bluuebunny/crossref_metadata_2025 huggingface dataset:
Water Resources Information Management System Based on Agent Model
Authors: Wang Fu
Published: November 2021

With the rapid development and wide application of computer technology and network technology, the Internet has become an important information infrastructure in modern society. However, the resource capacity used by the Internet is much smaller than the actual resource capacity. How to choose the right resources to serve the people has become a crucial issue. Huge data resources, heterogeneous distribution and unreasonable resource organization are important reasons for this phenomenon. When solving the problems of batch data, heterogeneous distribution, complex processing, and cumbersome use in a distributed heterogeneous network environment, the traditional methods of resource processing and resource aggregation services become more and more difficult. In recent years, how to redistribute and organize scattered resources in a dynamic and open environment, how to effectively gather different resources, realize resource sharing and full utilization, and provide users with reasonable and convenient resource collection services have become one of the main research points. This paper mainly uses the questionnaire survey method to study the water resources information management system based on the Agent model. First, it summarizes the characteristics of the Agent model and the problems existing in the water resource information management system based on the Agent model through the literature research method, and then uses the questionnaire survey method, investigate some evaluations and suggestions about the need to use the water resources system. The results of the survey show that in the evaluation of the use of the water resources information management system based on the Agent model, about 50% of people encounter the waiting time for the system. For long-term phenomena, about 30% of them are stuck. The recommendations for the use of water resources information management systems based on the Agent model are more concerned about the simple operation of the system, with about 54% of the choices, and about 36% of the people choosing when there is no lag.
Research on the Structure of Distribution Network Voltage Smart Grid Information System Based On Flexible DC
Authors: Yang Jingwen , Chen Zhongxiao , Qin Gang , Chen Jiarui , Fu Kaiqing
Published: November 2021

Since the concept of smart grid was defined, it has aroused the interest of many researchers, and many countries have also regarded smart grid as a key research project. Because it is the field of power grid research in the future, the structure of the smart grid becomes more complex with the deepening of research, the scale becomes larger, and the data contained in the system is bound to increase rapidly. Flexible DC grid technology has the characteristics of high reliability, good fault tolerance and good scalability, and can be used to solve some problems encountered in the application of smart grids. Based on the structure of the smart grid information system, this paper studies the characteristics of the smart grid data, as well as some safety issues encountered in the data, applies flexible DC power distribution technology, designs a new smart grid equipment management architecture, and System implementation was carried out. Through experimental verification, the new architecture proposed in this paper has high feasibility and safety. Finally, the realization of the management system function based on the new equipment management architecture and the analysis of the system function effect are given.
Computer Network Reliability Improvement Method Based on Genetic Algorithm
Authors: Huang Kun
Published: November 2021

With the continuous growth of economy and the continuous development of society, once the computer came out, it has been rapidly developed and popularized, especially now, people’s life is more and more inseparable from the computer, and they have a serious dependence on the computer. Some industries even directly use the computer as the business pillar, once such industries leave the computing industry Therefore, the reliability of computer network is a very important topic. It is very important to improve the reliability of computer network. In order to explore the effect of genetic algorithm on improving the reliability of computer network, two experimental groups are set up in this paper. The experimental group adds genetic algorithm in its computer network operation, while the control group uses the traditional algorithm. Finally, the experimental results show that the accuracy and security of the computer network in the experimental group are higher than those in the control group. For example, the highest accuracy and security of the experimental group are 99.78% and 98.83% respectively, while the highest accuracy and security of the control group are 84.31% and 88.58%. These experimental data show that the genetic algorithm can play a positive effect on the security of computer network.
Research on NC Machining Programming Technology in the New Era
Authors: Ye Weiwen
Published: November 2021

with the application and development of intelligent technology in the machining industry, the machining industry is gradually transforming from automation to intelligence. The basis of automatic machining comes from the programming of NC machining program. In the new era, CNC machine tools have high requirements for the accuracy and digitization of machining production. Macro programming technology and modularization design are introduced in NC programming. The first part of this paper introduces the NC machining programming technology. The second part analyzes the technical requirements of NC machining programming technology in improving the accuracy of machining parts; the third part discusses the automatic programming technology of NC machining from the perspective of macro programming technology. The purpose is to provide some reference for the application of NC machining coding technology.
Evaluation Method of Reservoir Heterogeneity Based on Neural Network Technology
Authors: Yang Shasha , Chen Ying , Yang Yong , Yuan Kekuo , Quan Juanjuan
Published: November 2021

