bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Adaptive Intrusion Detection Algorithm for In-vehicle CAN Bus Based on Periodicity of Message
Authors: Jiang Wenqi , Li Zhongwei , Tan Kai , Guan Yadong , Tong Weiming 
Published: January 2021

Abstract
Alongside with the convergence of In-vehicle network (IVN) and wireless communication technology, In-vehicle CAN communication with external networks reinforces the connectivity among systems of a vehicle. Vehicle communication is facing severe challenges. Intrusion detection technology is one of the most widely used technologies to ensure the safety of In-vehicle CAN communication, so an adaptive intrusion detection method for In-vehicle CAN bus based on message periodicity is proposed. Communication load of CAN bus in the vehicle, the unique priority mechanism and transmission waiting mechanism of CAN message cause a certain fluctuation in the message cycle. The influence of this fluctuation on the detection accuracy of intrusion detection algorithm is analysed while rules are determined by establishing and optimizing the detection threshold in order to further improve the accuracy. Experimental results show that the adaptive intrusion detection based on message periodicity can effectively detect injection and interruption attacks.
Prediction of Mechanical Properties of Glass Fiber Reinforced Epoxy Resin Matrix Composites Based on Homogenization Method
Authors: Wang Rui 
Published: January 2021

Abstract
A cell model of glass fiber reinforced epoxy resin matrix composite was established under the environment of finite element software Abaqus. Unidirectional deformation in six directions applied to the cell, and the average stress and average strain of the cell was obtained. According to the homogenization idea of the composite, the material for cell was supposed to three-dimensional orthogonal anisotropy homogeneous material. According to the relationship between elastic deformation stress and strain, the elastic modulus of homogeneous material were obtained as the elastic modulus of composite material. Compared with elastic modulus obtained by the experimental measurement or theoretical calculation, the effectiveness of the method was verified.
Use neural network algorithms to securely detect HTTP traffic
Authors: Pei Qiugen , Huang Dawen 
Published: January 2021

Abstract
HTTP traffic security detection is inseparable from the support of algorithms. However, in the traditional security detection methods, the classification ability of the algorithm is weak, resulting in detection results lower than expected. Therefore, based on neural network algorithm, a new HTTP traffic security detection method is studied. This research designs a collection module to collect HTTP traffic data. Structural features and statistical features are extracted to build a sensitive thesaurus. Based on neural network algorithm, HTTP traffic security is detected. The experimental results show that compared with the traditional detection methods, the detection method studied has better classification effect and the abnormal traffic data obtained is more accurate. It can be seen that under the application of neural network algorithm, the detection effect of the detection method has been further improved.
Particle Filtering Tracking Study of Automatic Extraction Tracking Range
Authors: Cao Jian , Wu Da 
Published: January 2021

Abstract
What needs to be solved is the problem of automatic tracking of pedestrians in a complex monitoring environment. In the actual monitoring environment, there are usually chaotic scenes, noise, light changes, and constant changes in human motion, in this context, the post-test probability and observation probability are non-Gaussic, nonlinear, so the framework of particle filtering is chosen to solve the pedestrian tracking problem. In target modeling, human motion is non-rigid body deformation, and color features for the target plane rotation, non-rigid deformation, partial masking and other situations are more robust, so in tracking pedestrians to choose color features. This paper proposes an overlay algorithm that automatically selects the maximum attribute area to determine the trace area. Finally, this paper uses color features to realize the automatic tracking of pedestrians under the theoretical framework of particle filtering.
Vanishing Point Detection based on Line Set Optimization
Authors: An Xiaoyun , Zhao Tongzhou , Jin Shanju , Yang Chengwan 
Published: January 2021

Abstract
Vanishing point detection plays an important role in camera calibration and 3D scene reconstruction. There are usually a lot of parallel lines in the real scene. Vanishing point is the intersection point of these spatial parallel lines projected onto the image. Commonly used Hough algorithm to detect vanishing points, which has high complexity and low efficiency. This paper proposes a vanishing point detection algorithm based on optimization of line set. Firstly, the LSD algorithm is used to detect the line. Secondly, the extracted line set is optimized to remove the invalid interference line in the image, which improves the accuracy of vanishing point detection. Thirdly, K-means algorithm is used to cluster and group the optimized line set, which improves the overall efficiency of the algorithm. Finally, random sampling fitting algorithm is used to fit the grouped line set to calculate the precise vanishing point. Compared with Hough algorithm, the running speed of this algorithm is improved by 19% in the actual scene. The experimental results show that the algorithm has low complexity and short running time.
The 2D-LC-ESPRIT algorithm based on Massive MIMO
Authors: Wu Yan , Li Ting Hui 
Published: January 2021

