bluuebunny/crossref_metadata_2025_split huggingface dataset:
Summary of research on stability of independent microgrid based on high permeability distributed generation
Authors: Wang Qun , Li Feng , Sun Baohua , Huo Yingzhe 
Published: March 2020

Abstract
The independent microgrid with high-permeability distributed generation is greatly constrained by the natural environment and economy, and lacks the support of large grid in operation. At the same time, the large-scale use of power electronic equipment such as converter will cause its stability problem to have new characteristics compared with the traditional grid, and therefore become the key of research. This paper summarizes the characteristics of microgrid stability, points out the problems existing in applying the traditional definition of power system stability to microgrid, and gives the definition and classification of the stability of the independent microgrid with high permeability DGS; reviews the analysis methods of microgrid stability from three aspects of signal stability, transient stability and voltage stability respectively; discusses the guarantee of microgrid stability The control method of signal stability and the technical measures to improve the transient stability of the microgrid are discussed. Finally, the key problems of the stability of the independent microgrid with high permeability distributed generation that need further study are summarized and prospected.
Application of Prony Algorithm Based on EEMD for Identifying PSS Parameters
Authors: Hao Qiu 
Published: March 2020

Abstract
Some problems may caused by controller poor optimal control performance because of PSS parameters are hard for debugging, this paper proposes EEMD (Ensemble Empirical Mode Decomposition) and Prony algorithm combined online identification method for power system low-frequency oscillation. Firstly the EEMD is used to deal with the unstable signal and select the IMF (Intrinsic Mode Function). Secondly the model parameters of low-frequency oscillation in power systems are obtained by analyzing the IMF with Prony algorithm. Finally the PSS parameters have calculated through the residue method base on oscillation system dominant mode. Simulative results of case study show that it is better to identify the dominant mode of the signal. The proposed method has a certain reference value for engineering application.
Research on the Influence of Distributed Wind Power Access Location on Power Supply Reliability of Distribution Network
Authors: Ouyang Jianna , Li Shan , Zhou Yangjun 
Published: March 2020

Abstract
In order to study the influence of distributed wind power access location on power supply reliability of distribution network, this paper adopts the method of simulation and comparative analysis. Distributed wind power with the same capacity is connected to 10kV distribution lines at different location on ETAP (Electric Transient Analyzer Program) simulation platform. The reliability indices of distributed wind power at different access location are analyzed. Results show that the accessing of distributed wind power can improve the reliability of 10kV distribution network effectively, and when the distributed wind power is connected to the end of the feeder, the improvement of the reliability of the system is more significant.
Location Optimization of Distributed Generation Based on Improved Particle Swarm Optimization Considering Permeability
Authors: Xing Yahong , Wang Zheng , Zhao Haibo , Shen Zeyuan , Wang Yao , Zhang Zhi , Hu Ende 
Published: March 2020

Abstract
Currently, existing location methods are difficult to adapt to increasingly distributed generation (DG), owing to the rapid growth of distributed accessing scale and the uncertainty of time and space in new energy generation. In this paper, a novel combined Greedy algorithm (GA)/particle swarm optimization (PSO) is proposed for optimal location of DG on distribution systems. The impact of different access locations of distributed power sources on network loss and voltage distribution of distribution network is analyzed. Considering the minimum network loss and voltage stability, the permeability range of different access modes to distributed power generation is proposed. Finally, the feasibility of this method is verified by IEEE-33 node distribution network.
Broadband and Tunable Active Microwave Absorbing Element
Authors: Xing Yahong , Wang Zheng , Zhao Haibo , Xue Lei , Li Qi , Xue Chao , Zhang Jia 
Published: March 2020

