bluuebunny/crossref_metadata_2025 huggingface dataset:
A Printed Dipole Antenna for 5G Millimeter Wave Application
Authors: He Xingyi
Published: March 2021

An essential point of the technology in the 5th generation (5G) communications is to utilize the available spectrum in high frequencies beyond 20GHz, whose corresponding wavelengths reach a relatively small millimeter magnitude. To cope with the challenge of such short wavelengths, this paper has proposed a printed dipole antenna with a geometric structure that two dipole arms are patched on opposite sides of a FR4 substrate fed by a microstrip line and triangular balun. Simulations have shown that the proposed antenna possesses a relatively effective performance operated at 21.6 ∼ 25.4GHz with a maximum gain of 1.62dB. Additionally, the impact of some geometric parameters, such as the sizes of dipole arms and triangle baluns, are also discussed in this paper.
Research on component preparation technology based on laser scanning modelling and additive manufacturing
Authors: Cui Kaibo , You Xuemin , Huang Xinxin , Jia Bo , Li Haiguang , Liao Chaozhi
Published: March 2021

When the artillery is damaged in the battlefield, the replacement of spare parts can quickly restore the combat capability. However, when the supply of artillery spare parts is insufficient, the technical performance and combat effectiveness of artillery will be seriously reduced. Based on the above considerations, the reverse design and selective laser melting technology are used to study the emergency manufacturing technology of artillery spare parts, to solve the problem of artillery spare parts supply and guarantee, and improve the quality and efficiency of artillery maintenance and guarantee.
The Point Interpolation Method Using Quadratically Consistent Three-Point Integration Scheme for Free Vibration Analysis
Authors: Jia Cheng , Chen Huihui , Wei Yuchen , Shen Yukai , Wu Yue
Published: March 2021

The formulation of quadratically consistent three-point integration scheme based on point interpolant method (PIM-QC3) is proposed for free vibration analysis of two-dimensional solids. Based on the condition with regard to nodal shape function and its derivatives for arbitrary-order approximations, PIM-QC3 is developed using point interpolant method and T6-Scheme for node selection. Thus, complex calculation of inverse matrix at every quadrature points is avoided. And the shape functions including corrected derivatives of nodal shape functions at quadrature points, adopt quadratic basis, meet the so-called differentiation of the approximation consistency as well as the discrete divergence consistency. In addition, the Kronecker delta property is possessed. Some problems for the free vibration of two-dimensional solids are employed to examine the accuracy and efficiency of the PIM-QC3. The numerical results indicate that PIM-QC3 is a very accurate, stable and highly efficient method for the structural analysis of free vibration.
Measured Stiffness Performance Evaluation Index of Industrial Robot in Side Milling
Authors: Sun Jiabin , Zhang Weimin
Published: March 2021

Industrial robot is a potential alternative of machining tool in some certain process due to its flexibility and large workspace. The traditional stiffness model of robot cannot explain the situation that stiffness exits difference in opposite directions. Aiming at optimizing the robot side milling process, a measured stiffness performance evaluation index is proposed in this paper. It is deduced and calculated through actual measured data, which overcomes the shortcoming of other indexes deduced from traditional stiffness model. Experimental case indicates that the new index proposed in useful in feed direction and tool-workpiece relative position optimization.
Static finite element analysis of three-closed box thin-wall beam based on Pseudo-elastic SMA hybrid composite material ANSYS
Authors: Zeng Lingqi
Published: March 2021

The Auricchio model based on shape memory alloy and the finite element analysis software ANSYS Workbench firstly simulated the pseudo-elastic characteristics of SMA bar during the stretching cycle loading and unloading. Secondly, based on ANSYS Material Designer module, a SMA/glass/epoxy resin composite Material model was established and its Material parameters were obtained. ANSYS ACP module was used to establish the finite element model of pseudo-elastic SMA hybrid composite box thin-walled beam. Finally, the static response of SMA composite box thin-walled beam under transverse load is studied, and the influences of SMA, layout Angle, width to height ratio and volume content of SMA layer on the static response of box girder are discussed. The results show that the transverse displacement of the free end of the thin-walled beam increases with the increase of the laying Angle whether there is SMA fiber or not. After embedding SMA, the transverse displacement of the free end of the box thin-wall beam of hybrid composite was smaller. The transverse displacement of the free end of the thin-walled beam with the change curve of the lay-up Angle under the two con Figurations is consistent and basically consistent. At the same laying Angle, the transverse displacement of the free end of SMA hybrid box thin-walled beam decreases with the increase of the width to height ratio and the volume content of SMA monolayer.
Optimization of Casting Process of Headstock Based on Numerical Simulation
Authors: Wang Yifei , Shan Zhongde , Yang Haoqin , Zhang Xueliang , Zhao Mengmeng
Published: March 2021

