bluuebunny/crossref_metadata_2025 huggingface dataset:
A crowdsourcing framework for retinal image semantic annotation and report documentation with deep learning enhancement
Authors: Shao Jiahui , Li Jin , Kong Weizheng , Liu Shifan , Wu Junyi , Wu Huiqun
Published: June 2021

To propose and implement a crowdsourcing framework for retinal image annotations to improve the annotation efficiency. In this study, open-source Bluelight was taken as backbone of the front end for online manual retinal image annotation for image semantic annotation and report documents, and based on that intelligent annotation and classification with deep learning (DL) was supplemented. For DL modules, we trained Mask-RCNN model to explicitly label the area of optic disc and macula. Furthermore, we trained Inception V3 model to classify diabetic retinopathy (DR) and normal retina. Then, we used Flask as the backend serving DL models. Finally, the implementation of interoperable annotation reports documentation and retrieval were conducted based on Lucene. The crowdsourcing framework was specially designed for professional doctors and computer researchers who have the ability to annotate. It efficiently and quickly completed the annotation of the retinal image and the macular area, and at the same time classified DR. Under this Browser/Server architecture, the tool achieved good cross-platform performance. In particular, the framework could provide annotation report documents to facilitate the optimization of subsequent DL models. Such crowdsourcing framework and reports documentation for retina semantic annotation could improve the effect of annotation and classification and worth further improvement and clinical validation.
Research on Intelligent Construction Algorithm of Subject Knowledge Thesaurus Based on Literature Resources
Authors: Wang Xiaoxia , Xu Xiaozhong , Zhang Jiarui , Zhu Yue , Fan Yuhang , Xu Pengjing
Published: June 2021

The implementation of National Science and Technology Innovation Strategy demands exponential growing in knowledge services on literature information institutions. It is the most important knowledge organization tool for Information Retrieval, which can be widely used for semantic citation, organization and retrieval of literature resources. This study aims to develop an innovative algorithm for constructing subject thesaurus based on massive literature resource data and mining academic neologisms, also the semantic relationship between academic neologisms and subject system. We firstly collect a dataset of literature corpus, corresponding work for data pre-processing carried out. Then using the FastText model to complete academic neologisms mining, we construct an automatic categorization model of academic neologisms based on the Bert and TextCNN algorithm. The algorithm proposed in this study is validated by 8.1 million multi-source and heterogeneous literature data in the field of marine disciplines. The result shows that the algorithm can effectively replace 90% of the manual annotation volume, mine a large number of high-quality marine neologisms and successfully build the marine science knowledge base with a pass rate of 82.6% reviewed by expert, which present high accuracy and certain engineering application prospects.
Network Security Monitoring Method Based on Deep Learning
Authors: Yu Tianxi , Yin Xiaoyao , Yao Menglin , Liu Tong
Published: June 2021

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With the rise and rapid development of mobile communication, big data and artificial intelligence technology, we are entering the era of mobile Internet. With the continuous intellectualization of network security and infrastructure, information technology has been widely used in the field of industrial control, making network security more and more open, which brings a new network security control system to the traditional relatively closed industrial control system. This paper mainly introduces the network security monitoring method based on deep learning. In this paper, the network security monitoring method based on deep learning is studied, and the network security monitoring planning is designed by using image analysis, and the feasibility of detection model and deep learning is analyzed reasonably. A network security monitoring method based on deep learning is designed. Through data collection, feature extraction and neural network model training of network security power consumption information, non-invasive network security monitoring is realized. This method can detect network security information attacks that cannot be found at the network level, and improve the security performance of network security. The experimental results show that the network security monitoring method for deep learning increases the network security efficiency by 24%. The limitations of the research on network security monitoring method for deep learning and the methods and paths to provide good network security monitoring planning for image analysis application are analyzed, discussed and summarized, so as to enrich the academic research results.
Training framework based on multi model competition for deep reinforcement learning
Authors: Lin Yixian
Published: June 2021