Reservoir is the underground storage and accumulation place of oil and natural gas. The accuracy of reservoir heterogeneity evaluation has great economic value for correctly guiding the production and development of oil and natural gas. The high-order neural network method is used to comprehensively evaluate the heterogeneity of the reservoir. This method was applied to the evaluation of reservoir heterogeneity in the PK area. The results show that the heterogeneity of sandy clastic flow sand bodies is the weakest, the sandy landslide sand bodies are medium, and the turbidity current sand bodies are strongest. The evaluation method of reservoir heterogeneity based on high-order neural network technology effectively solves the problem of inconsistent conclusions of single-parameter evaluation of heterogeneity in conventional methods, and can quantitatively characterize the degree of reservoir heterogeneity.
Underwater Image Enhancement Method Based On Color Correction and Dark Channel Prior
Authors: Chen Hao , He Hongsen , Feng Xinghua
Published: November 2021

Concerning to the problem in the distortion of color and the low contrast of underwater image, the image enhancement method in the underwater environment based on color correction and dark channel prior was proposed. When dealing with the color bias problem, the blue channel standard ratio is firstly calculated based on the blue channel, and the red and green channels of the underwater image are compensated to remove the blue and green background colors of the underwater image. In light of the problem in the low contrast of image in underwater environment, the dark channel prior (DCP) method based on the super pixel was used to enhance the corrected underwater image. Finally, the underwater object detection dataset images are tested, and the algorithm proposed in terms of the quality is made the comparison with six advanced image enhancement method in underwater environment. The experimental results show that the proposed algorithm earned the highest score in underwater quality evaluation index (UIQM) compared with the above algorithm.
LFM/PRBC Modulation Signal Parameter Estimation
Authors: Chen Shihong
Published: November 2021

Since pseudo-code phase modulation and carrier frequency modulation composite reconnaissance signals have both the good anti-interference capability and the low probability of interception, they have been widely used in electronic reconnaissance systems. This paper proposes a multi-parameter estimation method for pseudo-random binary phase code (PRBC) and linear frequency modulation (LFM) composite modulation signal in a complex electromagnetic environment. Firstly, this paper uses the square operation to remove the code phase information; secondly, we use the delay correlation and two times frequency estimation to estimate the starting frequency and the frequency modulation rate; finally, the wavelet transform algorithm is utilized to estimate the code rate parameter. Through the simulation analysis and full comparison with other methods, we can prove the performance superiority of this method under low signal-to-noise ratios (SNRs).
Application of Cloud Computing Technology in Information System Construction
Authors: Zeng Renxian
Published: November 2021

With the rapid development and improvement of information technology, information system construction has new requirements and goals. Cloud computing technology is an inevitable choice in the construction of information system. By taking cloud computing technology as the basic structure framework, the phenomenon of data information island can be broken. The purpose of this paper is to study the application of cloud computing in the construction of information system. Taking the management mode of university campus as an example, based on the research of cloud computing technology, virtual machine technology and Internet of things technology, this paper discusses the data resource management algorithm of smart campus. Aiming at the scheduling model, strategy and research objectives of cloud computing resources in data center, this paper proposes a method of initial allocation and adaptive dynamic scheduling of virtual machine resources. According to the multi-dimensional vector characteristics of virtual machine, this paper proposes a resource allocation algorithm based on multi-objective evolution, and gives four important strategies. The experimental results show that the four advantages and strategies can effectively reduce the number of virtual machine migration and reduce the adverse impact on the overall performance of cloud computing core network.
Research on Simulation System of Rubber Particle Mat Based on Web Technology
Authors: Zhang Jiali , Li Haichan , Qing Haohua
Published: November 2021

The current design of rubber granular floor mats is limited to a single fixed plane sample drawing, and it consumes a lot of time, manpower and material resources in obtaining customer design requirements. In response to this situation, the use of Web development technology to realize the free combination of particles in proportion, generate simulation application scenarios, provide interface operations, and finally complete the order process. By constructing a particle probability distribution model, establishing a particle position coordinate matrix, and developing a particle mat simulation system, based on the sample quality of the sampled data, it is compared with the real artificial mechanical product. Finally, by mixing and matching 9 different color values according to the industrial production ratio, randomly combining 10 groups and comparing with the real products of the same color ratio, quantifying the color difference, contrast, and particle position offset to obtain the production simulation floor mat sample and the actual product. The finished product is quite close. The system generates simulated particle mat maps and real sample maps with a high degree of simulation, and provides an interface that allows users to directly match the particle combination program that suits their needs, saving labor cycles and improving work efficiency.
Architectural Design of Building Information Model Technology in Internet Age
Authors: Wang Dong
Published: November 2021

