bluuebunny/crossref_metadata_2025 huggingface dataset:
Anthropometric Parameter Measurement from Equivariant Multi-view Images
Authors: Deng Lijiao , Yan Tingman , Zhao Qunfei
Published: July 2020

In this paper, we propose an anthropometric parameter measurement method that any customized parameter can be measured online by the pre-selected endpoints on the reconstructed 3D body models of equivariant multi-view images. The method includes 3D body model reconstruction, anthropometric parameter measurement, and parameter modification. In 3D body model reconstruction, we detect and segment the human body from its background and reconstruct a generative 3D body model from the segmented image with deep learning. And then we measure anthropometric parameter on the reconstructed 3D body model of each view. Before parameter measurement, we manually pre-select endpoints associated with all anthropometric parameters on the reconstructed 3D body model since all vertices of the reconstructed body model are ordered. However, the information of a single-view image is insufficient and the measurement result is varied regularly by the view changes. To improve the measurement accuracy, we design a convolutional neural network in the last step which can regress more accurate anthropometric parameters from equivariant multi-view measurements. Experimental results on the representative dataset demonstrate that the proposed method can measure planar and spatial anthropometric parameters automatically with comparable performance.
Automatic Attribute Learning for Person Re-Identification
Authors: Li Yang , Xu Huahu , Bian Minjie , Xiao Junsheng
Published: July 2020

Attribute based person re-identification is more robust to image appearance changes than low-level visual feature based methods. However, manual person attribute annotation has low efficiency, poor scalability and poor discrimination. Therefore, a scalable automatic attribute learning method for person re-identification is proposed. Firstly, the mapping matrix of person attributes is designed and generated automatically according to the principles of discernibility, sharing and low redundancy. Then the visual features are extracted using convolutional neural network and attribute classifiers are trained to detect person attributes, and the attribute based representation of person is generated. Finally, the person re-identification is carried out by comparing the similarity of the attribute based representations. Extensive experiments have been carried out on two common datasets Market-1501 and Duke MTMC-reID with the comparison to the Sate-of-the-Arts methods, the method achieved the best performance, which proves the superiority and effectiveness of the method.
Deep Reinforcement Learning based Path Planning for Mobile Robot in Unknown Environment
Authors: Wang Yang , Fang Yilin , Lou Ping , Yan Junwei , Liu Nianyun
Published: July 2020

It is a trend for robots to replace human in industrial fields with the increment of labor cost. Mobile robots are widely used for executing tasks in harsh industrial environment. It is an important problem for mobile robots to plan their path in unknown environment. The ordinary deep Q-network (DQN) which is an efficient method of reinforcement learning has been used for mobile robot path planning in unknown environment, but the DQN generally has low convergence speed. This paper presents a method based on Double DQN (DDQN) with prioritized experience replay (PER) for mobile robot path planning in unknown environment. With sensing its surrounding local information, the mobile robot plans its path with this method in unknown environment. The experiment results show that the proposed method has higher convergence speed and success rate than the normal DQN method at the same experimental environment.
Side Scan Sonar Image Geocoding based on Carrier Velocity Coarseness Correction
Authors: Kai Li
Published: July 2020

Gross error may occur in Geocoded side scan sonar image due to complicated water bottom environments and AUV maneuver. This paper presents a side-scan sonar image geocoding method based on carrier speed gross error correction. This method uses the side scan sonar image imaging principle and SIFT feature matching algorithm to calculate the AUV lateral velocity. This lateral velocity is used to detect and eliminate the gross speed error of DVL in underwater integrated navigation, and to perform gross error correction on the side-scan sonar image geocoding. This method can improve the performance of AUV underwater integrated navigation, and significantly improve the accuracy of side-scan sonar image geocoding.
Design and Implementation of a Desensitization Method of CT Medical Image based on DICOM
Authors: Yuan Jiantin , Wu Wei , Zhang Wenqiang , Lv Xiaoyi , Chen Chen
Published: July 2020

Medical big data, medical image processing and other fields are based on a large number of clinical data. Data desensitization is of great significance to the privacy protection of patients. CT image desensitization based on DICOM standard protocol only uses the strategy of hiding or deleting the data on the image, which greatly weakens the value of data use and cannot meet the normal value demand. Data desensitization should consider that it can still meet the needs of data mining and other applications on the basis of ensuring the privacy security of users. Based on the above application requirements, a strategy to anonymize patient identity is developed. Based on this strategy, a desensitization method that can meet the actual desensitization standards and analysis application requirements at the same time is proposed. This method can not only protect the privacy of patients to a great extent, but also ensure the availability and authenticity of desensitized data. In the future, this method has great potential in the application of CT image desensitization.
Prediction of Maximum Deformation of Single Nail Riveting Based on RBF Neural Network
Authors: Gu Jinyu , Yin Junqing , Chen Yongdang , Zhao Chengcheng , Cheng Yunfei
Published: July 2020

