bluuebunny/crossref_metadata_2025_split huggingface dataset:
Segmentation of Workpiece Rust Based on Cross Maximum
Authors: Yang Xu , Lu Xiaotao , Kong Qiming , Song Yuantao 
Published: March 2021

Abstract
Rust is an oxide produced by the reaction of metal and alloy surface with oxygen. It is a defect that greatly affects the quality of the workpiece. In order to solve the problem of rust segmentation more conveniently, a threshold segmentation algorithm based on cross extremum method is proposed, which determines the threshold of rust segmentation adaptively combining the global and local features of the image. Firstly, as the threshold is hard to determine in the small and medium area rust segmentation of a workpiece, the super red method and saturation method are combined to pre-process the image. Secondly, because the gray value of the rust spot area is the maximum value of the image neighborhood, the cross-extremum method is used to extract the characteristic points of the rust spot. Finally, the threshold of rust segmentation is determined according to the proposed feature points. Experiments show that the horizontal and vertical extremum method can complement each other to extract the feature points of rust as fully as possible. And the algorithm can extract some feature points of rust better for different workpieces in varying backgrounds. The detection accuracy of the algorithm reaches 96.3%, which has important signification of application.
Research on prediction of online purchasing behavior based on hybrid model
Authors: Chen Xi , Ding Shichou , Xiang Yongsheng , Liu Lin 
Published: March 2021

Abstract
The research on the potential purchase behavior of users can help merchants develop better marketing strategies. At present, many research methods of online purchasing behavior are based on simple rule prediction, and the prediction results are not satisfactory. We design a hybrid model of Gradient Boosting Decision Tree and logistic regression to accurately predict the purchase behavior of users, which combines the association characteristics between users and commodities. Firstly, clustering algorithm and association rules are used to solve the problem of data imbalance and mine more potential related features. This scheme not only improves the processing efficiency of large data, but also solves the problem of user cold start. Secondly, we construct a scalable tree enhancement system (XGBoost) to train the initial feature set, which is a strong classifier composed of several weak classifiers. A new training set combines the new features with the original features through feature reconstruction, and a hybrid machine learning system is constructed by logistic regression (LR) model. Finally, the LR model is trained by the new training set. Compared with the existing schemes, the integrated decision tree model can train more sample sets with less resources. The experimental results show that the accuracy of the hybrid model is better than single model, and the F1_score is higher.
Analysis of COVID-19 Based on Several Machine Learning Techniques
Authors: Sun Tonglin 
Published: March 2021

Abstract
COVID-19 sweeps the world with high infection and high death rates. It is essential for researchers to find an effective model to predict the trend of epidemic. With the good performances of several traditional models in predicting and analyzing previous epidemics, we compare several popular machine learning methods, including multi polynomial regression, logistic growth model and Long Short-Term Memory (LSTM) in epidemic prediction. We use least squares method for feature selection to determine the most relevant features and we also scale the data according to different experiment environments. We measure the accuracy using Mean Squared Error (MSE) and R2. We conclude that the LSTM model is the most effective model among all the competitors with the highest R2 (R2 = 0.97). We find that LSTM model is the most effective model among all the competitors. Our study gives a good example of feature and model selection for epidemic prediction and attempts to make a significant contribution to the government and hospital to supply the public resources and provide drugs to handle the incoming issues.
Transformer optimization system design based on deep learning and evolutionary algorithm
Authors: He Hongjia , Liu Peipei , Zhou Huili , Jiang Yanli 
Published: March 2021

Abstract
A single shallow learning algorithm cannot fit the characteristics of high-voltage reactors well. Aiming at the above problems, this paper uses the error back propagation neural network and the particle swarm algorithm optimized by adaptive inertia weight to optimize the combined prediction model B for data training, verification and testing are carried out to achieve the purpose of effectively reducing the manufacturing cost of high-voltage reactors. Through experimental verification, the maximum error between the predicted value and the true value is 2.9%, and the minimum error is 0.05%. This provides certain technical support and inspiration for future devices such as optimizing high-voltage reactors.
Design of Kinematic Mechanism of Wheel-legged Robot
Authors: Ying Lei 
Published: March 2021

Abstract
Mobile robots can be roughly categorized in wheeled type, tracked-skidded type, legged type, trunked type, etc. Among them, the wheeled mobile robot can move on the flat road, but with poor performance when crossing an obstacle; the legged type mobile robot has a slow motion speed and poor bearing capacity; the tracked-skidded mobile robot has a large weight; while the trunked mobile robot has limited use occasions. In order to overcome these shortcomings, this paper studies the wheel-legged structure and distributes the performance of various commonly used structures. On the other hand, by analyzing the newly emerged structure, the impact of the organization’s own shortcomings on performance is hoped to be reduced. By comparing the structure and distribution of different leg configurations, the advantages of the locomotion performance of each type of wheel-legged mobile robot and the development trend of the wheel-legged mobile robot in the future are analyzed.
A Systematic Review of Binary Program Vulnerabilities Feature Extraction and Discovery Strategy Generation Methods
Authors: Zhang Bo , Xi Zesheng 
Published: March 2021

