bluuebunny/crossref_metadata_2025_split huggingface dataset:
AAR-Unet: Blood vessels segmentation in ultra-wide-angle fundus images
Authors: Guo Xuedong , Xu Xiangcong , Wang Luquan , Liu Mingdi , Zeng Yaguang , Xiong Ke , Xiong Honglian 
Published: June 2021

Abstract
The structural information of blood vessels in ultra-wide-angle fundus images has important guiding significance for diagnosing ophthalmic diseases. Besides, efficient and correct segmentation of ultra-wide-angle fundus vascular images has become an urgent clinical need. However, manual diagnosis is a time-consuming and laborious work. Because of the limitation of primary medical resources, the situation of missed diagnosis and misdiagnosis would probably appear in n the diagnosis of artificial experience. In this paper, we proposed an automatic vascular segmentation algorithm based on attention gate based atrous residual (AAR) Unet combined with Top-Hat transform vascular enhancement. In AAR-Unet, we integrated atrous convolution into Res-Unet to expand the receptive field and improve the correlation between objects. To improve the segmentation effect of small blood vessels under low contrast, the attention gate module is introduced. The experimental results show the overall accuracy, sensitivity, specificity and DSC of the proposed algorithm are 0.988, 0.890, 0.993 and 0.875 respectively. The results indicate the algorithm can segment the blood vessels of ultra-wide-angle fundus images accurately.
Web service recommendation based on event ontology
Authors: Lv Hang , Pan Junjun , Wu Jinliang , Ren Haiyang 
Published: June 2021

Abstract
Web service recommendation is an important means to help users quickly discover and select services. Service recommendation combined with situational information is one of the development trends of Web services in the future. This paper proposes a Web service recommendation method based on event ontology, which abstracts Web service requirements into service event classes, according to the historical service records of the target users, Web service recommendations combined with service event ontology and content similarity calculation are recommended, and event class elements and hierarchical models in service event ontology are used as reference, calculate the service similarity and generate the fusion recommendation result according to the weight; Then, based on the current situation status of the user, the user’s current situation is located to a node on the event ontology situation model, the predictive recommendation of services is based on the semantic relationship between event classes in the event scenario model. Finally, the service with the highest similarity among the two parts of service recommendation is recommended to users. The experimental results show that this method can better improve the accuracy and diversity of service recommendation.
Boosting the Transferability of Adversarial Examples with Translation Transformation
Authors: Li Zheming , Zhang Hengwei , Liu Xiaohu , Wang Jindong 
Published: June 2021

Abstract
Although the adversarial examples have achieved an incredible white-box attack rate, they tend to show poor transferability in black-box attacks. Date augmentation is considered to be an effective means of enhancing the adversarial examples transferability. To this end, based on translation transformation we propose a new method to generate more mobile adversarial examples to attack the advanced defense model. By optimizing the original image, the input diversity is improved and the transferability of the adversarial examples generated by further training is enhanced. This method can also be combined with the attack method based on gradient, and the new method can make the attack success rate higher. Experiments on ImageNet data sets show that the proposed method is superior to gradient based methods such as MI-FGSM in black box attack, while maintaining a high success rate of white box attack. We hope that our proposed method of attack can serve as a benchmark for assessing the robustness of networks to opponents and the effectiveness of the different methods of defence.
Research on the Migration Law of Hornet Based on Machine Learning
Authors: Li Yunkai 
Published: June 2021

Abstract
Bumblebees prey on European honeybees, invade and destroy their nests, severely disrupting the local ecological balance and economic stability. In order to study the specific impact of the bumblebee, this paper establishes a gray Gaussian prediction verification model based on machine learning methods, which is used to predict the flight direction of the wasp through gray correlation analysis, and the Gaussian process regression model is used to determine the flight range; Through the discussion of negative ID, the Yolo model is used for feature extraction, the resnet101 model is used for classification prediction, and then a more summarized dimension is selected to find the corresponding bee species.
Migration knowledge graph framework and its application
Authors: Pu Tongzheng , Huang Ming , Yang Jingjing 
Published: June 2021

