bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the Application of Phased Array Detection Technology in Composite Insulator Interface Debonding Detection
Authors: Li Wenbo , Jiang Yue , Liu Lanlan , Zhu Jiran , Wang Jun , Xie Yi , Liu Zhenshan , Tian Xiangzhuang 
Published: August 2020

Abstract
The main reasons for the failure of composite insulator are the fracture of core rod and the breakdown of interface. However, due to the particularity of composite insulator, the traditional insulator detection method is not fully applicable to it. In this paper, phased array detection technology is used to detect the interface debonding defects of composite insulator sheath and core rod, and clear interface debonding signals are obtained. The research results can provide research basis for the application of phased array detection technology in the field of composite insulator defect detection.
Application Research on Ultrasonic Phased Array Technology in Weld Seam Inspection
Authors: Zhang Haixing 
Published: August 2020

Abstract
Welding seams are prone to safety accidents and failures during actual operation, which has an adverse effect on the economic benefits of the enterprise. When using traditional ultrasonic inspection methods to inspect the pipe butt welds, the staff needs to use the inspection probe to move as needed, which makes the inspection process difficult to operate and is greatly affected by human factors. The beam of conventional ultrasound cannot be deflected and focused. It is difficult to detect parts with complex geometric shapes and large anisotropic welds. Ultrasonic phased array is a new type of non-destructive testing method, which makes up for the limitations of conventional ultrasonic testing, and has great advantages compared with conventional ultrasound. Therefore, in order to reduce the misjudgment of defects caused by humans, this paper studies the application method of ultrasonic phased array technology in weld inspection, discusses the principles and characteristics of ultrasonic phased array inspection technology in nondestructive testing, and the defects were tested. The test results show that the phased array technology can effectively detect weld defects.
The Design of Peanut Seedling Cutting Test Bench
Authors: Cheng Xiaofei , Zhou Fuping , Li Yueyang , Song Weihai , Li Zhen , Yan Yongzeng 
Published: August 2020

Abstract
In order to solve the problems of the peanut harvester, such as unclean fruit picking and serious crushing, a peanut seedling cutting test bench is built. This paper starts with the selection and design of the components of the test bench, and then completes the design of the whole test bench, and finally completes the design of the peanut seedling cutting test scheme.
Research on the financing dynamics of product crowdfunding: based on the perspective of emotion
Authors: Qi Zihao , Zheng Haichao , Li Liting 
Published: August 2020

Abstract
Product crowdfunding provides new financing channels for entrepreneurs. How to screen crowdfunding projects has become an important issue in this field, and the financing dynamics of projects is the starting point to study the filtering of crowdfunding projects. Based on the perspective of emotions, this paper uses text analysis technology to extract the emotions contained in the comments of crowdfunding projects, and analyzes the influence of emotions on the dynamics of project financing. The main conclusions are as follows: for financing dynamics, anticipation, trust and sadness can help to increase the number of subsequent investors, while joy and disgust have significant negative effects on the number of subsequent investors. The conclusion of this paper is useful to the protection of crowdfunding investors and the operation practice of crowdfunding platforms.
Research on Application of Artificial Intelligence Technology in Electrical Automation Control
Authors: Jiang Chao , Xiong Xiaorui , Zhu Tanqing , Cao Jiajia , Yu Jiahao 
Published: August 2020

Abstract
Among the evaluation indicators of national development level, the degree of power system development is one of the important indicators. Economic and social needs have gradually expanded the scale of the power grid, and many distributed renewable energy sources are continuously connected to the power grid system, making the power system more and more complex; the data generated during the application of the power system presents typical big data characteristics, such as presenting large, heterogeneous, and multi-source characteristics. Faced with the new characteristics of power data, the requirements for methods of analyzing and processing power data problems have increased. The current research on artificial intelligence (AI) in the computer field is getting deeper and deeper, and the application of AI in various industries has made greater research progress. It is the key to future scientific and technological progress. In my country’s development strategy, it is clearly required to promote the development of AI and regard the power system as one of the main application areas of AI. The rapid development and advancement of artificial intelligence can provide powerful tools in many aspects of the power system, including power system planning and design, coordinated control, simulation, prediction and estimation, diagnosis and identification. This article first analyzes the artificial intelligence technology, introduces the two mainstream artificial intelligence technologies in the current situation, and analyzes the power system, and then studies and analyzes the application of artificial intelligence technology in the electrical system.
MsrFace: Multi-Sphere Radius Loss for Deep Face Recognition
Authors: Du Xi , Han Xiaoxuan , Qin Yu , Wang Dong 
Published: August 2020

