bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the Method of Information System Equipment Performance Analysis Based on Big Data
Authors: Zhu XiangLei , Lin Pan , Liu Yalei 
Published: April 2021

Abstract
As the business scale of the information system continues to increase and refined management, the increase in the load of the information system has become increasingly obvious, and the requirements for the reliability and stability of the information system are getting higher and higher. In order to improve the reliability and stability of the information system, a safe and stable performance analysis system must be established. Therefore, first obtain performance indicators such as throughput and response time of the information system. Secondly, establish a performance baseline between load, response time, and resource consumption. At the same time, it is necessary to introduce time, external time and other parameters for big data analysis, and finally conduct a situation assessment of the information system.
Design and Implementation of Basic Data Platform for University Library
Authors: Fan Zehua , Song Jiao 
Published: April 2021

Abstract
Considering the problems existing in the data management and use of university library, this paper puts forward the concept of constructing “basic data platform”, which can provide the guarantee for the production and business data of library and university. The system includes data acquisition system, library data exchange system, data access API interface, cold data transfer system, data visualization and management platform, data analysis and mining modules, forming a complete system of data storage, management and use.
A Study on Data Monitoring and Effect Optimization of Programmed Advertising Platform: Taking “Ocean Engine” as an Example
Authors: Yan Yu , Cao Sheng 
Published: April 2021

Abstract
Currently, programmatic advertising has become the most popular way to purchase online media in our country. More and more Internet companies are beginning to use their own data and technological advantages to build their own programmatic advertising service platforms. This article takes the programmatic advertising service platform of Bytedance Company-the “Ocean Engine” as the research object, and explores the strategy of data collection and effect optimization of programmatic advertising.
Research on the application of big data technology in college students’ innovation and entrepreneurship guidance service
Authors: Yuan Fang , Hu Die 
Published: April 2021

Abstract
The concept and mode of innovation and entrepreneurship education are embedded in the research university education system. From the four dimensions of external policy and public opinion environment, internal system module, operation mode and operation mechanism, this paper constructs the framework model of innovation and entrepreneurship education system in research universities. The model not only conforms to the training law of innovation and entrepreneurship talents, but also conforms to the training law of innovation and entrepreneurship talents. At the same time, innovation and entrepreneurship education can also be incorporated into the university education system. It also focuses on the internal system module of innovation and entrepreneurship education and the operation mode of three shift system. It lays a theoretical foundation for the promotion and implementation of the concept of innovation and entrepreneurship education in China. The relevant achievements of the construction of the innovation and entrepreneurship education system are optimized and improved accordingly. After putting it into practice, the innovation and entrepreneurship education level of our universities will be greatly improved.
Data visualization project implementation workflow of smart cold chain system
Authors: Zeng Xi , Liu Shuxian , Chen Yanru 
Published: April 2021

Abstract
Purpose: In response to the increasingly complex cold chain related work, the requirements for daily cold chain system data information collection, analysis and data information traceability continue to increase. This article starts from a design perspective, research how to improve the effectiveness and usefulness of data and information transmission in the cold chain system to build a smart cold chain system. Method: By mining the connection between smart cold chain and data visualization, analyze the goals and requirements of data information transmission and reception. The design uses a large data visualization screen as the carrier, mainly research the design process of data visualization large screen, it is used to construct the actual operation of the data visualization project of the smart cold chain system. Conclusion: Data visualization has great advantages in mining, disseminating and communicating data information. Combine the smart cold chain system with data visualization, provide effective data information for workers in the smart cold chain industry, highlight functions required to upgrade the smart cold chain system, consolidate the coordination between the various working links of the smart cold chain, strengthen the user experience of the staff related to the smart cold chain, improve the efficiency of smart cold chain work.
Deep learning for skeleton-based action recognition
Authors: Ye Lei , Ye Shiqing 
Published: April 2021

Abstract
In order to further improve the recognition rate of skeleton action recognition, and to break the limitation that most of the previous deep learning-based methods have the input content of human joint coordinates, we propose a human skeleton action recognition algorithm combining geometric features and LSTM networks. In this paper, we propose a human skeleton action recognition algorithm that combines geometric features with LSTM network. The algorithm selects geometric features based on the distances between joints and selected lines as the input of the network, and introduces a time-selective LSTM network for training. The ability to select the most recognizable temporal features using the time-selective LSTM network is demonstrated in the SBU Interaction dataset and UT Kinect dataset, achieving 99.46% and 99.30% recognition rates, respectively. The experimental results demonstrate the effectiveness of the method for human skeleton-based action recognition.
Application of Virtual Reality Technology in the Health Field Based on the Background of Big Data
Authors: Li Yizhou , Deng Kesui 
Published: April 2021