As a revolutionary technology to realize the construction industry information, BIM technology has been vigorously developed in China in recent years. The whole life cycle of a construction project includes planning stage, design stage, construction stage, operation and maintenance stage, with many participating units. This paper mainly studies the architectural design of building information model technology under the Internet era. This paper analyzes and combs the traditional structural design process, and summarizes the problems and defects existing in the traditional structural design process. Combined with the characteristics of BIM technology application, the BIM technology is combined with the traditional structural design process. Taking Project A as an example, the causality analysis, the analytic hierarchy process and the fuzzy comprehensive evaluation method are used. The architectural design quality of Project a based on BIM technology is evaluated, and the effect of adopting BIM technology in the design of Project A is compared and analyzed.
Simulation of Urban Storm Water Runoff Control Based on Big Data
Authors: Liu Yunzhu , Cao Jinbao
Published: November 2021

The acceleration of urbanization has brought about rapid economic development, but at the same time, it has also brought some damage to the ecological environment. The proportion of hardened area of the ground is higher and higher, and the rainwater runoff pollution caused by rainfall is more and more serious. In order to follow the sustainable development strategy, and for the more stable and high-speed economic development, the control of rainwater runoff pollution is urgent. The purpose of this paper is to simulate the urban storm water runoff control and find the most suitable scheme for storm water runoff pollution control. Because the simulation of SWMM is more accurate than other models, it can directly reflect the situation of rainwater runoff pollution, so the model selected for rainwater runoff in this paper is SWMM, and then build the model, through the collection and collation of the basic data of the study area, the generalization of the sub catchment area and drainage network is completed. Through the analysis of the characteristics of the study area, the rainwater garden and permeable pavement are determined as the scheme to control the rainwater runoff in the study area. Finally, the SWMM model is used to simulate the control effect of rainwater garden and pervious pavement on rainwater runoff pollution control. The experimental results show that the storm water garden can effectively control the impact of SS scouring effect on the environment, significantly reduce the discharge of SS, and significantly reduce the peak concentration of SS, and its ability to control SS increases with the thickness of the surface plant layer. The control ability of rain permeable brick pavement to SS increases with the increase of surface porosity, that is, the control effect of SS is the best when the porosity is 20%.
Computer Experiment Management in Virtual Environment
Authors: Deng Jianqing
Published: November 2021

With the development of the era of big data and the continuous updating of computer technology, the traditional teaching is not satisfied with the current diversified educational development concept, especially for the computer operation class, computer operation has become the mainstream of the current computer experiment class.With the increasing number of computer experiments and the extensive use of computers in open laboratories, how to manage computer experiments reasonably has become an urgent problem. The function of the computer is powerful, and students have different habits of using the computer, and the entertainment function of the computer is also loved by many students. Therefore, in the process of experiment, students often play games and watch movies, which is not easy to manage. In order to solve these problems, this paper studies the computer experiment management system under the virtual environment to help teachers manage the experiment process. This paper studies the function modules of the computer experiment management system, explains the key elements of the analysis of the implementation of the experiment management system, and explains the construction scheme of the virtual experiment teaching environment, and expounds the ant colony algorithm used in the design and management of the course scheduling system. This paper also analyzes the operation and load of computer experiment management through simulation experiment research, and tests and analyzes to prove the rationality of the management system. The experimental research shows that in the daily computer experiment management system, the most commonly used is the experimental teaching, and the conventional office, accounting for 27.35 and 26.33 respectively. The highest utilization rate of the computer experiment system is the daily teaching, accounting for 53.6%.
Prediction Study of Tianjin Port Throughput Based on GM (1, 1) Extended Model
Authors: Wang Yahui , Zhang Zhuoyi
Published: November 2021

Tianjin Port is the largest comprehensive main hub port and one of the main transshipment ports for energy and raw materials transportation in northern China. It has freight business with many countries. At the same time, Tianjin Port is the first port to carry out international maritime container transportation in China’s coastal areas. Tianjin Port was built in the 1950s, and the container business has been started since 1973, In recent years, with the rapid development of large-scale, intensive and intelligent container ships in Tianjin Port, cargo throughput is an important indicator in the comprehensive evaluation of port development, which represents the development level of a port. At the same time, it also brings new tasks to the navigation guarantee work, in particular, it puts forward systematic requirements for port and wharf construction, navigation aids layout, navigation aids efficiency display and navigation aids base layout. The annual throughput of port cargo or container is one of the bases of world ports. As an output index, port enterprises, shipping companies, navigation guarantee departments and shipping economic analysis departments attach great importance to it. Therefore, the prediction of Tianjin Port cargo throughput can provide reference for Tianjin Port’s next development planning, waterway use and navigation guarantee planning and layout, navigation aids setting, wharf construction, route mapping, etc. the article constructs of Tianjin Port. The average error is 0.29%, and the prediction accuracy is first class. This model can better predict the change trend of cargo for Tianjin Port, which is a better way to analyze the change trend for Tianjin port.
An Improved Convolutional Neural Network for Text Classification
Authors: Fan Xiaojing , Runa A , Pei Zhili , Jiang Mingyang
Published: November 2021

