bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design of Electric Steering Wheel for Agricultural Machinery
Authors: Li Yueyang , Deng Wenzhi , Cheng Xiaofei , Song Weihai , Li Zhen , Zhang Xianchong 
Published: August 2020

Abstract
Aiming at the automatic steering control system of agricultural machinery, this paper puts forward the method of using S7-200 intelligent PLC of Siemens company as the core controller, which uses the high-speed pulse signal output by the controller to control the stepper motor to drive the rotation of the steering shaft, realizes the automatic steering through the control of the motor speed and steering, uses the encoder to detect the rotation angle of the steering shaft to realize the feedback control, and selects the touch screen to realize the user interaction scheme.
Research on dynamic simulation technology and fault characteristics of Pumped Storage Power Station
Authors: Jin Long , Yu Yue , Zhan Rongrong , Meng Jiangwen , Liu Longhao 
Published: August 2020

Abstract
The fault equivalent circuit model of the pumped storage unit is established, the key electrical parameters of the generator motor of the pumped storage power station are analyzed, and the short-circuit fault characteristics of the generator motor of the pumped storage power station are studied. Based on the typical connection mode of pumped storage power station, a dynamic model test platform including dynamic model pumped storage unit, excitation system, frequency conversion starting device and its control system is established. The dynamic model tests of metal or transition resistance short circuit fault, stator ground fault and stator turn to turn short circuit are carried out.
Comprehensive Experimental Research on Complex Electromagnetic Environment of Aircraft
Authors: Tian Guansuo , Zhou Jun , Li Xiaosong , Li Dawei 
Published: August 2020

Abstract
The battlefield environment that modern electronic information equipment faces during use is very complicated, which has become one of the main characteristics of the informationized battlefield. This article starts with the composition and characteristics of a complex electromagnetic environment, references relevant standards, introduces the definition and composition of a complex electromagnetic environment, and summarizes its characteristics. On this basis, this article introduces the general methods of complex electromagnetic environment tests, including digital simulation tests, semi-physical simulation tests, and full-physical simulation tests. Among them, in the full physical simulation test, an equivalent method is generally used to achieve it. At the same time, this article introduces test evaluation methods, including element-level evaluation and effectiveness-level evaluation. Combining engineering practice, this paper puts forward the difficulties of constructing a complex electromagnetic environment. It is an inevitable requirement for the development of weapons and equipment to carry out comprehensive experimental research on the complex electromagnetic environment of aircraft, and to be able to assess the combat capability of the product. It is also an objective requirement for the development trend of the information military.
Modeling and Optimization of Bus-bar Local Stray Inductors in Converter
Authors: Liu Y , Liao Q H , Yao J K 
Published: August 2020

Abstract
Taking a two level inverter laminated bus as the research object, a mathematical model of local stray inductance is established. The ANSYS Q3D finite element simulation software is used to extract the self-inductance and mutual inductance of local stray inductances in laminated bus-bars. The equivalent local stray inductance is calculated according to the stray inductance mathematical model. The size and generation factors of the local stray inductance of the bus-bar are analysed, and the bus-bar structure is improved. By reducing the local stray inductance between the bus capacitors to IGBT module, the operational status of the converter circuits of the power converter is effectively improved. A double pulse test circuit is built to extract the local stray inductance of the bus-bar before and after optimization. The experimental results show that the improved bus-bar stray inductance is obviously reduced, the correctness of the theoretical analysis is verified, and it is helpful to optimize the bus-bar structure.
Optical parametric oscillator based on electro-optically polarization mode conversion
Authors: Li Lujie , Liu Hang 
Published: August 2020

Abstract
The back conversion of optical parametric oscillator seriously restricts its application in spectral analysis, optical holography, lidar and so on. The optical parametric amplifier output energy is simulated theoretically, and it is confirmed that the back conversion can be compensated by reducing the input energy of parametric light. An optical parametric oscillator with electro-optically polarization mode converter in the resonant is proposed to change the polarization state of the parametric light and adjust the proportion involved in the oscillation. The polarization mode conversion of MgO:PPLN crystal is analyzed theoretically. The experiment of energy regulatory structure is carried out. When the applied voltage of electro-optically polarization mode converter is 157 V/mm, the maximum output power of 1.47 μm and 3.84 μm are 4.4 W and 3.7 W, with a ratio of 1.2. It is confirmed that such structure can suppress back conversion and adjust the output ratio.
Intrusion Object Detection on Transmission Corridors Based on Deep Learning
Authors: Mu Xiaochen , Zhou Xuekun , Li Changyong , He Wenjun , Wei Xin 
Published: August 2020