In this paper, the casting process optimization design of a certain type of headstock is carried out by numerical simulation technology of casting process. Designed the pouring plan based on theoretical calculation; based on the numerical simulation results, quantitatively designed the riser size, and rationally arranged the pouring riser system based on the equilibrium solidification theory, which can reduce the shrinkage porosity and shrinkage defects in the casting process and increase the process yield; Finally, a sand core production plan is provided based on the precision machining technology of the moldless casting mold, which provides a new idea for the process plan design of complex spindle box castings.
Finite element analysis of stress and distortion for welding reinforced structure of angular steel used for power tower under load
Authors: Deng Hualing , Zhang Zhongwen , Yang Bo , Du Baoshuai , Suo Shuai , Li Xinmei , Xu Guoxiang
Published: March 2021

Based on thermal-elastic-plastic theory, a three-dimensional numerical model of residual stress and distortion in L-shaped welding reinforced structure of angle steel used for power transmission tower is developed. The characteristics of residual stress distribution and deformation are numerically investigated, which are compared with the stress and deformation under the action of lateral compressive load. The research results show that, a large stress is generated in and near the weld zone. With enhancing the weld bead length, both equivalent stress and residual distortion have a growth, and the equivalent stress peak reaches 329Mpa, slightly lower than the yield stress of base metal, meanwhile the longitudinal residual stress peak is 399Mpa, higher than the yield stress of base metal. Under the action of 15000Pa lateral compressive load, the stress has no obvious change in the near weld zone of reinforce structure compared with that without load, and the distortion peak reaches 11mm.
Shear Vibration Equivalent Method for Determining Vibration Frequency of Concrete Prefabrication Production
Authors: Li Xiaotian , Fang Junpeng , Zhang Shengjun
Published: March 2021

In order to solve the problem of determining the process parameters caused by the rheological property of concrete in the industrialized vibration compaction production, the shear vibration equivalent method for determining the vibration frequency of concrete prefabrication production is proposed. According to the equivalent effect of shear and vibration, the particle flow interaction theory is used to calculate the rheological parameters of cement paste in the flow field of rotary viscometer under vibration. The mapping relationship between vibration frequency and shear rate can be established when the amplitude is fixed. The apparent viscosity can be used as the evaluation index of the fluidity of concrete mixture in rheology. By studying the critical point of the influence of shear rate on the decrease of apparent viscosity of concrete mixture, the optimal shear rate which can make the apparent viscosity decrease to the limit value is obtained. Combining with the optimal shear rate and the mapping relationship between vibration frequency and shear rate, the optimal vibration frequency of concrete precast production can be determined. This method can be applied to the quantitative determination of vibration frequency in the vibration compaction production of precast concrete components, which is conducive to the improvement of product performance and control of energy consumption cost.
Wafer Crack Detection Based on Yolov4 Target Detection Method
Authors: Li Xingxing , Duan Chao , Zhi Yan , Yin Panpan
Published: March 2021

In recent years, the breakthrough of deep learning technology has brought a qualitative leap in the field of industrial detection. In the past, defects that are difficult to detect by traditional image methods can be detected by deep learning automatic feature extraction to find the expression of difficult samples. In the field of industrial silicon wafer defect detection, with the help of deep learning target detection algorithm, it can effectively adapt to different size, illumination, depth, length of defects. In this paper, yolov4 target detection algorithm is applied to silicon wafer crack problem. Yolov4 target detection algorithm uses many training skills, such as weighted residual connection (WRC), cross stage partial connections (SCP), cross Mini batch Normalization (CmBN), self-adaptive training (SAT) and mish activation make yolov4 better trained on a GPU, and can achieve 98.23% detection accuracy on the wafer crack detection data set.
10 kW Optimization of grid-connected wind power system and its application in Xiamen
Authors: Zhu Guangze , li Jiacheng , He Zihao , Chen Chengxiang , Zhu Qiangqiang
Published: March 2021

Coastal areas not only have large annual average wind speed, but also have more days of strong winds in a year. Xiamen >8 gale days, 22.4 days a year, so it is very suitable for wind power generation. This design is 10 kW wind grid-connected power generation system, each branch is composed of permanent magnet synchronous motor, rectifier, boost module, inverter and filter, 20 groups are used in parallel to form 10 kW system. Choose a single permanent magnet synchronous wind turbine power of 500 W, need 20. System DC voltage :12 V, when the power is fixed, the proper lifting of DC voltage is helpful to reduce the current, thus preventing the IGBT from causing device damage due to overcurrent. A two-dimensional fuzzy controller is used to select the outer loop error and error differential signal as input variables. In order to verify the correctness of fuzzy adaptive PI control strategy, a system simulation model is built.
Research on Optimizing Material Structure Based on Optoelectronic Physical Performance System
Authors: Ma Dinghan
Published: March 2021

