bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research and Detection of Fast-flux Botnet
Authors: Yang Lu , Gan Gang 
Published: March 2021

Abstract
With the development of Internet technology, there are more and more network attack modes. APT attacks, as one of them, will have a very serious impact due to its concealment, long-term nature, and purpose. Fast-flux botnets are widely used in APT attacks due to their spreading power and destructive power. This article first introduces the basic structure and related knowledge of FFSNs, and then summarizes and compares the previous papers on Fast-flux botnet research. In order to effectively detect the Fast-flux botnet, this experiment removed features that require a lot of resources and uncertain factors, and adopted a more convenient feature AA, which became a more lightweight detection model. At the same time, because the automatic update module of the detection system will promptly feedback the current traffic situation in the network, it will greatly improve the accuracy. The experimental results of the CTU-13 and ISOT public data sets show that the detection method proposed in this article Compared with other methods, the accuracy rate is increased to 98%.
Spatial-Temporal Evolution and Correlation Effect of FDI from China, Japan and South Korea to ASEAN
Authors: Liu Shuguang , Feng Xiaoshu 
Published: March 2021

Abstract
The economy of East Asia is related to the overall development of Asia and even the whole world. Use ArcGIS to analyze the spatial-temporal evolution and the time series from 2004 to 2018 to construct the correlation effect model of FDI from China, Japan and South Korea to ASEAN to analyze the correlation effect of cumulative impulse response and variance decomposition. The results show that FDI from China, Japan and the South Korea in ASEAN increased significantly, and the investment location choice of the three countries in the ASEAN was relatively stable and had similarities and differences. The FDI from China and Japan to ASEAN mainly focuses on cooperation and synergy for a long time, while there is competition between Japan and South Korea, and the FDI from Japan to ASEAN has a deep influence on China and South Korea. The FDI from China, Japan and South Korea to ASEAN is not a zero-sum game. It is also known as the investment cooperation mode that multiple parties make investment in the same region over time, in different industries in the same period and in different locations.
Research on the Application of YOLOv4 in Power Inspection
Authors: Sun Xingda , Hao He , Liu Yuan , Zhao Yuanyuan , Wang Yimeng , Du Ye 
Published: March 2021

Abstract
In order to meet the business needs of power inspection. The requirement is to identify the target quickly and in batches. In this paper, yolov4 convolution neural network is used as the technical to realize the target detection process of power inspection photos. Firstly, the training data set of power patrol inspection is accurately labeled by labelimg. Then it is trained by the deep learning framework of Darknet. And the results are satisfactory. The test results show that tthe Precision is 0.92 and the Recall is 0.904 after training by the self-designed training data set of electric power inspection target detection.This detection effect can meet part of the requirements of target detection in power inspection. However, there are two problems in this test: the lack of data annotation set in power inspection and the serious overlap of different objects in some photos of the data set. The author of this paper hopes the relevant researchers to correct and supplement.
A CFD Based Numerical Study of High-speed Refueling
Authors: Yang Ye , Liu Nan , Shao Weiguang , He Qiyang , Yin Haojie 
Published: March 2021

Abstract
Liquid holdup is an important indicator to evaluate fuel efficiency during high-speed refueling. This paper carried out a numerical study on the fluid flow as refueling a fuel tank based on the volume-of-fluid method in the commercial software FLUENT, and the effects of inlet velocity, injection angle, nozzle diameter, and the shape of the tank on impact phenome-non were examined and the corresponding relationships between these factors and the liquid holdup were found by a series of single-variable numerical experiments. The results indicate that: a smaller impact angle (30°-60°), lower inlet velocity (2.5-10 m/s), and larger nozzle diameter (36-40 mm) could result in a higher liquid holdup, and a tank with a square cross-section presents higher and more stable liquid holdup than that of a racetrack-like one. Besides, the effect due to the tank shape is greater than those of the inlet velocity, injection angle, and then the nozzle diameter. This work could be helpful for the design and control of a high-speed refueling equipment.
Human Activity Recognition Based on Residual Network
Authors: Zhang Jingxuan , Qiao Shaojie , Lin Zhiyu , Zhou Yang 
Published: March 2021

Abstract
With the development of information technology and the blooming of artificial intelligence, human activity recognition (HAR) has become a hot research topic. HAR has a certain prospect and practical value for mobile medicine and security monitoring, which has attracted the attention of many researchers. However, most of the existing HAR methods rely on the shallow feature learning mechanism, and the features learned by these methods are not completely consistent with the actual activities. To solve this problem, a human motion recognition method based on residual network (ResNet) is proposed. In addition, we modified the internal structure of ResNet by limiting the number of its network layers within a certain range to prevent over fitting and degradation. Our proposed method has better recognition performance than methods using pure convolutional neural networks(CNN), and it achieves 95.66% recognition accuracy.
Performance Evaluation of Cubature Kalman Filtering and Extended Kalman Filtering Based Phase Unwrapping For Insar
Authors: Liu WanLi , Zhang Qiuzhao , Zhao YueYing 
Published: March 2021

