bluuebunny/crossref_metadata_2025_split huggingface dataset:
Speckle noise suppression method using multi-azimuth SAR images.
Authors: Shi Yingru , Liu Yang , Xi Peili , Yang Wei , Zeng Hongcheng 
Published: December 2021

Abstract
Synthetic aperture radar images play an important role in military and civilian fields, but the presence of speckle noise has an impact on subsequent tasks such as target detection and target interpretation. With the development of multi-azimuth observation mode, the obtained multi-azimuth image sequences have high similarities. Therefore, combined with multi-azimuth image sequences, a novel method of SAR image speckle noise suppression based on clustering is proposed in this paper. In this method, multi-azimuth joint filtering framework based on two-level filtering is proposed, in which pre-filtering for single image and joint filtering based on Non-local Means algorithm for multi-azimuth image are used to suppress the noise. And k-means clustering is used to optimize the search area in the multi-azimuth joint filtering, so as to effectively suppress speckle noise while retaining structural details.
Design of Heat Exchange System of Sand Core Drying Furnace
Authors: Peng Yuhao , Ren Tianping 
Published: December 2021

Abstract
Heat exchange system is a circulatory drying system on sand core drying furnace. However, there are some shortcomings in the heat exchange system of sand core drying furnace in the current industrial field. For example, the temperature in the drying process is not stable enough, and the optimal temperature control parameters are difficult to choose. In this study, a proportional regulating heat exchange system is designed. The system adopts SIMATIC 1200 programmable logic controller as controller, motor-driven control valve as actuator and back propagation neural network proportion integral differential control algorithm. After sand core drying test, the results revealed that the proportional regulating heat exchange system can realize automatic control of sand core drying temperature and output the optimal combination of heat exchange system control parameters. Compared to the previous heat exchange system, it has better drying temperature control stability.
Design and Realization of Shooting Virtual Training System for UAV-borne Missile
Authors: Lin Shicong , Tang Xin , Lu Wanlin , Liu Zehui 
Published: December 2021

Abstract
UAV-borne missile is effective weapon to attack enemy ground targets. It is expensive, costly and difficult to live-fire drill. Using virtual training instead of actual training can greatly improve the training efficiency and the combat effectiveness. The article regards the operation training of a certain type of UAV-borne missile shooting training as the research object, based on the development of a visual simulation system for UAV-borne missile, uses the object-oriented design method to design a virtual training system based on LabVIEW. The system can realize the shooting operation training of trainees in a virtual environment, and achieve the goals of reduce training costs; improve training efficiency and shorten training period.
Computer System Integration Technology of Hydraulic Engineering Design Based on Machine Learning Algorithm
Authors: Liu Ting 
Published: December 2021

Abstract
With the development of water conservancy informatization, the research on water information system integration is born, which is the need of water conservancy informatization construction at present and also an urgent problem to be solved. Based on the machine learning algorithm, combined with the actual needs of water conservancy business field, the overall framework of computer system integration for water conservancy engineering design is put forward. The overall framework includes: resource layer, comprehensive integration layer and user layer, which exchange data with configuration monitoring software by means of communication. The analytic hierarchy process in machine learning algorithm is used to construct the risk prediction index system, and the risk prediction index and initial prediction results are taken as the input and output of extreme learning machine algorithm in machine learning algorithm. The simulation results show that the prediction accuracy of this method is 94.88%, which can accurately predict the risks existing in hydraulic engineering design computer system and improve the system security.
Research on Electronic Image Stabilization Technology of Vehicle-Mounted Remote-Controlled Weapon Station
Authors: Qin Shumin , Zhao Lizhen , Tian Xingke , Li Lidan , Liu Shuyun 
Published: December 2021

Abstract
The image information of the vehicle-mounted remote-controlled weapon station is jittered and blurred when the stance changes or vibrates, which increases the aiming difficulty and observation fatigue of the shooter, in order to realize the stable marching fire of the vehicle-mounted remote-controlled weapon station, the two-stage stable scheme with the shared gyro sensor is adopted in the system design, namely, the aiming device is rigidly fixed on the initially stable weapon platform, and then the electronic image stabilization is carried out. This paper proposes an approach combining two image stabilization schemes: gyro sensor data and image projection registration, optimizes the selection of image compensation data by registering and comparing the results of the two stable data, and uses the special features of the two schemes to improve the robust stability of electronic image stabilization, which ensure the observation effect of video image stabilization of the vehicle-mounted remote-controlled weapon station.
Design of classification model on high-dimensional imbalance data of motor bearing fault
Authors: Zhu Xiaocui , Hui Li , Sai Qian 
Published: December 2021