The influencing factors of riveting deformation are more complicated, and the specific relationship between the amount of deformation and each factor is difficult to express with general expressions, which is a non-linear problem. Aiming at this problem, this study uses RBF neural network to establish a model of the relationship between the maximum deformation of single nail riveting and various factors. Then, 1000 sample sizes were designed using the LHS method, with 90% of the sample size as training and 10% as testing. Secondly, the secondary development of the finite element software is carried out by using Python language to realize parametric modeling and batch processing. Finally, using the RBF neural network model to predict the maximum deformation of a single nail riveting, the maximum relative error and the average relative error were 8.43% and 2.948%, respectively. The results show that the RBF neural network can be applied in the field of prediction of maximum deformation of riveting and has high prediction accuracy.
From Artificial Neural Networks to Deep Learning: A Research Survey
Authors: Zhang Zhongwei
Published: July 2020

Deep learning (DL) is one of the hot topics in the field of artificial intelligence. As an extension of artificial neural network (ANN), deep learning models have more powerful learning and adaptation capabilities and they develop more and more rapidly. At present, because of the great advantages compared with the traditional methods, the development of convolutional neural network (CNN) is the hottest and it is widely used. This article first introduces the development of DL in chronological order and then analyses and summarizes artificial neural networks, and then uses the example of the LeNet-5 to explain the basic network structure of CNN and describe its training methods comprehensively. Based on the CNN model, many new convolutional neural networks with improved structure are analysed, such as AlexNet, ZFNet, VGGNet, GoogleNet and so on. The principle of each method is introduced in detail and the accuracy is compared with each other to conclude the correlation between the depth and the accuracy of DL. Then, for each method, it discusses some current problems existing in the corresponding method of DL, and points out future research and application directions worth exploring of each method. Finally, it summarizes the history of DL and the application of specific methods and the existing problems and solutions.
Design and Implementation of a Multi-scale Object Detection Algorithm on TensorFlow
Authors: Yanbin Chen , Huai Wang , Zhuo Han
Published: July 2020

The technology of object detection is a very important subject in computer vision task. It has been widely used in intelligent transportation, face detection, aerospace and medical image equipment. In this paper, a kind of object detection algorithm based on regression and region proposals is studied. We use a popular deep learning framework—TensorFlow, as the experimental platform. We propose a multi-scale object detection algorithm based on RPN region proposal network, which can extract the features of large and small objects by using the level of feature map. In addition, this paper also improves the classification regression model and proposes a two-dimensional loss function, which makes the region proposals closer to the groundtruth boxes in the final training, which makes the training process of the improved network easier. The experimental data set used in this paper is PASCAL VOC data set, the accuracy and speed of each category in 20 detection objects are calculated and analyzed. A number of experiments have proved that the proposed multi-scale object detection algorithm based on RPN have improved in accuracy and speed. The average detection precision on the PASCAL VOC dataset increased to 74.4%.
Design of Trajectory Tracking Algorithm of Isolated Observation Point Automatic Distribution Vehicle based on Visual Servo
Authors: Zhang Tao , Xu Ren-Ren , Zhang Jiu-Shi , Li Kun-Jie
Published: July 2020

The medical isolation observation point for epidemic prevention and control is an important part of the epidemic prevention and control link. With the attention paid by all countries to the epidemic prevention and control, the design and construction of the medical isolation observation point for epidemic prevention and control have put forward higher requirements. This design uses a visual servo-based automatic delivery car for trajectory tracking and research on the tracking algorithm to realize the automatic delivery car for the regular delivery of medicines, food and other daily necessities for isolated personnel. The application of automatic trolleys in the epidemic prevention and control medical isolation observation point can effectively alleviate the pressure on staff, avoid infection, and improve the efficiency of epidemic prevention. Aiming at the complexity of its motion trajectory, a tracking algorithm of vision and information fusion is used to implement the trajectory tracking of the smart car. The trend of the target trajectory is determined by the least square method. The image information collected by the image binarization algorithm is added to a certain anti-jamming program. The PID algorithm is used to optimize the control of the steering gear and the drive motor, improve the operating efficiency and system stability, and meet the actual application.
Trajectory Planning of Manipulator based on Improved Genetic Algorithm
Authors: Qiao Tieliang , Yang Daoguo , Hao Weidong , Yan Jingsen , Wang Ruiqing
Published: July 2020

