bluuebunny/crossref_metadata_2025 huggingface dataset:
Room-Temperature Self-Healing Elastomer based on Van der Waals Forces in Air and under Water
Authors: Niu Pengying , Liu Beibei , Li Huanjun
Published: December 2021

With the development of flexible wearable electronic devices, researches on self-healing conductive materials have become prevalent. However, the self-healing performance of most conductive self-healing materials is commonly achieved by the external stimulus that may cause damage to the equipment. Pparticularly, these self-healing materials may lose the self-healing properties when exposed to a high-humidity environment. Here, we adopted two hydrophobic monomers (2-methoxyethyl acrylate and ethyl methacrylate) to obtain a self-healing elastomer that could display self-healing properties in air or under water though van der Waals forces. The quality and mechanical properties of the elastomer material could keep stable after stored under water for half a month. This elastomer material was capable of self-healing in different environments with self-repair efficiencies more than 50% in deionized water, strong acid solution and strong alkaline solution. The self-repair efficiencies were up to 77% at room temperature(T=25°C) and 64% at low temperature (T=-20°C) in air.
Magnetic-Electric Behaviors and Physical Properties of The Thin Films on ITO-Glass Substrate
Authors: Liu Xiaofen , Wang Xiujuan , Zhang Zirui , Cao Jin
Published: December 2021

Polycrystalline BiFeO3 thin films on ITO glass substrates were prepared by radio frequency magnetron sputtering using a Bi1.1FeO3 target. The samples which were annealed with different annealing conditions are pure without impurities. We measured the magnetic properties and ferroelectricity of the BiFeO3 films. The measurement results show that the magnetic and electrical properties of the BiFeO3 films are significantly different under different annealing conditions.
Reinforcement Design and Physical Testing of New and Old Cushion Cap of Existing Bridge
Authors: Yang Yongcheng , Wang Xianggang , Shen Yongli , Xin Xing , Zhang Zhengpeng , Wang Yegang
Published: December 2021

As an important part of bridge structure, pile cap plays an important role in its operation. There is a lack of sufficient research in the design and construction of the existing bridges, especially in the operation process of the river crossing bridge, there will be more security risks, so it is urgent to strengthen the bearing platform. Combined with the general design theory of bridge cap, considering the feasibility of construction and the difficulty of operation, the new and old caps are planted with steel bars to make them bear the common force. Aiming at the problem of insufficient bearing capacity, the cap reinforcement method is proposed, so as to improve the stability of the bridge. The research results can provide reference for similar bridge reinforcement projects in the future.
A study on micro-morphology and impacts of curing temperature on bond strength of interfacial transition zone through scanning electron microscope
Authors: Na Binbin , Yan Bin
Published: December 2021

The influence of curing temperature on the bond strength of ITZ was studied in this paper. It is found that, Increasing curing temperature can improve the bond strength of ITZ in the early age, but it will significantly decreases the growth trend of the bond strength. The micro-morphology characteristics were examined by the method of scanning electron microscopy, It was found that, the higher the curing temperature is, the more uneven the hydration products distribution of ITZ is, and also the looser the ITZ structure is.
Research on the Physical Characteristics of Hot-Pressed Sintering Preparing Self-Fluxing Filler by X-Ray Diffraction
Authors: Li Xiupeng , Long Weimin , Shen Yuanxun , Zhong Sujuan , Pei Yinyin , Li Yunyue
Published: December 2021

In this paper, Al-12Si self-fluxing filler metal ring was prepared with Al-12Si alloying powders and KAlF4 flux by hot pressed sintering (HPS) method. The microstructure and mechanical properties of the brazing alloy and the brazed 3003 aluminum alloy joint were investigated. The results showed that Al-12Si self-fluxing filler metal ring could be successfully obtained by HPS at 470°C using a pressure of 300MPa. The prepared filler metal ring was dense and defect-free and the microstructure was mainly composed of Si phase with KAlF4 flux grain uniformly distributed in the Al matrix. The 3003 aluminum alloy joint interface brazed by the prepared filler metal was also well bonded and no pore and defect was found. A quite high joint strength of 75MPa was obtained which is equal to the strength of joint brazed using commercial Al-Si self-fluxing wires prepared by hot extrude method. The results revealed that the filler metal rings fabricated by HPS process had great potentiality in brazing of aluminum alloy especially for the Al-Al pipes joining due to its high joint strength, low cost and the convenience for industrial application.
Optimization of Schottky-contact process on 4H-SiC Junction Barrier Schottky (JBS) Diodes
Authors: Li Qingling , Zhu Tao , Li Jialing , Yan Hailiang
Published: December 2021

