bluuebunny/crossref_metadata_2025_split huggingface dataset:
Thinking about the Practical Teaching Reform of Equipment
Authors: Deng Bin , Hu Yamin , Wang Jingjing , Hu Yahui 
Published: October 2020

Abstract
This paper focuses on the demand of equipment application guarantee for talent cultivation under the new situation, researches on the practical teaching reform of equipment, analyzes the necessity of practical teaching reform of equipment under the new situation, probes into the current situation of equipment teaching practice, and based on this, studies in-depth the thinking and direction of practical teaching reform of equipment from the perspective of teaching mode, teaching platform construction and teaching team construction and other three aspects put forward specific reform measures to provide reference for the comprehensive plan of practical teaching reform of equipment, so as to promote the quality of teaching and personnel training.
Unknown Protocol Identification Based on Improved K-Means++ Algorithm
Authors: Feng Tian , Man Dapeng , Fu Hao 
Published: October 2020

Abstract
In recent years, the gradual popularization of mobile terminals and the vigorous development of the network have spawned the birth of a new Internet structure and promoted the growth of network traffic. Behind such a large network, effective supervision of network traffic is the cornerstone of network security protection. At present, many studies on the direction of network supervision focus on the analysis of unknown network protocol types. The protocol identification method combined with machine learning is a hot topic in this kind of research. This method extracts data stream features and builds data sets, using machine learning algorithms. The model analyzes unknown network traffic and can obtain better recognition results than traditional network protocol analysis methods. Aiming at the problem of unknown traffic identification, this paper proposes a reasonable unknown traffic identification algorithm. The feature normalization preprocessing, feature selection, LOF outlier analysis, etc. are introduced. The clustering process uses the K-Means++ algorithm, and the maximum local reachable density point in the outlier analysis is used to realize the initial cluster center point. Accurate positioning.
Power Loss Reduction Practices in the Supply Area of a Typical Substation in Huangshan City in China
Authors: Hu Liwen , Yao Dequan , Hua Yin 
Published: October 2020

Abstract
The negative impact of distribution power losses is often passed down as costs to customers. Besides, the percentage of distribution losses is one of the important indicators to evaluate the performance of a distribution company. Therefore, minimizing distribution power losses shall be one of the key objectives of a distribution company. In this paper, a typical case of power loss reduction and the project’s effect in the supply area of a typical substation in Huangshan city in china are given to demonstrate the common practices that China uses to reduce technical distribution power loss.
Dynamics Simulation Method of 3D Virtual Motion for Vehicle Based on GTENG Engine
Authors: Chu Weijun , He Xiaohui , Liu Qing 
Published: October 2020

Abstract
The self-developed GTENG engine technology is a complete set of real-time 3D engine based on Microsoft Windows, and the underlying interface is for above directx9.0 version. GTENG engine adopts real-time computer graphics algorithm, including computer graphics and highly optimized physical simulation algorithm set. This paper introduced two ways of using CVehicle of GTENG Engine to simulate vehicle motion, and illustrated the method of defining the amount and number of wheels and setting the scene node pointer associated with the wheel in initialization of vehicle. Further, we discussed setting their coordinates and determining the relation of nodes combined with 3D modeling, and gave the methods of setting other parameters including mass, traction, steering torque, wheel radius, shaft distance, drag, frictional factor and wheel number. At last, we analysed relevant dynamics simulation functions and their calculation in CVehicle to control the motion state of vehicle. The application shows that the simulation method of using CVehicle in GTENG Engine can be spread to write the other instances of dynamics simulation.
Detection of Ethnic Minority’s Symbols Based on Deep Learning
Authors: Feng Ye , Shi Zhuo , Kong Qian , Li Mingrui , Yang Ming , Zhang Mengxue , Zeng Shuzhen 
Published: October 2020

Abstract
Symbols are the embodiments of the ideology of ethnic minorities, the detection of ethnic minority’s symbols is an important part of the protection and inheritance of ethnic cultural heritage. Nevertheless, the ethnic symbols are miscellaneous and referred to some special combination style, it is time-consuming and inaccurate to detect them only by traditional detection methods based on machine learning. Therefore, in this paper, we propose a deep learning method based on Faster R-CNN to detect various kinds of Zhuang minority’s symbols from the Z-S dataset. Firstly, the original images of Zhuang minority’s symbols are prepocessed. Secondly, the processed images are sent to the ResNet-50 with FPN to extract feature maps. Moreover, RPN processes those feature maps to generate bounding boxes. Finally, ROI pooling layer in R-CNN converts those bounding boxes into fixed-length feature vectors, which fed into two sibling fully-connected layers for further detection tasks. Through the ablation experiments based on a certain amount of ethnic symbol images, the results indicate that the proposed method has higher detection quality (mAP), and can effectively reduce the training cost.
Research on Optimization of Static Path Planning Algorithm for UAV Autonomous Flight
Authors: Xu Kaiming , Cong Zhouyu , Wu Zhigang , Yang Zhe 
Published: October 2020