In this paper, we propose a simple, effective and universal deep reinforcement learning training framework, inspired by A3C algorithm and genetic algorithm. The framework uses multi-process technology to realize multiple model competition and optimal evolution to optimize the deep neural network during the training process. The experimental results show that the proposed training framework can improve the training effect of reinforcement learning algorithms to a certain extent.
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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.
Performance evaluation of man-portable devices based on the cloud center of gravity
Authors: WeiShi Peng , Wang Wu , Chen Li , Qing Li , Ying Li
Published: June 2021

In order to accurately assess the performance of man-portable devices, a method of evaluating the performance of man-portable devices based on the cloud center of gravity evaluation method is proposed. Firstly, a performance evaluation index system was constructed by analyzing the factors affecting the performance of man-portable devices. Then, using the cloud center of gravity judgment method, a man-portable device performance evaluation model is established and the weighted deviation is applied to determine the evaluation results. Finally, using examples, we verify the feasibility and effectiveness of the method. The research work provides ideas and references for scientific assessment of the performance of man-portable equipment, and further provides a theoretical basis for the modification and development of this type of equipment.
Study on Internal Friction of Dislocation Density in Bake-Hardening Steel
Authors: Xiaolong Jin , Feiru Zeng , Rongsheng Sun , Rendong Liu , Yan Li , Shunda Cai , Liwei Song
Published: June 2021

This study investigates internal friction of dislocation density in bake-hardening steel. The experiment was conducted as follows: pre-deformation being set at 2%, 5% and 10% with the baking set at 170°C×20min. The curve of internal friction and the configuration of transmissivity were also observed. It can be concluded that with the increase of the pre-deformation value, the Snoek peak of the experimental steel decreased. Moreover, both of the SKK peak and the dislocation density grew at first and then dropped. It is noted that while the pre-deformation was set at 5%, its SKK value and the dislocation density reached their respective peak value, whereas both decreased while the pre-deformation at 2% and 10%. This study investigates the changing mechanisms of dislocation density in bake-hardening steel in relation to different degree of pre-deformation.
Research on the Motivation of Construction Enterprises Accepting BIM
Authors: Ziye Chen , Shengyue Hao
Published: June 2021

BIM applications are often accompanied by a series of organizational changes. The resistance of employees to changes is an important obstacle that affects BIM applications. Top manager’s function is to lead the change and promote the active participation of the employees in change, which can promote the successful implementation of BIM. And engineering construction information level will be improved accordingly. This article uses questionnaire survey method and statistical analysis method to explore the influence mechanism of construction enterprise’s senior management on employees’ active acceptance of BIM behavior, and provides useful experience for BIM implementation in construction engineering enterprises.
Study on the implementation of reinforced concrete target in PELE with hood
Authors: Jun HE , Wei-xia Wang , Zhong-hua DU
Published: June 2021

In order to analyze the influence of the material and shape of the hood of the medium-caliber PELE warhead on the damage effect of the reinforced concrete wall with PELE projectile, the three-dimensional nonlinear dynamic finite element program LS-DYNA was used to numerically simulate the penetration of the PELE projectile with the hood of different shapes and materials into the 0.25 thick thin reinforced concrete wall target at various velocities. The results show that under the same conditions, the hollow cone shaped phenolic resin hood can achieve better damage effect of reinforced concrete wall. Chinese map classification number: TP391.9 Document identification code: A
Study on the law of ground subsidence caused by shield construction in composite stratum
Authors: Erbin Liang , zhikang Wang , Jun Wang , Chunxin Zhao
Published: June 2021

In this paper, based on the actual working conditions of the shield tunnel of Jinan R3 line through the composite stratum, the engineering monitoring work was carried out. Combined with the GTS/NX finite element calculation software, the numerical simulation of shield construction in the composite stratum was carried out, and the law of ground subsidence caused by shield construction in the composite stratum was obtained, which can provide experience for similar projects, to prevent the damage caused by excessive surface subsidence above the composite strata.
Bridge anomaly data identification method based on statistical feature mixture and data augmentation through forwarding difference
Authors: Qiu Yang , Jing Liang , Li Sheng
Published: June 2021