SiC Junction Barrier Schottky (JBS) Rectifier is a kind of unipolar power diode with low threshold voltage and high reverse blocking voltage. And the Schottky barrier Φ
BN is a main technology parameter, which could greatly affect the forward conduction power and reverse leakage current in the JBS rectifiers. Therefore, it is necessary to balance the influence of Φ
BN on the electrical characteristics of JBS rectifiers. In this paper, physical properties at the metal-semiconductor at the Schottky-contact could be optimized by the improvement of Schottky-contact process. And this optimization could significantly decrease Φ
BN to reduce the on-state voltage drop V
F and minimize negative impact on its reverse characteristics. After the completion of Silicon carbide JBS diodes, the static parameter electrical test was carried out on the wafer by using Keysight B1505A Power Device Analyzer/Curve Tracer. The test results show that the Schottky barrier height Φ
BN of JBS Schottky rectifier manufactured by the modified Schottky foundation technology decreased from 1.19eV to 0.99eV and I
R increased from 1.08μA to 3.73μA (reverse blocking voltage V
R=1200V). It indicated that the power consumption of Schottky barrier junction in JBS rectifiers could be significantly reduced by about 25%, and I
R could effectively be limited to less than 10μA.
Research on Internet of Things Technology for Intelligent Three-Dimensional Online Monitoring System of Marine Ranch
Authors: Chen Kuo , Chen Ke , Wang Lei
Published: December 2021

The online monitoring network of marine ranching ecological environment is one of the important development directions of marine ranching construction. Traditional marine monitoring systems are large in size, high in power consumption, and expensive. The investment in pasture construction cannot achieve a large amount of investment to form a monitoring network. There is an urgent need for a low-cost marine monitoring method that can afford a large area and high spatial density. This problem cannot be realized in traditional technology. Based on MEMS technology, this paper develops low-cost monitoring small floats that can be deployed in a large number of “swarm bees”, with high spatial and temporal resolution, and take into account environmental and biological population characteristics monitoring. Each small float is connected to a multi-node sensor chain and video monitoring node. The low-cost surface and underwater wireless transmission and wireless communication means are used for networking observation, which proposes a brand-new solution for the construction of the intelligent three-dimensional monitoring of the marine pasture environment.
Research on the Extraction of Image Edge Information in Convolutional Neural Networks
Authors: Zou Guanru , Luo Yulin , Feng Zefeng
Published: December 2021

Convolutional neural network is an important neural network model in deep learning and a common algorithm in computer vision problems. From the perspective of practical application scenarios, this paper studies whether padding in convolutional neural network convolution layer weakens the image edge information. In order to eliminate the background factor, this paper select MNIST dataset as the research object, move the 0-9 digital image to the specified image edge by clearing the white area pixels in the specified direction, and use OpenCV to realize bilinear interpolation to scale the image to ensure that the image dimension is 28×28. The convolution neural network is built to train the original dataset and the processed dataset, and the accuracy rates are 0.9892 and 0.1082 respectively. In the comparative experiment, padding cannot solve the problem of weakening the image edge weight well. In the actual digital recognition scene, it is necessary to consider whether the core recognition area in the input image is at the edge of the image.
Innovative design of exhaust enthalpy algorithm for small turbine
Authors: Zhu Lingkai , Wang Qian , Gao Song , Zhong Ziwei , Shang Panfeng , Guo Junshan , Han Yue , Zheng Wei
Published: December 2021

This paper presents a method to determine the exhaust enthalpy of small steam turbine. Starting from the feed water pump group, the feed water pump and small steam turbine are studied as a whole. Based on the thermodynamic method, the efficiency of the feed water pump is obtained separately, and then the efficiency and exhaust enthalpy of the small steam turbine are deduced. This method only needs to measure the inlet and outlet pressure, temperature, feed water flow of feed water pump, inlet steam pressure, temperature and flow of small turbine. It has the advantages of less measurement parameters, low measurement cost and small measurement error. It provides a reliable basis for a comprehensive understanding of the performance of small steam turbine and guiding its economic and safe operation.
Policy-based monocular vision autonomous quadrotor obstacle avoidance method
Authors: Zheng Baojin , Guo Xiao , Ou Jiajun
Published: December 2021

Aiming at the obstacle avoidance control problem of small quadrotor, a method of quadrotor obstacle avoidance based on reinforcement learning is proposed. The proposed method can make training converge quickly and has good environmental robustness. The proposed methods include: (1) a framework adopts perception module and decision module to improve the generalization ability of the obstacle avoidance model; (2) An Actor-Critic framework-based Proximal Policy Optimization (PPO) algorithm to provide quadrotor with policy-based decision-making capabilities; The experimental simulation results show that the strategy-based framework converges quickly and has a high success rate, the training time is much lower than that of the value-based framework. The monocular vision observation ability is limited, which leads to deviations between local observation and global state, So LSTM layer is usually added to increase model performance. Policy -based decision can have a good obstacle avoidance effect without adding the LSTM layer, and have good generalization ability after short relearning after changing.
Intelligent Calculation Model and Algorithm Optimization of Optimal Operation of Integrated Energy System
Authors: Wang Kun , Yang Guochao , Cheng Baohua , Gan Zhiyong , Qi Yan , Wang Sen , Bai Xinyu , Bian Jiang
Published: December 2021