High-voltage technology can effectively adjust the crystal lattice and electronic state of optoelectronic materials. It is a feasible means to adjust the physical properties of optoelectronic materials and an important method for synthesizing new optoelectronic materials. This article summarizes the current status of high-voltage research on optoelectronic materials at home and abroad, and introduces the effect of high-voltage on the crystal structure, electronic configuration and physical properties of optoelectronic materials. At the same time, the thesis looks forward to the development of high-voltage research on photovoltaic materials based on the properties of PbS gel mass dot solar cell photovoltaic materials.
Research on Key Construction Technology of Building Engineering Under the Background of Big Data
Authors: Qian Zhixin , Yang Xinyi , Xu Zian , Cai Weilang
Published: March 2021

In the era of the construction engineering industry informatization, the collection, storage, and reuse of big construction data is the only way to apply and inform big data in the construction industry. Relying on the reverse logistics management system, modern construction technology can simulate the timeliness of materials, funds, and time limits of the actual construction site according to the logistics reverse engineering principle. Then, reverse the active management status of the internal logistics model of the actual project. It is one of the critical problems for construction engineering informatization to study applying big data and cloud computing technology to solve problems from massive and complicated data or mass data. Since the research on big data and cloud computing technology started late in construction engineering, it is worth studying which aspects of these technologies can be used in the whole life cycle of this field. This paper proposes a structural construction optimization identification method based on IPEM rapid reanalysis. USES the co-solubility of reverse logistics structure construction technology and applied the data mining method to solve many problems such as refined construction management leftover material surplus in the later construction stage. Finally, a construction optimization model of reverse logistics building system based on improved data mining is proposed according to the actual engineering requirements.
Optimization of Bridge Crane Control System Using Fuzzy PID Control and Speed Control of Frequency Converter
Authors: Zhou Qicai , Wang Kai , Xiong Xiaolei , Zhao Jiong
Published: March 2021

Objective: As a carrier, bridge cranes are widely used in port cargo handling. Due to the structure of the crane itself, the load inevitably produces displacement deviation and lifting weight swing. Therefore, the optimization investigation of the bridge crane control system is carried out to guarantee the fast and secure operation of the crane. Method: According to the characteristics of bridge cranes, combined with the experience of on-site operating staff, the fuzzy rules that meet the working conditions of the site are designed by using the advantages of fuzzy PID (Proportion-Integration-Differentiation) control algorithm without relying on an accurate mathematical model, to set the parameters of the fuzzy PID controller. The speed control technique of frequency converter is adopted to design the system to improve the safety of the overall system. Results: The results show that the adjustment time of the swing angle of crane weight of the traditional PID control requires 6.79s, and the maximum swing angle of crane weight is 0.039rad, and the adjustment time under the fuzzy control is 4.89s, and the swing angle of crane weight is 0.013rad. The fuzzy PID controller surpasses the traditional PID controller in the positioning accuracy. It is not sensitive to changes in the internal parameters of the system. Also, it has strong adaptability to changes in operating conditions. The swing angle of crane weight is smaller, which further improves the robustness. The vector frequency conversion speed control has a more precise control effect on the speed and running track of the operating mechanism of the bridge crane. This method can be applied to the automatic operation mechanism of bridge cranes and achieve good control performance. Conclusion: The conducted optimization investigation of the bridge crane control system makes the control system flexible, simple and robust, providing important theoretical support for related explorations.
The Design of Detector to Illegal Ingredients of Kitchen Waste Based on Embedded Device
Authors: Chen Xing , Sheng Jinliang
Published: March 2021

In this paper, a kitchen waste illegal component recognizer based on embedded device is proposed, which can intelligently identify and record illegal components in kitchen waste. The recognizer is based on SSD-MibileNetV2 algorithm. The Quantization-aware training model is established in TensorFlow framework. The whole model is quantized by uint8 and transformed into TensorFlow Lite structure, and then deployed to the embedded device based on raspberry Pi 4b, which can finally achieve 4.5FPS and 76.35mAP. The recognizer can meet the requirements of real-time and accuracy in detecting illegal components of kitchen waste, and can effectively reduce labor costs and meet the requirements of intelligence.
Multi-Source Image Registration Based on Slic Superpixel Segmentation and Autoencoder
Authors: Zhao Xie , Yong Tianda
Published: March 2021