Abstract
This paper proposes a 2D-LC-ESPRIT localization algorithm based on Massive MIMO, aiming at the problem of high computational complexity caused by positioning accuracy caused by abundant antenna array resources. Firstly, the antenna matrix is partitioned, then the received signals are superposition and dimensioned. And then the eigenvalues and corresponding eigenvectors are obtained by solving the cross-covariance matrix. Finally, simulation results show that the performance of the proposed algorithm is improved compared with the traditional two-dimension ESPRIT algorithm.
Research on Carbon Emission Index Data of Turbine Unit Based On Variable Parameter Operation
Authors: Tu Changhuan 
Published: January 2021

Abstract
At present, the problem of climate warming caused by greenhouse gases dominated by CO2 has become the focus of global environmental governance, and China is facing severe pressure of carbon emission reduction internationally. In this paper, from the perspective of the operation of coal-fired units, based on the CO2 generation coefficient of unit standard coal consumption, combined with the consumption difference analysis, the influence degree of the main controllable operating parameters such as the pressure, temperature of superheated steam and reheated steam of the units, as well as the boiler exhaust temperature, on Qco2

, that is, the sensitivity of Qco2

to the changes of each parameter is studied. On-site operating personnel of the unit can focus on monitoring and real-time adjustment of controllable operating parameters that have a great impact on Qco2

, so as to ensure that the unit is at a low carbon emission intensity level, thus reducing the total carbon emissions of coal-fired power plants. Finally, through experiments, it is proved that the steam turbine parameter optimization method studied in this paper can provide higher unit efficiency and reduce carbon emission level.
Control on Abnormal Data Overflow of Distribution Network Management Platform
Authors: Li Bo , Zhao Ruifeng , Lu Jiangang , Guo Wenxin , Liu Yang 
Published: January 2021

Abstract
A large amount of system operation and equipment status data in current power systems are recorded and stored in text form, and text analysis has become an important basis for power system operation analysis. However, the current research still lacks relevant experience in applying it to the disposal of abnormal data spills in power grids. Therefore, the text-oriented data mining is first introduced in the paper to explain its basic concepts and implementation processes. Then, combining text grid-related data abnormal spillover requirements, text analysis and decision-making methods are proposed. Finally, considering actual development and application situation, the implementation benefits are analyzed. The experiment proves that the data abnormal overflow control technology studied in the paper can effectively guarantee the normal operation of the system.
Research on Subjective Evaluation Index of Infrared Image Processing Quality
Authors: Xu Hanwen , Zou Lanlin , Yao Changyu 
Published: January 2021

Abstract
With the continuous development of image technology, the quality of image processing has also been greatly improved. But its evaluation index is limited to objective evaluation, which results in high image quality but poor visual quality. However, subjective evaluation does not have specific indicators, it cannot be quantitatively detected, and it is poorly informatized and highly dependent on the observer’s knowledge background and emotions. Therefore, this study has conducted research on subjective evaluation, and proposed to use three-dimensional volume rendering and reconstruction as the auxiliary index of subjective evaluation to achieve the effect of stereoscopic image and reduce the degree of subjective dependence on the observer. The experimental analysis shows that the method has high practical application value and obvious effect, and can be used as an auxiliary index for subjective evaluation.
Application of Hybrid Monocular SLAM Method in Augmented Reality
Authors: Zhang Zuoming , Wang Hanwen , Shu Man , Wang Xin 
Published: January 2021

Abstract
In this paper, we design a hybrid (semi-direct) approach to simultaneous localization and mapping (SLAM) for monocular cameras and apply it to augmented reality (AR) for monocular cameras. We combine the advantagesof the direct method and the feature point method. We use both photometric bundle adjustment which is robust to camera exposure time and motion bundle adjustment which is geometrically robust based on feature points to do tracking process. This approach can maintain an intuitive direct local map as well as a reusable global sparse feature point map. Through the processing of point clouds, such as PCA plane detection and grid reconstruction, we greatly improve the effect of the augmented reality system.
Research and Application of Smart Contract Based on Ethereum Blockchain
Authors: Huang Yuxin , Wang Ben , Wang Yinggui 
Published: January 2021

Abstract
With the rapid development of blockchain technology and the increasing demand for partial decentralization of the Internet, the application of underlying technology based on blockchain has been widely concerned. Along with decentralized objects, the programmable financial system represented by Ethereum has been gotten more and more attention. However, smart contract sacrifices its security to improve decentralization. So Ethereum has the fatal problem with a large number of users, and negligence of users in coding contract threatens the entire Ethereum network. Therefore, this paper aims to research and expand applications of smart contract usage in Ethereum blockchain. We start from basic concepts to define structure of Ethereum, and then discuss security issues on smart contract. In the end, an optimized smart contract application of auction is implemented, which is useful for further consolidating and understanding of smart contract in practice.
The Impact of Primary Frequency Control of WTs on Ultra-Low Frequency Oscillation
Authors: Yang Lei , Zhang Xiaojie , Huang Wei , Wu Chen , Li Shengnan , Chen Yixuan , Kang Hongkai 
Published: January 2021