Abstract
In this paper, a new type of electrically tuned microwave absorbing material working in microwave band is proposed. The metamaterial unit consists of is composed three layers of metal and two dielectric substrates spaced apart like a sandwich structure. The varactor diodes and lumped element are embedded as active circuit components in slots of the top metal patch. By adjusting the bias voltage of the varactor diodes, the absorption band can be adjusted, that is to say, the absorption frequency can be reconfigured. The active absorbing material has great application potential and lays a foundation for the next generation of intelligent absorbing materials.
Attention residual convolution neural network based on U-net (AttentionResU-Net) for retina vessel segmentation
Authors: Zhao Shun , Liu Tao , Liu Bowen , Ruan Kun 
Published: March 2020

Abstract
Extraction of retinal vessels from fundus images is one of the basic steps for diagnosis of diabetic retinopathy. Although some scholars have proposed several segmentation methods, this segmentation is still challenging due to differences in retinal vascular network and image quality. At present, the main challenges of retinal vascular segmentation are noise (due to uneven light) and capillaries. Due to the high complexity of retinal vascular characteristic information, the existing algorithms exists some problems such as microvascular segmentation and optic disc segmentation, We propose a network segmentation model based on fusion residual block, Attention mechanism and U-net, Firstly, the image was enhanced by limiting contrast histogram equalization. Secondly, Gamma correction is used to improve image brightness information and reduce artifact interference. Finally, AttentionResU-et segmentation model is used for segmentation. This algorithm was tested on DRIVE dataset, and its AUC reached 97.93%.
Analysis of the Efficiency of China’s Cold Chain Logistics Enterprises from the Perspective of Green Supply Chain
Authors: Sun Xu , Gao Lan , Lan Yongqiu 
Published: March 2020

Abstract
China’s economy is developing rapidly, and the development of cold chain logistics is on the right track. With the expansion of market demand, people have put forward higher requirements for the safety and quality of cold chain logistics, which provide opportunities for the development of cold chain logistics enterprises. In recent years, due to the deterioration of the world environment and the continuous consumption of resources, green sustainable development has become an inevitable trend of society and the development of the times. The drawbacks of the traditional cold chain logistics continue to be highlighted. If the cold chain logistics enterprises with high energy consumption and serious pollution want to obtain the opportunity of survival, they must integrate the concept of green development into the company’s operation and management. Based on this, the paper builds a performance evaluation system for cold chain logistics enterprises based on green supply chain, and uses fuzzy analytic model to evaluate enterprise efficiency. After research, it is found that the scale but the low efficiency is an important reason that affects the development of China’s cold chain logistics enterprises. In order to achieve green and efficient operation, enterprises must accelerate capital management, and at the same time optimize talents and technology to gain market share in the wave of green sustainable development.
Research on Micro Service Architecture of Power Information System Based on Docker Container
Authors: Qian Lin , Chen Haiyang , Yu Jun , Zhu Guangxin , Zhu Jiyang , Ren Chunlei , Mei Zhu , Pang Hengmao , Xu Mingjie , Wang Lin 
Published: March 2020

Abstract
With the development of energy internet, the complexity of power information system is increasing day by day, and the ecosphere of cooperation and sharing among different industries is gradually formed. Based on Docker container technology and Kubernetes container layout technology, this paper studies the design principle and top-level architecture of power information system micro-service platform, and proposes the implementation scheme of service discovery, message communication and load balancing in power information system micro-service. Finally, the performance of the system is verified by simulation experiments.
Evaluation on the emission reduction benefits of China’s Carbon Trading Pilot
Authors: Zheng Tianli , Liu Ning , Zhu Jianling , Qi Zhaoyu , Hu Jianbo , Xiong Hongxia , Sun Jiahui , Peng Shitao 
Published: March 2020

Abstract
Evaluation on the emission reduction effect of the carbon trading pilot is very important for China’s energy conservation and emission reduction. This paper uses the generalized linear model to evaluate the emission reduction effects of China’s carbon trading pilot. The results show that existing Carbon Trading Pilot slow down the relative increase of carbon emissions in the pilot areas, and their emission reduction effect is relatively obvious before and after the establishment of the carbon trading pilots from 2010 to 2012. However, as time goes by, the emission reduction effects in the adjacent period become weak. Therefore, it is necessary to implement the national carbon market as soon as possible to promote the energy saving and emission reduction of national province scale.
Research on carbon emission reduction based on the optimization of transportation structure under VAR model
Authors: Li Yuqian , Zhang Qiong 
Published: March 2020