Abstract
Phase unwrapping is one of the most critical steps in InSAR data processing. Filter-based phase unwrapping methods can perform phase unwrapping and noise removal simultaneously, and show a clear advantage in dealing with high noise and density fringe interferograms. Based on the precision estimation theory of nonlinear functions in Extended Kalman Filter (EKF) and Cubature Kalman Filter (CKF) algorithms, we derive and analyze in detail the estimated precision of the EKF and the CKF on nonlinear observation equations in the phase unwrapping model. Results show that both EKF and CKF algorithms have similar precision in areas with better phase quality. However, in poorer quality areas, the precision of the two shows a certain difference and there is no consistent superiority for each algorithm. Experiments using simulated and measurement data confirm the validity of our theoretical analysis.
Evaluation and Analysis of GPS Operators Based on Multi-Layer Hierarchical Analysis
Authors: Wen Yanjie , Xu Wangtu 
Published: March 2021

Abstract
As a complex process, road transportation is restricted by many factors. In order to carry out safety management of road transportation, this paper puts forward an evaluation index system with multiple risk factors for the service providers of satellite positioning system (GPS) for tourist buses, long-distance passenger vehicles and dangerous goods vehicles. Through the construction of multi-level analytic hierarchy process (AHP) for the comprehensive evaluation of safety production and related management of satellite positioning operators, the weight evaluation model is obtained; and the evaluation results are compared with the neural network model by using linear regression model. The experimental results show that: in terms of evaluation, the average absolute error of neural network model is 0.137, and the hierarchical model is 0.232, the former is slightly better than the latter; in terms of stability, the hierarchical model performs best. Comprehensive comparison shows that hierarchical model has better performance in evaluation accuracy and stability. The method proposed in this paper provides technical support for the evaluation of satellite positioning operators.
The Application of Corpora on the Lexical Approach
Authors: Yuan Fei , Zhang Shichunzi 
Published: March 2021

Abstract
The linguistic scholars has used word frequency for research for a long time. With the rising of corpora study, researchers pay a lot attention to words and their frequency information, and even develop the teaching approach and teaching book. The Lexical Syllabus, The Lexical Approach and Data-Driven Leaning introduced by this paper are the representative of the development of corpora. From the background of this research, this paper gives the definition of some relative concepts, and discusses the arrangement of lexical syllabus and teaching content, and uses examples to explain the practice of The Lexical Approach.
Research on Classification Mining of Tank Driving Simulation Training Data
Authors: Deng Qing , Tan Yaxin , Zhai Kai , Luan Weizhen 
Published: March 2021

Abstract
Training with tank driving simulator is an important method to improve equipment operation skills. In view of the deficiency that it is difficult to find knowledge and rules from complex training data by statistical analysis method in the past driving simulation training, this paper proposes CSAGA-LSSVM algorithm to analyze tank driving simulation training data. Selecting key points to quickly generate shapelets, reducing the number of candidate shapelets; combining shapelets according to distance and time interval to enhance the ability of feature identification; designing adaptive genetic algorithm to dynamically adjust the probability of crossover and mutation to find the optimal parameter solution of least squares support vector machine. The algorithm is applied to the classification mining of shift operation data from a certain tank driving simulator to extract the operation characteristics of personnel.
Research on Compression Molding Process of Carbon Fiber Reinforced Polymer
Authors: Xie Jiuming , Wu Jin , Zhou Xuejun 
Published: March 2021

Abstract
The compression molding process of CFRP(Carbon Fiber Reinforced Polymer) is a multi-parameter coupled system, and its molding mechanism is very complex. Based on the Gel point and the glass transition temperature of the matrix material, the compression molding process of CFRP is divided into three sub-processes: thermal-chemical process, flow-compaction process and residual stress-deformation process, and the mathematical constitutive model of each sub-process is established. On the basis, the interaction and calling relationship of each sub-process are determined, which lays a foundation for the molding process simulation of CFRP and further analysis of its multi-parameter coupling effect mechanism.
An Information Model of Power Distribution IoT and Its Application
Authors: Liu Xianming , Sun Bowen , Cheng Ming , Qiu Rixuan , Wen Zhiming 
Published: March 2021

Abstract
Power distribution of Internet of Thing technology develops quickly nowadays, however, the basic information structure of power distribution IoT is still in research and development. This article raises a new information model of Power Distribution IoT and discusses logical topology, matching of measurement value for measurement point and isomorphic model of map location, it provides a consistent algorithm for information model of power distribution IoT as well. Based on existed research, a new hypothesis is raised, which focuses on the structure of connected data product of power distribution IoT and it discusses the process of how to realize the architecture further. Lastly, article introduces a successful research and development case of information model of Power Distribution IoT to prove practicability of it.
Research on Dust Generation Mechanism and Dust Reduction of Tidal Shotcrete in Underground Coal Mine
Authors: Dong Huihui 
Published: March 2021