Identifying abnormal data in the structural health monitoring system is of vital importance for correctly evaluating the structural service status. For the monitored data of a long-span cable-stayed bridge, this paper proposed a method to identify abnormal data, primarily including data augmentation through forwarding difference, and statistical feature hybrid. The average prediction results of the test set showed that the proposed method can significantly improve the classification accuracy of anomaly data compared to directly training the original samples. Besides, the comparison results of the confusion matrix illustrated that the prediction results based on classifiers of random forest and decision tree were more robust, and using the former as the classifier can gain better recognition performance.
Research on Deep Convolutional Neural Network in Damage Identification of Truss Structure
Authors: Gao Yiting , Yang Xiaolin
Published: June 2021

Aiming at the problem of damage identification inside the truss, through the convolutional neural network, after a large amount of data simulation, the deep learning convolutional neural network can effectively identify the internal damage of the truss and accurately determine the damage location as well as the damage recognition and effective prediction of other large roof trusses. First, we import the existing data into the convolutional neural network for identification, and calculate the damage identification process belonging to the truss. Then, we import another part of the data to verify the practicability and accuracy of the convolutional neural network, and obtain a series of data streams.
Research and Analysis on hydration heat effect of mass concrete for main tower cap of long-span self anchored suspension bridge
Authors: Luo Fajiang , Guo Kun , Li Peng , Wang Zhaobing , Li Jianning , Li Hualong , Dai Zizhou , Zhang Qinxiong , Luo Guolong , Liu Gang , Li Lizhong
Published: June 2021

The self anchored suspension bridge on Jiancai North Road in Xi’an city is a typical cable structure. According to the force transmission characteristics of the cable, the main tower bearing platform is planned to adopt the construction method of laying embedded parts in the bottom layer and pouring the upper layer at one time, which is very different from the traditional layered and phased pouring of the bearing platform. In this paper, the finite element analysis software is used to carry out the fine modeling analysis of the foundation cap and its foundation temperature diffusion area, and the actual simulation of temperature and stress is carried out, and the “temperature stress asynchronous” effect caused by the bottom layer embedded parts and the upper layer pouring construction is studied; by analyzing the asynchronous difference of stress and temperature peak, the transfer law of temperature core area and the temperature field change caused by surface temperature control effect, the construction and monitoring measurement scheme is optimized.
Study on Passenger Flow Assignment Method of Urban Rail Transit Based on Improved Logit Model
Authors: Liu Jiekang
Published: June 2021

With the advantages of small pollution, punctuality, safety and large capacity, urban rail transportation provides good ideas for solving China’s urban transportation problems and gradually becomes an indispensable part of China’s urban public transportation system. According to the current development of urban rail transportation, the era of networked operation has arrived, and the connectivity between different stations in the metro network and the mobility of operation and management have greatly increased. And for passengers, considering the convenience of seamless transfers, the complexity of the line network structure, and the rapid feedback of real-time passenger flow information on the line, it will cause the passengers’ travel behavior to be highly random. Different passengers are choosing the route selection scheme to reach the target station will also make the spatial and temporal distribution within the rail transit network more diverse and complicated. This paper adopts the method of analyzing the behavior of passenger travel route selection under the established urban rail transit network to establish a generalized cost function and Logit model, and contributes to the planning, design and operation management of urban rail transit.
Design and Implementation of a New Automatic Charging System for Metal Round Tubes
Authors: Yuankai Yang , Yihang Peng , Zhiqiang Liu , Yingran Xie
Published: June 2021

