bluuebunny/crossref_metadata_2025_split huggingface dataset:
Functional coating preparation based on zinc oxide using low temperature plasma
Authors: Nosov S A , Shinkarev A A , Gorelysheva V E , Savinkov A V 
Published: August 2020

AbstractThe work describes the synthesis of superhydrophobic coating based on zinc oxide with a UV-driven reversible switching between hydrophilic and hydrophobic properties. A coating of vertically oriented acicular crystals of zinc oxide with dimensions of 1-2 μm in length and 50-200 nm in width on a metal substrate was obtained. According to the phase composition and morphology, the crystals correspond to zinc oxide-zincite. The contact angle for the coating after its exposure in a box isolated from daylight for 14 days is 150 °, while for the control metal substrate, the contact angle is 40 °. It is shown that the use of low temperature Ar plasma of low pressure allows changing the surface topography of acicular nanocrystals due to etching of their vertices and edges.
Anomaly detection of power grid dispatching platform based on Isolation Forest and K-means fusion algorithm
Authors: Shouyu Liang , Zhang Kun , Fang Wenchong , Zhou Zhifeng , Hu Rong , Zhu Wen , Li Yingchen , Wang Yichang , Hou Jian 
Published: August 2020

Abstract
It is very important to detect abnormal Access IP of power grid dispatching platform accurately and rapidly to ensure the safety of power production. An Isolation Forest and K-means fusion algorithm is proposed, which not only solves the deficiency of Isolation Forest only being able to detect anomalies in binary classification, but also solves the defect of Isolation Forest threshold setting based on artificial experience or prior assumptions by designing a threshold setting strategy for Isolation Forest anomalies. The Access IP data of the southern power grid dispatching platform is taken as an example to evaluate the proposed algorithm and model. Through control experiments, the effectiveness and advancedness of the algorithm are illustrated in terms of AUC-ROC curve, accuracy, recall, and F1 score.
Optimization and Practice on the Course Content and Teaching Methods of Optoelectronic Testing Technology
Authors: Cui Shaobo , Qin Jiaqiong , Dai Jun 
Published: August 2020

Abstract
The research aimed at the characteristics and teaching requirements of the photoelectric detection technology course, optimized the teaching content and teaching methods of the photoelectric detection technology course, explored how to use scientific research results as the teaching content, and practiced how to put the new teaching method into the course and the teaching process. The practice has shown that the use of scientific research results in teaching is conducive to maintaining the rapid development of high and new technology and a dynamic atmosphere of the times; new teaching methods can improve students’ interest in learning and the quality of teachers’ teaching, and help to cultivate students’ innovative consciousness and ability.
Research on the temperature rise characteristics of power transformers based on fluid-solid-thermal coupling
Authors: Sun C C , Xiao C , Hou J , Yao X L , Ye J , Yu W J , Jiang L 
Published: August 2020

Abstract
The problems of overheating and insulation are the main influencing factors to the operation status of power transformers. Based on the physical model of a 50MVA/110kV oil-immersed self-cooling transformer, the electromagnetic, temperature and fluid field are introduced to establish a three-dimensional temperature rise model of the transformer in this thesis. The loss obtained from the electromagnetic field calculation model is taken as a heat source and input into the transformer temperature rise model. The results show that the hot spot temperature occurs in the core column and increases with the maximum load current when the single-phase ground fault occurs, and the hot spot temperature in the transformer exceeds the limit value. The temperature distribution trends of the core and high and low voltage windings under rated conditions and overload conditions are similar. In addition, the average temperature rise of the windings under overload conditions exceeds the limit value.
Intelligent quality detection system of the transmission tower
Authors: Tian Xiangsheng , Wang Hui , Zhou Kun , Cui Weihua 
Published: August 2020

Abstract
Aiming at the rapid development of the power transmission industry, with the huge number of iron towers and the large amount of tower material quality inspection work, however, the detection efficiency is low. This article analyzed five inspection items, inspection points, and their inspection data volume, which are required for tower material specification inspection, such as parts, galvanized layer, that must be performed in the tower material specification inspection, put forward the plan of tower material quality inspection system integrated by software management system and hardware detection instrument, and designed the system scheme, determined the typical testing equipment with real-time transmission function, and designed the architecture of tower material quality information management system. This system can realize the intelligentization of tower material testing, the digitization of the testing process, and the standardization of testing information management, greatly improving the efficiency and accuracy of tower material quality testing.
Research on Feeder Automation System for Urban Distribution Network
Authors: Huang Yibiao , Li Rong , Wu Linwei , Zhang Junqi , Xiao Zhiming 
Published: August 2020

