bluuebunny/crossref_metadata_2025 huggingface dataset:
Primarily research on the mathematical problem-solving abilities of grade X Vocational High School students for Computer and Network Engineering Competencies
Authors: Oktari A , Permana D
Published: January 2021

Computer and network engineering are one of the skill competencies in Vocational high school. Graduates of this major are expected to have problem-solving abilities to be able to compete in the working world. Mathematics is a subject that can develop mathematical problemsolving abilities. This study aimed to see, review and describe the mathematical problem-solving abilities of students and draw conclusions about these things as the phenomena found and to review the conditions of the learning devices used and developed by the teacher. This research used descriptive quantitative research methods. The data was collected through interviews, observations, and giving tests. Data analysis techniques used descriptive techniques for the results of observation and interview data, and scoring rubrics for mathematical problem-solving abilities for test result data. The results showed that the students' mathematical problem-solving abilities were still not relatively low. Some of the factors that cause this are 1) the learning was still using the lecturing method so that learning became meaningless, 2) students were accustomed to copying and memorizing formulas given by the teacher without understanding them, 3) the learning tools used were the same for each skill program, 4) a mathematics learning approach had not led students to be actively involved in the learning process and had not guided students to construct their knowledge in improving mathematical problem-solving abilities. Based on these results, further action is needed in the form of research on the development of constructivism-based learning tools to improve the mathematical problem-solving abilities of students in the Vocational High School for Computer and Network Engineering Competencies.
Development of learning media based on to improve the mathematical problem solving abilities of grade 11 senior high school student
Authors: Fikriah E , Arnawa I M , Yerizon  , Asmar A , Bahri S
Published: January 2021

As it was found in many schools, the learning media have not helped educators in facilitating students in supporting an effective learning process. Learning tools which consist of a syllabus, lesson plans, teaching materials and learning outcomes tests that were used do not involve students actively. One effort that can be used is through discovery learning methods that are valid, practical and effective. Where this method was implemented by connecting the concept of learning with problems in everyday life and aimed to improve students' problem-solving abilities and teaching them how to solve problems until new knowledge was discovered by students. The aimed of this development was to produce a learning media based on discovery learning by using GeoGebra on valid and practical for second semester topic. This type of research was a development research using the Plomp development model which consists of three phases where the initial investigation, the development phase and the assessment phase. The research subjects were students of class grade 11 in Senior High School Number 2 Pulau Punjung. The results of the validity of the data analysis indicated the ddiscovery learning were in valid criteria in terms of content and validity of lesson plan with a percentage of 86.78% and the validity of worksheet was 82.24%. Practicality of learning media, attractiveness, comfort and time efficiency were 95% based on teacher questionnaire responses and 85.30% questionnaire responses for student learning media with discovery leaning method and the affectivity of discovery learning in term of completeness was 83. 87%.
Mathematical Problem Solving Ability Package A Elementary School Equivalents In PKBM Kasih Bundo Bukittinggi
Authors: Bayu E P S , Fauzan A , Armiati
Published: January 2021

Good learning can maximize the potential of students through various active and fun activities. No exception for equality education in the form of the package A equivalent elementary school program. But in reality learning in the Package A program still experiences various problems, especially in problem-solving abilities that apply mathematical concepts through higher levels of thinking. It can be seen from the low it results that the achievement of problem-solving ability averages less than 20%. This finding is supported by the lack of understanding of educators in terms of implementation, age diversity students, and the content standard is quite dense while learning activities are less than optimal providing meaningful experiences. For this reason, one form of learning that can be done with the right learning approach, one of which is RME. This approach will integrate mathematical problem solving abilities into its application.
Development of constructivism-based mathematics learning tools for eleventh graders
Authors: Hidayati F , Arnawa I M , Bahri S
Published: January 2021