Abstract
With the construction and development of Chinese power grid, the scale of the power grid continues to expand, the transmission corridors environment is becoming more and more complex, the possibility of external damage caused by intrusion objects of the transmission line is constantly increasing, which seriously threatens the normal operation of the power grid and the reliability of power supply. In order to solve the above problems, it is particularly important to study a detection method that can replace manual identification. That method helps the field personnel to timely detect the intrusion objects within the monitoring scope of the transmission line, so as to improve the efficiency and accuracy of transmission channel inspection.
Influence of high voltage cable on insulation coordination of Pumped Storage Power Station
Authors: Ren Hongtao 
Published: August 2020

Abstract
The insulation cost of electrical equipment of 330kV and above EHV power station accounts for a large proportion. This paper establishes a typical electromagnetic transient analysis model of pumped storage power station, and conducts lightning overvoltage simulation calculation based on the model. It studies the length of high-voltage cable and summarizes the amplitude law of lightning overvoltage of main electrical equipment: with the increase of cable length, the amplitude of lightning overvoltage decreases. It has guiding significance for insulation coordination of Pumped Storage Power Station.
Research and application of digital virtual maintenance system for steam turbine
Authors: Hua Yudong , Zang Xudong , Bai Rongge , He Lirong , Yang Yuanqin , Xi Qiuyan , Jin Hanmeng , Pan Xiaolei , Lei Liu 
Published: August 2020

Abstract
After a 430MW machine unit was started with C repair finished, the shafting vibration of it increase rapidly at the phase of on-load. Using the on-line vibration monitoring and fault diagnosis system (TDM system) matched with the unit to check the vibration historical data, and according to the vibration characteristics, oil film vortex fault is diagnosed. In view of this, the vacuum test was carried out on the lubricating oil temperature of the main transformer engine and the condenser of the unit. The results show that the low frequency variable oil temperature and the condenser can be restrained in a large certain load range. The distribution measures of bearing load are adjusted by unit’s adjustment to increase the load of No.3 bearing, so as to eliminate the unit’s low-frequency vibration fault and ensure the normal operation of the unit.
Population Cross Learning Algorithm Combining Greedy Search for Community Detection
Authors: Wang Xiaogang , Yan Guanghui , Li Shikui , Zhou Ning 
Published: August 2020

Abstract
In order to improve the precision of modularity optimization and community detection, this paper presented a complex network community detection algorithm based on cross learning among individuals of population combining greedy search. Individuals’ codes indicated community partition. Individuals comparatively studied with each other to spread good genes and optimize modularity fast. Besides, aiming at improving the algorithm, the best communities, where some randomly selected nodes will move in, would be found by using greedy search maximizing the local modularity increment. The algorithm was tested on artificial networks and some typical real networks, compared with some typical algorithms. The results show that algorithm can get convergence quickly, achieve better modularity value, and finely detect and identify community structures.
Research on Employment Prediction and Fine Guidance based on Decision Tree Algorithm under the Background of Big Data
Authors: Li H Y , Zhang Y 
Published: August 2020

Abstract
Refinement of college employment guidance is the demand of the current era. Big data thinking and technology have created the conditions for it. In this paper, the factors influencing college students’ employment are discussed and the method of applying decision tree algorithm to predict college students’ employment is studied. On this basis, the paper analyses the effective ways to improve the refinement of college employment guidance based on employment prediction, from the four aspects of improving the scientificity of decision-making, the pertinence of guidance, the accuracy of service, and the timelines of assistance.
Object Detection of Remote Sensing Airport Image Based on Improved Faster R-CNN
Authors: Han Yongsai , Ma Shiping , Zhang Fei , Li Chenghao 
Published: August 2020

Abstract
In order to effectively improve the detection accuracy of remote sensing images in airport areas, basing on the representative deep network Faster R-CNN as the object detection method, a deeper basic network ResNet and feature fusion component FPN are used to extract more robust deep distinguishing features, and add a new fully connected layer to the end detection network and combine the softmax classifier and 4 logistic regression classifiers for object detection according to the inter-class correlation of the object. Experiments show that the improvement of the original network brings a 7.7% mAP improvement to 76.6% of the mAP. Compared with other mainstream networks, it also has a better accuracy rate. At the same time, by appropriately reducing the input amount of the proposals, the speed can be increased 3 times to 0.169s under the premise of reducing the accuracy by 2.2%. According to the specific task, the accuracy and detection speed can be reasonably weighed, which reflects the effectiveness and practicability of the network.
Numbers of Thoughts on Promoting Standardization Management Work in Innovative and Efficient Manners
Authors: Liu Bin , Jiang Hong , Jigui Zheng 
Published: August 2020

Abstract
This essay introduces some existing problems in standardization management of research institute. The essay analyzes the key points of standardization management, discusses the thoughts on standardization process design. Meanwhile, this paper expounds methods of standardization management in many fields such as module division, template index, information release, quick motivation, human and standard connection and level upgrade. The research achievement of the essay has important guiding significance on standardization and technical base management.
Application and Analysis on Geological Hazard Monitoring and Early Warning System Based on Internet of Things
Authors: Xiao Yigai , Dai Jun 
Published: August 2020