Abstract
The combination of artificial potential field method (APF) and A* path planning algorithm can optimize the path planning problem in the UAV static map. The artificial potential field method also has shortcomings, especially in avoiding obstacles. The simple A* algorithm takes too long to retrieve. The fusion of the two can improve the effect of obstacle avoidance. This article attempts to improve this fusion method. In this article, we introduce the application of artificial potential field method, A* algorithm and improved A* algorithm in static path planning. Finally, we will compare the artificial potential field method combining A* algorithm and improved A* algorithm.
Research on Quality Control Modeling of Tobacco Production Supply Chain Based on House of Quality
Authors: Liu Yang , Ji Daoyuan , Dong Jinxin , Liu Di 
Published: October 2020

Abstract
Based on the tobacco management information system, this project establishes a double-loop quality feedback control model for a single logistics link and the whole chain in the tobacco processing and production supply chain. The quality control standard is introduced into the house of Quality, and the hierarchical house of quality control model of supply chain for tobacco.
The Hamiltonian Properties of Rectangular Meshes with at Most Two Faulty Nodes
Authors: Xie Yingtai 
Published: October 2020

Abstract
In this paper we consider the Hamilton cycle problem in the rectangular meshes with at most two faulty nodes. We prove that this problem is solvable in polynomial time with a corresponding algorithm. We provided an entirely new approach to this problem being different from the method early used on this problem.
Deformation and Stress Analysis of Bucket Foundation under Multiple Loads
Authors: Zhang Xu , Yang Wei , Lin Yifeng 
Published: October 2020

Abstract
Single-pile composite tubular foundation is a new type of offshore wind turbine foundation. Offshore wind turbine single-pile composite tubular foundation (PBCF) can have the bearing advantages of pile foundation and tubular foundation at the same time. The transfer of load between pile foundation and foundation tube is the key of pile-tube cooperative bearing. The wide and shallow tubular foundation is a new type of offshore fan foundation developed for the load characteristics of China offshore. The classical formula for calculating the bearing capacity of foundation cannot accurately calculate the ultimate bearing capacity of wide-shallow cylindrical foundation under composite loading mode. By establishing a large-scale three-dimensional simulation model of single-pile composite tubular foundation-foundation, calculating its stress and deformation under the combined action of various loads, and evaluating the stability of single-pile composite tubular foundation, we think it is an important means of tubular foundation design. The research results can provide references for the selection and optimal design of infrastructure.
Memory Performance Optimization of DTN Relay Node Based on M/G/1
Authors: Ji Changpeng , Han Xingmei , Dai Wei , Ji Wenxin , Wang Zirui 
Published: October 2020

Abstract
Delay/Disruption Tolerant Networking is an internetworking architecture for reliable data delivery. It combined with the actual application scenarios of M/G/1 queuing model and based on the data delivery mechanism of store-and-forward and retransmission under Bundle Protocol/Licklider Transmission Protocol in DTN. The data delivery time can be divided into two parts by the last round of LTP data segments transmission process, the custody queue length model of BP data unit (i.e. bundle) in relay nodes memory space is determined by calculating the retransmission time of LTP data segments spent in different delivery parts, which can directly measure the consumption and use of relay nodes memory resources. In order to obtain a more perfect memory resources allocation strategy, the optimized length of LTP data segment and the optimized number of bundles aggregated by per LTP block are proposed as the joint optimization scheme. The simulation results show that in deep-space channel environment where bundle arrival rate and bit error rate constantly change, the joint optimization scheme proposed in this paper can always maintain the shortest average queue length, which means, occupy less memory space. Compared with the queue without optimization, the queue length of the joint optimization scheme is reduced by 76.65%, which demonstrates the superior performance of this scheme, and realizes the reasonable optimization and utilization of the memory resources of the relay nodes in DTN.
A Research on the Priority of Power Distribution Based on Graph Computing
Authors: Mao Zhongqi , Xu Aidong , Hou Wenjing , Jiang Yixin , Lei Wenxin , Zhang Yunan , Li Qing , Wen Hong 
Published: October 2020

Abstract
With the construction and gradual development of microgrids, multiple interest themes have emerged in traditional distribution networks, such as distributed power sources, flexible loads, etc. Microgrids can be integrated into large power grids or operated as independent power grids. Effectively improve the power grid’s ability to resist disasters and ensure the safety of power supply within the grid. It can also effectively achieve high-quality matching of power supply and consumption and optimize the distribution of power resources within the network. The ability to fully and effectively solve the problems of grid connection of distributed energy sources such as wind and solar is of great significance to the reasonable planning of the power system and the safe operation of the power system. This paper proposes a planning evaluation system that takes into account the microgrid connection, constructs a graph calculation-based distribution priority division and a node model under the microgrid central control system, and uses the Mean-shift clustering algorithm to obtain node attributes. Use the optimal sequence graph method to calculate the index weight of the distribution network planning scheme, and finally calculate the distribution plan between nodes through the graph path finding algorithm.
Position Prediction Method Based on Improved Decision Tree
Authors: Wang Wenzhe , Yue Xi , Tang Mengxuan 
Published: October 2020