Critical thinking skills are complex thinking abilities, so they can determine what students must believe and do. An attempt to improve the critical thinking skill is by applying the constructivist approach to the learning tools. The learning device was tested on students’ class XI of SMA N 2 Lubuk Basung. This research is development research that implements Plomp design. There are three stages that should be done. The first stage is the initial investigation stage (preliminary research). Next is the development stage (development or prototyping stage). Last is the assessment stage. This research is only limited to one to one stage because it is in the COVID-19 period. Three eleventh graders of SMA N 2 Lubuk Basung become the subject of this research. There are three instruments used in this study: validation sheets, student questionnaire responses, and interview sheets with teachers and students. If the learning tools satisfy content and construct validities, they are considered valid. The results of the validation of the RPP and LKPD experts were 0.95 and 0.96 with a valid category. The conclusion based on the research finding is that the constructivism-based mathematics learning tools for eleventh graders of SMA N 2 Lubuk Basung can be declared valid.
The Influence of Using Computers in Mathematics Learning to Students Mathematical Ability
Authors: Ulfa M , Yerizon  , Arnawa I M
Published: January 2021

The use of technology has entered all aspects of human activities, belonging education. The use of computer-based media in the learning process is very useful. This study aims to describe the results of various studies on the use of computers in the learning of mathematics. The method used is descriptive research. The aspects seen are the various types of software used and their effects on mathematics learning. Based on the results of the research, it can be concluded that the use of computers can help students visualize and understand mathematics material.
Research on the method of determining satellite state vector based on Kepler orbital parameters
Authors: Shao Changguo
Published: January 2021

to simplify the process of satellite orbit determination, can use limited conditions known to the calculation of satellite orbit dynamic state vector to determine satellite position to implement the standardization of satellite orbit, this paper introduces the satellite state vector at any time using the Kepler orbital parameters method, the calculation method of Kepler orbit parameters are mostly only for satellite without disturbing force movement. This paper is based on the three-point method which is used to calculate the orbit parameters of Kepler satellite in the case of satellite unphotographed.
Research on Visual Perception of Intelligent Robots Based on ADMS
Authors: Wu Changzhong , Ge Fan , Shang Guangchao , Guo Hengshuai , Wu Liang , Zhao Mingpeng , Wang Guitao
Published: January 2021

In application environments such as logistics, home services, and venue welcome, reliable and efficient autonomous environment modeling has become an urgent research need and technical challenge in the field of service robots. This paper introduces the three-dimensional simultaneous positioning and map creation (SLAM) of today’s highly potential (ADMS) technology research service robots, and uses cross-disciplinary research methods to carry out innovative theoretical research, principle derivation and experimental verification. The application of ADMS intelligent robots provides strong technical support.
Student Performance Protection Based On Blockchain Technology
Authors: Liang Xiao , Xu Shiyuan
Published: January 2021

In recent years, performance management has become more and more significant in terms of management and credibility of universities. They have to review student performance when issuing diplomas. Therefore, the reliability of student performance management is extremely important. Nowadays, many universities adopt a data-centralized management model. However, centralized database often brings about problems such as information leakage and easy tampering. With the development of blockchain technology, its decentralized and unforgeability characteristics have gradually attracted people’s attention. In order to prevent students’ scores from being maliciously tampered with, we utilize blockchain to design and implement a decentralized student score sharing management system. Moreover, by using the Ethereum smart contract to manage on-chain and off-chain data storage as well as on-chain query and verification, we ensure the traceability, tamper-proof, distributed storage, and the security of query process. Finally, this article explores the construction of prototype system based on the Ethereum environment. The experimental results show that the anti-tampering and traceability scheme proposed in this article is feasible. The application of blockchain can fully satisfy the needs of various participants in student performance management. Each subject’s information has a separate decryption private key, which perfectly protects student’s score information.
Research on Simulation Rendering Technology of Watercolor Painting Based on Canny Edge Darkening
Authors: Mai Xin
Published: January 2021

Watercolor painting is a branch of traditional painting art, which has a history of more than years of development. Watercolor painting has been widely used and popularized because of its bright colors, transparency, rich expression techniques, strong expressiveness, and simple production tools and materials. The artistic aesthetics of watercolor painting has a wide audience base, which is the premise of the research of watercolor simulation drawing. Edge detection technology is the basis of image measurement, image segmentation, image compression and pattern recognition and other image processing technologies, as well as the technical basis of watercolor digital rendering. Based on the Canny algorithm, this paper proposes a watercolor simulation drawing method based on Canny edge detection. From the experimental results, this method has a good simulation rendering effect.
State Evaluation of Circuit Breakers Based on Improved Fuzzy Comprehensive Evaluation Method
Authors: Wu Yuefei , Cao Na , Yu Qun
Published: January 2021