This paper analyzes the energy saving effect and optimal operation of the integrated park type energy system. The park type integrated energy system includes photovoltaic power generation system, ground source heat pump system, solar air conditioning system, regenerative electric boiler system and solar hot water system and so on. The energy saving benefit calculation model of each subsystem is established, and according to the operation history data of each subsystem, the calculation results of each subsystem are analyzed. It shows that: The energy saving income of photovoltaic power generation system is 734,200 yuan/year. The main revenue comes from the second and third quarters, during which it should pay attention to the maintenance of photovoltaic modules to ensure the maximum energy saving benefit. The energy saving income of ground source heat pump system in summer is 155,900 yuan/year, and the energy saving effect is not significant. It can cooperate with traditional units for cooling in summer. The heating in winter in the park is provided by ground source heat pump system, regenerative electric boiler system and solar energy air conditioning system. Its energy saving benefit is 3.995 million yuan/year which is the main source of energy saving income in the park, with remarkable energy saving effect.
Algorithm design and analysis of fire rescue problems
Authors: Fu Mengshuang
Published: December 2021

With the rapid economic development, the urban space environment is becoming more and more complex, various accidents and disasters occur frequently, and safety risks are increasing. The rescue tasks involved in the fire brigade are showing a trend of diversification and complexity. The fire rescue team always puts the people first and insists on serving the people wholeheartedly. It is the guardian of maintaining social stability in our country and safeguarding the health and safety of people’s lives and property and various disaster affairs. The society needs the participation in the fire rescue team. Aiming at the fire rescue problem, this paper uses the fire rescue call data onto 2016 to 2019 to predict the number of fire rescues / rescued calls based on the difference equation to improve the rescue efficiency of the fire brigade. Taking into account the impact on the domestic epidemiced in 2020 on people’s lives, the adjustment value was introduced to adjust part of the alarm data onto 2020 to ensure the accuracy and reliability of the data. Finally, the second-order difference equation is used to predict the alarm data onto 2021 through the least square method, which verifies the accuracy of the model.
Research on Image Classification Algorithm Based on Convolutional Neural Network
Authors: Luo Lihua
Published: December 2021

Nowadays, we are in the information age. Pictures carry a lot of information and play an indispensable role. For a large number of images, it is very important to find useful image information within the effective time. Therefore, the excellent performance of the image classification algorithm has certain influence factors on the result of image classification. Image classification is to input an image, and then use a certain classification algorithm to determine the category of the image. The main process of image classification: image preprocessing, image feature extraction and classifier design. Compared with the manual feature extraction of traditional machine learning, the convolutional neural network under the deep learning model can automatically extract local features and share weights. Compared with traditional machine learning algorithms, the image classification effect is better. This paper focuses on the study of image classification algorithms based on convolutional neural networks, and at the same time compares and analyzes deep belief network algorithms, and summarizes the application characteristics of different algorithms.
A Scrambled Image Blind Evaluation Method Based on Space and Frequency Domain
Authors: Wang Congli , Li Xiong
Published: December 2021

Most of the image scrambling degree evaluation algorithms rely on the statistical features of the original image, which cannot achieve blind evaluation. Based on the uniform distribution model of the statistical characteristics of ideal scrambled images, a blind evaluation algorithm of image scrambling degree combining space and frequency domain is proposed in this paper. In the space domain, the uniform distribution characteristics of the gray histogram of the ideal scrambled image are used, and the uniform distribution characteristics of the Discrete Fourier Transform (DFT) spectrogram in the frequency domain are combined with the gray correlation analysis theory. The two are weighted to realize the space and frequency domain evaluation of the scrambled image performance. The experimental results indicate that the evaluation algorithm in this paper can consider the performance evaluation of both pixel value and pixel position dislocation, avoiding the disadvantage of ineffective spatial domain evaluation when only the pixel position scrambling is performed. It has very sensitive to the histogram distribution and frequency domain features of encrypted images, and has good agreement with Human Visual System (HVS). The original image is completely independent, and it enables blind evaluation objectively.
Application study of UAV path planning based on the balanced search factor artificial bee colony algorithm
Authors: Hao Wenlong , Luo Bo , Zhang Zhiyuan
Published: December 2021

In this paper, aiming at the shortcomings of slow convergence speed and weak local search ability of traditional artificial bee colony algorithm in path planning, an artificial bee colony algorithm based on balanced search factor is proposed for UAV path planning. Using a search strategy based on balanced search factor, the depth search is carried out while maintaining a certain population diversity. The global search ability and local development ability are balanced, the average accuracy of path planning is improved, the robustness of path planning is enhanced, and the ability to obtain better path solutions is improved.
Research on application of single index membership function based on power coefficient method
Authors: Liu Na
Published: December 2021