This paper took the automatic charging process of metal round tubes as the research object. A traditional manual charging method was researched and an automatic charging system was designed in this paper. The system improved the existing enterprise processing mode significantly and the overall production efficiency of metal round tubes. This article introduced the composition of the automatic charging system for metal round tubes, and further analyzed the structural design features and operation principles of each component; in order to realize the automatic production of the charging system, a complete set of automatic control system was designed in the paper, enabling the orderly connection between the round tube cutting and edge chamfering processing procedures. The automatic charging design was used to replace the original cut round tube manually transported to the chamfering process and then manually load to the chamfering slot, thereby reducing the cost of enterprise labor, improving productivity and ensuring production safety.
Research on metro safety factors assessment based on comprehensive fuzzy algorithm
Authors: Liu Fanghua , Li Jianbiao , Zhang Bo , Zhang Shuxiang , Zheng Xuanrong , Chen Qingrui , Cheng Weikang , LV Gao
Published: June 2021

Shield crossing loess stratum will encounter many engineering problems such as excessive local soil deformation and ground collapse crater. Based on the phenomenon and characteristics of soil deformation caused by large-diameter shield crossing loess strata, this paper summarizes the soil deformation curve, analyzes the causes of loess reaction and ground deformation, and summarizes the main causes and laws caused by shield crossing loess strata. And the fuzzy mathematical method is used to analyze the main influencing factors and provide theoretical support for the subsequent numerical simulation objectives.
Cost Analysis of Multimodal Transport on Refrigerated Container
Authors: Meng Xiangru , Sun Jianmeng , Wang Haining
Published: June 2021

Refrigerated container multimodal transport is a long-distance interprovincial transportation, which effectively ensures the quality of agricultural products. The application of refrigerated containers and other means of transportation in the long - distance transportation of perishable agricultural products can reduce the cost of multimodal transport of agricultural products and improve the logistics efficiency. Therefore, it is of practical significance to study the multimodal transport cost analysis of refrigerated containers for perishable agricultural products. The article classifies the applicable goods in refrigerated containers and refrigerated containers; Erishable agricultural products have short shelf life and high damage rate. Refrigerated transportation tools have the particularity; In the cold chain logistics environment, in addition to considering the transportation cost, transit cost and time penalty cost of normal temperature multimodal transport, we should also consider the loss cost of perishable agricultural products in transit and the energy loss cost of refrigerated container refrigeration in transit.
Separation of non-metallic inclusions from high strength low alloy steel by electromagnetic stirring
Authors: Li Pengchao , Liu Daiwei , Pan Zheru , Zhang Peipei , Zhang Guifang
Published: June 2021

Non-metallic inclusions are the impurities that solidified during steel continuous casting. The compositions, sizes and shapes of inclusions significantly affect the steels’ mechanical properties such as ductility, formability and toughness. This paper mainly focuses on the observation and characterization of non-metallic inclusions in high strength low alloy steels, and especially is devoted to the homogenization of molten steel within the copper mold of continuous casters, as the primary purpose of this project is to discover the optimum operation parameters for electro-magnetic stirrers surrounding the copper mold. In this paper, non-metallic inclusions in high strength low alloy steel were observed and characterized, and separation of non-metallic inclusions from high strength low alloy steel by electromagnetic stirring was specifically studied. The nonmetallic inclusions in the billet can be greatly reduced when the electromagnetic stirring parameters of the mold are 300 A current and 3 Hz EMS frequency.
Research on online sag monitoring of transmission lines based on barometric pressure
Authors: Gong Xing , Wang Zhiming , Xu Wenping , Li Hangfeng , Wang Ke , Guo Jian
Published: June 2021

Transmission line is an important part of power system, and sag is an important parameter to evaluate the running state of transmission line. Because of the complex system and the high power consumption of online monitoring application used nowdays, this paper proposes an online sag monitoring system based on high precision barometer and relative height measurement method. Firstly, precision barometer will be installed in the middle of line to calculate the relative height of measuring points. Secondly, the span of space distribution can be calculatd which leads to complete the sag calculation. All the research above has passed the test.
Automatic Testing Design for Thermal Performance of Domestic Solar Water Heating Systems Based on PLC
Authors: Haiqin Yu
Published: June 2021