In order to quickly and effectively distinguish the operating state of the circuit breaker and improve the accuracy of the state evaluation, an improved fuzzy comprehensive evaluation model is proposed. The evaluation index is weighted based on the combined weighting method, which avoids the dependence of the traditional analytic hierarchy process on the subjective scoring of the weights. The gray correlation theory is introduced to modify the evaluation results, which effectively overcomes the inherent shortcomings of the principle of maximum membership. The improved fuzzy comprehensive evaluation method is applied to the state evaluation of circuit breakers, and the evaluation indexes are established through time parameters, speed parameters, circuit parameters and electrical characteristic parameters, and then a multi-layer fuzzy comprehensive evaluation model is established. Finally, the evaluation model is used to analyze the laboratory circuit breaker, which verifies the feasibility and effectiveness of the model.
Path planning using deep reinforcement learning based on potential field in complex environment
Authors: Jia Qingxuan , Yang Maonan , Miao Yu , Li Xulong
Published: January 2021

This paper introduces a deep reinforcement learning path planning method based on potential field for complex environment. Based on the potential field model in the artificial potential field method, we define states, actions, rewards in reinforcement learning, and use Deep Deterministic Policy Gradient (DDPG) reinforcement learning algorithm for optimization. By training robots in the environment, our method can effectively plan the path in a complex environment with massive obstacles, and avoid trapping in the local minimum region of the potential field.
Natural Thermal Convection Field Measurement Technology Based on Background Oriented Schlieren Technology
Authors: Chen Xi , Wu Min , Zhang Ming-Yuan , Yang Kai-Di , Liu Peng , Zhu Hai-Dong
Published: January 2021

Background oriented schlieren technology is developed from the combination of schlieren technology and PIV technology. It is an emerging non-contact flow field quantitative measurement method. The development and principle of background oriented schlieren technology are introduced in detail. A set of background oriented schlieren imaging system suitable for natural thermal convection field is built. The quantitative measurement research is carried out on the natural thermal convection field above the candle flame, and the density field is calculated. Distorted vector displacement map. The results show that the background oriented schlieren technology can be better applied to the quantitative measurement of natural thermal convection field, and it has broad development prospects.
A Method of Robot Grinding Force Control Based on Internal Model Control Principle
Authors: Wang Ting , Miao Hongbin , Shi Shangyao , Chen Zhenya , Zhang Huang
Published: January 2021

The application of robots in the grinding industry can solve the problems in traditional artificial grinding, such as high labor intensity, low work efficiency, unguaranteed processing quality and serious physical injury to workers. In order to ensure the grinding quality, it is necessary to control the grinding force. The aims of this study is use PID-IMC controller to control the grinding force. Carry on the robot dynamics analysis to establish the dynamics model. Based on the principle of internal model control (IMC), PID controller is optimized and PID-IMC controller is obtained, which is used to realize the constant force control of robot grinding. Simulation and experiments results show that, the dynamics model and control method proposed in this paper have a better effect in the control of robot grinding force.
Analysis of the Influence of the Number of Torque Converter Blades on Working Performance Based on the Response Surface Method
Authors: Xiong Pan , Sun Hongjun , Zhong Jiping , Zhen Chenping , Chen Xinyuan , Gao Huichao
Published: January 2021

To understand the effect of the number of torque converter blades on the performance of torque converters, in this paper, we employed computational fluid dynamics and the response surface method to optimize the design of the torque converter. The number of pump blades, stator blades and turbine blades were used as design variables, and the torque transmission ratio and pump capacity factor were used as objective functions for multi-factor optimization design. The results show that the number of turbine blades had no significant impact on the converter’s performance, while the number of pump blades and stator blades had significant impact and showed strong correlation. Compared with the original torque converter, the optimized converter increased the starting torque ratio by 0.12 and the efficiency by 4%. It shows that the computational fluid dynamics and the response surface method can be combined to determine the optimal number of blades in the design of torque converters to reduce the cost and experiment time.
Research on Machine Vision Technology of High Speed Robot Sorting System based on Deep Learning
Authors: Mou Hai Rong , Lu Rui , An Juan
Published: January 2021