Abstract
With the development of big data and artificial intelligence, virtual reality technology has penetrated into every aspect of daily life. Among them, the application of virtual reality technology in the health field is of great significance. Virtual reality technology can assist clinical medicine in the treatment of patients, and can also simulate the physical feelings of panic disorder and some disabilities to induce emotions similar to patients, produce empathy effects, enhance normal people’s understanding of patients, or improve health The effect of dissemination. This article discusses the current status of the application of virtual reality technology in the context of big data, and analyzes how virtual reality technology can promote health communication, disperse pain, treatment of psychological disorders, and begin to provide services for the elderly, which has great social and practical significance. This article reviews and compares the recent applications of virtual reality technology in the health field at home and abroad, and analyzes its prospects and shortcomings.
Research of UAV Controller-pilot Data Link Real-time Processing Technique
Authors: Chanying Qi , Yuchao Li 
Published: April 2021

Abstract
In traditional flight tests, ground monitoring is based on on-board telemetry data. With the rapid development of UAV design, the monitoring data source transitions from radio telemetry transmission to ground-to-air data link transmission gradually. Traditional ground real-time processing system can’t meet the new requirements. UAV controller-pilot data link real-time processing technique doesn’t rely on traditional PCM telemetry, via controller-pilot data link which is integrated into the UAV, ground controller system and flight tests data processing system, which promotes the efficiency of flight test dramatically, the data processing duration is also reduced significantly.
Intelligent recognition of surface defects of parts by Resnet
Authors: Wang Fushuai , Qiu Jiyuan , Wang Zhefeng , Li Wenrui 
Published: April 2021

Abstract
Nowadays, Automatic metal surface defect recognition is an important research direction in the field of surface defect recognition, and more convolution neural network algorithms are applied in this field. However, with the deepening of network layers, network degradation will occur. We propose a ResNet method for classifying metal surface defects. After experimental testing, we use ResNet34 to build an identification network. After training 300 epoch of the network using the NEU surface defect data set, the convergence of the network is very good. The accuracy of test set verification is 93.67% and higher than that of other surface defect recognition algorithms. Also, we can deepen the number of layers ResNet the network without worrying about network degradation.
Study on the correlation between grain size and processing limit in abrasive flow machining
Authors: Yinguang Li , Guizhen Song , Bowei Hou , Bowen Han , Jianming Cheng 
Published: April 2021

Abstract
The influence of particle size on the abrasive flow machining mechanism and processing limit was studied by establishing the processing model of different particle size. When many scholars studied the mechanism of abrasive flow machining in the past, they only established a machining model and ignored the effect of abrasive particle size. By comparing the size of different granularity abrasive particles and the workpiece surface in contact with each other, the large granularity abrasive particle processing model and the small granularity abrasive particle processing model were put forward, and their processing mechanism was analyzed respectively. On this basis, the reason of machining limit in different particle size abrasive processing process is explained. Finally, the theoretical analysis and experimental results were compared to verify the correctness of the processing mechanism and theoretical analysis of processing limit of abrasive with different granularity, and an optimal experimental scheme was proposed to break through the original processing limit.
Design of LQR Excitation Controller of Synchronous Condenser in HVDC System
Authors: Li Hao , Wang Honghua , Lu Hangtian , Wang Chengliang 
Published: April 2021

Abstract
As a kind of reactive power compensation equipment,a synchronous condenser is widely used in High Voltage Direct Current(HVDC) transmission system due to its small influence on the regulation ability and high strong excitation ability. In this paper,the practical state space model of the synchronous condenser is established and the parameters of the model are calculated. The linear quadratic regulator ( LQR) Controller for excitation system is designed and the controllability and stability are analyzed. In order to verify the voltage support ability and dynamic response performance of LQR excitation controller,the simulation is carried out in MATLAB/SIMULINK. The simulation results show that the grid voltage fluctuation can be quickly quelled and the strong excitation function of synchronous condenser is quickly exerted.
CarfRCNN: A Two-stage Effective Model For Instance Segmentation
Authors: Chen Yujie , Zhao Pengbiao , Chen Julin 
Published: April 2021

Abstract
With the rapid development of deep learning, many instance segmentation models have achieved good results in accuracy and time. But here are still many problems. In this paper, we proposed a two-stage model CarfRCNN. We proposed CAResNet to change the structure of the backbone, making the feature extraction of the input image more refined. At the same time, we also added the CRF module to add smooth constraints to the pixels, so that the segmentation mask fits the target contour more closely. We train and test on the COCO datasets, and compare with the Mask R-CNN. The experimental results prove that the model we proposed can greatly improve the accuracy.
Development of Virtual disassembly and assembly platform for marine air compressor
Authors: Wei LIU 
Published: April 2021