Abstract
C4.5 decision tree algorithm is one of the commonly used classification prediction algorithms. It is a tree structure. Its advantage is that the process of obtaining results is easy to understand and the calculation is small, etc. Its disadvantage is that it is easy to cause over-fit, and will be very complex when there are too many categories. In the process of analyzing skill proficiency and positions, different job positions are available for different levels of skill proficiency. When there are more job categories, the prediction effect of decision tree classification is poor and still needs to be improved. In this paper, an improved decision Tree algorithm WF_D-tree is proposed, which adds skill proficiency weight to each data in the data table. Through the calculation method of skill proficiency weight, the relative redundant data of table data are removed. Through the longitudinal calculation method of skill proficiency weight, dimension reduction of data. Experimental results show that the improved decision tree greatly reduces the running time of the decision tree algorithm in the job prediction, and also improves the accuracy of the prediction results. In terms of time, the WF_D-tree is also significantly higher than the decision tree before the improvement. In terms of accuracy, the decision tree was improved by about 11 percentage points.
Evolution and Hot Spot Analysis of University Public Opinion Analysis from the Perspective of Knowledge Map
Authors: Zhao Lili 
Published: October 2020

Abstract
In this paper, CiteSpace software is used to make statistics and Analysis on the literature related to public opinion research in Colleges and universities in China in recent years collected by CNKI, and visually display and analyze the literature data through the way of knowledge map, and also reveal the research status, research hotspots and trends in this field in a visual way. In recent years, the research in the field of public opinion in Colleges and universities has achieved sustained development, but there is a lack of high impact authors of core categories, and researchers have not formed a certain degree of concern; with the development of the network, the current research direction in this field mainly focuses on campus public opinion, network public opinion, emergency public opinion, new media public opinion, but the research force has not formed a scale We can rely on the new media and network technology to further expand the research of public opinion in Colleges and universities from the perspective of crisis management and ideological and political construction.
A Class of Optimal Cyclic Symbol-pair Codes from Combinatorial Designs
Authors: Yan Jie , Xu Xiaofeng , Wang Chengmin 
Published: October 2020

Abstract
Motivated by the application of high-density data storage technologies, symbol-pair codes were defined by Cassuto and Blaum recently. In this coding model, every two consecutive symbols are read together to address channels with high write resolution but low read resolution, so that individual symbols cannot be read off due to physical limitations. Since such kind of code was introduced, a lot of work has been carried out by many researchers, including upper bounds, constructions, decoding et.al. In this work, we continue the research on the construction of symbol-pair codes. We will present one special construction for cyclic symbol-pair codes from the perspective of combinatorial designs.
Integration of Big Data and College English Education
Authors: Zheng Saisai , Zhu Shengwen 
Published: October 2020

Abstract
With the arrival of the era of big data, the traditional English education has been difficult to adapt to the needs of social development. Under the background of big data, college English teaching needs to keep pace with the times. By analyzing the impact of big data on college English education, this paper discusses the innovative strategies of college English teaching. Only by making full use of high-quality resources in the era of big data, changing teachers’ traditional ideas, using data platform or learning software reasonably, and promoting the integration and development of various teaching modes, can the quality of college English education be improved.
Real Time Implementation of Terminal Security Policies Selection Based on Edge Computing
Authors: Xu Aidong , Wang Qianru , Jiang Yixin , Mao Zhongqi , Hou Wenjing , Zhang Yunan , Wen Hong 
Published: October 2020

Abstract
There are many kinds of terminals in the smart grid system, which have different functions and risks in the system. Different security policies are needed to protect the terminals. At the same time, the terminals will be subject to various attacks in operation. These attacks will change the security protection performance of terminals. Therefore, it is necessary to adjust the security policies in their operation. This paper proposes a real-time implementation method of terminal security policy selection under the edge computing based on the machine learning methods, which makes full use of the computing power of edge devices, adopts offline training and online judgment. The training of machine learning parameters can be completed in the edge side or in the cloud while the security strategies selection continues going on the edge computing side. By this way, the real-time training update and real-time selection of security policy in edge computing system are realized.
Fiber Bragg Grating Sensor Based Vibration Monitiring for Foreign Matter Invasion of Protective Barrier
Authors: Li Peng , Guo Yongxing , Fu Jianjun 
Published: October 2020