Workpiece sorting is an important link in industrial production and transportation, which will directly affect the accuracy and speed of the workpiece. In the traditional manual sorting, we will be affected by the environment and subjective factors, which will cause visual fatigue error. With the rapid development of computer technology, the intelligence of robot is higher and higher, which has been applied to many fields. Robot sorting has many advantages, such as high speed, small inertia, high positioning accuracy, which has become an important part of industrial manufacturing and express transportation. For sorting system, we need to focus on machine vision technology and deep learning algorithm. Through image recognition and target tracking, we can provide accurate basic data. Through deep learning algorithm, we can intelligent sorting, which needs our in-depth study.
Knowledge Graph Construction of High-Performance Computing Learning Platform
Authors: Dong Tianyue , Tang Lei , Peng Jinye , Zhong Sheng , Luo Hangzai
Published: January 2021

With the development of intelligent education, it has become one of the more efficient learning schemes to construct the knowledge graph which can excavate the knowledge base. People generally use RDF triples and use languages such as OWL to construct knowledge graphs, but this method has problems such as limited expression ability and too much manual annotation. In this paper, we propose a framework that combines statistical language models, neural network language models, and clustering and clipping algorithms. When processing unstructured text data, unsupervised extraction of representative key words as features of the structured graphs’ entities, so that the processed entity information has more accurate semantics and human learning relevance, and the method of clustering and calculating the learning rate is used to further clarify the learning order and mastery of knowledge points. We have conducted extensive experiments to collect data from the two major modules of HPC high-performance computing courses and domains as datasets, and used this framework to build many knowledge graphs which can provide practical learning. The knowledge graph of this paper can be obtained from: https://v2.easyhpc.net:10000/knowledge Knowledge Graph Module.
Three different SVM classification models in Tea Oil FTIR Application Research in Adulteration Detection
Authors: Zhang Yu , Li Tinghui
Published: January 2021

Fourier transform infrared spectroscopy (FTIR), as a new type of rapid environmental detection technology, has attracted extensive attention from researchers. In this study, FTIR combined with stoichiometry was used to establish and study the qualitative detection model of tea oil-doped soybean oil and corn oil. Different spectrum preprocessing and feature value extraction were performed on the infrared spectra of 105 samples of tea oil and adulterated oil in the spectral band of 600-4000cm-1. The KS sample selection method was used to divide the training set and the test set, and the training set was used to construct Support Vector Machine (SVM) Classification model, select the best model construction method based on the accuracy of the test set. The results show that the SVM tea oil adulteration detection model with convolution smoothing ( SG ) spectral preprocessing and random forest ( RF ) feature extraction achieves the best accuracy of 0.93, which is simple, fast, and pollution-free for the market to detect adulterated tea oil. Provide technical reference.
Slam and navigation of indoor robot based on ROS and lidar
Authors: Yang Xiaozhuo
Published: January 2021

For indoor service robot, this paper designs an indoor robot based on ROS (robot operating system) operating system. The robot uses two-dimensional lidar as the core sensor to collect the depth information of the environment and uses SLAM algorithm based on particle filter to realize the robot mapping; Based on the framework of ROS, A* algorithm and DWA algorithm are used to realize the navigation function of the robot; The map and navigation are simulated in the gazebo simulation environment to verify the function of path planning, local obstacle avoidance and navigation.
Guided Policy Search Methods: A Review
Authors: Du Jinyu , Fu Jian , Li Cong
Published: January 2021