Abstract
With the development of society, the demand for power supply reliability is also increasing, and the proportion of terminals with feeder automation function in the distribution network is increasing. It has become a research hotspot to find more optimized feeder automation strategy. This paper introduces three kinds of feeder automation schemes: centralized control type, local control type and distributed control type and expounds the fault isolation, non-fault section power supply self-healing strategy in detail. The comparison of several control schemes provides reference for choosing feeder automation scheme according to system architecture.
Research on Online Verification of Relay Protection Setting Value Based on Multi-source Information Fusion Technology and Bow-tie Model
Authors: Xu Yan , Chen Rui 
Published: August 2020

Abstract
In view of the complexity and flexibility of the current power grid, in order to make relay protection online verification more accurate and effective, a protection importance degree sequence assessment method based on the multi-source information fusion technology and bowtie model is proposed. Firstly, the cause of incorrect protection actions is analyzed by establishing a fault tree through multi-source information fusion technology, and the event tree analysis method is used to deduce the final development result of the event. Combined with the fault tree and the event tree, a bow-tie model is formed to visually and completely describe the whole process of the event. Then the economic loss of the event is analyzed as the basis for assessing the protection importance degree, and the online inspection of the protection setting value is completed from high to low according to the importance degree sequence. Finally, the IEEE 3-machine 9-bus system is used to verify the correctness and rationality of the method through simulation.
Research on Practice Teaching and Reform of RF Circuit Course
Authors: Cai Wanxiong 
Published: August 2020

Abstract
In the context of the era of high-correction transition to applied technology, as a highly applicable RF circuit course, students should continue to strengthen their practical ability. The traditional talent training model that emphasizes theory over practice is difficult to meet the actual needs of enterprises. Real cases and real training for job positions and practical work tasks are practical ways of reforming practical teaching. They are of great significance for improving students’ learning ability, combining theory and practice, and achieving seamless connection between talent training and corporate needs.
Test Analysis and Simulation Calculation of Temperature Field for Dry-Type Air-Core Reactor
Authors: Wu Jianling , Ou Zhonghua , Huo Feng 
Published: August 2020

Abstract
Based on test analysis and simulation calculation of temperature field for dry-type air-core reactor, the temperature rise rule of internal axial dimension and enveloping internal conductor were analyzed. The highest temperature rise point in the envelope is located about 1/4 of the packet seal. The temperature rise difference between the inner wires is small, and the temperature rise difference within the envelope is less than 1 °C. The radial distribution of temperature along the insulating impregnated glass fiber has a great gradient. The temperature in the middle of the airway is near room temperature, and the temperature rise is about 5K, and the internal temperature of the airway has a larger gradient. For airway width design, the influence of the change of the airway width of the temperature rise distribution should be considered.
A simulation study of argon discharge in PIG ion source with axial magnetic field
Authors: Li Jie , Ju Shaojia , Yue Aizhong , Zhang Xiaolei , Wang Hu , Lu Jie , Zhou Xiaohua 
Published: August 2020

Abstract
In this study, we used a two-dimensional fluid model to investigate the argon discharge in Penning ion gauge (PIG) ion source influenced by magnetic field and the structure of ion source. Under fixed anode voltage U and pressure P, the relationships between the axial magnetic field, the structure parameter K, which is the ratio of the distance of two cathodes and the diameter of the anode tube, and the electron density are obtained. For fixed magnetic field B=0.01 T and pressure P=0.5 Torr, the electron density along the central axis has the maximal value when K=0.8. With fixed K=0.8 and P=1 Torr, the maximal electron density was found when B=0.1 T. Our results imply that there are optimal values for magnetic field and K which induce the maximal plasma density.
Short-term Power Forecast of Wind Power Generation Based on Genetic Algorithm Optimized Neural Network
Authors: Zhou Canzong , Tang Bin , Cui Wei , Yao Zhengmao 
Published: August 2020

Abstract
With the rapid development of economy, human consumption of fossil energy has caused a global energy crisis. Nowadays, countries all over the world are making great efforts to develop clean energy. Wind energy as one of the pollution-free, renewable and high-quality clean energy, has attracted widespread attention. However, wind power generation is easily affected by natural factors and is instable. In order to improve the quality of wind power, this paper analyzes the influencing factors of wind power, studies the prediction method of wind power forecasting, and uses genetic algorithm optimization neural network to forecast the wind power of a wind farm in Northwest China, which may provide some reference for the power generation and grid connection of wind power plants.
Design and analysis of cable-driven mechanical gripper for complex manipulation
Authors: Zhang Deyang , Cheng Bo , Yue Zhiyong 
Published: August 2020