This paper studies the text classification based on deep learning. Aiming at the problem of over fitting and training time consuming of CNN text classification model, a SDCNN model is constructed based on sparse dropout convolutional neural network. Experimental results show that, compared with CNN, SDCNN further improves the classification performance of the model, and its classification accuracy and precision can reach 98.96% and 85.61%, respectively, indicating that SDCNN has more advantages in text classification problems.
Analysis Methodology of Unusable Fuel Supply for Large Rotorcraft Airworthiness Certificate
Authors: Li Sheng
Published: November 2021

The unusable fuel quantity plays a key basis for calibration of aircraft fuel gauge and fuel measurement system. Using large helicopter fuel tanks as case study, the paper described airworthiness requirements for fuel system design and current research development. In particular, the paper presented an analysis method can be utilized and referenced as means of compliance for airworthiness requirements. This method will reduce the qualification time and save money for physical and dynamic bench test/flight test in the future.
Method of Locating Ground Fault in Low Resistance Grounding Distribution Network by Grounding Wire Current
Authors: Yang Bo , Fan Yuanchun , Yang Chen , Xu Jun , Zhou Yang , Gao Yang , Chen Kui
Published: November 2021

Three-core cables are increasingly used in urban distribution networks. The shielding layer, armor layer of the three-core cable and the earthing electrode constitute the earth-electrode network. When a ground fault occurs, a regular ground wire current distribution is formed in the network. This paper analyzes the distribution law of ground current, and according to the distribution law, puts forward a kind of grounding fault location method of neutral point small resistance grounding grid, and finally designs and implements the grounding fault location system.
Engine Cooling Device of New Energy Vehicle
Authors: Liu Feifei
Published: November 2021

With the environmental pollution and the shortage of oil resources becoming more and more serious, the development and application of new energy vehicles have attracted more and more attention. Engine is an important part of new energy vehicles, and its performance has a great impact on the vehicle. Compared with traditional industrial motors, new energy vehicle engines have higher requirements on power density, and the improvement of power density poses new challenges to the design of motor cooling system. The purpose of this paper is to study the engine cooling device of new energy vehicles and improve the overall performance of the vehicle. The main research content of this paper is to lay a foundation for the theoretical basis of the engine cooling device, elaborate the working principle of the motor cooling system and the loss of the motor in operation. Then, the heat dissipation system of permanent magnet synchronous motor based on heat pipe is studied experimentally. Aiming at the problem of only considering the temperature rise and ignoring the pressure loss in the flow channel design, a flow channel design method considering the motor temperature rise and the flow channel pressure loss is proposed, and the motor flow channel is optimized. The test results show that the maximum temperature rise at the end is close to 16.56 °C, which is in good agreement with the simulation results. It shows that the heat pipe based heat dissipation system can effectively reduce the temperature rise of motor winding, which provides a new idea for the heat dissipation design of permanent magnet synchronous motor
Model-based Intelligent Recognition for Aluminum Plate Seam Defects
Authors: Liu Hongming
Published: November 2021

In order to study the application of nonlinear ultrasonic in the quantitative identification of defective aluminum plate, different depth cracks are machined on the aluminum alloy plate with a thickness of 10 mm by wire cutting to simulate the defects in the plate. The normal and defective aluminum plates are selected to establish the experimental model, and the continuous wavelet transform (CWT) is used to extract the characteristic parameters of the aluminum plate nonlinear ultrasonic signal. The dimensions of the data are reduced by principal component analysis (PCA), and the principal component with the top three contribution rate are selected as the characteristic value. Finally, the support vector machine (SVM) algorithm is used to analyze the aluminum alloy plate state and classify the defect signal. The experimental results show that the feasibility of nonlinear ultrasonic signal recognition of aluminum plate defects is verified by combining principal component analysis and support vector machine model.
Fruit Processing Equipment based on Model Processing
Authors: Kang Di , Fan Youhua , Chen Zejun , Ma Fang , Peng Shaofeng , Wang Yong
Published: November 2021