Abstract
At present, the cyber security situation has turned increasingly serious across the globe. The cyberspace has become the fifth domain of various nations following the four domains of land, sea, sky and outer space. It is gradually obvious for the cyber attacks to collectivize and nationalize. Under this circumstance, as the first line of defense in maintaining cyber security defense, the control on the vulnerabilities is extremely significant. In consideration of the problem of low discovering efficiency in current vulnerability fuzzy testing discovery methods, this paper intends to explore the binary program vulnerability feature extraction and vulnerability discovery guiding strategy generation methods. Then, the extraction of the program control flow and data flow information and slicing operation are obtained according to program logic. Depending on a potential assessment model of binary program vulnerabilities based on the main hierarchy analysis method, the paper achieves a reasonable assessment of the potential of vulnerabilities in different slices of the program. Finally, in accordance with the evaluation results, a generation method for the vulnerability discovery path is proposed to improve the efficiency of binary program vulnerability discovery.
Research on Means of Compliance for Airborne COTS Software
Authors: Hua Hui , Luo Jialu , Chu Yi , Xu Bing 
Published: March 2021

Abstract
The cost of airborne software development is very high, and the functions implemented by airborne software are becoming more and more complex. Using the COTS software has become a trend in case of saving cost. The COTS software brings conveniency, meanwhile raise problems when showing compliance to airworthiness requirements. This paper researches the design assurance method of COTS software, summaries the certification risks and propose a feasibility analysis of using COTS software, thus providing reference for airborne systems designs.
Architecting commercial aircraft with a Domain Specific Language extended from SysML
Authors: Li Haomin , Zhan Chao , Wu Haomin , Yu Miao , Dai Jie , Zou Wenbin 
Published: March 2021

Abstract
Architecting commercial aircraft has been always challenging due to the complexity of the product. A Model-Based Systems Engineering (MBSE) method was employed in this paper to handle this challenge, and a widely used general-purpose systems modeling language - SysML - was adopted to support the architecting work. To ensure compatibility between the modeling language and the specific aircraft architecting methodology, we explored construction and application methods of a Domain Specific Language. A new Domain Specific Language was created, in which several extensions to SysML were made, including Function & Components, Port, Exchanged Item and Relation. Benefiting from this new Domain Specific Language, an overall aircraft architecture model was precisely constructed.
Research on Optimization of Rebar Cutting Process for Prefabricated Concrete Components Based on BPI
Authors: Wang Ru , Wang Yue 
Published: March 2021

Abstract
In view of the characteristics of the production of precast concrete components and the cutting of rebar, from a production point of view, the introduction of BPI (business process improvement) management ideas has been introduced to optimize the rebar cutting process of precast concrete components. A multi-objective prefabricated concrete component rebar cutting model is established and an improved genetic particle swarm hybrid algorithm is proposed. It is proved by examples that the model reduces the number of raw materials and the number of rebar cuts by rationally arranging the rebar cutting combination plan, and the optimization of the prefabricated concrete components rebar process can rationally use the rebar remaining material and improve the utilization rate of rebar.
Research on Pressure bearing capacity of Defective Urban Gas Polyethylene Pipes
Authors: Hai-zhou Lv , Ming Sun , Yu-bin Xu , Yun Wu , Long-long Sun 
Published: March 2021

Abstract
Polyethylene pipes have been widely used in the urban gas industry. However, there are few researches on the safety performance evaluation of polyethylene pipes in use at home and abroad, which makes it impossible to carry out Fitness-For-Service evaluation of defects found in the inspection, and thus cannot accurately judge the safety status of defective polyethylene pipes. In this paper, two typical polyethylene pipe materials, PE80 and PE100 are selected. Based on the tensile performance test, the constitutive model is established. Using the method of finite element simulation, the ultimate pressure bearing capacity of 9 defect models was analyzed and studied. And the relationship between defect size and pressure bearing capacity was initially determined. Provides a foundation for subsequent engineering applications.
System Dynamics Modeling of the Supply Chain Performance of Prefabricated Construction Based on the Stakeholder Analysis
Authors: Yin Yue , Zhang Youzhi , Jin Kai 
Published: March 2021