Laser cladding technology has been used in many applications, and repair of high-value broken drills is one of them. Aiming at the problem of trajectory planning of cladding repair access sequence in multiple damaged areas of the drill bit, the trajectory planning of the cladding path is based on an improved genetic algorithm. Firstly, the modified D-H representation was used to model the manipulator, and the kinematics analysis was performed. Based on this, an improved genetic algorithm is used to select the optimal order of multiple damaged areas for the damaged parts that need to be repaired. In order to avoid falling into the local optimum, adaptive genetic operators are used, and an evolution reversal step operation is added to improve the search ability. Finally, the fifth-order polynomial interpolation method is used in joint space for trajectory planning. After simulation analysis, the path points obtained through genetic algorithm optimization can smoothly perform cladding repair operations in various areas.
Data Analysis of MYO Signals during Upper Limb Movements of Enhanced Exoskeleton
Authors: Lei Sun , Jialong Gao , Honglei An , Hongxu Ma
Published: July 2020

Equipped with enhanced exoskeleton in the individual combat system can effectively enhance the soldiers’long-term load-bearing capacity and enhance the combat effectiveness of the army. In the exoskeleton control system, accurate recognition of human movement intentions plays an important role as upper-level control. This paper uses MYO armband as a sEMG sensor to collect 8 channels sEMG signals. Neural network method is applied to estimate the joint angles during arm movement. Motion capture system is used to verify the estimation accuracy. PCA (Principle Component Analysis) method is performed on the 8 channels data collected by MYO and processed dimensions were selected by experiments to make the estimation accuracy the highest. The results show that when the principal component dimension is selected as 8, which makes the estimation accuracy of the joint angles the highest.
A Fault Diagnosis Model of Marine Diesel Engine Fuel Oil Supply System Using PCA and Optimized SVM
Authors: Hou Liangsheng , Zhang Jundong , Du Baisong
Published: July 2020

The fuel oil supply system of the marine diesel engine contains many components, which fits plenty of sensors to monitor the condition of all components. A fault sample consists of data collected from all the sensors at certain time, which lead the dimension of the fault sample is very high. When the ship is sailing, there is a randomness in fault categories and fault duration, which leads the fault data unbalanced. This paper proposes an appropriate combinational approach to address the above problems. First, to reduce computational complexity, the high dimensional fault samples are converted into the low dimensional ones using the principal component analysis (PCA). Second, a sample size optimization (SSO) strategy is proposed to address the problem of the learning from the imbalanced datasets, which improve the classification performance of support vector machine (SVM). Third, a three-dimensional Arnold mapping is introduced into the particle swarm optimization (PSO) algorithm to improve its generalization capability. Finally, the SVM optimized by the improved PSO is trained as the classifier to identify the ten faults in the fuel oil supply system. Results demonstrate that the average correct diagnosis ratio can be as high as 93.9%.
A Heuristic Rule-based Control Strategy Using for Series Hybrid Tracked Vehicles
Authors: Zhai R Q , Zou Y , Zhang X D , Zhang Z G , Lei H H
Published: July 2020

A heuristic rule-based energy management for a series hybrid electric tracked vehicle is proposed and verified in this paper. Based on the results of equivalent consumption minimization strategy (ECMS), the new control strategy extracts the optimized control rules and considers the fuel consumption and battery manners together by adjusting the control mechanism. The series hybrid electric tracked vehicle model and the driving cycle are built in MATLAB/Simulink. The simulation results show that the proposed strategy have a better fuel economy and battery manner than traditional rule-based strategies. Compared with the equivalent consumption minimization strategy, the new method also shows the easiness and convenience, but a nearly close fuel consumption and battery manner. This heuristic strategy can show us its advantages and serve some experiences when designing the control strategies in practical application.
On-line Monitoring of GIS Using Fourier Transform Infrared Spectroscopy
Authors: Zheng Wenjie , Li Chengqi , Qin Jiafeng , Li Jie
Published: July 2020

Different decomposition component gases caused by different insulation defects in gas-insulated switchgear will accelerate insulation degradation, which is a major threat to human and equipment safety. In this paper, we proposed online monitoring of GIS based on Fourier transform infrared spectroscopy. Firstly, we analysed the absorption characteristics of infrared light in SO2 and moisture. Secondly, we introduce the design principle and signal stabilization method of the laser. Thirdly, we propose the methods for measuring the concentration of SO2 and moisture. Finally, experiments with various concentration of SO2 and moisture are deployed, which proves that the GIS on-line monitoring method for decomposed gas has small measurement error and can be applied in practical applications.
Construction of Typical Vehicle Use Environment based on Virtual Simulation Test
Authors: Kang Hao , Chen Youyi , Zhao Hailong
Published: July 2020