A new Harris-AE feature matching algorithm based on image edge information combined with SLIC superpixel segmentation method is proposed to achieve high-precision registration of visible and infrared images. First, perform edge enhancement and histogram equalization processing on visible light and infrared images, superpixel segmentation technology is used to eliminate sub-images with low information entropy, and then by constructing a multi-scale Gaussian pyramid to detect the Harris corners of the image edge information, using autoencoder neural network to generate feature descriptors corresponding to feature points, and match the feature points of two images through the fast nearest-neighbor algorithm with bidirectional matching strategy. Finally, the RANSAC algorithm is used to purify the matching points, and the spatial geometric change parameters between the two images are estimated by the least-squares solution to complete the registration of visible light and infrared images. Experiments have proved that this algorithm improves the accuracy of matching while shortening the registration time.
Research on Computer Multimedia Software Graphics and Image Processing and Analysis System in Colleges
Authors: Na Bao
Published: March 2021

With the development of computer software and hardware technology in colleges and universities, the application of multimedia computers has become increasingly widespread. Graphics and image processing occupy a major position in the application of multimedia computers in colleges and universities. Image display is the basis of image processing. The key of special effect display is to divide the image into different image area blocks. The usual image special effect display method is to divide the image into different image blocks according to certain rules. Based on the analysis of the principle of image special effects display, this paper proposes a template-based image special effects display method. Experimental results show that compared with traditional interpolation algorithms, such as bilinear interpolation and bicubic polynomial interpolation, this algorithm has better interpolation effects and overcomes the speckle interference in single wavelet interpolation.
Design and Application of Automatic Meter Reading System For Anti Stealing Electricity
Authors: Fan Hongshen
Published: March 2021

Based on the high-speed development of computer technology, VLSI and communication technology, this paper studies an anti stealing wireless meter reading system which can improve the power supply enterprise’s anti stealing ability and collect, count and analyze the power consumption of large users timely, effectively and accurately, and analyze the characteristics and components of the system design to meet the market demand. The system studied in this paper is mainly used for power supply enterprises to control power stealing for large users.
Research on Practical Byzantine Fault Tolerant Consensus Algorithm Based on Blockchain
Authors: Zheng Xiandong , Feng Wenlong
Published: March 2021

Practical Byzantine Fault-tolerant Algorithm (PBFT) is the most widely used consensus algorithm in alliance chain, which has the advantages of fault tolerance and large throughput. However, PBFT also has some problems that can’t be ignored in specific blockchain applications, such as bad behavior of master node, high network communication overhead and low system flexibility. In this paper, the improvement measures of PBFT consensus algorithm are summarized from many aspects, and then compared with traditional PBFT algorithm. Finally, the development direction and trend of PBFT algorithm are prospected, hoping to provide reference for the research and innovation of PBFT consensus algorithm in the future.
Research on Transmission Resource Allocation in Communication Management System
Authors: Wang Huiqing , Chen Junwei , Zhang Feng
Published: March 2021

This paper studies the completion of power communication technology and transmission network planning. It summarizes the basic research and current situation analysis of transmission technology and business network planning. First, it focuses on the functions of power communication business, information flow, transmission channels and bearing requirements. The characteristics of various power grid technologies and grid communication business models in China are analyzed. Secondly, it carried out analysis and research on the basic design principles of power communication technology and transmission network business planning, evaluation of main indicators, and focused on elaborating the digital communication network management system of synchronous transmission of power communication, the characteristics of ason power communication technology, network protection and management and basic principles of power communication technology and transmission network such as restoration.
Research on holographic image and hierarchical classification evaluation of power suppliers based on Intelligent System
Authors: Zhang Xiaofeng , Wang Chao , Chen Xi , Wang Ying
Published: March 2021

Based on the current new situation, not only to more scientific assessment of the supplier’s equipment quality and technical level, but also on this basis to take into account the equipment in the supply chain life cycle of the production, procurement, operation and decommissioning of the cost, through the evaluation of equipment quality and cost, to achieve the asset-wide life cycle management of the supplier intelligent evaluation, the establishment of supplier intelligent evaluation management information system in order to achieve the establishment and perfection of supplier classification performance evaluation management system.
A survey report on demand characteristics of wisdom supply chain management talents facing Yangtze River Delta and surrounding areas
Authors: Huang Xiaodi , Chen Jianghua , Wang Erchun
Published: March 2021

Wisdom supply chain is a new supply chain model developed in the new generation of information technology revolution, which makes the organization and management mode of supply chain undergo an inevitable change. As an important intersection connect “One Belt and One Road” and the Yangtze river economic belt, integrating wisdom supply chain industry into the regional resource construction system and cultivating wisdom supply chain management talents are the urgent requirements for the Yangtze River Delta urban agglomeration to adapt to the adjustment and upgrading of industrial structure and pursue higher quality development. This survey analyzes the new characteristics of wisdom supply chain and the new demand for human resources by using the methods of literature analysis and enterprise research. Then, explores the demand characteristics of market-oriented wisdom supply chain management talents by mining the recruitment information of supply chain and logistics posts in the Yangtze River Delta and its surrounding areas based on clustering, statistics, text mining and other data analysis methods.
Design of electric power remote meter reading system
Authors: Zhang Ran , Sun XiaoLu , Chen Wei Min , Zhong Li
Published: March 2021