Abstract
The use of virtual reality technology to assist equipment maintenance and skills training has a broad application prospect, but the existing systems are often lack of sense of reality, over-simplified because it’s difficult to establish the disassembly process model, the lack of 3D interaction design, etc. Taking marine air compressor as an example, this paper analyzes the functional requirements of the virtual disassembly and assembly platform, studies the key technologies of multi-source data integration, 3d modeling with high sense of reality and high complexity disassembly process modeling, uses Maya/Unity3D and other software to realize relevant technologies and functions, and gives the development process of the system. The developed system has been applied in many maritime institutions in China. It has been demonstrated with reference value and application prospect.
Quality by Design (QbD): Application of Comprehensive Risk Analysis in Blending Process for XLGB Capsule in Medicine Industry
Authors: Zuo Yamin , Huang Jie , Deng Xuehua , Sun Yichun , Wu Qing 
Published: April 2021

Abstract
Intelligent development is becoming an inevitable choice for the development of green manufacturing enterprises, improving the medical quality and guaranteeing the safety is an important role player in the intelligent development of medical industry. Since the risk model prediction is crucial in many areas of medical work, risk management and communication are meaningful in industry management. The framework of comprehensive risk management of Chinese Patent Medicine (CPM) has been presented and constructed at presence. To enhance the quality level and safety management of medical service, this article explored the different theory meanings of innovation and conducted a comprehensive risk evaluation of Chinese medicine industry. This paper provides a foundational reference for future research that how to apply quality-by-design (QbD) approach for the development of medicine industry. This study demonstrates that the application of the QbD concept is a novel area in CPM quality.
Dynamic Scheduling Method of Production Plan in Automobile Manufacturing Workshop
Authors: Ren Nver , Li Maoying 
Published: April 2021

Abstract
In order to adapt to the needs of dynamic adjustment of production plan between different automobile manufacturing workshops and deal with emergencies, a dynamic scheduling method of production plan based on genetic algorithm is proposed in this paper. According to the requirements of different workshops, multi-layer fitness functions are designed, buffer zones are set between workshops, and the production planning scheduling is dynamically adjusted by sliding window. The experimental results show that the dynamic scheduling method proposed in this paper has the advantages of high efficiency and adjustment.
Part point cloud segmentation method based on model registration
Authors: Si Lei , Yang Han , Li Zhongming , Duan Liming 
Published: April 2021

Abstract
In order to analyze the machining errors of parts more accurately, a point cloud segmentation method based on model registration was proposed for mechanical parts. First, the surface information of the standard model of the part is extracted from the Initial Graphics Exchange Specification (IGES) file; then, the part point cloud is registered to the standard model using the method of the moment principal axis method and the Iterative Closest Point algorithm (ICP); then, by calculating the distance between each point in the point cloud and each surface in the standard model, it is used to determine the corresponding relationship between the model surface and the point cloud, and then the point cloud is segmented; finally, the segmentation results are surface-fitted and benchmarked to obtain a segmentation with better alignment quality. The experimental results show that this method can automatically segment the part point cloud according to the surface features of the part when only the IGES model and the point cloud model are input, without setting any empirical parameters, and obtain the segmentation result with clear boundaries.
Few-shot learning approach for 3D defect detection in lithium battery
Authors: Wu Ke , Tan Jie , Li Jingwei , Liu Chengbao 
Published: April 2021

Abstract
Detecting the surface defects in a lithium battery with an aluminium/steel shell is a difficult task. The effect of reflectivity, the limitation of acquiring the 3D information, and the shortage of massive amounts of labelled training data make the 2D detection method hard to classify surface defects. In this work, a few-shot learning approach for 3D defect detection in lithium batteries is proposed. The multi-exposure-based structured light method is introduced to reconstruct the 3D shape of the lithium battery. Then, the anomaly part of the 3D point cloud is transferred into 2D images by the height-gray transformation. The MiniImageNet datasets are used as the source domain to pretrain the Cross-Domain Few-Shot Learning (CD-FSL) model. The accuracy in our experiment result is 97.17%, which means that our method can be used to classify the surface defects of the lithium battery.
Research on the Stability of an Air-to-Air Missile Compound Control System with a Pulse Modulator
Authors: JianQi Wang , DongMei Wang , Liang Yan 
Published: April 2021