The power coefficient method can determine the satisfactory value and the unallowable value of the index, quantify multiple targets, and then determine the power coefficient value of each target. Combining the distribution characteristics of the four types of membership functions, this paper innovatively proposes to solve the regional distribution problem of single-index membership functions by means of an improved efficiency coefficient method, and combined with empirical research, the application of this mathematical method in practical engineering.
Computer Mathematical Statistics and Comparative Analysis of Meteorological Conditions in the Bohai Rim Region through Big Data Digitization
Authors: Jin Tiantian , Li Yang , Du Jianshuang , Wang Lei , Mao Zhizheng
Published: December 2021

Based on the data of environmental monitoring stations and meteorological stations in typical city in the Bohai Rim region in June 2021 and June 2020. The air quality in June 2021 was better than that in the same period in 2020. Ozone (O3) was the primary pollutant in June 2021 and June 2020. The overall meteorological conditions in May 2021 were relatively favorable. In June 2021, the number of light wind days and wind speed had no significant impact on air quality compared with the same period last year. The dominant wind direction in June 2021 was southeast wind, which was not conducive to the increase of ozone concentration compared with the southwest wind frequency in the same period in 2020; the relative humidity in June 2021 was slightly higher year-on-year, which was slightly conducive to the hygroscopic growth of pollution; the static stability index in June 2021 was lower year-on-year, and the weather conditions for comprehensive pollution diffusion were preferred year-on-year; the height of the mixed layer in June 2021 was lower year-on-year, the vertical diffusion weather conditions were deviated year-on-year; the average temperature, sunshine hours and total radiation in June 2021 were all low, which was not conducive to the generation of ozone.
Research on the computer intelligent recognition of electric appliance by Yolo V5 algorithm
Authors: Zhang Xiaolong , Qian Bin , Si Haitao , Zeng Liuying , Wang Hui
Published: December 2021

In the process of power operation, the correct identification of tools can lay a foundation for the detection of violations in power operation. In order to realize the recognition of power instruments, based on the current Yolo V5 algorithm, a detection algorithm for power instruments is proposed by improving Yolo V5 algorithm. Firstly, the model of Yolo V5 algorithm is introduced. Then the establishment of the power tool database and the process of model training are analysed. Finally, the test results are analysed and evaluated. The models generated after training were accelerated by TensorRT and then deployed on Jetson Xavier NX.
CFD-Based Wind Field Correction Method for Terrain Wind Tunnel Tests
Authors: Zhou Qi , Zhu Yuxiang , Wang Yu , Han Jiceng
Published: December 2021

At present, the wind tunnel test results will have certain deviation and distortion when the wind tunnel test is conducted on certain mountainous terrain with complex local terrain and large variation of wind field characteristics due to the accuracy range of the measuring instruments used in wind tunnel test. In order to correct and obtain correct wind tunnel test results, the wind tunnel tests and numerical simulations were conducted on a super-large bridge in the mountainous area of Southwest China, and the wind parameters of the wind field at the bridge site were obtained. The CFD results were compared with the wind tunnel test results to confirm the credibility of the CFD results; a method was proposed to correct the deviated wind tunnel test data based on the CFD simulation results; the deviated wind tunnel test data were corrected and predicted with the above method, and a more satisfactory correction result was obtained.
Study on Full-scale Measurements of Wind Field Characteristics of Coastal Complex Mountainous Terrains
Authors: Shao Shuai , Luo Kewei , Zhang Hongjie , Li Yangsen , Fu Benzhao , Lin Ruizong
Published: December 2021

Based on full-scale wind field measurements of coastal complex mountainous terrains, data of fluctuating wind velocities at the height of 30m for four sites, including mountaintop and hillsides, are obtained. The wind load characteristics of mean wind velocities, wind directions, turbulence intensities and speed-up ratios of wind velocities are comprehensively examined. Results show that the maximum mean wind velocity at the mountaintop site is 12.4 m/s. The probability density distributions of mean wind velocities for the four measurement sites can be well represented by the Weibull probability model. The predominant wind directions are around the northeast and southwest. The longitudinal, lateral and vertical turbulence intensities decrease with the increase of mean wind velocities. The turbulence intensities for the mountaintop site are as many as 0.13,0.12 and 0.089 under maximum wind velocities, respectively for the previously mentioned three directions. The speed-up ratios of wind velocities between mountaintop and hillside sites are reduced, as the wind velocities increase. However, in cases of intensive wind with mean wind velocities larger than 8 m/s, the speed-up effects of wind velocities can also appear. The maximum speed-up ratio can reach 1.17.
Computer Mathematical Statistics and Analysis on Automobile HFCs Reduction Path Using Big Data Technology
Authors: Ren Jiabao , Liu Xuefeng , Wang Chaoqian , Wang Lei
Published: December 2021