Recording the electricity consumption of users is a monthly routine of the electric power department, which often requires a lot of material and manpower. Therefore, using new technical methods, with the help of automatic remote and local meter reading technology, to achieve the purpose of automatic meter reading to monitor the electric energy meter, work efficiency is improved, and the real automatic power management is realized, and the remote electric meter reading system becomes Alternative meter reading problem solutions for grid companies. This system can meet the remote data recording, collection and real-time monitoring functions of the user’s electric energy meter in the remote power meter reading system within a certain range.
Study on a CNN-HMM Approach for Audio-Based Musical Chord Recognition
Authors: Li Taixiang
Published: March 2021

Convolutional Neural Network (CNN) has shown its strength in image processing task, and Hidden Markov model (HMM) is a powerful tool for modeling sequential data. This paper presents a new architecture for audio-based chord recognition using a CNN-HMM mixture model. This architecture replaces the Gaussian mixture model (GMM) and Deep Neural Network (DNN) layers of GMM-HMM and DNN-HMM models with CNN. The model performance is evaluated through a dataset using different combinations of chroma vectors (STFT, CQT, CENS) as features, based on that, a scale recognition sub-model is tested.
House price prediction using polynomial regression with Particle Swarm Optimization
Authors: Zhou Chenhao
Published: March 2021

This paper combines the characteristics of the real Washington DC house price estate market and the theoretical model of housing prices to conduct an empirical analysis and comparison of the current mainstream housing price index prediction models. It is found that the current mainstream model only studies the trend of the housing price index itself, and is not sensitive to the characteristics of the house itself. Therefore, this paper uses a multiple regression model to integrate the advantages of external factors and use the improved housing price composition establishing a multiple regression prediction model with the particle swarm optimization. It not only makes up for the disadvantages of poorly determined housing price regression indicators and lack of statistical data in multiple regression prediction, but also enables the model to reflect the inflection point of housing prices in advance. PSO is used for selection of affect variables and regression analysis is used to determine the optimal coefficient in prediction.
User Behavior Set: Medley of User Behaviors to Eliminate Data Spatio-Temporal Sparsity
Authors: Huang Yangjun , Hu Xuanrui , Lian Jieyu , Jiang Xingpeng
Published: March 2021

A sequential recommendation system is war-ranted, and several models have been created to meet this need. However, sparsity is a major problem in this field. In order to deal with the space-time sparsity problem in a sequential recommend-dation system and avoid the unreliability caused by manually generated data, we have established the UBS structure. We treat user behavior sequences in batches. Each batch gets the inte-grated data set UBS after K iterations through a two-step cycle of clustering and merging. The results are connected as inputs of a sequential neural model. We use three baseline deep learning algorithms –Caser/SASRec/HGN to evaluate the model. We compared the UBS model with the original model in terms of normalized discounted cumulative gain ms(NDCG) and Recall. It is found that when the UBS model is applied to a short sequence of user behaviors and the iteration number K=2, it can improve the recommendation efficiency compared with the original algorithm (represented by K=0).
Research on Modern Construction Cost Economic Management Based on the Whole Process of Genetic Algorithm
Authors: Chen Guo
Published: March 2021

Genetic algorithm and neural network are both ideas and algorithm skills. The flexibility of this method provides a stage for many researchers and applications. In view of the complexity of general construction engineering valuation problems and the advantages of genetic algorithm and neural network algorithm, this article proposes a new construction engineering valuation model. Taking the actual residential project as an example, the feasibility and reliability of the genetic algorithm to optimize the neural network model are verified, and it is better than the simple neural network model, which provides an effective method for actual project investment estimation.
Research on Data Secure Transmission and Processing Method of a LoRa IoT System
Authors: Gu Jiting , Li Zhiqiang
Published: March 2021

The smart grid covers the traditional power grid and the Internet of Things network, including smart meters, which helps manage and monitor various customer consumption patterns in near real-time. To achieve data reading and effective management of terminal, smart meters connected to the power metering system, the article proposes using low-power wireless network (LPWAN) technology to connect terminal, smart meters to data gateways and private power clouds to achieve smart power metering Technical solutions. The solution uses the LoRa wireless module to realize the two-way interaction of power metering data and has the advantages of reliable operation, low cost, low power consumption, and remote access. This article also focuses on using emerging LPWAN technology to help build smart meter wireless access solutions and demonstrates the system implementation for smart meter end-to-end LoRa connection.
VSSHA: A Vehicle Scheduling Scheme for Tourist Attractions Based on Intelligent Heuristic Algorithm
Authors: Lin Yuan
Published: March 2021