This paper puts forward the importance and advantage of using virtual simulation experiment to test the performance of vehicle environment. Through the construction of virtual pavement under different environments such as typical virtual test ground and wading test ground, the mobile performance experiment and capacity experiment of different types of heavy trucks were carried out, and the vehicle performance was evaluated as a whole. The virtual simulation test, by simulating the typical environment that may be encountered in the process of vehicle driving, collects the vehicle running state and driving parameters, studies and analyzes their performance, and provides an important basis for the improvement and improvement of vehicle design.
Variational Bayesian with Embedded Laplace Approximation for AR Model with Outliers
Authors: Wan Hongjie , Zhang Haiyun
Published: July 2020

The student-t distributed innovation is robust to Auto regressive (AR) observations with outliers. However, the characteristics of student-t distribution lead to unclosed solution while using Variational Bayesian (VB) to estimate the model parameters. This paper proposed to embed the Laplace approximation in VB framework to get closed form solution. Markov Chain Monte Carlo (MCMC) is a typical method to unclosed form solutions, while it is known that MCMC has large computation costs. The degree of freedom parameter (DOF) changes greatly before and after the outlier points has been deleted, so the estimation can be improved. Experimental results show that, more accurate estimation coefficients estimation are obtained using the proposed methods compared with using the Gaussian innovation, and more accurate estimation is obtained after the additive outlier is deleted.
Generative Decoding of Intracortical Neuronal Signals for Online Control of Robotic Arm to Intercept Moving Objects
Authors: Li Chenyang , Zhang Yiheng , Wang Tianwei , Xu Xinxiu , Wang Qifan , Xu Bradley , Cui He
Published: July 2020

Brain-machine interfaces (BMIs) are being developed for translating neural signals to control an external device such as a robotic arm. The prevalent decoding strategy of current BMIs is the continuously conversion of neural spike trains to motor variables via a discriminative algorithm, but this typically results in un-natural and slow robotic motion. Recently, we implemented a BMI under feedforward control for interception of moving targets, though the decoding accuracy was insufficient for accurate online control. To improve the BMI performance, a generative algorithm called Latent Factor Analysis via Dynamical Systems (LFADS) [1], was applied to data pre-processing for de-noising. The results indicate potential advantages of feedforward control with generative decoding in improving BMI design.
A Real-time Method on Robot with Continuous Trajectory for Low-drift Odometry and Mapping
Authors: Jialong Gao , Lei Sun , Xiaojia Xiang , Zhenyi Li
Published: July 2020

This paper mainly proposes a real-time method on the robot with a continuous trajectory for low-drift odometry and mapping, by using range measurements from a 3D laser scanner, but without any other external reference. The common problem of the classical simultaneous localization and mapping (SLAM) method based on lidar is that the estimation of position and attitude is prone to jump discontinuity. It is mainly caused by the vulnerable performance of the optimization solver while it is in a complex scene. By adding kinematic and dynamic constraints into optimization function, our method achieves a lower mean square error(MSE) compare with the original one, and it has been tested in an outdoor experiment with only 3.5% MSE in yaw relative to state of the art.
Research on the Framework Construction of Three-dimensional Cost Standard System of Power Grid Engineering based on the Computer Technology
Authors: Sun Anli , Xiang Chun , Yu Jianbo
Published: July 2020

In the process of power grid construction, the pressure of project cost management is increasing gradually. With the continuous updating of information electronic system, people have higher and higher requirements for power grid engineering. The construction task of power grid engineering is more important. Standards for grid engineering have been revised to a higher level. The construction cost of power grid project is also increasing year by year. After years of research and practice, researchers found that the construction of three-dimensional cost standard system is the main opportunity to help power grid engineering improve the overall level. Based on the computer technology and three-dimensional structure of power grid and the actual characteristics and application of power grid engineering, this paper describes the main standards for the construction of power grid engineering cost system. Finally, the guarantee of its future development is put forward.
A Study on the Relationship between Oil Micro-occurrence State and Oil Source in Low Permeability Tight Sandstone Reservoir Based on Computer Technology - a Case Study of Daqing Oilfield
Authors: Liu Chen , Sergeevna Chernova Oksana
Published: July 2020

Well logging is a method of measuring earth parameters using a variety of geophysical properties. In oil fields, it is often referred to as field geophysical exploration, petroleum and mineral geophysical or geophysical logging. The use of logging technology can reduce the workload of drilling and coring, improve the exploration speed and reduce the cost of exploration, so it is widely used in oilfield development activities. This paper takes Daqing oilfield, the largest oilfield in China since 1960s, located in the middle of songliao plain, as an example, and analyzes the application of logging method based on computer technology in oilfield development.
Research on Design and Optimization of Geotechnical Engineering Based on BIM(Building Information Model) Technology
Authors: Xu Cheng , Wang Wei
Published: July 2020