China has submitted an application to join the Kigali amendment to the Montreal Protocol. As the second largest hydrofluorocarbons (HFCs) consumer industry in China, the automotive industry is facing enormous pressure to reduce HFCs. This paper analyzes the current situation of HFCs use in the domestic automotive industry, and makes a simulation prediction of HFCs use data in the automotive industry from 2024 to 2030, analyze and evaluate the advantages and disadvantages of different technical routes. The relevant contents of this paper will provide reference for the formulation of HFCs reduction policy.
Intelligent Numerical Computing Methods for Determining the Concentration of Citric Acid by Accurate Measurement and Calculation
Authors: Fu Yueyang
Published: December 2021

According to the Bronsted-Lowry theory, an acid is a proton donor, and a base is a proton acceptor. An acid-base reaction involves the proton transfer between chemicals, where a base containing hydroxide ion (OH-) accepts a proton (H+) from an acidic solution to form water (Khan,2016). In the above equation, HCl as an acid donates one H+ ion, and NaOH as a base accepts the proton to form one water molecule (H2O). So, a proton from the acid is transferred to the anion of the base. Then, the metal cation (Na+) and the conjugate base anion (Cl-) form the salt NaCl.
Study and application of computer information big data in basketball vision system using high-definition camera motion data capture
Authors: Wei Jingwei
Published: December 2021

Contemporary computer big data technology is developing rapidly, and it has played a role in promoting the intelligent development of sports. Based on this research background, the thesis revolves around the application of computer big data artificial intelligence in the field of basketball training. The study found that computerized big data in basketball training and teaching is mainly reflected in the following aspects: high-definition camera motion data capture, player analysis to obtain assisted training system, etc. The final paper uses a basketball vision system as a case study to analyze specific applications of big data for computer information.
Real-time vehicle detection and computer intelligent recognition through improved YOLOv4
Authors: Ni Zhenhao , Liu Tingna , Li Ke , Bai Yongqiang , Zhu Zhongjie
Published: December 2021

Vehicle detection is one of the key techniques of intelligent transportation system with high requirements for real-time and accuracy. To better balance the requirements, a vehicle detection algorithm based on the You Only Look Once (YOLO) v4 is proposed in this paper. On the one hand, the improved depthwise separable convolution is adopted to ensure the real-time performance. On the other hand, a novel feature fusion network is designed to gather more original feature information of different depth network layer. Experimental results show that the proposed algorithm can reduce the detection time by half while ensuring the accuracy, compared with the pristine YOLOv4.
Research on Automated Information System of Non-sense Attendance Using Face Recognition and Large Database
Authors: Wang Taiyou , Chen Litiao
Published: December 2021

In order to meet the needs of today’s large-scale enterprise human resource management attendance business, this paper designs an embedded face recognition attendance system, and designs and analyses the implementation method of the system in detail. The system consists of two parts: face-swiping attendance and attendance management. Among them, face-swiping time attendance uses the Face Boxes model to detect faces, and the Face Net model to identify the person who punches in. Tests have found that the system is simple to operate, has high recognition accuracy, and has a certain practical value.
Research of Metric Learning-Based Method for Person Re-Identification by Intelligent Computer Vision Technology
Authors: Rao Qiyu
Published: December 2021

Person re-identification technology aims to establish an efficient metric model for similarity distance measurement of pedestrian images. Candidate images captured by different camera views are ranked according to their similarities to the target individual. However, the metric learning-based method, which is commonly used in similarity measurement, often failed in person re-identification tasks due to the drastic variations in appearance. The main reason for its low identification accuracy is that the metric learning method is over-fitting to the training data. Several types of metric learning methods which differ from each other by the distribution of sample pairs were summarized in this article for analysing and easing the metric learning methods’ over-fitting problem. Three different metric learning methods were tested on the VIPeR dataset. The distributions of the distance of the positive/negative training/test pairs are displayed to demonstrate the over-fitting problem. Then, a new metric model was proposed by combining the thoughts of binary classification and multi-class classification. Related verification experiments were conducted on VIPeR dataset. Besides, the semi-supervised metric learning approach was introduced to alleviate the over-fitting problem. The experimental results reflect gap between training pairs and test pairs in the metric subspace. Therefore, reducing the difference between training data and test data is a promising way to improve the identification accuracy of metric learning method.
Smart Boat Detection Based on Feature Pyramid Network and Deformable Convolution
Authors: Li Kaipeng , Wang Yunge , Shao Yuan , Wu Xingxiao
Published: December 2021