With the development of tourism, vehicle traffic scheduling in scenic spots has gradually become a research hotspot. Aiming at the problem of vehicle scheduling and route planning at multiple service points in the scenic spot, we propose a method to minimize the total cost of vehicle scheduling and route planning tasks at the service point under the constraints of the weight of the required goods and the vehicle volume. First, we classify the demand points and assign the corresponding service points; then we aim to minimize the cost of vehicle scheduling and establish a nonlinear programming model under the constraints of the weight of the demand product and the volume of the vehicle; then, we will The model is reduced to a single service point TSP problem, and based on the improved ant colony algorithm, a solution model based on TSP is designed. The experimental results show that our model and algorithm can make the distribution cost of multiple service points the lowest and the iteration speed is faster.
A Novel Computer-Aided Cloud Type Classification Method Based on Convolutional Neural Network with Squeeze-And- Excitation
Authors: Li Guanshen
Published: March 2021

Clouds have a huge impact on the energy balance, climate and weather of the earth. Cloud types have different cloud radiation effects, which is an important indicator of cloud radiation effects. Therefore, determining the type of cloud is of great significance in meteorology. In this paper, the Convolutional neural network with Squeeze & Excitation Networks (SENet) are mainly used to solve this probelm. CNN can automatically learn the filters that need to be manually set before, and can learn complex edge, spatial and texture information in the image which are difficult for traditional methods to learn and extract. Moerover, a website and a deep learning framework are established to showcase the results of this article and to further develop our models and methods through open source methods.
Research on Computer Simulation Big Data Intelligent Collection and Analysis System
Authors: Liu Hongying
Published: March 2021

As a characteristic of big data, the individual data in it is no longer isolated, and the data and its underlying mechanisms have complex associations, which make all data into an indivisible whole. The dynamic generation and disappearance of data will change its original relationship and affect the overall characteristics of the data. This feature of big data makes the subject-oriented analysis methods such as data mining present limitations: the presupposition of the subject and the analysis by subject split the interaction relationship between the subjects, leading to the loss of the implicit mechanism in these relationships. Aiming at the problems of traditional network big data multi-resolution acquisition methods such as high acquisition cost, long completion time and low acquisition accuracy, a JA-va3D-based big data network multi-resolution acquisition method is proposed, and average interactive data is introduced. The extraction method estimates the power spectral density of the network data multi-resolution acquisition, and uses the ADASYN algorithm to remove the invalid multi-resolution data, and realizes the large data multi-resolution accurate acquisition. Experimental results show that the proposed method has lower acquisition cost, shorter completion time, and higher acquisition accuracy; it has certain practical value and can be widely used in various fields.
Neural Network Training in Distribution Computing Method
Authors: Zhao Zhongyu
Published: March 2021

This paper raises some method to make neural network training can work on distributed computing clusters well.
Application of Artificial Intelligence in Rehabilitation Assessment
Authors: Mu Pengyu , Dai Mingyu , Ma Xuenan
Published: March 2021

Assessment is the core and fundament of rehabilitation, which can guide the whole treatment process. In the rehabilitation, doctors or therapists need to assess the function of patients in upper/lower-limb, based on subjective assessment and objective assessment. While it may cause large error and high cost by traditional ways. Therefore, artificial intelligence technology is applied to the field of medical rehabilitation. This review will summarize the application of objective assessment methods which are base on artificial intelligence including not limited, trajectory error feature, joint angels and joint angular velocity, sEMG signal feature. Finally, the review concludes that existing objective methods are generally affected by the scale of data and the number of feature. This review will give instruction for a lager application in rehabilitation field.
Template-Based Collaborative Design Task Management for Complex Products
Authors: Zhou Junhua , Xue Junjie , Shi Guoqiang
Published: March 2021

The task template system of this system combines the business requirements of the work and provides the classification management function of work packages and work package templates. At the same time, data integration with other systems such as the main data system and resource library is realized. Through this system, users can instantiate a single work package to form a single work item, and can also establish the front and back relationship of the work package through the work package template, thereby realizing the instantiation of the work package process.
Design of Intelligent Electronic Boundary Pile Based on IoT
Authors: Min Youjia , Pan Jicong , Xia Weiran , Jia Bowen
Published: March 2021

Boundary pillars are important symbols of the junction, and at present, the most common way of managing boundary pillars in China is to employ a full-time boundary pillar maintainer in order to maintain the pillars themselves better. Damage to or loss of reference materials such as the "borders" can cause considerable problems in resolving boundary disputes and controversies.