The BIM is short for “building information model”, first originated in America in the 1970 s. After the completion of the three-dimensional geological modelling of the project site, the section interception tool provided by the modelling software can be used to obtain the engineering geological map of any section. Different from the two-dimensional section results provided by the geotechnical engineering survey, the section obtained by the software is projected vertically with the information of all geotechnical layers in a rectangular box on the surface.
Based on Computer Aided Technology, the Analysis of Percolation and Oil Recovery in Peripheral Tight Reservoir and its Test Results
Authors: Liu ChunMei
Published: July 2020

Due to the relatively long time interval between the completion of mining and the flooding of bottom water, the identification of oil-water layer is difficult due to the same nature of formation crude oil, so the interpretation of oil layer is very challenging. In this paper, the boundary oil, injection oil and bottom oil propellants of each oil layer in the study area, as well as the oil source and inflow direction of the oil layer, are summarized by using computer aided technology according to the geological characteristics of the block and the characteristics of permeability and oil recovery. The resistivity of water injection, oil flooding at the side and the bottom decreased obviously. Secondly, the typical reservoir of the new well is determined by comparing the logging data of the same layer between the old well and the new well and combining with the production dynamic test results of the adjacent old well. The logging response characteristics of the reservoir are analyzed, and the sensitive parameters such as deep lateral resistivity, shallow lateral resistivity, deep lateral resistivity amplitude difference, deep lateral resistivity, flush resistivity amplitude difference are optimized.
Application of Computer Artificial Intelligence Control Technology in the Comprehensive Utilization of Green Building Energy
Authors: Gao Dehao
Published: July 2020

In order to meet the needs of capital city construction and development, this paper studies the problems of building energy conservation from the aspects of computer intelligent control, green energy-saving building and integrated system of new energy utilization. Using computer intelligence to establish a comprehensive utilization of renewable energy demonstration system, namely the heat pump technology, building CCHP and total heat exchange ventilation system, set up a computer intelligent monitoring system, monitoring and control of building energy consumption, indoor heat and humidity environment, air quality and energy system, optimize the system operation[1].
A Numerical Study on the Treatment Performance of Bent-grooved Casing Based on Free Deformation Method Using Computer Data Analysis Technique
Authors: Ba Dun , Yuan Chenguang , Du Juan , Zhang Hongwu
Published: July 2020

In this study, inspired by the limit streamlines on the compressor casing. Combined with computer data technology to reduce the efficiency loss caused by the increase of casing processing.
Research on the Autonomous Learning Mode in the Environment of Computer Network Technology
Authors: Ni Eryan
Published: July 2020

Autonomous learning is an important part of basic education for all. At the same time, with the continuous development of computer network technology, it provides a new model for autonomous learning to some extent and improves the efficiency of learning. This paper mainly studies the needs of residents’ autonomous learning under the computer network technology environment and how to combine computer technology for efficient autonomous learning. Through the analysis of this paper, for the students to create a good learning atmosphere, provide reliable learning guidance, and how to implement the “happy learning”, “learn well”, “learned” as the guiding goal of the educational training model to provide reference.
Application Research of Big Data Analysis Technology in Oil and Gas Field Development
Authors: Hu Feiyuan , Hao Chenxi , Huo Xiaoju , Chen Yan
Published: July 2020

The goal of oil and gas field development is to maximize the benefits of exploitation work. In some large oilfields entering the mid-to-late development stage, to maximize the input-output ratio of oilfield exploitation, in oilfield development work, you will receive Due to the influence of many interference factors, in the field of oilfield exploitation, it is necessary to reduce the economic cost of oil and gas field exploitation as much as possible and continuously improve the economic benefits of oilfield mining units. In the mid-to-late production of oil and gas fields, the use of big data to establish a reasonable and scientific production plan for oil fields and an effective decision support system provide an important guarantee for the development and production of oil and gas fields in the middle and late stages. Through the use of effective production-increasing technology and production decision-making, comprehensively consider some oilfield mining areas and newly-added resource mining areas, comprehensively optimize and set up the development of oilfield resources in the middle and late stages and use big data technology to develop oilfields. Among them, the resource advantages are effectively transformed into economic advantages, in order to provide a good work plan for the middle and late stages of oilfield development.
RETRACTED: Study on the Formation Process and Effect of Tactical Performance Ability of Youth Training Team Based on Big Data Analysis
Authors: Peng Feng
Published: July 2020

Football is not only an important way to enhance international communication and the physical quality of the whole people, but also to enhance the feelings between people, strengthen unity, and create a positive fighting spirit. The article first briefly describes the current situation of domestic football development, then points out the great influence of football in world politics, economy, culture and its incredible commercial value, and combines the development of big data to train and evaluate the tactical play and consciousness of the youth training team. And get the positive effect of big data on the training effect.
Innovation and Practice of MOOC System Construction in Meteorological Industry
Authors: Jing Guodong , Zou Liyao , Ji Wenbin , Zhao Yongming
Published: July 2020