Abstract
According to the characteristics of high-dimensional imbalance distribution of motor bearing fault data, a design scheme of classification model is proposed for the high-dimensional data reduction problem in the classification algorithm. For details: Combining standard particle swarm optimization algorithm and random forest algorithm, a new high-dimensional data reduction algorithm is proposed. Aiming at the imbalance problem of data categories in the classification algorithm, we proposes to use machine learning under the sum of squares of dynamic deviations criterion to divide the minority sample data set into mixed regions, high-purity minority sample regions and outlier regions, and then use smote algorithm to complete the data equalization processing, so as to make the sample data equalization processing more reasonable, Focusing on the task of motor bearing fault classification, a design scheme of using standard particle swarm optimization algorithm to improve the least squares support vector machine model is proposed.
Access Data Analysis Technology and Implementation of Electric Power Big Data Achievement Sharing Platform through Artificial Intelligence
Authors: Qian Wang , Na Mi , Zenan Yi , Yue Sun Ming , Qing Liu 
Published: December 2021

Abstract
With the rapid development of the information age, the data generated by all walks of life is showing an increasing trend of “blowout”. According to statistics, the total amount of data generated by mankind in the past 40,000 years is less than the total amount of data generated from 2010 to 2013 alone. The global big data reserves reached 8.61ZB in 2015 alone, and the growth of data in the future will reach an unpredictable value, entering the data age in an all-round way. Traditional power data computing technology and intelligent analysis technology are undergoing profound changes, and emerging big data intelligent analysis platforms are gradually emerging. With the in-depth development of power informatization and the concept of smart grid, the power industry data has grown exponentially, and the business demand for intelligent analysis of large amounts of power data is increasing day by day. Therefore, the access data analysis technology and realization of the power big data achievement sharing platform based on AI is of great significance. The AI-based power big data achievement sharing platform constructed in this article is a research on previous data analysis, and it aims to use the current cutting-edge artificial intelligence technology to build a scalable and highly available power big data analysis and processing platform to provide fast and reliable smart data services for the power industry, smart grid and other grid businesses. Research has shown that the overall availability of the ultrasonic partial discharge recognition system of the artificial intelligence-based electric power big data achievement sharing platform is 99.9967%, which meets the high availability index requirements, and verified that the artificial intelligence-based power big data achievement sharing platform provides highly available computing, storage and other services for its applications.
SAR Images Change Detection based on Sparse Coding and NMF
Authors: Wang Shaona , Liu Yang , Wang Yanan , Li Linlin 
Published: December 2021

Abstract
There are many applications for SAR image change detection, from military and agriculture to detection and management. But in fact, there is the speckle noise in SAR images inevitably. Therefore, the difficulty to detect change is increased. For purpose of reducing the interference of noise, we propose an unsupervised feature learning method using the non-negative matrix factorization algorithm and an improved sparse coding algorithm. First, non-negative matrix factorization method is used to obtain a dictionary which contains spatial structure information. Then, in order to increase the discriminate ability, we extract features for each pixel and apply sparse coding. Finally, the result of SAR image change detection is generated by applying simple k-means clustering method to divide the learned features into two different clusters. The superior performance of the proposed method is verified on several real SAR image datasets through comparisons with several existing change detection techniques.
Capacity optimization of renewable energy microgrid considering hydropower cogeneration
Authors: Fan Lijun , Cui Jiedong 
Published: December 2021

Abstract
This paper proposes a renewable energy system based on photovoltaic power generation, wind power generation and solar thermal power generation, combining thermal power plants with low-temperature multi-effect distillation. Through the electric heater and the thermal storage system photovoltaic and wind power will spare capacity in the form of heat energy, at the same time by thermal power generation system to maintain the stability of the power supply, run under constant output scheduling policy, to the levelling of the smallest energy cost and the design of power rate of maximum satisfaction as the goal, using multi-objective particle swarm optimization (PSO) algorithm to find the best combination of capacity, this system is established. At the same time, combined with low-temperature multi-effect distillation, compared with reverse osmosis seawater desalination cost is lower, reduce energy consumption, has a good application prospect.
Research on Logistics Carbon Emission Mathematical Estimation and Compensation by Computer Statistics and Data Analysis
Authors: Chen Hao , Wang Haiming , Li Ping 
Published: December 2021