In recent years, the Geographical Information System (GIS) has been in a stage of rapid development, both theoretically and in terms of application. With the advancement of network information technology and the increasing maturity of GIS technology, WebGIS combining the two has gradually been widely used in various industries, while the Internet of Things (IoT) is also developing rapidly, on which a more complete set of intelligent electronic boundary pillars based on IoT technology has the theoretical basis to emerge.
An improved ant colony algorithm for TSP application
Authors: Jiao Deqiang , Liu Che , Li Zerui , Wang Dinghao
Published: March 2021

Aiming at the problems of slow convergence speed and easy to fall into the optimal solution of ant colony algorithm, genetic algorithm and nonlinear optimization are used to optimize ant colony algorithm. After the initial iteration of the ant colony, the solution formed by all paths is the initial population, and then the genetic algorithm is used for selection, crossover and mutation to improve the ability of global search. Finally, the nonlinear optimization algorithm is used to increase the ability of local search of the algorithm. Through this improvement, the convergence speed of the ant colony algorithm is improved and the problem of easy to fall into the optimal solution is solved, which is applied to the traveling salesman problem.
Research on Computer Assisted English Teaching in Foreign Language Teaching in Colleges
Authors: Zhu Weihua
Published: March 2021

The continuous development of network technology in the information age has provided hardware guarantees for networked teaching, and the deepening of computer-assisted teaching research has promoted the development of networked computer-assisted teaching. With the popularization and application of informatization in colleges and universities, the use of modern information technology to change the traditional teaching mode has become the focus of attention. The C++ network-assisted teaching system uses computers and networks as the main means to develop network-based teaching and learning auxiliary teaching methods. This system is a mixed mode of network teaching and traditional teaching, which can enhance the communication between teachers and students, and can also play the role of the student-based teaching mode in network teaching.
Reliability analysis of logic control system of automatic ground control neutral section passing
Authors: Song Yuwei , Xiao Baodi
Published: March 2021

Neutral section passing technology in railway power supply had always been a technical problem in current domestic traction power supply industry. In recent years, there are many technical schemes for passing neutral section. There are two main schemes of automatic neutral section passing at present: the vehicle control neutral section passing and automatic ground control neutral section passing, the automatic ground control neutral section passing is a relatively popular technical route in both schemes. Now incorporating fail-safe principle of signal specialty in automatic ground control neutral section passing and proposing the logic control system of automatic ground control neutral section passing based on the idea of "fail safe" in the interlocking system, and the risk identification and safety analysis are carried out based on the dynamic fault tree and HAZOP method. The fault tree is constructed based on the results of HAZOP analysis. Finally, the system reliability is quantitatively calculated through the fault tree.
Face Recognition Based on CD-RBM and BM-ILM
Authors: Qiao Weisong , Chen Binbin , Zhao Jiabao , Guo Shudong
Published: March 2021

In recent years, the application of neural networks in face recognition has improved its accuracy greatly. However, it still suffers from the disappearance of the network gradient and the training cost. In this paper, we propose a new hybrid method which combines the contrast divergence algorithm (CD) accelerated Restricted Boltzmann Machine (RBM) and the Integrated Learning Method (ILM) with the Boosting algorithm (BM). First, we use RBM to establish a minimum energy model of the sample distribution. Then we use CD to speed up the feature extraction of samples in RBM. And then we build a multi-classifier with heterogeneous samples for ILM by BM. Finally, we experience our proposed method on the ORL database and the AR database. The results show that, with a simpler neural network determined by CD-RBM and BM-ILM, the recognition accuracy is better than that without the proposed method.
Research on the Attribute Extraction Algorithm of People and Vehicles Based on Video Structure
Authors: Zhang Chaoying , Liang Baolin , Ma Sicong , Xiang Chao , Bai Zhen , Wang Jianxiu
Published: March 2021

With the development of sensor technology and computer vision, the speed of video generation is increasing exponentially. The workload of video browsing and the amount of stored data are increasing. In order to achieve fast browsing and efficient storage, video structure technology is increasingly important. This paper focuses on the video structure technology in the construction of smart cities, outlines the system process of video structure, and studies the extraction algorithm of human and vehicle target attributes based on deep learning. And combined with the actual video monitoring scene, the experiment is carried out. Compared with traditional image processing methods, the video structure target attribute extraction model based on deep learning has high detection accuracy and strong algorithm generalization ability. The intelligent analysis and processing of data by video structure technology is conducive to quickly increasing the speed of target search, reducing storage capacity, solving the problem of long-term storage, and realizing full automation of surveillance video.
Automatic Machine Learning Method for Hyper-parameter Search
Authors: Su Minglan , Liang Baolin , Ma Sicong , Xiang Chao , Zhang Chaoying , Wang Jianxiu
Published: March 2021