China Meteorological Administration-Massive Open Online Course, CMA-MOOC is an industry-oriented, international-oriented and public-oriented networked learning system of China Meteorological Distance Education Platform, which is hosted by the China Meteorological Administration Training Center of China Meteorological Administration. The CMATC provides technical support throughout the long-range international training on national observation equipment support along the “Belt and Road” and the demonstration training on nowcasting techniques for severe convective weather in ASEAN countries, successful completion of the first online cross-border training for meteorological distance education. The World Meteorological Organization, WMO Education and Training Office, appreciates this new initiative and shares within WMO innovative practices in international training for cadre colleges.
Research on Cognitive Radio Spectrum Sensing Security Mechanism Based on Blockchain
Authors: Zhang Guowei
Published: July 2020

In cognitive wireless networks, the collusion attack of malicious users has brought great challenges to the safety perception of the spectrum. Based on the analysis of the characteristics of existing attacks, a hypothetical analysis of possible attack behaviors, and the effective combination of blockchain technology and existing mechanisms are introduced, and a new secure spectrum sensing method based on blockchain technology is proposed. This method can treat the user’s historical interaction as a public ledger, and effectively monitor the user’s collusion attacks.
Cost Control Analysis of Manufacturing Enterprises Based on Computer Aided Technology
Authors: Liu Hongmei
Published: July 2020

With the advent of the new socialist era, China’s manufacturing industry is facing the challenge of transformation and upgrading under the new economic background. However, the development of computers has provided a huge impetus to China’s manufacturing industry. Facing the global market competition, the manufacturing industry, as a stabilizing force of the real economy, should not only develop vigorously with the support of national policies, but also rely on the development of computer aided technology. Cost is closely related to the benefits of an enterprise[1]. Therefore, scientific and reasonable cost control and management may directly affect the economic benefits of an enterprise and further improve its core competitiveness. The purpose of this paper is to realize cost control more effectively under the promotion of computer aided technology.
Computer Model and Analysis on Pavement Performance and Pavement Structure of Polypropylene Fibre Material Concrete
Authors: Liu Hongxia , Wang Na
Published: July 2020

With the great progress of road construction ability and construction technology, new materials are constantly developed, the choice of road surface materials is more diversified, and the pavement structure is more reasonable and the performance is more optimized, which brings great convenience for the first paving and later maintenance of the road. In this paper, by studying computer modeling and analysis technology, the polypropylene fiber concrete pavement in the road is analyzed and studied, and the experiment is designed in detail to describe the current actual situation, and the conclusion is drawn for study and research reference.
Particle Swarm Optimization for Solving Medical Image Reconstruction Ill-conditioned Problems
Authors: Li Hongyan , Wan Zhonglin
Published: July 2020

Particle swarm algorithm applies to the field of computer neural networks a lot. In this paper, the medical image is used as an example to realize the modeling process based on the particle swarm algorithm. For the modeling and simulation analysis of medical images, the geometric model accuracy and physical model accuracy need to be solved. The mobile cube (MC) algorithm is used for surface reconstruction. At the same time, the quadratic error measurement (QEM) method is used to reduce and smooth the triangular patch. The Delaunay method is used to deduce the volume mesh model based on the surface mesh. and finally, the corresponding physical model is selected according to the target organization to use the finite element (FEM) method for analysis, and uses OpenGL to display the cloud chart of the equivalent stress. The analysis results show that the function and metabolism of human tissues and organs can be more accurately understood through the reconstruction of SPECT medical images.
RETRACTED: Building the Training System of Physical Education Innovation Ability in Higher Vocational Colleges Based on Computer Information Technology
Authors: Ma Hui
Published: July 2020

The rapid development of computer information technology is promoting the progress of all aspects of society, sports and physical education are not outside, but is using computer information technology to gradually innovate and walk with the times. In this paper, the author expounds the demand of the development of physical education for the application of computer technology and the importance of the establishment of the innovation system of physical education development to society, education, health and individual.
RETRACTED: Evaluation Method of Campus Football Implementation Effectiveness Based on Computer Simulation Model
Authors: Xu Jia
Published: July 2020