This paper mainly introduces the method of using PLC to realize the automatic test for the thermal performance of the domestic solar water heating systems, including 4 functional modules as automatic water temperature control, automatic water supply control, automatic circulation control, and automatic data collection control. Through verification, it can meet the test requirements of the standard GB/T18708-2002 “Test Methods for Thermal Performance of Domestic Solar Water Heating Systems”.
Floc Morphological analysis of macromolecule heavy metal flocculant CSAX
Authors: Li Xizohong , Hao Xuekui
Published: June 2021

The purpose of the flocculation operation is not only to remove the substance causing turbidity, but also to give the causing particles with the ability to be trapped in subsequent operations. This paper discusses the process of generating the floc, sedimentation characteristics, separation effect and so on, when the macromolecule heavy metal flocculant CSAX used in water treatment, especially for heavy metal ions and turbidity of coexisting system. The research is the popularization and application of this kind of flocculant that expand the types of multifunctional flocculant, decreases the number of the water treatment unit, which provides a certain reference value.
Development Trend and Prospect of New Energy in Tibet under the Background of Carbon Neutrality
Authors: Sun Yaxun , Wang Ze , Du Yangfan , Wang Yuanhao , Wang Shifeng
Published: June 2021

In view of the severe situation of global warming, China puts forward the carbon emission reduction target of “achieving carbon peak by 2030 and carbon neutrality by 2060”. Among all production activities, the energy sector emits the most carbon dioxide of nearly 90%, followed by the industrial sector of more than 10%. Therefore, the focus of carbon emission reduction is to reduce carbon emissions in the energy sector. Tibet possesses unique natural conditions and geographical environment, which is rich in renewable energy and water energy resources. There is a huge space for the development of renewable and clean energy in Tibet. In order to provide sufficient energy for the Tibetan people and achieve the goal of carbon neutrality, Tibet needs to vigorously develop clean energy in the next 40 years. First of all, it is necessary to formulate a systematic energy development plan for the next 40 years, and formulate different energy development plans according to the natural conditions of different regions, so as to put the energy development plan in place. Tibet can not only achieve the goal of carbon neutrality on time, but also contribute to the power transmission from the West to the East.
Accuracy analysis of current sensor based on magnetic field
Authors: Xin Mingyong , Xu Changbao , Meng Lingwen , Zhang Li , Tian Bing , Liu Zhong
Published: June 2021

Current is the most important parameter in power system, and its accurate measurement is the basis of system operation. With the research of new current measurement technology based on magnetic field, such as Hall effect and giant magnetoresistance, the current can be measured without contact with the conduct. However, due to the different wire diameters and the deviation of wire position, it is impossible to measure the multi-range current through the sensor with a single structure in practical use. In this paper, the error analysis of current technology based on magnetic field is studied. First, the measurement model is analyzed, and the measured wire current and magnetic field measuring point model is established. Through simulation, the influence of wire diameter and position deviation on the measurement accuracy is tested, which supports the design of current sensor based on magnetic field.
Signal timing optimization of shifted left-turn intersections
Authors: Li Zhichao , Liu Hong
Published: June 2021

A signal timing optimization method based on shifted left turn lane intersections is proposed to increase the efficiency of shifted left turn lane junctions. In previous studies, vehicle delays were often the only concern but vehicle exhaust emissions were ignored, which could easily aggravate environmental pollution. A multi-objective optimization model was developed in this paper for intersection signal timing from a vehicle and environmental perspective, using vehicle delay, capacity and exhaust emissions as indicators. A modified particle swarm algorithm was used to resolve the impact of a shifted left turn lane on vehicles at a selected junction in Shanghai. The proposed scheme can reduce vehicle delay by 24.58%, increase traffic capacity by 17.09% and reduce tail gas emission by 34.68% in peak period compared with before improvement. In low peak period, the delay, exhaust emission and traffic capacity are reduced by 49.04%, 41.68% and 17.09% compared with those before improvement. Using this optimization scheme can improve vehicle delay to a certain extent, improve vehicle traffic capacity and reduce pollution caused by exhaust emission to the environment. It also verifies the validity of the model and provides some theoretical basis for setting the signal timing for shifted left-turn lane intersections.