Abstract
The supply chain performance of prefabricated construction plays an important role in the development of prefabricated construction. In this paper, in order to improve the supply chain performance of prefabricated construction and identify its factors, the indicators system for the supply chain performance of prefabricated construction based on the stakeholders’ perspective on the three dimensions of schedule, cost, and quality was built. Based on the indicators system, the system dynamics simulation model of supply chain performance of prefabricated construction was established. This study provides a dynamic performance management tool for prefabricated construction supply chain stakeholders.
Reuse Strategy for the Previously Qualified Software Tool of Airborne Software
Authors: Liu Jianfang , Zhang Xinai , Zhao Yi , Fan Hui 
Published: March 2021

Abstract
Although the software tool qualification should be based on the specific airborne software, it is impractical to develop the software tool for one software program. Most software tools, especially for the COTS tools, would be reused in multiple software programs. This paper capture and analyzes the requirements for the previously qualified software tool in the related standards and certification guidance, and proposes a strategy and framework for the reusing the previously qualified software tool to meet the requirements of different standards and certification authority.
Research on Safety Management of Small and Micro-sized Mining Enterprises
Authors: Ronggang Lv , Qizhong Luo , Jianqiao Yang 
Published: March 2021

Abstract
In view of the characteristics, status and present situation of small and micro-sized enterprises and small and micro-sized mines, this paper investigates the common safety problems or hidden dangers of small and micro-sized mining enterprises on the basis of practice, analyzes their causes, discusses the current safety management system and operation mechanism of small and micro-sized mines, and puts forward various effective ways to improve the safety management of small and micro-sized mines. It has strong practical and theoretical significance for mine safety.
Research on the calculation and improvement of a company’s activity cost based on activity-based costing and industrial engineering method
Authors: Gao Xiaoqin 
Published: March 2021

Abstract
The traditional cost management mode of China is used to make the cost of the production, and the cost management of the “commodity” is the cost management of the production process, the cost management of the product development and design of the pre-production, which is increasingly difficult to adapt to the needs of the modern social and economic development, has greatly hindered the improvement of the competition capacity of the enterprise commodity market. Based on the operation cost method, the paper will provide an example for the application of the operating cost method in manufacturing. In addition, the research on the final implementation of cost management is not very good. Combined with the methods of reducing the cost of industrial engineering, this paper continuously improves and controls the problems in the company’s operating cost management, and verifies the feasibility through empirical research and a large number of experiments.
Automatic 3D CAD Model and 2D Drawings Generation in Construction Engineering
Authors: Jin Sheng , Zhang Yuanrui , Yamazaki Tomohiro , Jiang Zhu 
Published: March 2021

Abstract
Automatic CAD design is difficult in construction field, since the construction environments vary case by case. Although the steps are similar, each creation is very time-consuming. Therefore, in this research a method that could automatically generate 3D CAD models and 2D drawings from the onsite measured geomorphological features is proposed to solve the complicated and similar process. This proposed method was implemented through the API (Application Programmable Interface) of CAD system and has been verified in practice that labor costs and time costs have been greatly reduced. In addition, mixed reality is applied to verify the assembly results, and an effective and realistic experience is provided to the user and the customer.
Stakeholder’s Needs Analysis Methodology For Civil Aircraft Projects
Authors: Yuwei He , Haomin Li , Xinai Zhang , Yaming Shi , Fudong Chen 
Published: March 2021

Abstract
Aircraft product development process is quite complex, involving many stakeholders. Therefore, aircraft owner manufacturers need to fully capture the needs of stakeholders at the beginning of design, establish analysis methods of stakeholder’s needs, and transform “customer voice” into aircraft development requirements, so as to ensure that the aircraft products can meet the needs of stakeholders. This paper introduces stakeholder’s needs analysis methods such as quality function deployment (QFD), analytic hierarchy process (AHP), and analytic network process (ANP). This paper establishes a Stakeholder’s needs analysis model, which can be used to carry out stakeholder’s needs analysis of civil aircraft.
Weibo Text Classification Based on Knowledge Graph
Authors: Liu Yingjun 
Published: March 2021

Abstract
As a platform for sharing and communication, Weibo can produce a large amount of short text data every day. Because the Weibo text is short and the text features are sparse, it contains less information, serious colloquialization and weak anti-noise ability, so it is difficult to achieve the desired results by using the traditional text classification method to classify Weibo text. This paper proposes a Weibo text classification method based on knowledge graph, which uses knowledge graph to expand text semantics and enrich text features on the basis of the original Weibo text. Then the TextCNN model is used to classify Weibo texts with extended semantics. The experimental results show that the classification accuracy of this method is better than that of Weibo text classification directly.
Topic-to-Essay Generation with Corpus-Based Background Information
Authors: Luo Dan , Ning Xinyi , Wu Chunhua , Wang Maonan , Wu Jing 
Published: March 2021