Abstract
Based on pulse modulator, a method of lateral force and aerodynamic compound control system design in air-to-air missile and the stability is studied. First, the lateral force is assumed to be continuous and blended with aerodynamic fins accordding to a certain proportion, and the compound control is designed based on three-loop control method. Then the switch order of direct force device is obtained based on the pulse modulator. At last, the stability of control system is analysed based on describing function method, and then the parameter of pulse modulator is properly chosen. Simulation results show the validity of the proposed design.
Design of Motor Operation Monitoring and Cooling Control System
Authors: ya xian Zhang , huai feng Cui , yuanchang Lin , zhen quan Liu , shi yun Wu , guotian He 
Published: April 2021

Abstract
Combined with PLC control technology, a motor monitoring and cooling system is designed. The main function of the system is to remotely control the motor and monitor the working environment and operating status information of the motor through the mobile phone app, and to cool the motor through the cooling system; it can effectively improve the operating efficiency and reliability of the motor, and improve the user experience. The article puts forward the design scheme of the motor monitoring system and summarizes the various functions of the system control. It also analyzes and describes the realization method and key technology of the control system in detail.
Mechanical Safety Risk Analysis of Smart Factory
Authors: Cheng Zhou , Likai Ju , Min Cao , Xiangyan Zhang 
Published: April 2021

Abstract
In view of the mechanical safety risks of industrial robots, AGVs and other mobile devices that are widely used in smart factories, a mechanical safety risk analysis of smart factories method is carried out. First, it analyzes the mechanical safety risks of CNC machine tools, industrial robots, AGVs, and warehouses in smart factories. Then, a specific seal production workshop is taken as an example. It conducts a mechanical safety risk analysis and gives a safety plan to reduce the risk. The mechanical safety of the personalized seal workshop has achieved sufficient risk reduction. This article can provide a certain reference for conducting mechanical safety risk analysis during the construction of smart factories.
Scheduling optimization of aging employees considering physical load
Authors: Zhou Jian , Wang Rentu 
Published: April 2021

Abstract
Considering the influence of age on the task completion time of the workforce, the scheduling problem of the workforce under physical load was extended, and a mathematical optimization model was proposed, preventing the workforce from continuously engaging in high workload work in the same body part and minimizing the standard deviation of task completion time. The influence of age on the workforce's reaction and endurance ability was discussed and formulated reasonably. The high and low workload of the workstation was evaluated by Rapid entire body assessment. A particle swarm optimization algorithm was designed by permutation coding based on set rules, and the rationality of the model and the effectiveness of the algorithm were proved by an example. The results show that the model can not only eliminate the risk of continuous high workload but also improve the performance of the assembly line.
A Novel Self-adjusting Ultrasound Transducer Stabilized Elastic System Realized by 3D Printing
Authors: Wu Dan , Lu Wenhuan , Li Yuxuan , Shi Haiqiang , Wei Jianguo 
Published: April 2021

Abstract
The human tongue is a significant organ for swallowing and speaking. The measurement of tongue function is challenging because it is hidden inside the mouth. Ultrasonic imaging is often used to study and record tongue movement. In order to ensure the validity and authenticity of the collected data, numerous methods are proposed to stabilize the transducer. However, in the long-term data acquisition, few devices consider issues such as whether the jaw is in compression during speech and whether the participant can autonomously complete the adjustment, which leads to data frame discarding and experimenter discomfort. This paper describes a novel self-adjustable ultrasound transducer stabilization elastic system using 3d printing technology that allows free head movement and flexible jaw movement. The system performance is evaluated quantitatively. It shows that in the 95% confidence interval, the average translational offset of the transducer relative to the head is 2.44mm and the rotation angle is 3.21°. Furthermore, the small head constraint makes the voice close to its natural state and more suitable for scientific studies of voice and swallowing.
Attitude control of self-balancing vehicle based on sliding mode variable structure control
Authors: Le LIU , Li-hua XING , Zhang-jun SUN 
Published: April 2021

Abstract
The two wheeled self balancing vehicle belongs to a typical nonlinear system. Aiming at the problem of attitude control stability of two wheeled self-balancing vehicle. A new sliding mode reaching law of integral sliding mode variable structure control was proposed. The feasibility and effetivenes of the controller are proved by theory and experiment. The experiment results show that the designed controller has remarkable advantages of steady state characteristic,fast dynamic response and strong robustness to external disturbance to compared with traditional PID controller.
Simulation installation space of the vehicle to solve the problems of component layout, electrical wiring and wire routing
Authors: Fedorov E , Ferenets A , Dudka N , Snegurenko A 
Published: April 2021

Abstract
The presented work is devoted to modeling the mounting space of a vehicle onboard electrical equipment complexes for solving the problems of assembling elements, wiring of electrical circuits and routing of wires. A model of the mounting space of the onboard electrical equipment complex has been developed. Various modifications of on-board electrical equipment of modern vehicles under various restrictions are considered and investigated.