Abstract
Through the research on the source and mechanism of the dust generated by the tidal shotcrete in coal mine, and the inevitability analysis of the tidal shot from the aspect of construction technology, the main influencing factors of the dust are summarized, and the tidal shot,which is The direction of concrete dust reduction and related measures.
Filling Missing Value Method for Power Quality Data Based on Correlation Analysis
Authors: Liang Yundan , Jiang Wei , Liu Weiwei , Lei Shuya , Lu Weijiang 
Published: March 2021

Abstract
A large number of monitoring indicators own strong correlation among them which help to better fill missing values in these sensor data. In this study, we propose an electric power quality data filling method based on correlation analysis. Firstly, normalized mutual information method is applied to deal with nonlinear correlation which makes up for the deficiency that the traditional Pearson correlation coefficient. Additionally, the measurement of correlation is calculated to obtain the closely correlated indicators. This study utilizes the regression model to build the strong regression model. Experimental results show that the approach can effectively improve the accuracy of filling, reduce the filling error, and improve the quality of data.
Zero-Shot Entity Recognition via Multi-Source Projection and Unlabeled Data
Authors: Yi Huixiong , Cheng Jin 
Published: March 2021

Abstract
With the widespread of transfer learning, great success has been achieved in named entity recognition on languages without labeled data. Prior works can be mainly classified into two categories: direct model transfer and annotation projection. However, these works only utilize part of available data, including monolingual word embeddings, labeled data in multiple source languages, and unlabeled data in the target language. To make full use of these data and extract more information, we propose to train multiple teacher models on multiple source languages via the annotation projection method. Then a student model is trained on the unlabeled data in the target language with supervision from all labels obtained from multiple teacher models. Extensive experiments are conducted on three benchmark datasets, and the experimental results prove the effectiveness of the proposed method.
Hyperspectral Open Set Classification towards Deep Networks Based on Boxplot
Authors: Liu Yu , Hou Jing , Peng Yuanxi , Xu Yunpeng , Jiang Tian 
Published: March 2021

Abstract
Recently, hyperspectral imaging (HSI) supervised classification has achieved an astonishing performance by using deep learning. However, most of them take the ideal assumption of ‘closed set’, where all testing classes have been known during training. In fact, in the real world, new classes unseen in training may appear during testing. Obviously, traditional supervised classification methods cannot operate correctly in the real world, which requires classifiers not only to classify known classes, but reject the unknown in order to avoid false positives. This challenge is called ‘open set classification’(OSC). Considering the increased applications of deep learning in the real world, rejecting unknown classes during classification is of vital importance. To tackle it, we present a simple but effective HSI OSC method toward deep networks. In this method, we tighten the decision boundaries of SoftMax function of the last layer of the deep networks by using boxplots to analysis the statistical characteristics of the probability distribution of known classes and generate a proper rejection threshold for each known class. To test the performance of the proposed HSI OSC method, experiments are conducted on three HSI datasets. The results show that the proposed method outperforms existing state-of-the-art HSI OSC methods.
An Improved Data Fusion Method for Water Quality Sensors
Authors: Wang Zhaoli , Xiao Jian , Yang Yiwei 
Published: March 2021

Abstract
This paper proposes an improved data fusion method for water quality sensors. First, a deep learning network model is formed by stacking automatic encoder and sparse automatic encoder, so as to realize feature mining and sparse representation of sample data. Second, after large-scale sample training, the network model may fit complex nonlinear functions, and has certain generalization ability for low-quality sample data. As a result, the accuracy of prediction and classification can be improved. The experimental results demonstrate that the proposed method can obtain higher classification accuracy.
Comprehensive Calibration Platform Based on Instrument-shared Networks
Authors: Lu Bing , Zhang Jun , Jian Zini , Zhou Wei , Wang Xianpei 
Published: March 2021

Abstract
In power test units at all levels, the calibration of equipment is one of the daily tasks. Various departments have repeatedly purchased many standard equipment, and some calibration tasks require moving the standard equipment to temporarily build a corresponding calibration system, which is expensive and unfavorable for the maintenance of the standard equipment. The paper proposes a comprehensive calibration platform based on the network sharing of instruments. The platform optimizes the standard equipment configuration of each department and automatically allocates the standard equipment on the platform according to the calibration task. Then it builds the calibration platform and completes the calibration task in accordance with the calibration process. The platform can perform multiple same or different calibration tasks at the same time and generate corresponding calibration certificates, which reduces the workload of calibration personnel and improves the reliability and utilization of standard equipment. The paper gives the model architecture and workflow of the platform. Experiments verify the effectiveness of the platform.
Study on Nonlinear Dynamic Numerical Analysis Method of the Suspension Crossing Frame
Authors: Zhao Jiangtao , Cheng Yongfeng , Xia Yongjun , Ma Yong , Peng Fei 
Published: March 2021