Abstract
Loss functions is one of the main challenges in face recognition problems. Recent works focus on designing loss functions that make learned features more discriminative by a larger angular or cosine distance. In this paper, in addition to the method based on additional angle margins, we propose a Multi-Sphere Radius Loss (MsrFace) to add radius constraints. MsrFace pushes learned features to hyperspheres with different spherical radii and the classes can be separated more strictly. We present experiments on several widely used benchmarks to show that MsrFace has a better performance in comparison with some recent state-of-the-art face recognition methods.
Research on sentiment analysis of short text based on Attention
Authors: Li Haotian , Hui Cao , Xiaxia Zhang 
Published: August 2020

Abstract
In order to classify the short essays, a circulating neural network is used to classify the texts by natural language processing technology. Recurrent neural network has some advantages in processing text sequence with memory function. In this paper, BiLSTM algorithm is used to extract text data features, and self-attention mechanism is introduced to improve the fitting ability of the model. The accuracy of this model algorithm on text emotion classification task is 78.1%, which is improved compared with LSTM and CNN neural network model.
Topic Evolution Analysis of COVID-19 News Articles
Authors: Bai Yun , Jia Suling , Chen Lao 
Published: August 2020

Abstract
Recently, numerous media publishes various news on the latest developments every day due to the global spread of COVID-19. The news provides rich information about COVID-19 and includes a wide range of evolving topics. Our study is intended to develop a dynamic topic analysis system to monitor the evolution of the large-scale text data topics and assist with the social management and policymaking. The system expands the Dynamic Topic Model (DTM) with two modules: data sparsity computing and topic number selecting, which makes the experimental process more natural and generalizable. Data sparsity is designed to determine the length of single time slice. UCI, UMass and NPMI are introduced for choosing the optimal number of topics. This paper explores CBC news articles using DTM and captures the impact of COVID-19 on various aspects and the development of specific events. The experimental results demonstrate the effectiveness of our system for discovering and tracking the evolving topics. This system also plays an important role to improve the awareness of the public and serves as an analysis platform for government.
An Efficient Configuration Scheme of CGRA for Block Ciphers
Authors: Wei Jinghe , Wang Yufeng , Sun Jinjun , Yang Jinjiang 
Published: August 2020

Abstract
An Efficient Configuration Scheme based on Configuration Context (ECSCC) is proposed to decrease the size of configuration memory and the time of configuration transmission. The ECSCC is applied to a coarse-grained reconfigurable architecture (CGRA) which is implemented under TSMC 40nm CMOS technology to compare with similar work. The results show that the proposed ECSCC improves the area efficiency by 21.56 X and the energy efficiency by 3.97X.
Analysis of DNS Security Threats on campus network
Authors: Sha Feng , Wei Ying , Wenzhi Wu 
Published: August 2020

Abstract
DNS, as the entrance to Internet application access, is the only way for all business access. Normal services must access services through DNS, and malicious programs also need to be connected through DNS. In this paper, we focus on the analysis of campus network egress data using traffic analysis technology. And we pay attention to DNS-related data, hoping to find useful information about network attack. Since we collected data for about a month (mainly data about DNS data), we found many attacks and a large number of computer viruses. They are hidden in the normal data stream, but can be recognized by DNS data.
Analysis of identifying COVID-19 with deep learning model
Authors: Fan B B , Yang H 
Published: August 2020

Abstract
Coronary Virus Disease 2019 swept the world and caused serious impact on human society. Doctors usually use CT scan pictures and chest X-ray images to determine whether a patient is infected. Many researchers try to use deep learning methods to test COVID-19 of patients. However, there are many problems when using deep learning methods for feature extraction, such as: fewer data samples, unclear pictures, and pictures containing special marks. This article uses deep learning methods for COVID-19 detection and visual analysis of popular deep learning methods. Experiments verify that when using deep learning in the public small sample COVID-19 dataset, a small part of the test results are not reliable. We propose solutions to the problems of deep learning during COVID-19 detection.
SoS Architectural Requirements Modeling and Analysis
Authors: Dong Qingchao , Xu Junming , Qiao Yongjun , Ren Huifeng 
Published: August 2020

Abstract
Analysing the architectural requirements of System-of-Systems is a daunting task, usually involving a complicated process of enterprise architecture modeling and verifying. So the paper proposes a method of capability-oriented requirements modeling for developing the architecture requirements of System-of-Systems. A multi-layer ontologies framework is suggested to model the architecture requirements. To check the consistency of performance requirements, a formal inference method is designed to verify the requirements models. Finally, a case study is provided to demonstrate the applicability of the method.
Kernel correlation filters based on feature fusion for visual tracking
Authors: Yang Bo , Hu Xiaopeng , Wang Fan 
Published: August 2020