Abstract
This paper studies the design and analysis problem of a class of cable-driven mechanical gripper for complex object manipulations. More precisely, a new structure design of mechanical gripper with cable-driven mechanism is first proposed with details for effective object grasping. In addition, an effective method is developed to prevent overload of axial rotation torque of the gripper. Based on the designed gripper, the kinematic analysis is then carried out and the caging grasp analysis is shown.
Design and Implementation of an Indoor light supplement control system based on STM32 microcontroller
Authors: Yuan Fusen , Zhao Xuchen , Chen Hao , Ming Yue , Zhang Jie 
Published: August 2020

Abstract
At present, most traditional lighting methods use energy conversion methods, which not only causes great harm to the environment, but also has great functional limitations and low solar energy utilization. This paper proposes an indoor adaptive precise light supplement system that can be applied to multiple scenes. This system introduces the hardware and software components of the adaptive and accurate light supplement system from three aspects: the light follow-up system, the light supplement system, and remote monitoring. It realizes the information interaction between users and the system, which significantly improves the accuracy and efficiency of indoor lighting, and has great strategic significance for the full development and utilization of solar energy.
The Designation and Implementation for Human Skinned Mesh Animation Based on XNA
Authors: Zhang Shi-Nan 
Published: August 2020

Abstract
The technology of human skeletal mesh animation is one of the most important research focuses, and remains problematic in the researching field of computer animation. Firstly, this paper gives a comprehensive analysis on the theory and implementation of skeletal mesh animation, and then an engine framework was design and completed by using Visual Studio 2012 and XNA4.0 as development tools. In oder to improve the executing efficiency and reality of animation, Effective measures such as optimizing rotating algorithm, animation blending and using GPU to update vertexs are used here.
Application of Information Science in Museum Lighting Design and Psychophysics
Authors: Zhao Guohua 
Published: August 2020

Abstract
This paper mainly discusses the influence of different lighting methods and building height on visitors in the museum environment. This study takes Ningbo Art Museum as the experimental site. Four exhibition areas with different floor heights and different lighting methods were selected for objective field measurement, and subjective scores were given according to the types of lamps, lighting methods and the atmosphere created by control methods. Objective data measurement and subjective questionnaire survey were used in the experiment. In the subjective part, 20 visitors were selected to investigate the emotion of visitors through questionnaire survey. Finally, SPSS is used to analyze the data. Through field investigation and subjective information analysis, this paper closely combines electrical engineering with information science research, which lays a solid foundation for improving the integration of Museum electrical lighting design and visitors’ psychological information.
Complex network
Authors: Tan Yangxin , Wu Junlin , Zhong Qing 
Published: August 2020

Abstract
With the improvement in the accuracy of solutions and the increase in the complexity of social problems, social division becomes more important, and teamwork has become an important way to solve complex problems. The efficiency of a team is affected by many factors. How to evaluate the operation of a team is a very meaningful topic. A team consists of members. The characteristics and abilities of members determine their roles in a team, and naturally affect the efficiency of the team. The cooperation between team members is also an important factor in achieving high efficiency.
Storm Scheduling Based on Non-cooperative Game
Authors: Ma Haixu , Xin Feng , Wang Guilei , Sun Kaiwei , Xiong Mingyuan 
Published: August 2020

Abstract
With the continuous development of Internet technology, a large amount of data with rich value has been generated, and lagging data analysis will affect the timeliness of data, so real-time streaming data processing is becoming increasingly important. Storm is a pure streaming data processing framework, but it uses the polling scheduling algorithm by default. This algorithm ignores the network communication overhead between workers and cluster load balancing. Aiming at Storm’s default scheduling problem, a non-cooperative game-based Storm scheduling algorithm (G-Storm) was proposed. Storm extracts the source data in real time through the component “Spout”, passes it to the logical processing component “Bolt”, and finally loads it into the target warehouse. The experimental results show that the game scheduling algorithm proposed in this paper reduces the system processing delay by 28.6% compared with the default scheduling algorithm.
Industrial Time Series Data Forecasting of LSTM Neural Network Based on Attention Mechanism
Authors: Jiang Zhiwei , Peng Xiudong , Sun Yuanfeng , Zhu Mengyun 
Published: August 2020

Abstract
At present, the maintenance mode of industrial equipment is still based on regular maintenance and after-the-fact maintenance, and with the development of industrial production intelligence, the production data of equipment has increased dramatically. In order to reasonably carry out maintenance activities in the use stage of CNC machine tools and other industrial equipment, this paper proposes an industrial time series data prediction method based on LSTM of attention mechanism. Firstly, based on the LSTM recurrent neural network, combined with the complex historical data of CNC machine tools, the overall characteristics of important time series are obtained. Secondly, the mechanism of attention analysis is introduced, and the algorithm of network structure design and prediction process is given. Finally, the accuracy of prediction is compared with experiments with standard BP neural network. The experimental results show that, compared with the standard BP neural network, the LSTM model based on the attention mechanism has higher prediction accuracy, which verifies the effectiveness of the method.
Research on water extraction technology of remote sensing image based on neural network
Authors: Zhang Qiang , Wang Xiao-Nan , You Ya-Nan , Li Han 
Published: August 2020