Abstract
Comprehensive knowledge of migration involves many fields, such as demographic, economic, social, and political. However, the results of migration theme knowledge retrieval and query are often the knowledge of a single domain, lacking of direct association between different fields. A spatiotemporal migration knowledge graph framework based on migration datasets and Baidu Encyclopedia is presented, and the validity and accuracy of the model are verified by an experiment implemented on the data of 2000. Visualization and Neo4j graph database technologies are used to migration knowledge graph framework which is perfectly adequate for both human beings and machine processing such as graph mining and knowledge reasoning. The migration knowledge graph can quickly and accurately obtain the comprehensive knowledge of migration, significantly improve the ability of human being to apply and analyze the knowledge and data of migration, which has wide theoretical and practical value in the field of migration.
Keyword extraction method for machine reading comprehension based on natural language processing
Authors: Li Ruiheng , Zhang Xuan , Li Chengdong , Zheng Zhongju , Zhou Zihang , Geng Yuyin 
Published: June 2021

Abstract
The traditional keyword extraction method has the problem that the accuracy of identification and extraction decreases when the amount of data is increasing. This paper introduces natural language processing technology and designs a keyword extraction method for machine reading comprehension. In this process, considering that the information in the text of machine reading comprehension may come from the web page, we can refer to the NLP system of natural language algorithm. Firstly, analyze the content of a single document, then analyze the short string level, and finally organize the preprocessing of natural language text information, so as to achieve the preprocessing of machine reading and comprehension of Chinese text. At the same time, the SKEA keyword extraction algorithm system is designed to merge text words with the same meaning, locate the location information of document resources, and identify the annotated words in the resource base. After the annotation processing is completed, the annotation information is extracted. In addition, a comparative experiment is presented to prove the effectiveness of the proposed method compared with the traditional method.
Dual-mode Integrity Measurement System Based on Virtualized TEE
Authors: Jialiang Duan , Guoming Cai , Kaiyong Xu 
Published: June 2021

Abstract
The Trusted Execution Environment (TEE) is mainly used to protect sensitive information and ensure information security. TEE has been used in the system structure of various mobile devices. With the development of TEE, attack methods against TEE gradually appear. The virtualized TEE architecture proposed by existing research can solve some security problems caused by TEE architecture, but there are still some deficiencies. To enhance the TEE architecture, a virtualized TEE-based kernel integrity measurement scheme is proposed, and identity-based and neural network-based integrity measurements are used in different scenarios. The experimental results show that the designed dual-mode integrity measurement system can effectively detect attacks against different kernel objects and has little impact on system performance, thus achieving security enhancements for virtualized TEE.
Research on the Growth Point of Sports Consumption Based on Extended Linear Expenditure System -- Taking Jiangxi Province as an Example
Authors: Zhang Lipeng , Zhang Li 
Published: June 2021

Abstract
Sports activities play an important role in strengthening physique and improving the quality of life, which makes the proportion of sports consumption in China’s national consumption increase year by year, but the current supply of sports service products in China has not increased with the demand of mass consumption, some sports consumers’ needs are not met, and personalized sports service resources are especially short, which is not conducive to the healthy development of sports economy. Therefore, by analyzing the current sports consumption of mass fitness in Jiangxi Province, this paper introduces an extended linear expenditure system to analyze the new sports consumption growth points in Jiangxi Province from the perspective of consumer demand, and puts forward relevant sports consumption development suggestions in a targeted manner to increase the options for the public to carry out sports consumption and provide reference for promoting the diversification of sports consumption in Jiangxi Province.
Institutional Investors’ shareholding, CEO Tenure and the Speed of Enterprise Internationalization—Based on Regression Method in Statistics
Authors: Guo Rong , Wang Qiwei 
Published: June 2021

Abstract
Based on the sample of Chinese A-share listed companies in Shanghai and Shenzhen from 2012 to 2019, this paper focuses on the effect of institutional shareholding on the speed of enterprise internationalization. The empirical results show that the overall institutional investor ownership has a significant negative impact on the rapid international expansion, and the classified independent institutional investors and non-independent institutional investors have a significant inhibitory effect on the speed of corporate internationalization, and with the extension of the term of CEO, the negative relationship between institutional investor shareholding and the speed of enterprise internationalization has been alleviated. The research of this paper can be used as a reference for optimizing the investor structure of the capital market and improving the strategic decision-making efficiency of enterprise management.
Construction of security protection system based on online security monitoring technology of acquisition terminal
Authors: Shu ZhiMeng , Liu YongGuang , Wang HuiNan , Sun ChaoLiang , Lv Lin 
Published: June 2021