Abstract
On the basis of reviewing the development of technology at home and abroad, this paper proposes the architecture, functions, and characteristics of a geological disaster monitoring and early warning system based on the Internet of Things (sensor network). The geological disaster monitoring and early warning system based on the Internet of Things (sensor network) includes on-site sensors and data acquisition processors, (wireless, wired) communication modules, and background data processing and information release system software. The system has the characteristics of intelligence, scale, standardization and real-time, reliability and security. Finally, combined with China’s national conditions, several key technologies and basic theoretical research directions of the geological disaster monitoring and early warning system based on the Internet of Things (sensor network) in China are proposed.
The influence of imprecise quantum measurement on quantum dense coding
Authors: Ma Zhiqiang , Luo Bingbing , Huang Chaowei , Wu Tianxiong , Wei Jiahua , Zhao Haiyan , Xing Wei 
Published: August 2020

Abstract
In this paper, the influence of imprecise quantum measurement on quantum dense coding would be analysed. The realization processes of dense coding under the condition of imprecise measurement are given in detail. The performance of dense coding is analysed from the successful probability and average classical information. The successful probability and the classical information are immune to the phase parameter error of quantum measurement. However, with the increase of amplitude factor error, both probability and classical information will decrease. The results of this paper would be useful in the field of quantum communication.
A Privacy protection scheme for carpooling service using fog computing
Authors: Kou Bangyan , Cao Suzhen , Lv Jia 
Published: August 2020

Abstract
As the traffic environment becomes more and more crowded, an increasing number of people are willing to carpool. Carpooling services provide convenience for drivers and passengers to share their journeys. But carpooling requests are uploaded to cloud server for processing and analysis in most existing schemes, resulting in communication delays and leakage of user privacy. To solve this problem, we propose a privacy protection scheme for carpooling service using fog computing. First, identity-based digital signature technology is used to achieve anonymous authentication. Second, location tags, bloom filters and fuzzy extractors are utilized to match passengers and drivers without disclosing the users’ location; Consortium blockchain technology is adopted to store carpooling records. Finally, security analysis and experiments results show that our scheme offers privacy preservation and security, while maintaining low computational cost.
An Automatic Online System for Detecting and Analyzing Quality Data of Products in Manufacturing Process
Authors: Bei Yijun , Zhou Yingang , Cheng Xuelin , Zhao Bin 
Published: August 2020

Abstract
As the business volume is getting bigger, more and more problems are exposed to product quality testing. For example, the application of the traditional statistical process control (SPC) is not flexible on different occasions due to the fixed testing rules and the manual data collection. These problems lead to large deviation and low efficiency. In order to fasten the testing process and optimize the results of testing, we design an online system that integrates the Drools rule engine and automatic collection mechanism based on some common communication protocols and devices into SPC to replace traditional manual quality testing. In this paper, we introduce the principle of the system design in detail. The experimental results show that we can utilize SPC in a more convenient and efficient way.
A Fusion Method for Satellite Multi-sensor Based on Improved Support Matrix
Authors: Li Ze , Li Yonghua 
Published: August 2020

Abstract
In this paper, a satellite multi-sensor data fusion method based on improved support matrix is proposed. The cross-correlation function is used to describe the support degree between multiple sensors, and the measured signals are weighted and fused optimally from the SNR perspective. Compared with the method of distance measurement, this method does not need to set threshold and the calculation process is simpler. Simulation results show that this method can objectively reflect the reliability of each sensor, effectively eliminate redundancy and error information, and select the optimal sensor combination.
Octave Residual Network for Image Motion Deblurring
Authors: An Qi , Jiang Lifen , Sun Huazhi , Liang Yan , Xu Tongtong , Xu Fan , Zhou Yongheng 
Published: August 2020

Abstract
Image motion deblurring technology is an essential topic. Traditional methods with a high algorithm complexity when estimating the blur kernel require a lot of calculations. To solve this problem, we proposed Octave convolution residual block, and proposed Octave Residual Network (ORN) based on this block. ORN is a Generative Adversarial Networks, where the generator is a multi-scale recurrent network, and the discriminator is a deep neural network. ORN restore sharp images in an end-to-end manner where blur is caused by various sources. We present multi-scale loss function that mimics conventional coarse-to-fine approaches. To verify the validity of ORN, we trained our model on GOPRO dataset, the peak signal-to-noise ratio (PSNR) of the model reached 30.04, and the operation time of each step is reduced by 0.04 seconds. Experimental results show that our method achieves the state-of-the-art performance of image motion deblurring not only in performance but also in training speed.
Rumor detection based on topic classification and multi-scale feature fusion
Authors: Tan Li , Ma Zihao , Cao Juan , Lv Xinyue 
Published: August 2020