The technology and equipment of this study can improve the technical level of the equipment for peeling and cleaning of Camellia oleifera fruit. Based on the biological characteristics of Camellia oleifera fruit, the size distribution model of Camellia oleifera fruit was established, and the equipment structure and key parameters were determined based on the working principle and design method of the shelling and cleaning mechanism. Based on the analysis of the movement track of the shell stripping and cleaning executive parts, the test scheme is established, and it is optimized that when the crankshaft speed is 240-260r/min and the track speed is 0.4-0.6m/s, the treatment capacity can reach the level of 2000kg/h, and the purification rate is more than 99%. When the vibration frequency of the vibrating motor is set to 50Hz and the horizontal inclination of the separation belt is 50 ° ∼ 55 °, the cleaning effect of the equipment is the best.
Distortion of AISI 1020 steel substrate in the process of laser cladding of E-300 powder material
Authors: Lyukhter A B , Frolov K A , Kochuev D A , Zavitkov A V , Gusev D S
Published: November 2021

The results of experimental studies to determine the effect of power during laser powder cladding on temperature deformations of the substrate at a constant cladding rate and the mass flow rate of the powder are presented. Steel 1020 was used as the substrate material, from which samples of sizes 90x90 mm and a thickness of 8 mm were made. Laser powder cladding was performed by using a wear-resistant powder E-300 on a robotic complex with an ytterbium fiber laser and a coaxial powder feed. Single tracks were applied to the sample by laser powder cladding using various parameters of technological modes. The amount of deformation of the substrate was estimated taking into account the depth of the mixing layer. The cladding mode is selected, which provides minimal temperature deformations, with maximum process performance.
Expansion of technological capabilities of the electron beam welding installation
Authors: Starkov I N , Rozhkov K A , Olshanskaya T V , Trushnikov D N , Zubko I A
Published: November 2021

The direction of electron beam technologies is promising and is rapidly developing. Quite recently, the electron beam was a tool for welding, and nowadays, electron-beam additive technologies and beam hardening technologies have become widespread. At the moment, there is no electron beam system that unites all these technologies. Expensive equipment has been developed to implement each technology. The article deals with expanding the technological capabilities of the 15E1000 electron-beam welding installation in order to implement new methods and techniques for processing metals with an electron beam.
Optimization of CSO algorithm based on adaptive inertia weight coefficient
Authors: Suo Dongnan
Published: November 2021

The traditional CSO algorithm is easy to fall into local extremum in optimization. In this paper, a CSO algorithm based on weight coefficient is proposed. In the CSO algorithm, the inertia weight coefficient is introduced into the hen position formula, and the learning factor influenced by the rooster is added to the chick position formula. Finally, using the idea of heredity, individuals with excellent fitness value are selected for crossover and mutation with a certain probability. Through the simulation comparison of five typical test functions, the simulation results show that the improved CSO algorithm can avoid local optimization, strengthen the global extreme value search ability, and improve the convergence speed and accuracy range of the algorithm.
Knowledge dialogue generation with multi-head attention mechanism
Authors: Yang Fengrui , Wu Xiaosi , Zhao Luwei
Published: November 2021

An increasing number of research efforts are focusing on knowledge dialogue generation. Less attention is focused on increasing knowledge diversity in generated responses. A model of knowledge selection guided by a multi-head attention mechanism is proposed. First, the current input discourse and knowledge content are input into the Bi-GRU module to obtain the coding vector, and then obtain multiple aspects of semantics from the user input discourse coding vector based on the multi-head attention mechanism, so as to select different knowledge. A punishment item method is proposed to force different attention to focus on different aspects, and finally, use the user input and selected knowledge for the decoding stage. Experiments with manual and automated evaluations have proven that the model is superior to the baseline model compared to previous work.
Improved visual inertial odometry based on deep learning
Authors: Wang Jiabin , Gao Faqin
Published: November 2021

The traditional visual inertial odometry according to the manually designed rules extracts key points. However, the manually designed extraction rules are easy to be affected and have poor robustness in the scene of illumination and perspective change, resulting in the decline of positioning accuracy. Deep learning methods show strong robustness in key point extraction. In order to improve the positioning accuracy of visual inertial odometer in the scene of illumination and perspective change, deep learning is introduced into the visual inertial odometer system for key point detection. The encoder part of MagicPoint network is improved by depthwise separable convolution, and then the network is trained by self-supervised method; A visual inertial odometer system based on deep learning is compose by using the trained network to replace the traditional key points detection algorithm on the basis of VINS. The key point detection network is tested on HPatches dataset, and the odometer positioning effect is evaluated on EUROC dataset. The results show that the improved visual inertial odometer based on deep learning can reduce the positioning error by more than 5% without affecting the real-time performance.
Structured Knowledge Base Q&A System Based on TorchServe Deployment
Authors: Ye Xia , Liu Ruiheng , Yue Zengying
Published: November 2021