Abstract
With the rapid development of space-based facilities and the increasing number of remote sensing satellites, more and more effective observation data can be obtained on the ground. The traditional manual translation method will not meet the requirements of remote sensing application. Aiming at the problem of water body extraction in remote sensing application, an automatic water body recognition method based on U-Net deep neural network is proposed. The results of water body NWDI index evaluation are considered comprehensively, and the interference elimination model is used to process the results of water body rough recognition, so as to further improve the extraction accuracy. Using the image data of a remote sensing satellite to verify the water body recognition method, the results show that the proposed method can automatically extract the water distribution area, and the extraction accuracy is better than 85%.
Color transfer based on color classification
Authors: Xie Bin , Zhang Kang , Liu Ke 
Published: August 2020

Abstract
In order to solve the problem that the global color transfer algorithm may fail in color-rich images and the resulting images do not have a sense of hierarchy, this paper proposes a color transfer algorithm based on color classification mapping. When faced with a colorful image, the global color transfer algorithm will be weak, and the resulting image will not have a sense of hierarchy. Therefore, it is necessary to use a local algorithm for color transfer. The k-means algorithm based on color classification is used in this paper. Through this algorithm, rich color information can be classified, so that it can be transmitted separately in each color classification. A large number of experimental results show that compared with the global color transfer algorithm, the color transfer algorithm used in this paper is more layered, the result is more accurate, and it has a better performance in terms of visual effects.
A Survey Deep Learning Based Relation Extraction
Authors: Zhang Xiaxia , Dai Yugang , Jiang Tao 
Published: August 2020

Abstract
From human understanding of natural language to machine understanding of natural language, NLP has become the mainstream technology in the world.Extracting useful information from massive information, namely information extraction (IE), such as relation extraction (RE), is one of the important semantic processing tasks.With the explosion of web texts and the emergence of new relations, the margin of human knowledge has increased dramatically, and unstructured text processing has become a problem that needs to be overcome, so people have been working on RE for many years. From the earliest pattern matching to the current popular neural network, RE has made significant progress. After reviewing the development history of relation extraction, this paper analyzes and discuss the development of existing neural network models and pre-trained language models from static technology to dynamic technology and reinforcement learning; finally, combined with the latest development of NLP research technology, the future research direction and trend of entity relation extraction are prospected.
Modeling and verification of CTCS-3 level code sequence verification scene based on UPPAAL
Authors: Xiao Wei , Kuang Wenzhen 
Published: August 2020

Abstract
Taking the code sequence verification scenario of the autonomous CTCS-3 train control system as an example, on the basis of introducing the code sequence verification function, it is proposed to take the security function attributes, functionality and time requirements as the verification objectives, at last, the workflow of the scheme is analyzed in detail, and the behavior and action of each module of the system are standardized by the timed automata language. The timed automata network model of the workflow sequence of the code sequence verification scheme is established, which lays the foundation for the later verification. Then, the nature of the system is verified by the UPPAAL verification tool. The research shows that: in the process of model establishment, strictly in accordance with the specification content, the description of the specification is accurate, and at the same time, the modeling and verification method of the train control system based on the time automaton can effectively study the security, timing and characteristics.
Research on equipment fault prediction expert system based on big data dimension reduction
Authors: Zhu Ningning , Song Bin , Lu Yan , Li Yingtang , Zhu Zhongzheng 
Published: August 2020

Abstract
Due to the complex structure and massive volume of large equipment in petrochemical enterprises, it was very difficult to carry out inspection and maintenance work. The traditional expert system used a single knowledge base and reasoning machine, so the processing efficiency and prediction accuracy were low. In this paper, the dimensionality reduction which is used to process a large amount of physical information collected by the sensors, remove redundant components and extract main characteristic parameters. Meanwhile, combined with the powerful pattern recognition and judgment ability of fuzzy neural network, the forward reasoning mechanism and error back propagation keeping continuous training correction until meeting the accuracy requirements, the expert system gave the equipment fault prediction conclusion. Finally, taking main fan oil station circulating oil pump and motor of heavy oil catalytic cracking unit and nine stages of bearing damage as monitoring objects, the fault predictions was implemented by the following steps: data collection, feature extraction, dimension reduction of big data and expert system with the fusion of fuzzy neural network, and it is proved that the expert system with fuzzy neural network based on dimension reduction can greatly improve the convergence speed.