Abstract
This paper presents a CF-based method for robust visual tracking by multiple features fusion. HOG features and high-level CNN features are used to enhance tracking performance. First, different features are extracted from the target. Secondly, the extracted features are employed to learn the corresponding discriminant models, which are used to generate response maps respectively. Finally, an accurate response map can be obtained by fusing multiple response maps. In addition, we propose a model update strategy to reduce model drift under occlusion. The OTB benchmark is used to test the proposed method. Experimental results show that the proposed method can significantly improve tracking performance in complex situations especially in occlusion and fast motion. In addition, compared with several state-of-the-art methods, the proposed method shows competitive accuracy rate and success rate.
X—Ray Digital Image Advanced Processing and Buffer Layer Defect Intelligent Identification of Power Cable
Authors: Liu Sanwei , Zhang Liu , Duan Jianjia , Zhang Jun , Huang Fuyong , Duan X-Iaoli , Zeng Zeyu 
Published: August 2020

Abstract
With the rapid modernization of the city, power cable has been widely used in the process of urban construction. In the course of cable operation, cable faults become more and more frequent, which has a great impact on national economy and people’s life. The method of digital X-ray imaging can realize the nondestructive testing of power cable body and obtain clear and intuitive X-ray digital image. But it lacks the advanced processing and defect recognition method of X-ray digital image, and can not directly detect and identify the cable body and defect from the original digital image. Therefore, this paper studies the power cable X-ray digital image advanced processing and buffer layer defect intelligent identification technology. By using gray scale processing technology, the original image gray scale range is compressed to the human eye identifiable range, and then the defect identification is carried out. Then the traditional convolution neural network CNN and the full convolution neural network FCN are used to train the image data to realize the intelligent recognition of the power cable buffer layer defect. The research shows that compared with the traditional convolution neural network CNN, the full convolution neural network FCN proposed in this paper has more clear and intuitive recognition effect.
Simulation and Optimization of Flow Field in Jujube Hot Air Drying Room
Authors: Liu Rui , Dong Ji-Xian , Wang Dong , Wen Jia-Hao , Wang Yi 
Published: August 2020

AbstractNumerical simulation of the flow field of chrysanthemum hot air drying chamber before and after optimization was carried out by using porous media model. To solve this problem, by setting the optimization scheme of the turbulence fan, the wind speed non-uniformity coefficient M in multiple sections was reduced from 125.51%, 149.27%, 144.81%, 135.63% and 106.45% to 90.44%, 116.15%, 86.92%, 77.49% and 76.67%, respectively. After flow field optimization, airflow velocity in the middle and rear of drying chamber increases significantly, and airflow uniformity in the whole space is improved.
Design and Optimization of Extraction Process of Sterile Seed Long Fiber
Authors: Sun Juyan , Liu Jiazhen , Tang Yu , Duan Shiming 
Published: August 2020

Abstract
We carried out research & analysis and development & design on the problems such as unreasonable structure of outdated process equipment and device, imperfect matching process and incomplete process link in the sterile cottonseed long fiber extraction, presented structural schemes for main machine and key fittings, and configured novel processing technology for sterile seed long fiber extraction, which achieves higher flexibility and adaptability of the processing technology and a machine-hour processing capacity of 400kg/h which is 2~3 times that of old model. And we proposed that the linear speed ratio of taker-in roller to roller shall not exceed 2,500, and obtained their reasonable speed at the optimum performance. The promoted application of this technology is of great significance to improve quality and efficiency of textile and cotton tailings treatment.
Analysis of key technologies to achieve autonomous driving on closed roads in the near future
Authors: Yang Guang , Chen Xiaoyue 
Published: August 2020

Abstract
In recent years, autonomous driving has received widespread attention worldwide. Many car companies and Internet companies have been competing for research and development. This article first reviews the current status of autonomous driving at home and abroad, then discusses key technologies for autonomous driving such as environmental perception, high-precision maps and navigation and positioning, path planning, and motion control. At the same time, the current situation, problems and solutions of autonomous driving on closed roads are discussed.
Instantaneous torque control is directly based on sliding mode control of SRM
Authors: Huang Xianghui , He Shuaishuai 
Published: August 2020