The submarine cable guarantees the electricity and communication of the island residents. The operation of fishing boats poses a major threat to the submarine cable. Due to the complex environment, manual monitoring has defects such as strong subjective factors and easy fatigue. The paper adopts the intelligent monitoring method, using the object detection algorithm based on deep learning and the camera to monitor the boats on the sea. Use feature pyramid network to enhance the detection of smaller and farther boats. Use deformable convolution to solve the problem of few samples. Experimental results show that model can detect boats. The detection ability of the feature pyramid network is stronger, especially for the distant and smaller boat targets. Using deformable convolution can improve the accuracy of models trained on small dataset.
RETRACTED: Application Research of Software Engineering Technology and Algorithm Optimization in the Era of Big Data
Authors: Xin Zhang
Published: December 2021

Starting from the overview of technology of big data and software engineering technology, this paper discusses the core technology of software engineering and the application of software engineering technology. In order to better follow the development trend of the times and promote social and economic construction, it is necessary to do a good job in the research of software engineering. Relevant people can analyze the application of software engineering technology from the perspective of digital information based on the background of the times, so as to promote the continuous improvement and development of software engineering technology.
Modeling analysis and optimization of temperature curve of welding furnace
Authors: Sun Huiting , Liu Hongkun , Wang Ying
Published: December 2021

Reflux welding is widely used in SMT (surface patch technology) During this production process, the quality of the product is essential to maintain the temperature and the furnace speed required by the process. The furnace temperature curve in the furnace is an important form of reaction welding process. In order to improve the process efficiency of the return furnace, the heating welding process model is established based on the Fourier heat conduction law,1 D heat conduction model and Newton cooling law and draws the furnace temperature curve model. Then, the upper boundary of the conveyor speed using the boundary analysis and multiple target planning, and further explore the research and optimization direction of subsequent process flow. At the same time, this paper examines and analyzes the modeling process and results, and effectively demonstrates the scientific nature and accuracy of the model. Finally, the paper analyzes the significance of the above model and research in chip processing.
Application of Computer Remote Video Technology in Network Assisted Art Innovation by Computer Artificial Intelligence
Authors: Geng Yunshan
Published: December 2021

In response to the needs of the teaching of art majors in colleges and universities today, this paper constructs a “based on campus network art major’s hybrid auxiliary teaching innovation platform system”. The system uses a perfect campus network to establish a secure network-assisted teaching platform system that integrates B/S structure and advanced ASP. NET technology with multi-level users. The platform provides a complete network-assisted teaching environment and realizes the integration and sharing of teaching resources in the largest range. Practical application shows that the highly operable courses of art majors in colleges and universities can stimulate students’ initiative and improve students’ learning ability under the application of this mode.
Research on breakpoint area detection of computer communication network transmission data based on cloud framework
Authors: Zheng Shichuang , Li Jiajun , Chen Shuai , Liang Yujia , Lin Jiangtao
Published: December 2021

Traditional detection method of data breakpoint in computer communication network has some disadvantages, such as time consuming, etc. Firstly, the data of computer transmission breakpoints are stored based on cloud framework, and the density distribution characteristics of the region are extracted according to the breakpoint data. Then the optimal data breakpoint detection path is selected. Finally, the similarity of each data breakpoint is detected by the computer, so that the detection of data breakpoints is realized by computer. After experiments, the data breakpoint detection is realized, the results show that the designed method can detect data breakpoints accurately, which is time-saving and has a certain significance of popularization.
Research on the Application of Artificial Intelligence Technology in Power System Intelligent Dispatching Automation
Authors: Liu Hongying
Published: December 2021

From the perspective of meeting the power quality requirements of users, the article analyses the characteristics of traditional voltage and reactive power control mode and the regional power grid reactive voltage optimization centralized closed-loop control mode (AVC system) based on the dispatch automation system (SCADA/EMS) from the perspective of technical management. Combining the reactive power/voltage real-time optimization control model, a real-time optimization control method of the regional power grid based on the improved differential evolution algorithm is proposed. The particle swarm algorithm is combined with the characteristics of reactive power/voltage control to improve the initial particle quality, reduce the optimization space, and introduce a crossover operator to improve the calculation speed and efficiency of the algorithm. Taking an actual regional power grid as an example, the simulation calculation of reactive power/voltage real-time optimization is carried out. The results show that the proposed algorithm and control strategy are feasible and effective.
Research of Computer Aided Costume Design Application with Image Processing and Drawing Software
Authors: Jing Fei , Gui Yu
Published: December 2021

Computer aided design (CAD) is a practical course in the major of costume design. In the future, computer information technology will be more mature, the use of computers is more popular. The computer technology assisted in costume design specialty can better promote the development of this specialty to follow the trend. The use of computer-aided technology in costume design can enrich the content and make the skill training more real. However, to break through the existing problems, it is necessary to make the teaching of professional courses keep pace with the development of the industry. The use of computer aided technology in primary school teaching will also bring impact from the traditional clothing teaching. We will further promote teaching reform and improve teaching quality.
Segmental Intelligent Model Test of Box Girder Bridge Strengthened By a Cable-Stayed System by Mathematical Calculation
Authors: Wang Xianggang , Shen Yongli , Yang Yongcheng , Zhou Xinxin , Xu Gangnian , Chen Zihua
Published: December 2021