Abstract
With the completion of the construction goal of “full coverage, full collection and full cost control” of the power consumption information acquisition system, the power consumption field of power grid has been fully transferred into the operation and maintenance period. In the process of security detection and sampling of the acquisition terminal, it is found that there are security risks in the field operation of the acquisition terminal, lack of online security protection processing mechanism for network risks and their own vulnerabilities, and there is a risk of being vulnerable to large-scale malicious attacks. Therefore, it is urgent to study the online security monitoring technology of the acquisition terminal and strengthen the construction of online security protection system of the acquisition terminal Design. In this paper, through the construction of the security protection system based on the online security monitoring technology of the acquisition terminal, the online security monitoring system of the acquisition terminal is built to collect and analyze the security data information of the acquisition terminal in real time, and monitor the acquisition terminal uniformly, so as to realize the security situation awareness of the acquisition terminal and the region; through the security analysis, the security risks in the operation environment of the acquisition terminal are found in time, so as to realize the security Threat identification and attack traceability, improve the level of terminal security operation protection. Through the construction of the security protection system based on the online security monitoring technology of the acquisition terminal, it can effectively support the security monitoring of all kinds of terminal equipment in the power Internet of things.
Research on generic technology identification issues in non-ferrous metal industry
Authors: Fengyan Li , Xiangmin Zhang , Jing Zhang 
Published: June 2021

Abstract
Non-ferrous metals are the basic strategic materials for national industrial manufacturing. Exploring the development process of the industry and identifying generic technologies in the field play a vital role in breaking through the technical bottleneck of the non-ferrous metal industry and achieving transformation and upgrading. This paper selects Derwent patent database as the data source, uses CiteSpace software to construct a visual map of the retrieved non-ferrous metal industry patent data, identifies and analyzes the generic technologies and hot fields of the non-ferrous metal industry, and puts forward reasonable suggestions for the future development of the industry.
An empirical analysis of Expanding Effective Investment to Promote Industrial Development——Take Hubei Province as an example
Authors: Yang YanJun 
Published: June 2021

Abstract
The industry is the main body of the economy and the leading force of regional economic development. To analyze the influence mechanism of consumption, investment, and export on the industry of Hubei Province, this paper uses the monthly data of Hubei Province from 2011 to 2019 to establish a VAR model. The results show that investment has the most significant impact on the industrial development of Hubei Province. It is necessary to expand effective investment according to the industrial base of Hubei Province, to promote industrial transformation and achieve high-quality development.
Scale-free Characteristics and Link Prediction in Complex Railway Network
Authors: Zengping Zhang , Yu Han , Kuanyun Gao , Bo Li , Yinghao Zhou 
Published: June 2021

Abstract
The link-prediction of complex networks is a new method of network structure mining, which is different from the traditional methods based on machine learning. It reveals those existing relations and predicts possible ones, by using the similarity index of network structure. This paper studied the topology of the railway and link-prediction. The railway dataset was firstly obtained by sampling and pre-processing. Its degree obeys the power-law distribution with the scale-free characteristics. Then, we give some predictions for railway networks. These tests reached good prediction accuracy. The research result has demonstrated that the topological structure of network could be better choice to the link-prediction of a real complex networks.
Computing Personality Trait Based on Multi-source
Authors: Chuanqin Zheng 
Published: June 2021

Abstract
Personality computing is a hot research field recently, which mainly uses the individual’s traces on social platforms to understand, predict and analyze their behaviors, to make a certain accurate judgment of user personality types. The application of personality traits is of great significance to intelligent medical, personalized service customization, and other fields. The current personality computing research is mainly based on social media, the data source is limited, can not reflect the real situation. This paper collects college volunteers’ network access logs, the data is more comprehensive and complex, not limited to only the traces on social media. According to these network access logs, the calculation results show that the personality traits of users in different social media are not consistent, and the access preferences of network resources are not exactly the same as the personality traits reflected by social media. Therefore, it is more accurate to integrate multi-source network information to calculate an individual personality than a single data source.
Extraction of Elements of Protest Based on BERT Model and TextTeaser improved algorithm
Authors: Zhang Yueguo , Dong Lili , Li Shenghong 
Published: June 2021

Abstract
A protest is a document that the procuratorial organ exercises the power of legal supervision and submits it to the judicial organ. Element extraction is the basis for tasks such as case card filling, document correction, cause analysis, and case recommendation. At present, there are no effective tools and methods for extracting the elements of criminal protests. Most of them are manually marked, with low accuracy and low efficiency. In response to this problem, this paper is to propose a method to extract the elements of the criminal protest by sub-category, based on Bert model, using natural language processing technology. The experiments are demonstrated to illustrate the effectiveness of the proposed method.
Based on CiteSpace Knowledge GraphAnalysis of the Status Quo of Research on Expenditure Forecast
Authors: Tang Haoning , Liang Xin 
Published: June 2021