Abstract
In the process of rapid economic development,protecting the environment has becomean important task.As the world’s second largest greenhouse gas emission sector, the transport sector’s emission reduction situation is not optimistic. Based on the theoretical mechanism analysis of the impact of transportation structure on carbon emissions, this paper studies the impactof transportation structure change on carbon emissions, aswell as the duration,degree and response direction of transportation structure optimization and carbon emissions.Based on the empirical results, the dynamic interaction mechanism between structural factors and transportation carbon emissions is discussed in the hope of contributing to environmental protection.
Study on the Strategy of Mass Health and Physical Fitness Promotion in Tibetan Plateaus from the Perspective of Environmental Science
Authors: Yang Ying jie 
Published: March 2020

Abstract
Based on the methods of literature, questionnaires and mathematical statistics, the health status and physical fitness activities of Tibetan plateau people are studied based on environmental factors. In response to the existing problems, it is recommended that the management department rationally and scientifically avoid environmental unfavorable factors in the context of “precise poverty alleviation” and “counter aid construction”, and take measures to promote the physical health and physical fitness activities of the Tibetan plateau masses. We will promote the implementation of the national fitness program in Tibetan areas and accelerate the poverty alleviation in Tibetan areas.
Design and Implementation of Vulnerability Scanning Tools for Intelligent Substation Industrial Control System Based on Openvas
Authors: Xia Yongjun , Wang jin , Liu Chang , Yu Kaiming 
Published: March 2020

Abstract
This paper analyses the current status of the intelligent substation industrial control system network and the main problems of security protection methods. Based on the analysis of the characteristics of intelligent substation industrial control network, a vulnerability scanning system based on OpenVAS is designed. The vulnerability scanning system is superior to the original vulnerability scanning system in performance and functionality, which effectively improves the security performance of the entire system and reduces system risk.
Research and analysis on parameter identification of model system based on running, gymnastics and other physical exercise population
Authors: Gou Xiaoping , Zhang Wanjun , Guo Qiurong , Li Bingze , Yang Chunhua , Zhang Feng 
Published: March 2020

Abstract
The increase of population in running, gymnastics and other physical training is an important factor in improving the quality of sports in China. By establishing the model system parameter identification of running, gymnastics and other physical exercise population in old areas of Shaanxi, Gansu and Ningxia, and using the method of random sampling of social survey, 900 college students were investigated. It also conducted in-depth research on the parameter identification of running population, gymnastics population identification and other types of sports population parameter identification, and through the analysis of parameter identification patterns, increased the number of running, gymnastics and other sports students’ sports population. It provides a reference for the study of college students’ sports population. The simulation results verify the feasibility and effectiveness of the parameter identification method of the model, which is of great use and reference value in the research of scientific research theory.
Recent Progresses on Detection of Mercury Ions for Protecting Vegetable Products Safety
Authors: Xing Yanxia , Zhu He , Chang Guifang , Yu Kexue , Yue Fengli 
Published: March 2020

Abstract
In vegetable industry, heavy metal pollution is a serious problem, which possesses a serious impact on the human health, hinder the development of vegetable industry. It is valid to promote the detection of mercury ions for protecting food safety, especially, vegetable is a sensitive kind of agriculture product for it need amount of water to irrigate, which would bring exogenous mercury ion into it. Among them, mercury ion (Hg2+) is the most poison substance. Detection of mercury ion includes atomic absorption spectroscopy, atomic fluorescence spectroscopy, inductively coupled plasma mass spectrometry, although they have high detection sensitivity, but no information compared their differences for pointing which one is more suitable for detection of mercury ions in vegetable processing industry. Thus, we reviewed the advanced detection skills in analysis of Hg2+, and pointed that anisotropic characteristics of gold nanorods to achieve differential imaging under polarized light microscopy is the suitable method to analysis Hg2+. As well as, we gave a prospective for the future of this detection skill.
Division of Driver’s Vision Plane Based on K-means Cluster Analysis
Authors: Ji Bingkui , Yao Xueping , Men Yuzhuo , Li Mingda 
Published: March 2020