Abstract
Since entering the 21st century, as wind power develops rapidly, wind power plays an increasingly important role in the safe and stable operation of power systems. Since the wind turbines under traditional control don’t provide frequency support, the frequency dynamics of the power grids after load disturbance will be deteriorated. Thus, wind farms are required to equip primary frequency control in many countries. Most existing researches on primary frequency control of wind turbines focus on control strategies and the impact on system frequency, but few studies pay attention to the impact of primary frequency control of wind power on ultra-low frequency oscillation. This paper first proposes an analysis framework for ultra-low frequency oscillations in power systems with wind power. On this basis, a motion equation model of wind turbines is established. Finally, an extended three-machine nine-node system is used as an example to analyze the impact mechanism of primary frequency control on ultra-low frequency oscillation. The impact mechanism provides reference for the design of primary frequency of wind turbines in some regional power grids with ultra-low frequency oscillation.
Design and application of component-based automatic test system software
Authors: Yang Yang , Yan Tao , Zhao Xiucai , He Wenan 
Published: January 2021

Abstract
Aiming at the problems of low reuse and long development cycle caused by the increasing complexity and scale of automatic test system software, this paper describes the design of a component-based automatic test system software. The essence of this design is to design the general functional modules into relatively independent components by analyzing the software requirements of typical test system, and to carry out the research and development of modular software to improve the reuse rate of software modules. The practice of a large number of projects has proved that the software design of componentized automatic test system accelerates the speed of software development and improves the quality of system products.
Experimental Study on the Effect of Medium in Optical Path on Digital Image Correlation Measurement
Authors: Tang Xiaojun , Tang Caiyan , Zhang He , Yu Juan , Li Haixia 
Published: January 2021

Abstract
To explore the effect of optical media on digital image correlation measurement, the experiments of digital image correlation measurement under different optical media conditions were carried out. By analyzing the speckle images non-special optical path medium, common ordinary glass medium and quartz glass medium in the optical path, the effect of medium change in the optical path on digital image correlation measurement is discussed. The results show that the effect of different optical media on the accuracy of digital image correlation measurement is different, and the effect of optical media on absolute displacement measurement is much greater than that of rigid body displacement measurement. The effect of optical medium on different measuring areas is also different. The effect of quartz glass state on strain measurement is greater than that of ordinary glass. The effect of optical medium on the measurement of vertical optical axis displacement is much less than that of optical axis displacement measurement. Whether ordinary glass or quartz glass is added, the measurement error of camera optical axis direction is much larger than that of vertical optical axis direction; the stability of DIC displacement measurement in different optical path media is in turn ordinary glass medium, quartz glass medium and non-special optical path medium.
Identification and analysis of vehicle traces in traffic accidents
Authors: Cao Silin 
Published: January 2021

Abstract
this article in view of the different types of traffic accidents of vehicle trace difference analysis, including motor vehicle accidents, accident of motor vehicles and non-motor vehicles, motor vehicles and solid content etc., combining with the factors influencing the accuracy of the vehicle trace identification results, by studying the vehicle trace identification in judging whether had collision with other vehicle, clearing the accident vehicle type, vehicle crash site, determining vehicle relative direction, clearing the specific application of hit-and-run vehicle. Its purpose is to improve the level of vehicle trace identification and to speed up the handling of traffic accidents.
Research on Countermeasures of Intelligent Manufacturing Training Base Serving Local Industry Collaborative “Three Chains” Innovation
Authors: Zhu Ximing 
Published: January 2021

Abstract
With the needs of the transformation and upgrading of the manufacturing industry and the continuous iteration of high-end technology, the service transformation of enterprises and the service of local industries by higher vocational colleges are strategic challenges that schools and enterprises need to face together. Research has found that technological innovation and school-enterprise cooperation model innovation can promote service-oriented transformation, but there is currently a lack of in-depth interpretation of the synergistic interaction between the two. This article takes the intelligent manufacturing training base of higher vocational colleges serving local industries in Liaoshen as an example to study the dynamic interaction mechanism of the deep integration of schools and enterprises under the background of manufacturing technology and service transformation. The author puts forward the process mechanism of school-enterprise cooperation on the industrial chain of local industries and other “three chains” collaborative integration and innovation. The research result of this paper is to find that the mode of intelligent manufacturing training base is the key to the transformation and upgrading of manufacturing enterprises to serve local industries. At the same time, the author finds that the transformation process of manufacturing enterprises is a process of industrial chain collaboration, integration and innovation.
Design and Development of Database System for Turning and Milling Compound high-speed Machining
Authors: Li Zhou , Feng Lin Jun , Chao Miao Ying 
Published: January 2021