Abstract
This paper uses CiteSpace software to conduct text mining and visual analysis of 744 academic papers related to funding forecasts in the CNKI database in the past 20 years, sort out the literature time, journals, authors, and institutions of funding forecasts, and use keywords co-occurrence and subject terms Clustering and other methods reveal the current research status and evolutionary laws of funding forecasting, hoping to provide reference and reference for the selection of other types of funding forecasting methods.
A cross-domain authorization access control model based on security label attribute
Authors: Wang Yuntao 
Published: June 2021

Abstract
This paper proposes a minimum diffusion and cross-domain security authorization strategy based on security label, which solves the security problems of minimum visible range and cross-domain authorization in access control mechanism. The strategy makes full use of security label attributes, introduces multi-level constraint mechanism in access control, and makes the scope of knowledge controllable in cross-domain authorization. Through the experimental validation of different security domain scenarios, compared with the traditional access control mechanism, the diffusion speed of sensitive files in the access control based on security label attributes is significantly reduced. If the number of security labels is set as Nlabel
, and each label has Nscale
values, the file diffusion speed of the network is only

1

Π

N

s
c
a
l
e

times that of the linear diffusion speed.
Moving object detection in dynamic background
Authors: Ding Xiaoyun 
Published: June 2021

Abstract
The application of RPCA model in moving object detection can accurately extract the moving foreground, but the effect of the model is not ideal under complex dynamic background conditions. Based on this, this paper proposes an improved RPCA model based on rank–1 regulation and 3D-TV. The improved model uses regulation term to describe the low rank of video background, 3D-TV to constrain the spatiotemporal continuity of moving objects, and F-norm to eliminate the dynamic interference in video background. The experimental results show that the improved model proposed in this paper can effectively deal with the complex dynamic background and obtain a complete foreground object.
Liability insurance premium income forecast based on improved GM (1,1) - A case of Shandong Province
Authors: Yang Xiaojun , Zhao Mingqing 
Published: June 2021

Abstract
Liability insurance premium income is not only an important source of insurance company profits, but also an important aspect used to evaluate the development level of the insurance industry. Therefore, it has important practical significance for accurate prediction. This paper uses improved GM (1,1) to predict the premium income of liability insurance in Shandong Province, and the results show that the fitting effect is very good.
Guide for the establishment of the decomposition model of the probability density function based on the hyphal extension rate of fungi
Authors: Shi Shangyang , Guo Senxin , Zhang Yaotian 
Published: June 2021

Abstract
The main purpose of this paper is to provide readers with a guide to mathematical modeling. The idea of establishing a model is roughly as follows: extract the probability factors of the research object, analyze the research object itself, observe the changes of the research object, and observe the effects of environmental changes on the research object. In this article, taking the 2021 American Mathematical Competition in Modeling (MCM) as an example, using the proposed modeling guidelines, a mathematical model was established to describe the decomposition of woody fiber by fungi, and the independent variable was set to hyphal extension rate, temperature conditions, climate conditions, etc. Set the dependent variable to decomposition rate, and fit a series of logarithmic expression and exponential expression according to the data provided by references[1][2]. Establish a community evolution model to realize the dynamic evolution of the interaction between different types of fungi, fungi with a higher competitive ranking will have a higher hyphal extension rate than the original without the interaction. As a result, fungi with a higher competitive ranking is in a dominant position in the colony, and fungi with a lower competitive ranking is in a subordinate or inferior position in the colony. In order to use the relative advantages and disadvantages of various fungi in different environments to predict the exact composition of fungi in the colony, considering the influence of initial climatic conditions on the evolution of the community, and bring about relative changes in the competitive ranking of different types of fungi. The model example in this article reflects the correctness of the modeling guidelines.
Financial Performance Evaluation of Listed Companies Based on Improved Catastrophe Progression Method——Take the express industry as an example
Authors: Li Bingwei , Liu Baoping , Tang Haoning , Gao Kun 
Published: June 2021

Abstract
As China’s express delivery industry plays an increasingly important role in the national economy, evaluating its financial performance has become an unavoidable issue for operators and investors. This paper constructs a financial performance evaluation index system for listed companies, and uses the entropy weight-Catastrophe progression method to evaluate the financial performance of listed companies in china’s express delivery industry from 2017 to 2020, and makes a brief analysis of the evaluation results. Studies have shown that it is feasible to evaluate the financial performance of listed companies through the improved catastrophe progression method. The evaluation results can reflect the weakness in the development of companies and provide references for operation and investment decisions.