Abstract
Since the sliding mode control (SMC) of the sliding mode can be designed, and is independent of parameter variations and disturbances outside of the control target, the sliding mode control has the advantages of fast response, insensitive to the parameter change and external disturbance, and is easy to realize other control systems. It is an effective way to solve nonlinear problems. Characteristics inherent nonlinearity and strong coupling of the switched reluctance motor (SRM) itself, based on the traditional text directly on the instantaneous torque control, the torque distribution function provides a real-time compensation scheme. In Matlab/Simulink environment, the simulation results show that the improved control strategies can reduce torque ripple of SRM, increase the robustness of the system.
Review of Intelligent Development of Cigarette Maker’s Control System
Authors: Zhang Lihong , Yu Yonglong , Li Yuliang , Jin Wenliang 
Published: August 2020

Abstract
In recent years, the electronic control system of cigarette maker has been developed rapidly. The embedded IPC replaces the traditional “PLC+ high-speed processing board card” and is applied in the electronic control system of ultra-high speed winch unit, which solves the problem of poor stability of the original multi-platform. Under the new EtherCAT architecture, the intelligent development of the electronic control system of cigarette maker has become a new trend. In order to better improve the intelligent function of the electronic control system of cigarette maker, the intelligent development trend of the electronic control system of cigarette maker based on embedded IPC will be elaborated in detail.
Research on Intelligent Optimization of Bulk Cargo Terminal Control System
Authors: Wang Xuelin , Shi Hankun 
Published: August 2020

Abstract
Aiming at the problems of lagging automation and low informationization of bulk cargo terminals, this paper has optimized the control system of bulk cargo terminals, and improved the characteristics and functions of the control system. Based on the completion of the existing remote start and stop processes and equipment, the database, fault diagnosis and information management of the bulk cargo terminal control system are optimized, which improves the control efficiency and operability of the control system. The transformation and upgrading of the control system has played a good role in promoting the development and construction of smart ports.
Research on the design of intelligent cognitive training products for the elderly
Authors: Xue Yanmin , Zhang Yuanle 
Published: August 2020

Abstract
The purpose of this article is to design and study the smart cognitive training products for the elderly.This paper mainly studies how to prevent and improve the cognitive decline of the elderly in the market,analyzes the current situation and problems of the products in the market,studies the needs of users, finds out the functional needs, emotional needs and interactive experience needs of users, and further designs the intelligent cognitive training which is helpful to the cognitive training of the elderly according to the research result.
Design and application of double closed loop weight control system for cigarette maker
Authors: Li Yuliang , Zhou Xiaozhong , Zhang Lihong 
Published: August 2020

Abstract
In order to solve the problem that the precision of cigarette weight control system is not high enough in cigarette machine production, a double closed loop weight control system of cigarette machine is designed according to the characteristics of cigarette machine control system. This system takes IPC as the control core. Firstly, the current cigarette weight is obtained, then the weight deviation is calculated, and then the distance to be moved by the actuator is calculated based on the deviation. Then the current position of the actuator is obtained, and the target position of the actuator is calculated. The results show that the long-term deviation of the weight control system using the double closed-loop control method can be reduced to less than 4.0mg during the production of the target weight of 490mg cigarette, which is 0.8mg lower than that of the single closed-loop control method. This technology can improve the quality of cigarette process and reduce the overall consumption.
A Robust Beamforming Algorithm Based on Covariance Matrix Reconstruction and Steering Vector Estimation
Authors: Liang Jian , Jiang Defu , Han Yan , Zhang Yujie , Xie Zaipeng 
Published: August 2020

Abstract
Adaptive beamforming algorithms often suffer from performance degradation due to the presence of the desired signal component in the interference-plus-noise covariance matrix (IPNCM) and mismatch of steering vector. In order to improve the robustness of the beamforming algorithm performance, a new robust adaptive beamforming algorithm is proposed in this paper. In the proposed algorithm, Capon spatial spectrum is first used to reconstruct the IPNCM. Then, based on the robust Capon beamforming algorithm based on the steering vector uncertain set, new constraints are added so that the steering vector does not converge to the interference direction. The proposed beamforming algorithm is a non-convex quadratic constraint quadratic programming (QCQP) problem that is solved using semidefinite programming (SDP) relaxation. Simulation results show that the proposed algorithm is more robust than some other existing algorithms and is closest to the optimal solution.
Harm and control of hydraulic oil pollution in coal mine machinery
Authors: Zhang Huirong , Yao Zhongfu 
Published: August 2020

Abstract
Coal mining machinery such as shearer is one of the most important comprehensive mining equipment in coal mine. Once it breaks down, the consequences cannot be estimated. The data shows that about 2 / 3 of the faults in the hydraulic system of coal mine machinery are caused by the pollution of hydraulic oil. Therefore, this paper first analyzes the types and properties of various pollutants, then describes the harm of pollutants to the hydraulic system, and finally puts forward a comprehensive control scheme of hydraulic oil pollution, which provides a reference for engineering practice.