Abstract
In order to realize the advantages of high-speed cutting machine and improve the efficiency of high-speed cutting, a turning and milling compound high-speed machining process database was studied. According to the data information of cutting lathes, workpiece materials, tools and high-speed machining parameters, the functional requirements, system roles and system data relationships of the database system were analyzed. Based on the above information, the functional module, basic database, user permission and system architecture were designed, and a compound high-speed machining database system which is suitable for lathes and milling machines was developed.
Research on Key Performance Evaluation Technology of Intelligent Unmanned Platform
Authors: Zhang Qi , Su Yiming , Yang Shuiwang 
Published: January 2021

Abstract
According to the evaluation requirements of ground unmanned platform, this paper designs from three aspects: main function evaluation, technical index evaluation and tactical index evaluation, and preliminarily forms the evaluation method of unmanned platform, which lays the foundation for establishing relevant technical specifications of unmanned platform.
Lip Viseme Analysis of Chinese Shaanxi Xi’an Dialect Visual Speech for Talking Head in Speech Assistant System
Authors: Lu Zhao , Czap László 
Published: January 2021

Abstract
Recently, multimedia, especially animation, has played an important role in language learning. It has made a significant contribution to the language learning process of the hearing impaired for learners of all ages, especially the 3D animation of virtual teachers in computer-assisted language learning applications. Researches on viseme in various official languages and 3D facial animations have emerged in various countries. This paper has done lots of work in order to created Chinese Shaanxi Xi’an Dialect viseme data base by lip viseme analysis. Series of lip visemes frame data was gained by processing this dialect images and videos taken by camera. The classification of the lip viseme of this dialect also made based on the lip viseme classification of Mandarin. This work has great significance to create realistic 3D facial animation of this dialect.
Digital core image registration based on SIFT features
Authors: Wang Yuxue , Zhang Xue 
Published: January 2021

Abstract
In this paper, SIFT features and FLANN matching are applied to digital core image registration to achieve the purpose of fast digital core image registration. In this paper, three groups of digital core images data are used to carry out experiments from different aspects of rotation, brightness, translation and the combination of the three. The experimental results show that the method in this paper can effectively perform digital core image registration.
The reform of modern education during the COVID-19 pandemic
Authors: Xu Yan , Tang Qianqian 
Published: January 2021

Abstract
Great changes have taken place in modern education methods under the influence of the COVID-19 pandemic. Information science technology has broken through the time and space limits of education, as well as the boundary between physical and virtual objects in learning, and has converted the process of learning from passive to active. These characteristics just meet the needs of education under the challenges of the COVID-19 pandemic. Therefore, the new education mode which integrates information science technology has been developing rapidly during this period of time. This paper summarizes how the development of modern information science, especially network technology, multimedia technology and virtual reality technology, has influenced modern education. Meanwhile, our efforts and work in regard with digital museum will be introduced in this article.
An Infrared small target detection method based on local contrast measure and gradient property
Authors: Li Xiang , Xu Guili , Wu Quan 
Published: January 2021

Abstract
Infrared small target detection plays an important role in infrared search and tracking applications. In order to solve the problem of detection has high false alarm rates and low probabilities with complex backgrounds. An infrared small target detection method based on local contrast measure and gradient property (LCG) is proposed in this paper. Initially, the contrast map of the input image is calculated using the modified local contrast measure which is employed to enhance target and suppress background. Then, according to the property of distribution regularly around the target, the gradient map is calculated from the input image to further suppress clutters. Next, the feature map is achieved by integrating the local contrast map and gradient map in a pixel-wise multiplication manner. Finally, an adaptive threshold is used to extract the target region. Experimental results on two real sequences demonstrate that the proposed method has a good performance in background suppression and target enhancement. Besides, the proposed method has satisfying robustness under complex backgrounds.
Research on training top-notch applied talents of statistics based on OBE concept
Authors: Tian Xiujie , Cheng Chunlei , Wu Di 
Published: January 2021

Abstract
In the context of big data, the massive amount of data generated at all levels and fields of society and economy has made the market for top-notch statistical talents increasingly demanding. However, the current training of statistics professionals is mostly curriculum-oriented. It pays more attention to theoretical knowledge while the effect of practical ability training is not good. It is teacher-centered and ignores the fundamental goal of student learning results. Reform the training model of top-notch applied talents in statistics from the perspective of OBE education concept, that is, to be oriented by industry needs, clarify the learning outcomes and graduation requirements of statistics to reform the teaching system, then cultivate top-notch statistical talents who can meet the needs of the times and social development.