Dongming Yellow River Highway Bridge is an important super large bridge across the Yellow River on national highway 106. In order to effectively improve the cracking and deflection of the bridge, the cable-stayed system is used to reinforce the main girder of the project. In order to analyze the stress state of joist, bracket and box girder, the static loading of cable is carried out through scale model test to study the mechanical properties of concrete box girder segment, joist and bracket, verify the reliability of bracket and concrete box girder anchorage, and optimize the reinforcement method of cable-stayed system according to the test results.
Smart Risk Assessment Model of Water Inrush in Submarine Tunnel through AHP-TOPSIS and Intelligent Computing
Authors: Song Qian , Zhou Binghua , Kong Fanmeng , Jiang Xudong , Yu Yuehao
Published: December 2021

In tunnel construction, water and mud inrush disasters are prone to occur when the tunnel traverses water-rich faults, which leads to structural damage and tunnel instability, which is one of the most severe hazards in tunnel excavation and construction. This paper proposes a method of combining AHP and TOPSIS. The weights are determined through the analytic hierarchy process utilizing expert scoring. The determined weights are evaluated and predicted by TOPSIS for water inrush risk. The Jiaozhou Bay Subsea Tunnel is used as a case to carry out the tunnel crossing the fault zone. Water inrush risk prediction provides a new idea for water inrush risk prediction.
Intelligent numerical computation method and quantitative study on morphological characteristics of multi-scale aggregate
Authors: Yang Haodan , Mei Yingjun , Feng Guangyu , Dou Peiyuan , Zheng Yiwei , Zhao Haidong
Published: December 2021

Use Image-Pro Plus software, high-precision inductive sensor TR200, electro n microscope and ENVI image processing system to quantitatively study aggregate mo rphology from three scales: macro, meso, and micro, and obtain P, As, R, Ry, Rsm, et c. 17 quantitative indicators of morphological characteristics, compared with the occup ancy rate of the aggregate broken surface and the roughness of the aggregate surface. T he results show that the 17 morphological characteristics indexes are feasible for multi -scale quantification of aggregate morphology. Macro-morphological characteristics di rectly indicate the angularity and needle-like shape of materials, micro-morphological characteristics directly indicate the roughness of materials surface, and micro-morphol ogical characteristics directly indicate the micro-morphological characteristics of mate rials. The quantitative indexes of aggregate morphology at micro-scale and micro-scal e are improved, and the results are helpful to reveal the morphological characteristics o f aggregate comprehensively.
A FEA Method for Mathematical Calculation and Prediction Analysis Cross-sectional Ovalization of Tubes under Rotary Straightening
Authors: Zhang Ziqian , Zhong Ying
Published: December 2021

The section flattening phenomenon (namely Bazier effect) will occur in the large bending deformation stage of thin-walled pipe in the continuous straightening process. The maximum section flattening amount and the residual section flattening amount are important process parameters, which are the basis for calculating the subsequent process parameters of the flattening circle, and directly determine the roundness of the final pipe and the product quality. However, it is hard to be obtained by the theoretical or experimental methods. Therefore, based on the structure and process parameters of the leveler, a finite element model was built to simulate the section flattening process. Then, ANSYS/LS-DYNA software was used to dynamically simulate the bending flattening phenomenon of thin-walled pipe in the continuous straightening process, and the stress and strain nephographic of the flattening deformation zone was obtained. By recording the position curve of the key nodes in the preventing process, the section flattening amount of the thin-walled pipe in the large bending deformation stage in the continuous straightening process was determined. The simulation results show that the dynamic simulation method can effectively predict the section flattening of thin-walled pipe in the process of continuous straightening.
The High-Reliability Optimization of Dead-Time Circuit for Push-Pull DC-DC Converter
Authors: Guo Huixia , Li Xiang , Jia Libin , Hao Yongqin , Ren Wu
Published: December 2021

Aiming at of the problem of common conduction state in push-pull DC-DC converter’s power transistor, an optimization solution by improving pulse width modulation(PWM) mode and reasonable setting parameters of the transformer and the inductance was proposed. The solution was analyzed in detail and test of the optimized circuit are carried out. The results show that the optimized circuit can effectively eliminate common conduction state, make the converter have a suitable dead-time and greatly improve the reliability of the converter.
Research on Intelligent Information System of Library under Big Data and Digitization Technology
Authors: Wang Chunyu , Sha Zhengyu
Published: December 2021