Automatic Machine Learning (AutoML) uses automated data-driven methods to realize the selection of hyper-parameters, neural network architectures, regularization methods, etc., making machine learning techniques easier to apply and reducing dependence on experienced human experts. And hyper-parameter search based on automatic machine learning is one of the current research hotspots in the industry and academia. We mainly introduce the hyper-parameter search framework based on automatic machine learning and the common hyper-parameter search strategies. Combined with specific data sets, the classification accuracy of the model under different hyper-parameter search strategies is compared to find the model parameter configuration that can maximize the classification accuracy. Compared with the experience-based parameter adjustment method, the hyper-parameter search based on automatic machine learning can reduce labor costs, improve training efficiency, and automatically construct a dedicated convolutional neural network to maximize the model effect.
A Convolutional Neural Network-based UHF Partial Discharge Atlas Classification System for GIS
Authors: Zhang Congcong , Wang Gang , Gao Dong , Yin Wei , Wang Kai , Lu Ming , Liu Yingnan
Published: March 2021

In order to solve the difficult problem of partial discharge pattern recognition caused by large amount of partial discharge detection data and complex multi-source, a partial discharge pattern recognition algorithm based on VGG-16 convolution neural network is proposed. The parameters of VGG-16 network model are optimized in convolution layer, pool layer and connection layer by means of migration learning. The VGG-16 model is superior to LeNet-5 model and has higher recognition accuracy.
RETRACTED: Research on the Development Quality of College Student Party Members Based on the Internet Environment
Authors: Pan Yihui , Pan Yajing , Tu Keqin
Published: March 2021

With the wide popularization of computer network at any time, students’ computer technology operation level has been greatly improved than before, and students have more channels to obtain information. In the Internet environment, the development of high-quality student party members is an extremely important work for the party’s construction, and has practical significance for the realization of the two centenary goals and the great rejuvenation of the Chinese nation.
Research on Providing Data and Space Calculation Support for Site Selection of Power Transmission and Transformation Projects
Authors: Jin Yao , Yu Wenxing , Zhao Jie , Song Zhuoyan , Li Hongzhu , Liu Bo , Xie Dan , Zheng Yaobin , Duan Shengchao , Zhao Zhipeng
Published: March 2021

With the acceleration of urban construction, the urban electricity load has increased rapidly, and electricity shortages have also appeared in various places. However, the rapid development of cities has resulted in a shortage of land. The location of substations and the selection of transmission lines are particularly important in planning. In this paper, distributed power transmission and transformation project to optimize network access with locating and sizing problems, establish an annual loss of power as the objective, and consider the output load timing characteristics of multi-period optimal power flow model. Use representative scenes to simulate the situation throughout the year, and give a method for determining scenes and their weights.
Design and Implementation of office automation network security system
Authors: Nan Tianwei
Published: March 2021

Socket based network communication is a flexible, easy to implement, low cost method. It can run on a variety of networks that use THE TCP/IP protocol as the communication protocol. So the design in VC++ environment, through the Socket to establish the original Socket, monitoring network traffic, and suspicious data through Access database records, to provide reference for administrators, so as to achieve network security.
Research on Seeker Servo Platform Based on BP neural network controller
Authors: Tang Wei , Jiang huhai , Pu bin , Zhang Tongtong , Mao Rui
Published: March 2021

Seeker is the core of precision guided weapon. The performance of its servo mechanism has a decisive impact on the accuracy of guidance weapon. The controller design of seeker servo system is of great significance to improve the function of seeker servo system. The mathematical model of the seeker servo system in the form of transfer function is built. The traditional PID control and BP neural network PID control methods are used to design the controller respectively. Aiming at the limitation of BP neural network, the BP neural network is improved. Finally, the simulation experiment is carried out in Matlab/Simulink. Simulation results show that the neural network PID controller has better performance than the traditional PID controller, so that the system has better adaptability and robustness.
A Combination of Lexicon-Based and Classified-Based methods for Sentiment Classification based on Bert
Authors: Zhang Jiaxin
Published: March 2021

Sentiment classification is a crucial problem in natural language processing and is essential to understand user opinions. There are two main approaches to solve this problem, one is the classified-based method, the other is the lexicon-based method; however, both methods perform not well on the long-sequence methods, and each method has its advantages and disadvantages. This paper introduced a new method called Lexiconed BERT, which cream off the best and filter out the impurities from the above two methods. The evaluation shows that our model achieves excellent results in the long sequence sentence and reduce resource consumption significantly.
Research on Station Balance of Robot Production Line Based on Improved Double Population Genetic Algorithm
Authors: Zhou Zheng , Meng Qingyu , Du Lifeng , Wang Xin , Liu Yang
Published: March 2021

Aim to solve the balance problem of robot production line, an improved double population genetic algorithm is proposed. The priority relation of production process is treated as the constraint condition, the selection function of crossover probability and mutation probability is designed according to the individual fitness of the population. Then the beat optimization algorithm is used to optimize the production rhythm of a switch shell welding line. The simulation result show that the balance rate of this robot welding line is improved and the production rhythm is optimized.