Abstract
The division of the driver’s vision plane is the basis of study on the driver’s fixation objects and area of interest. This paper firstly collected the driver’s eye movement data through a large number of real road tests. Then, considering the driver’s areas of interest in driving, the K-means clustering was adopted to cluster plane coordinates of the drivers’ the fixation points to divide the driver’s vision plane. Through the comparison of the clustering results, the best clustering result was selected, and the driver’s vision plane was divided into eight regions. Finally, this paper studied the distribution of the drivers’ fixation points in each region at parking, straight going, left turn and right turn. The results have verified the higher accuracy of the K-means clustering for the division of the driver’s vision plane.
Application of Blockchain Technology in Pet Medical Industry
Authors: Zhang Huajie , Wu Shaofei , Wang Shenkuo , Xia Ning 
Published: March 2020

Abstract
According to the development status of the pet diagnosis and treatment industry, it can be found that the industry is still on the rise at present, but the island phenomenon of information in the traditional medical industry information system also exists. The authenticity and timeliness of information interaction cannot be guaranteed, and Problems such as difficulties about industry chaos and data access also limit the development of the industry. This paper puts forward a model of pet medical data sharing based on block chain, and it has many characteristics, such as safety reliable, decentralized applies to resolve such problems as pet medical industry data sharing. The existing consensus mechanism has been improved, and then the solutions of the model and the possible impacts are discussed and analyzed by comparing the problems of the industry.
Research on Principle and Application of Convolutional Neural Networks
Authors: Zhou Hang , Sun Qichen 
Published: March 2020

Abstract
At present, in the field of image recognition, convolutional neural networks have become a research hotspot. Based on the neural cognitive machine, it further reduces the complexity of network models.Convolutional neural network (CNN) has the characteristics of simple structure, less training parameters and strong adaptability because it reduces the weight of nodes.In this paper, the network structure, neuron model and training algorithm of convolutional neural network are studied. On the basis of this, the application of CNN in shape recognition is taken as an example, and the related network structure and experimental results are given.
Anomaly Detection of Arm X-Ray Based on Deep Learning
Authors: Wang Jingchen 
Published: March 2020

Abstract
The goal of this paper is to determine whether the arm has a fracture by detecting the X-ray of the human arm. This paper used the Keras deep learning framework and use the NASNetMobile model for training. The data set is MURA-v1.1, and the test accuracy on the verification set is about 70%. After downloading X-ray photographs of fractured arms, this paper performed an anomaly detection of the single image to test the accuracy of the model.
Design on the Cultivating mode of Applied Talents Based on the OBE
Authors: Liu Renshan 
Published: March 2020

Abstract
The upgrading of social industry requires a large number of applied talents. Cultivating applied talents is the objective requirement of the transformation and development of local universities. OBE (Outcome-Based Education, which is expected to result oriented education) is a kind of education structure mode, which takes learning outcomes as the center to organize, implement and evaluate education. This paper systematically expounds the connotation and theoretical basis and characteristics of OBE education. Through the concept of OBE education, the paper designs process of formulating objectives and standards of cultivating applied talents, at the same time, integrates the curriculum system with the project decomposition method. Research and practice shows that the cultivating method based on OBE can effectively improve the engineering practice ability and innovation ability, which can to provide operable theoretical guidance for developing high level applied talents cultivating.
Handwritten Digital Image Classification Based on PCA Dimensionality Reduction
Authors: Li Xingxing , Duan Chao , Zhi Yan , Yin Panpan 
Published: March 2020