Abstract
In recent years, with the rapid development of Internet technology, the spread of network rumors has become one of the important obstacles to maintain the stable development of social networks and ensure the public security. Most of the existing researches focus on the detection of rumors in general fields, ignoring the differences among different fields. According to the characteristics of rumor in the health field, this paper proposes a rumor detection method based on topic classification and multi-scale fusion. Different methods are used to extract features from different sub datasets of different scales, taking into account the overall, inter topic, and intra subject correlation and differences, and then judge after feature fusion. The experimental results show that this method is better than the general detection method in the data set of health field, and has some improvement compared with the algorithm in the same field.
Design of Agricultural Machinery Positioning and Monitoring System Based on Beidou/GPS
Authors: Li Yueyang , Li Zhen , Qin Zhenhua , Yang Shuolin , Li Chunlei , Zhao Jingkun 
Published: August 2020

Abstract
This paper designs an agricultural machinery positioning monitoring system, which can collect the positioning information of agricultural machinery operation, and is of great significance for precision agriculture. The system uses stm32f103rct6 as the controller, with Beidou + GPS dual positioning module and display screen and other related accessories, to achieve the accuracy and real-time positioning of agricultural machinery.
Development and Practice of Virtual Experiment Platform Based on Blender and HTML5--Taking Computer Assembly and Maintenance as An example*
Authors: Cai Lilu , Yang Gang 
Published: August 2020

Abstract
The use of virtual training, can solve the problems such as the shortage of training resources, slow update of equipment, lack of training supplies, risks and environmental pollution and other issues in pure physical equipment training. This paper applies Blender and Html5 technology to student’s experiment in colleges and universities, and designs an interactive virtual experiment platform which integrates learning and experiment and supports muti-terminal visualization. The design scheme, main function and implementation technology of the platform are introduced in detail, and applied to the course of computer assembly and maintenance. First, the 3D model is constructed by the free open source modeling software Blender and exported in a specific format recognized by the WebGL library. Then, this library is used to add interactive function for the application program, which can realize the real-time interaction between user’s Browser and 3D model. HTML5 is used to eliminate the problem of customizing special web pages for different devices, and adaptive page design is realized to support multi-terminal access. Based on this platform, the virtual reality learning system of computer assembly and maintenance was designed. After the completion of the study, knowledge acquisition, skill assessment, psychological feeling and cognitive load were measured. Practice shows that the application of this technology can enhance the immersion and intelligence of the experimental process, and improve the user’s interaction and experience. At the same time, the system has a cross platform, free plug-in, easy maintenance and other characteristics, can solve the problems of poor user experience and compatibility of traditional virtual experiment platform.
An improvement design of multi-sensor test bench
Authors: Fan J.H , He Y.Y , Tang F 
Published: August 2020

Abstract
Parallelism error is researched for a three-coordinate testing bench that simulates the automotive environment to test the performance of multi-sensor. The studies showed that the parallelism error between the sensor and the magnet and the signal wheel has an effect on the experimental data. A calibration device with multiple sets of force sensor probes was designed to improve measurement accuracy. And probe measurement results were used to compensate parallelism error in several directions. Results show that this method can reduce above-mentioned error and improve the accuracy of experimental data effectively.
Research on Cross-border E-commerce Platform Supplier Credit Evaluation Based on Big Data Interconnection
Authors: Zhang Yi-Wen 
Published: August 2020

Abstract
This paper first analyzes credit assessment of cross-border E-commerce platform suppliers based on big data from two aspects: credit evaluation index system and credit evaluation model. On this basis, this paper summarizes the recommendations of supplier credit assessment for cross-border E-commerce platform based on big data, in order to provide reference for the work of supplier credit assessment for cross-border E-commerce platform from the perspective of big data, hoping that this study can help promote the cross-border E-commerce platform construction and cross-border E-commerce industry development.
Recognition method of wide area measurement abnormal data based on GRA-IForest
Authors: Xing Zhou , Zhi Yong , Liu Wenfei , Li Jiawei , Qing Can , Ma Rui 
Published: August 2020

Abstract
Aiming at the anomaly recognition method of large area measurement system (WAMS), a method based on Grey Mrrelatian Aru and Isolation Forest algorithm is proposed, considering the attributes of power data and the big data characteristics of large area measurement system. In this method, the relational matrix of power data attribute sequence is obtained through grey relational analysis, and the dependent attributes are selected according to the relational matrix for attribute sequence merging. Then, the data set is partitioned by cascaded isolated forest model and abnormal data are detected. Taking the data of a province’s wide-area measurement system as an example for experimental simulation, compared with LOF, Kmeans and IForest, under the same inspection time, the GRA-IForest model has achieved good inspection results and achieved a higher overall detection accuracy and lower standard deviation.