Campus football is an important part of football reform in China, which undertakes the arduous task of promoting the all-round development of students and training football reserve talents. However, at present, there are few studies on the evaluation methods of the implementation effect of campus football in China, and the construction of a complete and scientific evaluation system of the implementation effect of campus football is not perfect, which seriously restricts the sustainable and healthy development of campus football. Therefore, this paper analyses the problems existing in the development of campus football, and discusses the possibility of applying the computer simulation model to the evaluation method of the implementation effect of campus football. On this basis, this paper puts forward the basic principles and key evaluation indexes of the implementation effect evaluation method of campus football, and constructs the structural equation model of the evaluation method, which provides a solid theoretical support for the evaluation of the implementation effect of campus football and the high-quality development of campus football.
RETRACTED: Research on the Integration of Chinese and Russian Original Ecological Dance Elements and Modern Elements Based on Computer Big Data Analysis
Authors: Li Jingbo
Published: July 2020

China, with its vast territory and long history, retains a large number of original dances. Russia is China’s neighbor with a vast territory, and there are also a large number of original ecological dances preserved from history. If the original ecological dance elements of China and Russia can be combined with the modern elements, the dance effect will be brought out to the common. Therefore, this paper analyzes the original ecological dance elements and modern elements in China and Russia by using the computer big data technology, and studies how to better integrate the two.
Research on Key Technologies of Performance Monitoring and Operation and Maintenance of Optical Fiber Transmission Network Driven by Big Data
Authors: Zhao Jinghong , Jin Lei , Liu Dong , Cheng Shuo
Published: July 2020

The traditional network operation and maintenance technology is that the administrator passively waits for the network fault to report and then carries on the emergency treatment. This method lacks active mechanism and has many disadvantages in dealing with network communication failure. The low timeliness of operation and maintenance reduces the reliability of network communication operation and maintenance to a certain extent, so it is particularly urgent to explore the research of network communication operation and maintenance technology driven by big data. This article describes the difference between several different transmission modes in the field of optical fiber communication, and discusses the related factors that restrict the reliability and timeliness of the optical fiber transmission network. On this basis, this paper analyses the possibility of integration of big data technology and the optical fiber network, and lists the typical application of big data technology in the optical fiber network, which provides a new thinking direction for the performance monitoring and operation maintenance of the optical fiber network.
A study on Strategies of Stimulating Students’ Participation in English Teaching Based on Computer Information Technology
Authors: Wu Jingling , Wu li , Jiang Xiujuan
Published: July 2020

Improving students’ participation and enthusiasm in class can help students better learn and master knowledge and improve teaching quality. Therefore, how to stimulate students’ participation and enthusiasm in class has long been a hot issue in the field of education, especially in the process of English teaching. Thanks to the development of computer technology, we are provided with more research practices. By using computer technology to analyze the application of computer information technology in English teaching, this paper studies how to stimulate students’ participation in class.
RETRACTED: Research on College Students’ Psychological Identification and Cultivation of Socialist Core Values based on the analysis of Big Data
Authors: Huang Lan
Published: July 2020

With the progress and development of the times, network technology has gradually changed the way people live and learn. The continuous development of network technology has brought many new opportunities for China’s education. Nowadays, network technology has been widely used in the college teaching process. However, the emergence of network technology, in addition to providing convenience and advantages for China’s education, has also brought many problems to the mental health of college students. More and more college students are gradually experiencing mental health problems, which have a great impact on their own learning and growth. Therefore, only in-depth analysis of the impact of the mental health education of college students and continuous exploration of effective improvement measures and solutions through the analysis of big data, so as to better play the positive advantages of the network environment, can promote students’ better learning and development.
Research on Automatic Operation and Maintenance Technology of Optical Fiber Communication System Based on Computer Control Network
Authors: Jin Lei , Zhao Jinghong , Huang Xing , Lu Bin
Published: July 2020

The essence of optical fiber communication transmission technology is to use light as the carrier of information, and to achieve the purpose of information transmission through the optical fiber network. The communication mode based on optical fiber communication technology has been widely recognized in the field of industrial production and telecommunication transmission due to its good information transmission performance. However, with the expansion of the construction scale of optical fiber communication network and the improvement of user coverage, the disadvantages of the management and maintenance of the traditional optical fiber communication network are becoming more and more obvious. Therefore, this paper describes the characteristics of the optical fiber communication technology, and analyses the existing problems in the optical communication system and their causes. On this basis, this paper analyses the automatic operation and maintenance technology of optical fiber communication system. The analysis results in this paper provide some technical support for the deep integration of computer control technology and optical fiber communication automatic maintenance system.
Establishment of Environmental Art Design System Based on Computer Virtual Reality Technology
Authors: Liu Li
Published: July 2020

Multiple modern scientific and technological means are changing people’s lives unconsciously. The emergence of computer technology and virtual reality (VR) technology has broken through the inherent traditional mode, endowing higher practical value to the environmental design scheme and its applications. In this paper, the VR technology and its practical application in environmental art design are expounded, and the far-reaching influence of VR technology on the actual design process is explored to provide a reference for broadening the environmental art design concept.
Research on the Integration of Bridge Structure and Landscape Art Combined with Two-dimensional Computer Image
Authors: Liu Li
Published: July 2020