Abstract
This study aims to generate more topic-related and coherence essays based on user-defined topic words. Existing research generates essays without considering the semantic information from the corpus. However, the corpus contains statistical relationships of words which can be used to guide the model to generate more coherent and fluent essays. To fill this gap, we propose a corpus-based topic-to-essay generation model (C-TEG). We elaborately devise a background network based on the co-occurrence relationships of words from the corpus. The empirical results demonstrate that our approach has achieved 4.14 average score in subjective evaluation and a better BLEU-2 score, which shows that our model is able to generate more topic-related and coherent text than existing models.
Research on Distributed Operation Mode of Internet of Things
Authors: Li Yijie 
Published: March 2021

Abstract
The application of distributed system in the Internet of things makes the system control completely networked, realizes the connection of point-to-point and star data transmission control, makes the system highly scalable, convenient for centralized management, and is suitable for multi-functional Internet of things applications. In the distributed architecture, data is distributed on multiple servers. A distributed database is composed of multiple logically related databases distributed on the Internet of things. Each node on the network has independent processing ability, so it is necessary to find a suitable distributed system solution between code and database.
Real-time facial emotion recognition using lightweight convolution neural network
Authors: Li Qi , Liu Yun Qing , Peng Yue Qi , Liu Cong , Shi Jun , Yan Fei , Zhang Qiong 
Published: March 2021

Abstract
In recent years, facial expression recognition has played an important role in the field of human-computer interaction, and the application of deep learning technology has enabled it to develop more rapidly. In this paper, we create a lightweight network model for real-time emotion classification to recognize student facial expressions. The system includes: using Haar cascade for face detection, combined with the idea of Xception to propose a lightweight CNN network model, using pre-activation in the residual block to optimize the model and reduce the impact of overfitting. The experimental results on the FER2013 database show that our model has a better expression classification effect than other state-of-the-art methods. Besides, our model uses fewer parameters, which reduces the complexity of network training. When real-time emotional recognition of students, the system can help teachers adjust their teaching methods according to the emotional state of students.
Performance research and prospect exploration of distributed object storage of meteorological data in domestic platform
Authors: Cheng Kexin 
Published: March 2021

Abstract
Meteorological data are important information data in China, and have made tremendous contributions to disaster prevention and disaster reduction in China. However, the current meteorological system has a long-term dependence on foreign hardware and software platforms, showing obvious security problems. It is an urgent task to complete the domestication and performance improvement of the meteorological system. At the same time, as the black box architecture of flash memory devices greatly hinders the co-optimization of software and hardware, open-channel flash memory has begun to attract attention as a new type of flash memory architecture. In this article, we have adopted new excellent domestic products including Phytium chips, Starblaze open-channel flash memory devices, and Kylin operating systems as components of a new domestic software and hardware platform. The object storage system of meteorological data has been implemented in a real environment by Ceph. We provides a built solution and optimizes the parameters. Based on the comparison with the commercial platform storage system, the problems and challenges faced by the meteorological data distributed object storage system in autonomy are discussed. Finally, this article looks forward to the distributed storage of meteorological data under domestic platforms.
Bibliometrics and Knowledge Graph Analysis of Domestic Big Data Management Research
Authors: Weihua Yang , Dong Xu 
Published: March 2021

Abstract
This article uses CiteSpace software to perform a visual analysis of the knowledge graph of the literature about the direction of big data management in the CNKI database using the method of document measurement. The analysis content includes: paper attention, author of the article, hot keywords, and the organization of the article, and big data is found. The hot research of management can be summarized into four categories: education management, information management, enterprise management and government management. The domestic scholars’ research status on big data management is obtained, and the development trend of big data management research is revealed, with a view to providing reference for the research and development of big data management in various subject areas.
Speaker Identification Based On Ivector And Xvector
Authors: Yuan Xinyu , Li Guanyu , Han Jiao , Wang Di , Tiankai Zhi 
Published: March 2021

Abstract
As an important branch of AI (Artificial Intelligence), speaker recogniti-on technology has developed rapidly in recent years. At present, speaker recognition technologies based on traditional methods and deep learning methods are very mature and have achieved good results. As a key technology in human-machine voice intera-ction, speaker recognition has changed human life in many ways. However, there is almost no research on speaker recognition in Tibetan. This paper uses Gaussian mix-ture model and deep neural network TDNN as the theoretical basis. On the Tibetan language corpus, the speaker identification on the ivector of GMM-UBM and the speaker identification on the xvector of TDNN are performed respectively, and the experimental results are compared. The experimental system is divided into prepro-cessing, feature extraction, model training and decision.