bluuebunny/crossref_metadata_2025 huggingface dataset:
A fast calibration method of the robot’s 3D vision system
Authors: Qin Lei , Zheng Zhenxing , Diao Shipu
Published: June 2020

Calibration accuracy and convenience are very important for the rapid production of vision-based robots. Although there are many calibration methods for the 3D vision system, the convenience of calibration cannot meet the needs of industrial sites. In this paper, we propose a fast calibration method based on a 3D calibration block. Its key point is to complete the calibration process through multiple space point constraints, and the space points used are jointly solved by multiple planes obtained by local point cloud fitting. The experimental results show that the proposed method can quickly complete the calibration of the robot’s 3D vision system, and the calibration accuracy can meet low precision occasions.
BDS RTK High-precision Positioning Algorithm for Deformation Solution
Authors: Zhou Bo , Wang Shouhua , Feng Siyu , Tang Donghai , Weng Chenghao , Dong Hang , Chang Xiaochi
Published: June 2020

In view of the increasing scope, scale and quantity of landslide, debris flow and other geological disasters and without achieving long-term stable high-precision monitoring in the exist, a solution algorithm on RTK high-precision differential positioning deformation is presented in this paper. The algorithm uses high-precision board receiver as the satellite positioning reference station, the u-blox receiver as the monitoring station. The carrier phase double difference relative positioning model is based on the carrier phase observation and pseudo range observation, combined with the RTK unscented Kalman filter model and smooth filtering algorithm, and then more accurate position results are obtained. This method can be used to calculate the position of deformation monitoring body with high precision, which is simple, easy to realize and practical. The positioning accuracy of deformation monitoring is higher. After smoothing, the horizontal precision can reach 3mm, and the elevation precision can reach 5mm.
Design of Home Service Robot for Pet Caring
Authors: Deng Weilun , Shi Yongtao , Li Chuanqing , Zou Tian , Tian Chunlai
Published: June 2020

Pet dogs are good friends in people’s home living. Some people sometimes are inconvenient to take care of pet dogs. A smart robot for caring pets is designed in this paper. The robot can actively interact with the pet dog in the way of serve and relieve the separation anxiety of the pet. During the serve process, the multi-stage gears and rack meshing transmissions are used to achieve near, medium and long-range launch modes with stable convenience performance. The structure of this companion pet robot is displayed. It is mainly composed of feeding system, serve system, grasp system, driving system and real-time monitoring system. It is demonstrated here with the feasibility of the machine function and the rationality of the structure design is analysed. The robot will support a good convenience help to pet caring in home living.
Home Position and Tool Coordinates Calibration for 6-DOF Robot Based on Fixed-point Constraint
Authors: Zhao Honghua , Zhao Jian , Lin Yifei , Han Qifei , Cao Baolu , chen Mianpeng
Published: June 2020

In the application process of industrial robots, it is necessary to ensure that the home position is correct when the robot changes the end tool, so that the coordinate values of tool can be calculated more accurately and the accuracy of the robot’s trajectory can be satisfied. A comprehensive calibration method of tool coordinates and home position of serial industrial robots based on fixed-point constraints is presented in this paper. Based on Denavit-Hartenberg (D-H) kinematics theory, the error models of tool coordinates and home position errors of 6-DOF serial industrial robots are established. By constraining the tool center point (TCP) of the robot with fixed points, the joint data of calibration points with different postures at the same position are collected, and the error value of the controlled object is identified by the least square algorithm. The calibration experiment results are basically consistent with the factory calibration parameters, which proves the feasibility of the calibration algorithm.
Research on Fault Diagnosis of Complex Equipment Based on Artificial Intelligence
Authors: Zhou Quan , Liu Lan
Published: June 2020

According to the requirement of fault diagnosis for complex equipment, the fault diagnosis signal is reconstructed by wavelet analysis technology and the multi-information fusion method of fault diagnosis based on evidence theory is established. The intelligent fault diagnosis method and fault reasoning method are established by using Bayesian network technology which provides the theory and method support for fault diagnosis of complex equipment.
Skin Reflectance Model for Multispectral System
Authors: Feng Sui , Zheng Jinjin
Published: June 2020

This is a pre-study on the non-invasive detection and contrast observation of pigmented lesions. We obtained a proper skin reflectance model of a multispectral imaging system that generates images perpendicular exposure of skin perpendicularly exposed reflectance in the wavelength ranging from 470 to 630 nm at an internal of 2 nm, altogether 81 different wavelengths in the visible range. The reflectance data was collected form 27 different skin lesions each 500*500 pixels in various conditions from 8 persons. Since the spectrum is mixture of layers of skin tissue distribution, independent component analysis (ICA) and pure components analysis were proposed to fit the experimental data, and the layered-dependent skin parameters melanin content, blood volume fraction, and haemoglobin content were extracted from the skin reflectance model. The skin reflectance model fitted spectrum curves show 4% average (12% maximum) difference from the experimental data, which were acceptable. The skin model is accepted for the multispectral imaging system in further studies.
Research on Monopulse Angle Measurement Algorithm in Pseudolite Local Positioning System
Authors: Yan Enqi , Yang Jun , Meng Zhijun , Guo Xiye , Zhang Yufeng
Published: June 2020