In the big data environment, we develop personalized information of college libraries based on big data from three aspects: the overall architecture of the system model, the functional model of the system, and the design of system interface modules according to the design principles and requirements of the personalized information service system of the university library Service system design. In terms of the functional design of the platform, the service platform is divided into four levels: accurate identification of user needs based on big data, personalized customized services based on artificial intelligence, academic research and discussion space based on integrated media, and fine-grained subject resource aggregation based on knowledge. On this basis, a centralized model of individualized services of university libraries including internal and external personnel, information resources, technology, services, processes, platforms, and environment has been constructed.
Computer Intelligent Cloud Server Platform of Coal Preparation Plant Based on Big Data Cloud Technology
Authors: Zhang Qing , Chen Hao , Wang JiaYin , Zhu YuGe , Zhou ChangZhong
Published: December 2021

This article combines the actual situation of the coal preparation plant and uses big data cloud technology to carry out detailed system requirements analysis and monitoring platform design. The entire design includes server framework design, database design, cloud service deployment and mobile client prototype design. According to the on-site working conditions of electromechanical equipment, the article uses ER model and 3NF method to abstract it and establishes a MySQL real-time database of equipment operating status. Finally, the ECS cloud server is used to complete the deployment, and the JSP technology is used to realize the display of the system’s man-machine interface, as well as remote monitoring services for equipment monitoring, information management, and user management. Practical application shows that the system can improve the comprehensive automation and information level of the enterprise, reduce the operating cost of the enterprise, and improve the production efficiency of the enterprise.
Digital Twin Based on 3D Visualization and Computer Image Recognition Technology in Coal Preparation Plant
Authors: Zhang Qing , Chen Hao , Zhu YuGe , Wang JiaYin , Zhou ChangZhong
Published: December 2021

The digital twin coal preparation plant is a potentially effective way to realize the intelligent interconnection and interactive integration of the manufacturing physical world and the information world. Aiming at the difficulty in predicting and maintaining the state of the shearer in a harsh working environment, combined with the high-fidelity behaviour simulation characteristics of the digital twin and the powerful data mining capabilities of deep learning, a coal shearer health prediction driven by the integration of the digital twin and deep learning is proposed. Method. The article builds an information management and integration platform composed of a real-time database and a comprehensive information platform, and realizes the unified management of data integration and application systems.
Integer Ambiguity Fixation Based on SC-PAR Algorithm
Authors: Jia Xizi , Ji Yuanfa , Fu Wentao , Liang Weibin , Pan Bingye
Published: December 2021

In terms of quality control of ambiguity estimation, the common partial ambiguity fixation algorithm is improved, and the SC-PAR (Single frequency Combined Partial Ambiguity Resolution) algorithm is proposed. After the algorithm fails to fix the full ambiguity, it filters the ambiguity subset step by step according to the number of continuous satellite lock epochs, satellite elevation angle, satellite signal-to-noise ratio, geometric precision factor, ambiguity variance and ambiguity precision attenuation factor, and searches Optimal ambiguity subset. According to the R-ratio value and the success rate index, the search results are jointly tested, and the remaining subsets are corrected with the subsets that pass the test. The results show that compared with the FAR and conventional PAR algorithms, the fixed rate of the SC-PAR algorithm is increased by 65.01% and 27.97%, respectively, and the accuracy is also significantly improved.
Mathematical modeling of a new way of renal artery denervation
Authors: Makarov VN
Published: December 2021

The aim of the work is to create a new design of electrodes for renal denervation. In standard RFA systems, monopolar heating is most often used, by introducing an RF electrode inside the vessel. This approach leads to the need to interrupt blood flow during the procedure. In addition, the monopolar mode of operation requires the contact of the inserted electrode with the vessel walls, which greatly complicates the design of the electrode system. Point contact of the electrode system with the vessel can damage the inner walls of the artery. It is proposed to use a multi-electrode structure for external stimulation by creating a hollow cylindrical thermal field for effective treatment. It has been established that external heating will create the required thermal field without direct contact with the walls of the artery. The external arrangement of the electrodes makes it possible to regulate the temperature on the external surface of the vessel. With such heating, it is not necessary to block the blood flow, and due to the symmetry of the arrangement, continuous heating can be obtained without moving the electrodes during the procedure. Mathematical modeling confirms the possibility of vascular denervation during external heating.
Numerical Modeling of Climate (on Yakutia example)
Authors: Pomortsev O A , Kashkarov E P , Pomortseva A A
Published: December 2021

Numerical modeling of time series of observations of Yakutsk meteorological station was used for the first time to construct a model of heat and moisture climate variability over the course of a century cycle of solar activity (SA). The lag of precipitation relative to temperature for ¼ of the rhythmic wave was revealed. Consecutive change of climatic phases: cold-wet (CW) warm-wet (WW), cold-dry (CD) and warm-dry (WD) has been established. The nonlinearity of the solar-tropospheric relations at level of intra- and secular oscillations is confirmed. The trends and anomalies of climate changes and permafrost response for the next decades and the current century as a whole are determined.