Structured tabular data are widely used in various information systems, especially with the development of big data technology, making it more difficult to query on these complex data. SQL facilitates the query on structured tabular, however, the mastery of SQL has a certain threshold for most non-expert users. Therefore, in order to facilitate ordinary users to quickly obtain the required information in complex structured data, we design and implement a Q&A system for structured knowledge. First, we make a detailed distinction between Q&A scenarios for structured data and design different approaches, respectively. Then, we introduce deep learning models in system algorithm layer to enhance the generalization ability. Finally, the TorchServe framework is used to optimize system deployment and improve system performance using batch inference. The experimental results show that the prototype system has certain generalization ability and also has some advantages in performance compared with traditional methods.
Application Analysis on PSO Algorithm in the Discrete Optimization Problems
Authors: Chen Qinglong , Peng Yong , Zhang Miao , Yin Quanjun
Published: November 2021

Particle Swarm Optimization (PSO) is kind of algorithm that can be used to solve optimization problems. In practice, many optimization problems are discrete but PSO algorithm was initially designed to meet the requirements of continuous problems. A lot of researches had made efforts to handle this case and varieties of discrete PSO algorithms were proposed. However, these algorithms just focus on the specific problem, and the performance of it significantly degrades when extending the algorithm to other problems. For now, there is no reasonable unified principle or method for analyzing the application of PSO algorithm in discrete optimization problem, which limits the development of discrete PSO algorithm. To address the challenge, we first give an investigation of PSO algorithm from the perspective of spatial search, then, try to give a novel analysis of the key feature changes when PSO algorithm is applied to discrete optimization, and propose a classification method to summary existing discrete PSO algorithms.
Target Tracking Using Kalman Filter Based Algorithms
Authors: Ling Jiankun
Published: November 2021

Kalman filter and its families have played an important role in information gathering, such as target tracking. Data association techniques have also been developed to allow the Kalman filter to track multiple targets simultaneously. This paper revisits the principle and applications of the Kalman filter for single target tracking and multiple hypothesis tracking (MHT) for multiple target tracking. We present the brief review of the Bayes filter family and introduce a brief derivation of the Kalman filter and MHT. We show examples for both single and multiple targets tracking in simulation to illustrate the efficacy of Kalman filter-based algorithms in target tracking scenarios.
Multi-operator feature enhancement methods for industrial defect detection
Authors: Zhou Bo , Fan Yi Chao , Liu YuXin , Yin XuDong
Published: November 2021

Deep learning based object detection algorithms have been gradually applied to industrial defect detection, but the resulted accuracy does not fully meet the needs of industrial inspection. In order to enhance image features, this paper proposes a series of image preprocessing schemes based on edge detection operators, using a single-operator preprocessing scheme, a multi-operator serial preprocessing scheme and a multi-operator parallel preprocessing scheme for image preprocessing of data to enhance the edge features of images. The validation experiment of the SSD based object detection algorithm is performed on dataset used for industrial inspection, to verify the effectiveness of the processing schemes above. The result shows that the multi-operator based image preprocessing method is effective in improving the accuracy of surface defect detection in the field of industrial defect detection.
Automatic Term Recognition Method for Military Domain
Authors: Song Ani , Jia Xiaoxia , Jiang Wei
Published: November 2021

With the development of military intelligence, higher requirements are put forward for automatic term recognition in military field. In view of the characteristics of flexible and diverse naming of military requirement documents without annotated corpus, the method of this paper uses the existing military domain core database, and matches the data set and core database by Aho-Corasic algorithm and word segmentation technology, so that the terms to be recognized in the data set can be divided into three types. The possible rules of word formation of military terms are summarized and phrases that conform to the rules of word formation are found in the documents as the term candidate set. The core library and TF-IDF method are used to calculate the value of the candidate terms, and the candidate terms whose value is greater than the threshold are selected iteratively as the real terms. The experimental results show that the F1 value of this method reaches 0.719, which is better than the traditional C-value method. Therefore, the method proposed in this paper can achieve better automatic term recognition effect for military requirement documents without annotation.
Research on Wafer Surface Defect Pattern Detection Method Based on Incremental Learning
Authors: Yu Naigong , Li Xin , Xu Qiao , Jiang Kai
Published: November 2021