Guided policy search methods (GPSs) have become important methods in the field of reinforcement learning in recent years. GPSs are a kind of policy search methods that utilize trajectory optimization methods to generate training data, guiding supervised learning. In theoretical research, GPSs combine convex optimization and deep learning, and have achieved fruitful results. In practical applications, they have achieved good results in complex control fields such as robots learning, especially manipulator operations. This paper mainly elaborates the development process and improvement route of GPSs. Firstly, the theoretical knowledge related to the GPSs is introduced. Secondly, the framework and basic methods of GPSs are analyzed; Thirdly, various improved GPSs based on the basic methods are generalized. Finally, the development and future improvement directions of GPSs are summarized, and the problems and future development trends are discussed.
Research on Optimal Cooperative Attack Strategy of Multiple UAVs
Authors: Wang Wenhua , Wang Xiaoping , Liu Bo , Zhou Wen
Published: January 2021

Aiming at the problem of the optimal coordinated attack strategy of multi-UAV system against multiple moving targets in a known environment, a PMMAXQ layered reinforcement learning algorithm applied to multi-UAV cooperative attack is proposed. Firstly, the problem of multi-UAV coordinated strike, the successful strike conditions and the movement strategy of moving targets are described. Then the moving targets are allocated rationally through the 0-1 planning method. Finally, the MAXQ algorithm is improved by the Bayesian probability statistical formula. The simulation results show that, compared with the MAXQ algorithm, the PMMAXQ algorithm converges faster and the average cumulative reward value that the UAV can obtain is higher.
Research on the Performance of Character Convolutional Neural Network in Different Text Encoding Formats
Authors: Bao Zhiyao
Published: January 2021

With the continuous progress and development of society, text classification has become an important task in the field of text data mining and text value exploration. Compared with existing text classification technology, deep learning technology has many advantages, such as high accuracy and effective feature extraction. This paper is mainly based on the character convolutional neural network to study the classification performance of different texts, hoping to provide experience for related research work. Through research, it is found that character-level convolutional neural network deep learning technology can achieve Chinese text classification more effectively.
A Kind of new parallax algorithm based on symmetric continuous optimization
Authors: Jiang Kaiwen , Zhang Degan , Xu Haixia
Published: January 2021

With the fast development of 3D imaginations becomes more and more fascination, multi-view stereo based 3D reconstruction is a significant technique for those application. To facilitate the subsequent processing of 3D reconstruction and reduce the possibility of other algorithms falling into local optimal solutions, attempting to get better and faster performance, a new parallax calculation based on symmetric continuous optimization is proposed in this paper. The algorithm is proposed here will be tested respectively in the same data, in order to certificate the algorithm applied is better than traditional minimize El
algorithm.
A high-precision time-to-digital converter applied to CDC
Authors: Xin Xiaoning , Hu Yifan , Jian REN , Li Yuxuan
Published: January 2021

This paper presents a high-precision CMOS time-to-digital converter (TDC) applied to a capacitance-to-digital converter (CDC). The time-to-digital converter in the capacitance-to-digital converter is used to measure the time interval between the charging time of the capacitor under test and the charging time of the internal reference capacitor. The time resolution of the TDC directly determines the capacitance resolution of the CDC. In order to improve the measurement resolution of TDC, a TDC structure based on phase-locked loop (PLL) is proposed. This paper first gives a capacitance-to-digital converter scheme, and then introduces the time-to-digital converter used in the scheme. The frequency multiplication technology of the phase-locked loop optimizes the integral nonlinearity (INL) of the interpolator and greatly improves the interpolation of the interpolation ratio. The TDC was realized in a 0.13-μm CMOS process, and the measurable time interval is 21.14μs. When the external reference clock is 200MHz, the resolution is 40.3ps and only 31 delay units are needed.
Decision making method of University Asset Allocation Based on Deng’s grey relational analysis
Authors: Wang Hongrui , Jia Guangtian , Wei Ran
Published: January 2021

At present, most of the domestic colleges and universities have been using management information system which records the history and status of all assets in detail to achieve asset management. Mining and analyzing the huge asset data of colleges and universities can better provide scientific basis for university management and decision-making. This paper proposes to use Deng’s grey correlation analysis method to analyze the situation of assets replacement in colleges and universities, so as to provide decision support for asset allocation.
Improvement of Virtual Network Mapping Based on OpenVirteX
Authors: Zhang Yuan , Qin Jian , Li Xiaoping , Zhang Shiling
Published: January 2021