Abstract
Global warming is one of the most serious environmental problems facing human society. Greenhouse gases represented by CO2 are considered to be an important cause of climate change. The development of human society is the main reason for the generation of CO2. Economic development and population growth make the use area of fossil fuels continue to expand, which is an important factor leading to the increase of CO2 emissions. The logistics industry is developing rapidly. Its development not only brings value-added economic benefits, but also increases CO2 emissions, and the carbon emission of the logistics industry has gradually become one of the hotspots of attention. Based on the previous theories on carbon emission, this paper determines the research on carbon emission estimation and carbon compensation in the operation of logistics industry, and estimates the carbon emission of logistics industry around the official statistical yearbook data and survey data. Finally, this paper further improves the carbon compensation mechanism of logistics industry from the perspective of compensation subject, compensation standard, compensation mode, process management and carbon price formulation, and puts forward the corresponding measures of carbon compensation mechanism from the perspectives of planning, management, technology, market and publicity.
Numerical simulation study of mining process of upper and lower walls of normal and reverse faults
Authors: Zhuang Bian 
Published: December 2021

Abstract
Mining coal seams near faults are prone to various mine disasters, and different mining sequences have different effects on coal seam disasters. Under this background, the numerical models of normal fault hanging wall, normal faultfoot wall, reverse fault hanging wall and reverse fault footwall under the same geological conditions are established. It is found that the stress concentration of coal pillar is the largest in the mining process of hanging wall of normal fault and footwall of reverse fault, and the possibility of inducing coal pillar rockburst is the largest. Affected by the fault, the coal pillar abutment stress between the working face and the fault shows an upward trend. When mining the coal seam near the fault, various methods such as hydraulic fracturing should be adopted to reduce the coal pillar abutment stress and reduce the risk of mine disasters.
Effect of Reaction Temperature on Adsorption Efficiency using Computer Mathematical Statistics Visible Spectorphotometer
Authors: Zhang Yongli , Li Ruiting 
Published: December 2021

Abstract
In this paper, waste shrimp shells extracted from the head of the chitosan material; static adsorption experiments manner by wastewater containing Fe(III) added chitosan, vis spectrophotometer absorbance before and after the measurement experiment was obtained by reacting the size of the metal ion concentration, adsorption conditions whereby chitosan Fe(III) and the ability to explore. Experiments show that. In the case where the reaction temperature is less than 55°C, chitosan has adsorption rate Fe(III) smaller rise, the optimum temperature was 55°C, but the effects on the reaction temperature adsorption rate is not large; Adsorption when control time 30 min to 50 min, the absorption effect is increased with increase in the time, to reach the optimal reaction time 50 min.
Research on the Adsorption Effects of Biomass by Microstructural Characterization and Intelligent Numerical Computation Method
Authors: Zhang Yongli , Li Ruiting 
Published: December 2021

Abstract
In this paper, sodium sulfide solution as a simulation of sulfur-containing wastewater, using orange peel as adsorbent, through the change of the absorbance of simulated wastewater to analyze the orange peel adsorbent on the treatment effect of simulated wastewater, to explore its optimal experimental conditions. The experimental results show that the adsorbent has a certain adsorption effect on the sulfur compounds in the sulfur-containing wastewater. With the change of the pH value of the adsorption environment, the adsorption rate has changed. The addition of different chemical modifiers in the water will affect the adsorption and effect of orange peel.
The Application of Industrial CT Detection Technology in Defects inspection of lithium Ion Battery
Authors: Hu Shuai , Xu Jiankang , Lv Mengchuan , Zhu Zhengbing , Jia Jusheng , Li Weiquan , Weng Wenxiang 
Published: December 2021

Abstract
Industrial CT can intuitively display the internal structure, material composition and defect status of the tested object in the form of two-dimensional sectional image or three-dimensional image without damaging the structure of the tested object. It is widely used in the location, size, density change and distribution of internal defects of composite materials. It is the best nondestructive testing technology for internal micro size structure. Compared with the traditional detection technology, the defect detection of lithium-ion battery using industrial CT detection technology has many advantages, including component measurement of complex battery internal structure through high-density information in a non-contact and non-destructive manner. This paper introduces a series of defects of lithium ion battery scanned by industrial CT, analyzes the causes and how to improve the process.
Study on afterbody-effects of multi-stage separation at high-speed
Authors: Zheng Yongqian , Jia Hongyin , Cui Pengcheng , Li Huan , Wu Xiaojun 
Published: December 2021

Abstract
The stage separation of high-speed vehicle is complicated at high dynamic pressure, usually accompanied by strong shock and vortex interaction. There exists a strong interaction between first stage and second stage, which called “afterbody-effects”. The aerodynamic mechanism of “afterbody-effects” is studied in this paper based on numerical simulation. The aerodynamic characteristics of a simplified three-dimensional projectile model at different distances between stages at 0° angle of attack is researched with structural mesh. The results show that the vortexes of stages have a significant impact on the aerodynamic characteristics of different stages, As the distance between stages increases, the drag coefficient of the first stage increases, and the drag coefficient of the second stage increases first and then decreases.
Computer Intelligent Numerical Simulation of TIG Welding Using Platy Tungsten Electrode
Authors: Zhang Jianhua , Huang Zicheng , Xie Yulun , Zhao Qiming , Wang Ketao 
Published: December 2021