Wafer manufacturing is an important step in quality control and analysis in the semiconductor industry. The defect pattern classification algorithm of wafer maps has received extensive attention from academia and industry. At present, most methods for detecting wafer surface defect patterns focus on static data model classification and analysis. However, in the production process, static data models cannot satisfy the dynamic analysis of wafer defect patterns in the form of streaming data. In this regard, this paper proposes a wafer surface defect pattern detection method based on incremental learning. Our experiment uses Resnet as the backbone network, and the data set uses the WM811K wafer data set. Experiments have proved that our method can achieve better classification accuracy in the field of wafer defect detection, which provides the possibility for continuous learning of wafer defects in the future.
Design of Single-lamp Monitoring System for Airfield Lighting Based on Broadband Power Line Carrier Communication
Authors: Yang Xiaolong , Yang Hao , Li Tuo , Ma Xiaodan , Chen Fei
Published: November 2021

Considering the problems of low communication rate and large communication delay of the traditional single-lamp monitoring system for airfield lighting based on narrow-band power line carrier communication technology, a solution of single-lamp monitoring system for airfield lighting based on broadband power carrier communication technology is proposed. Firstly, this paper has made a comparison of advantages and disadvantages between narrow-band power line carrier communication technology and broadband power line carrier communication technology, and briefed the problems faced by traditional single-lamp monitoring system based on narrow-band power line carrier communication. Taking technical characteristics into consideration, broadband power line carrier communication technology is selected for the development of a new single-lamp monitoring system for airfield lighting. Secondly, this paper articulated the design and development process of new airfield lighting single-lamp monitoring system based on broadband power line carrier communication technology, from the formulation of the overall architecture scheme of the system to the realization of local convergent equipment, and focused on the analysis of hardware and software development process of single-lamp monitoring module. Finally, this paper set up a test environment, and verified the performance index by experiments. The test results show that the system meets the design index requirements, can improve the performance of the single-lamp monitoring system for airfield lighting, effectively solves the problems faced by the traditional system, and can further meet the needs of the airport for airfield lighting monitoring and control.
Event Monitoring of Transformer Discharge Sounds based on Voiceprint
Authors: Cai Rui , Wang Qian , Hou Yucheng , Liu Haorui
Published: November 2021

This paper investigates the operation inspection and anomaly diagnosis of transformers in substations, and carries out an application study of artificial intelligence-based sound recognition technology in transformer discharge diagnosis to improve the timeliness and diagnostic capability of intelligent monitoring of substation equipment operation. In this study, a sound parameterization technology in the field of sound recognition is used to implement automatic discharge sound detections. The sound samples are pre-processed and then Mel-frequency cepstrum coefficients (MFCCs) are extracted as features, which are used to train Gaussian mixture models (GMMs). Finally, the trained GMMs are used to detect discharge sounds in the place of transformers in substations. The test results demonstrate that the audio anomaly detection based on MFCCs and GMMs can be used to effectively recognize anomalous discharge in the high scenario of transformers.
Research on manipulator control based on deep reinforcement learning
Authors: Chi Haoyu
Published: November 2021

With the gradual improvement of the influence of intelligent robots in production and life, it has greatly facilitated people's production and life. Therefore, people's requirements for intelligent robots are also increasing, and are developing towards more humanization and intelligence. However, at present, there are still many imperfections in the field of intelligent robot technology in China. In order to solve the problems in work, we must further strengthen the research on artificial intelligence theory and robot technology. Only in this way can we realize the all-round development of intelligent robot system. So this paper will discuss the deep reinforcement learning in the theory of artificial intelligence, and explain its basic theory, research status, existing problems and future development direction. Moreover, under the background of the overall improvement of the current industrial development level, this paper will also talk about the manipulator widely used in the industrial field and the research status of manipulator control based on deep reinforcement learning, hoping to provide effective help for the development of related fields.
Monitoring and Early Warning of Transmission Line External Breakage Based on Satellite-Ground Coordination
Authors: Yang Zhi , Deng Yuanjing , Li Mengxuan , Liu Yi , Zhao Binbin , Chen Zhiyong , Liu Shuai , Kong Liang , Zhao Bin , Wang Jian
Published: November 2021