With the change of the public’s aesthetic concept, people’s requirements for the landscape and art of bridges are constantly improving. The connotation of bridge has developed from the original traffic architecture to the carrier of human landscape and historical culture. Therefore, integrating the concept of landscape art into bridge design is an important development direction in the field of bridge design. This paper expounds the connotation of landscape art in bridge design, and enumerates the typical application of the landscape art concept in bridge design. On this basis, this paper analyses the advantages of computer two-dimensional image technology for bridge landscape design, and discusses several aspects that should be improved in future bridge landscape design, which provides new thinking and reference for modern bridge design.
Exploration of Dermato-venereology Teaching Combining the Problem-oriented Teaching Method with Computer Technology
Authors: Li Li , Wu Qing , Chen YuLin , Li Sha , Hu XiaoJian
Published: July 2020

The problem-oriented teaching approach (PTM) is a teaching approach that focuses on problem-oriented study and teaching through identification and solving of problems. Since the 1990s with teh development of computer, some medical schools and colleges in China and Southeast Asia have started to apply the problem-based teaching approach and computer technology gradually. Currently, it is still in the initial and exploratory stage in China, and the lecture-based learning (LBL) plays a leading role in medical teaching. PTM is distinctly different from the traditional LBL teaching model where the teachers give lectures and the students are spoon-fed in classes. It has broken through the traditional teaching confinement based on explanations by teachers, and students can take the initiative to analyze and solve problems pertinently in teaching.
Simulation Analysis of Soil Covering Process
Authors: Li Liyan , Gong Xin , Xu Ting , Guo Pan
Published: July 2020

Soil mulching device is an important part of precision seeder, its structural parameters and performance will directly affect the uniformity of seed distribution and the thickness of soil, and ultimately affect crop yield. Using the EDEM tool based on the discrete element method, the optimized structure of the earth covering device was simulated and analyzed. The soil-slot test was used as a comparative test of the soil simulation experiment. The comparison between the results of the simulation test and the earth covering process test confirmed the applicability of the discrete element method to the earth covering process, which provides a new way for the research and design of the earth covering device and the earth covering process.
Psychological Test System and Signal Processing Algorithm for Intelligent Wheelchair
Authors: Xu Binfeng , Hu Yarong
Published: July 2020

Intelligent wheelchair based on BCI is a hot spot in recent research, and brain activity is actually a reflection of psychological activity. Completing the design of psychological test system is the key to BCI. ERP reflects the psychological activity of the brain, is a psychological test good tools such as cognitive neuroscience research. And there is psychological test system is mostly based on the traditional theory of external behavior inference, unable to objectively evaluate people’s psychological activity. In the study of psychological tests and event related potential theory, the article improved FastICA algorithm, and applied to feature extraction of ERP. Eventually set up a complete set of psychological test system. Experiments show that the system can effectively detect the ERP feature extraction, and faster, better than other conventional psychological test system. So as to lay the foundation for the completion of the design of Intelligent wheelchair.
RETRACTED: Realization of Building Energy Saving and Solar Heating in Cold Areas based on Computer Technology
Authors: Zhao Lili
Published: July 2020

The climate of cold area is cold in winter (the average temperature of the coldest month is 0 ∼ - 10 °C and < - 10 °C), the outer envelope of the building bears the interference of low temperature, wind and snow, hot in summer, and the outer envelope of the building bears the interference of high temperature, solar radiation and rain. Therefore, the design of buildings should meet the requirements of winter heat preservation, cold prevention and antifreeze. At present, 95% of the new buildings built every year in China are still high energy consumption buildings. The heating energy consumption per unit building area is about three times of that in countries with similar climate. The building energy consumption in China accounts for nearly 30% of the national energy consumption. With the development of building technology, the improvement of people’s awareness of energy and the attention of government departments, China should vigorously develop building energy saving, which is urgent. The demand of solar energy is increasing day by day, and the situation of energy utilization is tense. However, the large-scale use of conventional energy will have a negative impact on the environment. As a kind of renewable energy, solar energy is inexhaustible and will not increase the environmental load. It will become an important part of the future energy structure. In the building energy consumption, the energy consumption of domestic hot water and heating accounts for a considerable proportion. Using solar energy to meet the requirements of low-grade energy consumption, such as domestic hot water and heating, has great energy-saving benefits. Therefore, solar energy heating technology has been paid more and more attention. At the same time, with the development and maturity of computer technology, it also provides more support for solar heating technology. This paper analyzes the realization of building energy saving and solar heating in cold areas by using computer technology.