Network virtualization allows the flexible sharing of physical networking resources by multiple users (tenants). Each tenant runs its own applications over its virtual network. OpenVirteX, a network virtualization platform, provides virtual Software Defined Networks (vSDNs). Each vSDN is customizable in terms of topology as well as addressing scheme. However, the virtual network mapping process of OpenVirteX does not take into account resource constraints and deployment cost, just to complete the virtual network mapping. To solve this problem, this paper proposes to deploy the classic mapping algorithm named Improved-vnmFlib on the OpenVirteX platform and designs the overall process of implementation. Finally, we build a complete simulation environment to test the new platform, the test results show that the new platform can take a virtual network mapping combined with the deployment cost under the premise of resource constraints, and can create the virtual network automatically according to the mapping result.
Optimization of cable vibration response signal in cable force analysis of cable-stayed bridge
Authors: He Bozhou , Zou Lanlin
Published: January 2021

In the cable force detection of the cable bridge, the frequency method is the most suitable and most commonly used method. And in the application of the frequency method, the core issue is the pickup of the natural frequency. In the practice of the general frequency method, the natural frequency is often picked up by collecting the vibration response signal of the bridge cable, and then analyzing the spectrum to pick up the natural frequency. This method can be applied to most cables. However, for some cables with unsatisfactory acquisition signals, the periodicity of the signal on the spectrogram will not be obvious. At this time, further cepstrum analysis of the cable signal can better analyze the spectral period of the cable vibration response signal in order to obtain a more accurate natural frequency and calculate a more accurate cable force value.
Solving Approximate Nearest Neighbor by Hash Aggregate and Clustering in High Dimensional Euclidean Space
Authors: Hu Hangfei , Wang Hongya , Tan Zongyuan
Published: January 2021

Approximate Nearest Neighbor search has attracted great attention in the field of information search. The method based on Locality-Sensitive Hashing has good performance with probability guarantee, which needs m hash functions for collision detection. In the hash table corresponding to each hash function, collision counts are performed respectively during querying, which will result in additional collision counts and longer response time. To avoid the shortcoming, we aggregate the m hash values as the representation of the original data object. Then the aggregate values of all data objects in the dataset are clustered. In the process of querying, it is needed to find the class of the aggregate value of the query for searching. Experiments show the effectiveness of our method.
Wau: A User Authentication System Based on Channel State Information and Deep Neural Networks
Authors: Wang Zhengjie , Dou Wenwen , Huang Zehua , Zhang Chengming , Chen Da
Published: January 2021

Recently, user authentication techniques have attracted more attention and played a more important role in human-computer interaction applications. In this paper, we propose a user authentication system based on CSI (channel state information) called Wau. This system works in a device-free way and has no privacy violation because it facilitates the crucial characteristics of CSI that the unique CSI variation from different user activity can be measured and recognized. We adopt deep neural networks to realize the authentication of 8 people in three environments, including a through-the-wall scenario. The highest recognition accuracy reaches up to 98%. These results validate the feasibility and effectiveness of the user authentication system using CSI and deep neural networks.
Review on Quantum Walk Algorithm
Authors: Zhou Wenda
Published: January 2021

Quantum walk is the quantum version of classical random walk, which has shown great advantage over classical algorithms. In this article, main discoveries and breakthroughs along with several applications in the last two decades are reviewed and discussed. Reducing hitting time and diminishing mixing time, as two hot research fields, are addressed. Possibility of universal computation with more generic case of quantum walk is also mentioned. In the future, we can expect new methods and models being feasible ways to approach the theoretical lower bounds of related problems, as well as more efficient applications on specific scene.
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

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.
On the Formal Solutions of a Type of Singular Partial Differential Equations
Authors: Zhao Xuan , Li Pingli
Published: January 2021

In this paper, we research a partial differential equation with three complex variables. According to the theory of singular differential equations, it is proved by direct calculation that it has a special form of formal power series solution.
Prediction of Mechanical Properties of Glass Fiber Reinforced Epoxy Resin Matrix Composites Based on Homogenization Method
Authors: Wang Rui
Published: January 2021

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

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

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

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

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

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

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

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

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

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

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

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

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

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.