Bayesian Markov-Switching GARCH Approach
Authors: Li Mingyang , Liao Ruofan , Sriboonchitta Songsak 
Published: August 2020

Abstract
This study analyzes Bayesian Markov-Switching of the single regime and the two regimes to forecast the risk of the exchange rate in three ASEAN countries, and various GARCH family and distribution are selected by DIC to find the best fitting models. This study will help governments to prevent the recurrence of events like the 1997 financial crisis. The study finds that Thailand has the best exchange rate stability and the lowest risk and is most suitable for foreign investors seeking stability.
Additive Calibration Model for NO2 Based on Linear Interpolation
Authors: Xu Yan , Xu Enhua 
Published: August 2020

Abstract
The paper proposed the additive model for NO2 considering the influence of internal and external factors. Linear interpolation filling the missing values could be effectively solved the problem of data missing and improved the effect of the addictive model of ARIMA and multivariate linear regression. The addictive calibration model by ARIMA and Multiple linear regression for NO2 was reconstructed based on linear interpolation filling. The error analysis showed that the accuracy of NO2 was improved. The prediction effect was also improved by considering the interaction effect.