Abstract
In order to reveal the law of arc plasma flow and heat transfer in the process of flat tungsten electrode TIG welding as auxiliary heat source for hardfacing of cast iron surface. According to the free burning TIG arc using platy tungsten electrode, A three dimensional (3D) model for tungsten inert gas welding using platy tungsten electrode has been developed. The whole region of platy tungsten TIG arc, namely, platy tungsten cathode, arc plasma and anode surface is treated in a unified numerical model. By using fluent software to do the second development of equations source and solve these equations, the distribution of temperature, velocity and current density are obtained. The simulation results show that the current of flat tungsten electrode is more dispersed, and the heat generation of arc is more dispersed, which leads to the decrease of arc temperature; The current density on the cathode is much higher than that on the anode.
Comparison and adaptability evaluation of formation pressure calculation methods and computer simulation in Jingbian gas field
Authors: Liu Haifeng , Wang Hua , He Lei , Zhang Fang , Fu Yu , Zhang Yuanjie 
Published: December 2021

Abstract
In the process of oilfield development, formation pressure is an essential parameter for evaluating oilfield development effect, calculating dynamic geological reserves, conducting daily dynamic analysis of oil and water Wells and predicting oilfield performance. The pressure recovery time of conventional gas well after shut-in is very long, and it is difficult to effectively carry out targeted implementation due to the influence of gas field external supply task. In this paper, based on the actual data of Jingbian gas field, through the comparison of several calculation methods of formation pressure, the best method to calculate formation pressure is comprehensively screened out. The results show that: ①For a single method, the accuracy of the method from high to low is the well head casing pressure conversion method, the pressure drop curve method, the binomial productivity equation method, and the quasi-steady state mathematical model method.②The absolute error of multi-method comprehensive calculation method is 0.9MPa, which is far less than the average absolute error directly calculated by one method. The multi-method comprehensive calculation method is reliable when applied to the formation pressure evaluation of typical gas Wells in Jingbian gas field, which lacks data.
Study on Smart Numerical Simulation Mechanism in Complex Reservoir Using Embedded Discrete Fracture Model
Authors: Wang Yong , Jiang Hanqiao , Li Junjian , Lv Chunhua , Liu Jianbo , Ma Xiaobin 
Published: December 2021

Abstract
The embedded discrete fracture model (EDFM) method is used to study the mechanism model of the reservoir with a complex fracture system, and the sensitivity analysis of the development effect is carried out. The results show that: 1) the EDFM method can directly characterize the fracture morphology and fracture attributes in the reservoir; 2) Through comparative analysis of reservoir type, capillary force, and fracture development degree, it is found that different reservoir types have great differences in development effect, fracture opening has little influence on the reservoir, capillary force and fracture density have a great influence on the reservoir development effect, and with the increase of fracture density, the reservoir development effect increases significantly.
Numerical simulation on the leakage and diffusion of the natural gas of the underground pipeline in the soil
Authors: Hu Meijuan , Li He , Chen Li , Xie Ping , Zhang Zheju , Yang Ming , Wu Mingze , Zhang Qingming 
Published: December 2021

Abstract
For the transportation pipeline with the diameter 1.219 m and the internal pressure 3-12 MPa, the leakage and diffusion of the natural gas of the pipeline in the soil was studied by numerical simulation. First, the finite model containing both pipeline and soil was established, and the porous media was used to simulate the real soil environment. And, the leakage amount of the natural gas was calculated at the cases with different porosities, the pressures inside the pipeline and the diameters of leakage port. Based on the classical theoretical leakage model of small hole in the air and simulation results analysis, the formula of the leakage amount was modified by the soil coefficient α to be suitable for soil environment. Then, the variation trends of the diffusion concentration of methane along different directions in the soil were analyzed by simulation, the influences of internal pressure of pipeline, the diameter of leakage and the porosity of soil were also discussed. Besides, the relationship of the safety distance with time was obtained.
Pedestrian Re-identity Based on ResNet Lightweight Network
Authors: Li Xingxing , Duan Chao , Yin Panpan , Wang Ningxing 
Published: December 2021

Abstract
With the development of deep learning technology, pedestrian re-identity technology has been widely used in multi-target tracking and cross mirror tracking tasks. In this paper, the classical deep learning ResNet18 network is used for pedestrian re-identity tasks. The advantage of the network is that it can easily realize lightweight deployment. In addition, the labeled smooth cross entropy loss function and migration learning technology are used in the process of training the network, which can realize the accuracy of map 67.8 on the Market1501 data set while lightening the network, and promote the engineering landing of pedestrian re-identity network.