This article first proposes a high-precision spatio-temporal registration method between satellite remote sensing images and ground sensors. Then, using satellite remote sensing images, an intelligent identification model for typical external damage hidden dangers of transmission lines based on satellite remote sensing is established to realize intelligent identification of transmission line construction work areas and mining affected areas. Aiming at the results of intelligent identification of construction work areas and mining-affected areas, the proposed YOLOv4-based external damage identification algorithm for transmission lines is used to detect external damage hidden dangers. Through the method in this paper, it is possible to realize a regular general survey of hidden dangers of external damage (construction work area, mining affected area) with full coverage of transmission channels, and carry out targeted 24-hour monitoring on the ground. The test results show that the satellite-ground coordinated transmission line external damage monitoring and early warning in this paper. The method timely and accurately realizes the monitoring and early warning of the external breakage of the transmission line.
Research on LDPC in an OFDM System
Authors: Shi Chong-Yue , Li Hui , zhou You-Ling , Wang Ping , Li Qian , Xue Liu-Xun , Xu Jie
Published: November 2021

In this paper, LDPC codes and OFDM technologies are studied, and combines LDPC and OFDM to simulate and verify the performance. The encoding of LDPC and logarithmic domain BP decoding algorithm and the principle of OFDM are introduced. Through MATLAB, the simulation of OFDM-LDPC system in different channel, different code length, different iteration times, LDPC and OFDM-LDPC in the same conditions are compared. Through simulation analysis, we can know that the performance of OFDM-LDPC system will improve with the increase of the code length. When the SNR is small, the number of iterations has little effect on the performance of OFDM-LDPC system. When the SNR is large, the performance of the system will be improved with the increase of the number of iterations. The performance of OFDM-LDPC codes is better than that of LDPC codes. The performance of OFDM-LDPC code is better than LDPC code in multipath Rayleigh fading channel.
Development of the Electroencephalograph-based Brain Computer Interface System
Authors: Gao Xiang , Fnu Gesangzeren , Wan Xianshu
Published: November 2021

A practical BCI-based application design contains a variety of design stages are needed to be considered. The design challenges are majorly present in 3 major stages: brain signal acquisition, signal processing unit, and signal classification. Combinations of different approaches have to be employed to achieve the functional and accurate performance of the overall design. Those design choices, algorithms, and methodologies that are meant to solve design challenges presented in the previously mentioned three stages have become a hot subject of a number of studies. This paper aims at providing a thorough overview of existing methodologies for BCI-based application design, comparing their principles and performance and recommending suitable design choices that would yield an objective result for the application.
Features of growth and development of Abies alba Mill. seedlings in the conditions of Voronezh (Russia)
Authors: Degtyareva S , Dorofeeva V , Shipilova V
Published: November 2021

Phenological observations are one of the methods for studying the reaction of introduced species to new conditions and subsequent introduction into regional phytocenoses. This research wants to assess growth and development of Abies alba Mill., currentlyexotic in the Central Black Earth region of Russia. Seeds, obtained from individuals growing in the natural range (the Carpathians) in 1987 were sown in the university nursery. Then five-year-old seedlings were planted in the University arboretum. At the age of 22 the arboretum habitat was inferior to natural analogues. Phenological observations of bud opening and formation of annual growth coincide with the beginning of the growing season in natural plantings. High rates of seed germination (80%), high annual growth rates of seedlings (and transplanted plant) determined final success of silver fir in forest-steppe conditions. Precipitation has a dominant influence on growth and development, as shown by the correlation analysis between climate and growth, despite the fact that the species is drought-resistant in natural habitats. The study emphasizes the factors that control growth and development of silver fir. The use of this method of sowing is ecologically sound, which can further improve the success of species adaptation to the individual conditions of regional phytocenoses.
Investigation of the impact interaction of pelleted seeds with the soil environment
Authors: Lysych M N , Bukhtoyarov L D , Shabanov M L
Published: November 2021

The issues of studying the impact interaction of seeds with the soil environment by the method of discrete elements are considered. The main parameters of the used virtual stand are described and a brief description of the interaction model is given. As a result of the study, the depth of penetration of the seed, its displacement in the horizontal plane and the greatest depth of the crater were obtained. Analysis of the data showed that on unbound and loosely bound soils, a penetration rate of 50 m/s is sufficient for almost 100% penetration into the surface layer without noticeable displacement of the pelleted seed. On medium cohesive soils at a speed of 50 m/s, stable seed penetration is not ensured. The probability of its release is about 10%. At speeds of 75 m/s, almost 100% penetration into the surface layer is provided without noticeable displacement of the coated seed. On cohesive soils at speeds of 25 m/s, the seed is always ejected from the crater over a considerable distance. At a speed of 50 m/s, the probability of seed ejection is reduced to 30% and at 75 m/s to 10%.