Abstract
Dimensionality reduction is an important idea in machine learning. In the machine learning, some high-dimensional data sets are often encountered. In the case of high-dimensional data, data samples are sparse and distance calculations are difficult. Such problems are serious problems faced by all machine learning methods. “Dimensional disaster.” In addition, linear correlation between features is easy to occur in high-dimensional features, which means that some features are redundant.
Research on Group Risk Security Decision Based on BP Neural Network Algorithm
Authors: Wang Yue , Lu Na 
Published: March 2020

Abstract
Aiming at the uncertainty and diversity characteristics of risk assessment objects in group decision making, this paper proposes an information security risk assessment method based on BP neural algorithm. The paper gives a detailed risk assessment process and evaluation method for group decision-making security. The established group decision-making risk assessment system adopts the BP neural network method, which is a non-linear method, without obvious subjective components and human factors, making the evaluation results more effective and more objective. The example shows that the calculation results are close to the success story results
Intelligent Control System of Water and Fertilizer in Greenhouse Based on Tomato Phenotype Discrimination and Growth Environment Prediction
Authors: Qiu Qin , Cao Shanshan , Kong Fantao , Zhou Xiangyang , Han Shuqing , Sun Wei 
Published: March 2020

Abstract
In this paper, the real-time greenhouse tomato phenotypic parameters data were obtained, and the current tomato growth and growth status were identified based on the in-depth learning method. Combined with the tomato phenotypic parameters data under the optimal water and fertilizer conditions, the comparative analysis was carried out. According to the difference of phenotypic parameter data of tomato, the deficiency status of water and fertilizer was identified, and the target scheme of water and fertilizer was determined. Based on LSTM neural network model, the predicted value of environmental parameters was obtained, and compared with the standard value of environmental parameters for the purpose of stopping irrigation and fertilization.
Vortex Beam Generation Method based on Spatial Light Modulator
Authors: Peng Kaifei , Shen Xueju , Huang Fuyu 
Published: March 2020

Abstract
Aiming at the problem that the vortex beam is difficult to obtain under laboratory conditions, a vortex beam generation method based on spatial light modulator (SLM) is proposed. The collimated laser beam is modulated into a vortex beam by uploading a spiral phase mask attached to a grating on a SLM. Simulation results verify the effectiveness of the proposed method. The beam obtained from the experimental results also conforms to the properties of the vortex beam.
Study on the Quality Difference between Hainan Ruijin Black Pork and Ordinary Pork by MR Imaging
Authors: Yang Fang , Xu Jianmei , Li Jiping , Huang YuYan , Lin Qing 
Published: March 2020

Abstract
This study is based on low field nuclear magnetic resonance (LF-NMR) to detect water content, and discuss with the Hainan Ruijin Black Pork and common lean pork differences at the molecular level, which provided data support for Hainan Ruijin Black Pork as brand pork. From the ratio of peak apex time and peak area of combined water, non-flowable water and free water, the difference between the two kinds of pork can be seen. Hainan Ruijin black pork has a lower peak time than the free water T23 of ordinary lean meat type pork, but the ratio of T23 peak area is high, indicating that the cell gap between Hainan Ruijin black pork and water is tight and the water content is high.
User Preference of Different Artificial Intelligence Level in Vehicle System
Authors: Ma Jun , Zuo Yuanyang , Gong Zaiyan 
Published: March 2020

Abstract
With the development of artificial intelligence technology, the functional requirements of the vehicle central control panel becomes various and abundant. This work studies the preference degree of the user’s in different artificial intelligence level, which is of great significance to the application research of artificial intelligence technology in the car interaction design. This paper uses the driving simulation test method to conduct experiments. Through the qualitative research on 20 users, the Chinese users’ preference has been studied, which provides a new research content for the application of artificial intelligence technology in the driving process.