Abstract
A vibration monitoring system based on fiber Bragg grating is proposed to meet the need of protective barrier along the railway to monitor the foreign matter invasion. A high sensitivity fiber Bragg grating vibration sensor based on cantilever structure is developed. Three vibration sensors were deployed to a protective barrier with a length of 20 meters to conduct intrusion vibration monitoring test. Test results show that: 1) the fiber Bragg grating vibration sensor can well monitor the vibration signal; 2) the vibration intensity decreases obviously with the distance impact position increasing; 3) the response time of vibration measurement of different sensors is also in sequence when the distance impact location is different. Therefore, the magnitude of the external impact and the impact position in the protective barrier can be analyzed through the response amplitude distribution of each sensor and the response time sequence of the sensors.
Method for Identifying Abnormal Access to Sensitive Data Based on Network Flow
Authors: Ma Yong , Feng Jing , Li Jingyi 
Published: October 2020

Abstract
With the increasing scale and quantity of civil aviation information system, the data carried in the information system is becoming more and more important and sensitive. In the face of a large number of information systems, sorting out and monitoring whether passenger information in the information system has been accessed in violation of regulations is an urgent problem in the civil aviation industry. In this paper, the civil aviation business system is deeply studied, and a method of identifying abnormal access to sensitive data based on network traffic is proposed. Through the collection and analysis of network traffic, and then identify the sensitive information in the network traffic, and use k-means clustering method to classify the access behavior of sensitive information. Finally, combined with expert experience, the malicious access behavior for sensitive data is accurately identified.
Virtual SDN Network Embedding Algorithm Based on Load Balance
Authors: Ran Jinpeng , Wang Xiang 
Published: October 2020

Abstract
Aiming at Software Defined Network (SDN) virtualization environment, a virtual SDN (vSDN) network embedding method based on fruit fly algorithm is proposed to minimize the overall load imbalance and average control delay of the network. The simulation indicates that the proposed method improves the vSDN request acceptance rate. Besides, it has good load balance performance of the underlying physical SDN network, and reduces the communication delay for controller-to-switch.
An Improved Mask Approach Based on Pointer Network for Domain Adaptation of BERT
Authors: Lu Pengkai , Jiang Dawei , Li Ying 
Published: October 2020

AbstractPre-trained BERT model has shown its amazing strength on downstream NLP tasks by fine-tuning. However, the results with fine-tuned BERT will decrease when the model is directly applied to a series of domain-specific tasks. he original fine-tuning method does not consider accurate semantics of tokens in a specific domain. Different from random selecting, we present a more efficient mask method which utilizes a pointer network to decide which tokens should be preferentially masked. The pointer network sorts tokens in a sentence by their recovery difficulty. Then we train a BERT model to predict top tokens that are replaced by [mask] in original sentences. We tested the new training approach on biomedical corpora. Experiments show that the new trained model outperforms the original BERT model in some domain-specific NLP tasks while consuming extra domain corpus.
Research on Convenience Index of Urban Life Based on POI Data
Authors: Ye Xinyang , Tan Hongli , Zhang Yongzhi , Zhang Liang , Zhang Zhaohu 
Published: October 2020

Abstract
The urban life convenience index is the most important evaluation standard of the livable life. The convenience of residents’daily use of public and service facilities could represent the life convenience of people’s urban life. Analytic Hierarchy Process (AHP) is a decision method that decomposes elements related to decision-making into levels such as objectives, criteria, and programs to perform qualitative and quantitative analysis. POI data has the advantages of high coverage of public service facilities and widely coverage of data, so it is effective to calculate the life convenience index and establish the system for assessing the convenience index of city life based on the POI data and AHP. It not only provides a practical reference for the special planning of urban public service facilities, but also explored good methods for planning applications using opened data.
Study on Spatial-Temporal Characteristics and Influencing Factors of Network Attention: The Case of Guilin, China
Authors: Yao Jiansheng , Liu Yanling 
Published: October 2020

Abstract
To research the spatial-temporal distribution characteristics and influencing factors of tourism network attention is meaningful for understanding the current situation of the development tourism, revealing tourism customer market, and providing guidance for tourism planning, service, management. Took Guilin of China as an example and based on Baidu Index, this paper studied the spatial-temporal characteristics and influencing factors of tourism network attention by using seasonal concentration index, variation index, geographic concentration index, coefficient of variation and regression analysis. The research found that mobile network attention has a major share and has obvious seasonality. The PC network attention occupies a low share, which is not affected by the peak seasons, but fluctuates periodically with working days and rest days. In Guilin, the main factor influencing the time distribution of the network attention is precipitation, and the climate comfort has not reached a significant level. The regional distribution of the network attention is neither centralized nor balanced. The population size, the network development and the distance are important factors affecting the spatial distribution of network attention.