Abstract
At present, the calculation method based on statics does not consider the impact of the conductor on the crossing structure under the condition of disconnection or running. Therefore, the research on the element type of the suspension crossing frame and the conductor in numerical calculation and the behaviours of conductor breaking and running were carried out. Through the free swing test of the conductor, it was found that the conductor had certain flexibility under a certain length. Truss element should be selected to discretize the fiber rope of the conductor and crossing frame and this method could simulate the physical characteristics of the conductor and fiber rope objectively and truly. In the case of running line, the horizontal velocity of the conductor had almost no change along the axial direction of the conductor, while the vertical velocity presented a fluctuating distribution along the axial direction. In the case of the broken conductor, the horizontal and vertical velocity of the conductor were fluctuating along the axial direction of the conductor. The height of the conductor not only affected the horizontal velocity of the conductor, but also affected the vertical velocity of the conductor. It had important reference significance for the numerical calculation of nonlinear dynamics of the suspension crossing frame.
Correlation Analysis between NPP-VIIRS Nighttime Light Data and POIs Data —a Comparison Study in Different Districts and Counties of Nanchang
Authors: Wang Yuqian , Li Yue , Song Xuepeng , Zou Xin , Xiao Jiajun 
Published: March 2021

Abstract
The study of urban spatial structure is very important for understanding the relationship between people and urban infrastructure as well as urban planning . This paper selected the 2016-2019 NPP-VIIRS NTL data and POI data of Nanchang City to conduct a pixel-level correlation analysis of Nanchang urban districts and counties. Firstly, the NPP-VIIRS and POI datasets should be respectively preprocessed to synthesize NPP-VIIRS annual average dataset and the POI kernel density dataset. Secondly, these datasets were respectively subjected to logarithmic transformation. Finally, they were divided into administrative districts for linear regression analysis. Experimental results showed that the correlation coefficients between NPP-VIIRS NTL data and POIs data gradually decreased from urban to rural districts.
Research on Technologies of Vulnerability Mining and Penetration Testing for Satellite Communication Network
Authors: Dong Kun , Zhang Haixia , Liu Yanmei , Li Yang , Peng Yuanyuan 
Published: March 2021

Abstract
According to the specific characteristics of software, hardware and network protocols, the cyber security problems of satellite communication network have gradually attracted the attention of the industry in recent years. This paper proposes a technical framework including information collection and detection, vulnerability mining and penetration testing. It introduces mining methods such as taint analysis, symbol execution and fuzzy testing, and combines with machine learning algorithms to improve the efficiency and accuracy of vulnerability mining. It uses buffer overflow, SQL injection, cross-site attack and Trojan horse penetration to test the security of satellite communication network. It is helpful to improve the ability of proactive defense and security guarantee of satellite communication network.
Collision and Communication of Life and Death View of Buddhist Architecture in Jiangxi Province
Authors: Xu Feijin , Hu Yu , Xie Fang 
Published: March 2021

Abstract
Before India’s early Buddhist view of life and death was introduced into China, the traditional view of life and death of Chinese hundred schools had already formed a relatively perfect philosophy system, such as Mohism, Taoism and Confucianism. Their philosophy has a certain height of the discussion of life and death, and in this case, through the investigation of Jiangxi Buddhist architectural culture, from the perspective of Jiangxi to explore how the Buddhist philosophy is to change itself, and actively integrate into China and Jiangxi’s environmental secular world.
Finite Element Simulation of the Autoclave Curing Process of Aerospace Resin-based Composite Material
Authors: He Jun , Cong Fanglin , Cao Meng , Li Xiaodong , Wang Shuo 
Published: March 2021

Abstract
Due to the influence of the wall thickness, uneven heat transfer, and heat generation inside the resin during the molding of the composite material, the uneven temperature field distribution of the composite material is caused. This paper uses ABAQUS to perform finite element simulation on the temperature field of the forming process and obtains the distribution of the internal temperature field of the composite material. On the premise of obtaining the temperature field, through thermo-solid coupling simulation experiment, the influence of various factors on the entire curing process is compared. Based on the use of finite element simulation software, several comparative tests were carried out, and the residual stress problems in the curing process were verified by calling the stress and strain values of representative points. This article focuses on the analysis of temperature and energy data in heat transfer and 15 sets of stress-strain data under coupling action. On the premise of giving the reasons for each data, the accuracy and practicality of the data are analyzed.