The pseudo-satellite local positioning system can solve the problem of blind spots in satellite navigation systems, such as tunnels, underground parking lots, and indoor positioning. The method of direction-finding positioning can be combined with distance-finding positioning to improve positioning accuracy, and it can also independently realize positioning functions. The basis of direction-finding positioning is to accurately estimate the direction of the signal source. The sum-difference patterns of amplitude monopulse angle measurement algorithm has mature applications in the field of tracking radar, and can achieve accurate angle estimation. The sum-difference patterns of amplitude monopulse angle measurement algorithm is applied to a pseudo-satellite local positioning system. Through simulation experiments, the angle measurement performance of the algorithm under different conditions is analyzed.
Synthesis Warning Algorithm of Landslide Deformation
Authors: Feng Siyu , Hu Dingmei , Wang Shouhua , Zhou Bo , Tang Donghai , Weng Chenghao , Dong Hang , Chang Xiaochi
Published: June 2020

Landslide is one of the most harmful geological disasters in the world. In order to effectively warn the landslide, Kalman filter is used to smooth the real-time Kinematic (RTK) positioning information of each monitoring point, remove outliers, improve monitoring accuracy, and extract information such as effective displacement. The attitude computation algorithm is used to solve the real-time attitude of the monitoring target, and the attitude prediction is realized which based on the deformation prediction information. Use the extended Kalman filter to realize the fusion of displacement deformation, velocity and acceleration data at multiple sites in the monitoring network, and to achieve the optimal estimation of comprehensive displacement. Use the MGM (1,1) gray model algorithm to realize the deformation displacement prediction. Use the comprehensive information amount to judge the landslide deformation grade. The early-warning algorithm is simple, easy to implement and practical, and can meet the actual requirements of landslide deformation early-warning.
Research and Application of Data Mining Technology in Library Office Information Construction
Authors: Wang Weifeng , Meng Luyang , Wu Lei , Zhang Jing
Published: June 2020

With the rapid development of the Internet, the amount of data related to users has shown a rapid increase. At the same time, in the library office system, the problem of how to effectively use and process massive data needs to be solved urgently. Data mining technology, as a technology combining machine learning, pattern recognition, and data visualization, can effectively solve many problems in the process of library office information construction. The data mining technology mainly includes many analysis methods such as association analysis, data segmentation, and deviation analysis. The mining results of these algorithm models are presented to users in a visual way, and the results of the rules, trends and concepts discovered can be applied to During the application of the system.
Formalization of the Gateaux derivative of functional and application in the principle of virtual work
Authors: Jingzhi Zhang , Ximeng Li , Guohui Wang , Yong Guan
Published: June 2020

Analytical mechanics provides the central guidelines for the design of engineering machinery in use today. One of the main pillars for analytical mechanics is the principle of virtual work. In the establishment of this principle, the Gateaux derivative plays an indispensable role. In this paper, we formalize the Gateaux derivative in the interactive theorem prover HOL Light. On this basis, we formally verify the principle of virtual work. This effort paves way for the computerized formalization of analytical mechanics. Thus, it will ultimately contribute to the verified design of engineering machinery, which comes with correctness guarantees beyond what is enabled by the currently adopted validation techniques.
Analysis of BeiDou/Galileo combined pseudo-range positioning performance in urban environment
Authors: Wu Youlong , Yang Zhong , Xu Nan , Yu Jiming
Published: June 2020

The observation conditions have a significant influence on the positioning performance. GNSS signals are easily blocked in urban environments, which leads to discontinuity and instability of position solution. With the construction of BeiDou and Galileo satellite navigation system in the final stage, multi-satellite fusion will be the future development trend of GNSSs. This paper introduces the mathematical fusion model of Galileo and BeiDou satellite navigation system, typical urban coverage conditions are simulated, and a detailed in the aspects of number of visible satellites, positioning error and PDOP values are analysed. The results show that the positioning accuracy of the integrated navigation system in the horizontal is within 3 m, the elevation is within 5 m, and the PDOP value are less than 1.5 in the open sky condition. In any coverage conditions, Galileo stand-alone system cannot guarantee the positioning continuity in the whole day, and positioning performance is the worst in the north coverage condition, unable to obtain the position solutions for more than 40% time in the whole day. In the north coverage condition, BeiDou has the best positioning performance, with a minimum of 4 visible satellites and 99% of PDOP values are less than 10.
Evaluation Model of the Regional Economic Vitality
Authors: Hu Jinyan , Cai Yongfang , Cheng Jiaming
Published: June 2020

Regional economic vitality is an important part of regional comprehensive competitiveness. Accurate assessment of regional economic vitality can reflect the state of economic development among different regions and provide reference to the developing policies of regional economic. To measure the regional economic vitality of main Chinese cities, in this paper, we first establish a mathematical index system based on five aspects (i.e., industrial vitality, capital vitality, innovation vitality, talent vitality and humanistic vitality). Then, the evaluation model of regional economic vitality is constructed using entropy method. The result shows that among 19 main cities of China, Guangzhou and Hangzhou have the highest economic vitality in the first-tier and second-tier cities, respectively. Besides, the change of the comprehensive evaluation of economic vitality among the first-tier cities is more obvious than that between second-tier cities. The evaluation results reflect regional differences in Chinese economic development and can provide valuable reference for exploring benign sustainable policies for regional economic development.
The Exploring on University Archives Management System Based on Information System
Authors: Lv Zuheng , Shi Heyuzi
Published: June 2020

Archive management is one of the routine tasks of colleges and universities. The effective use of college archives is of great significance to college brand building, cultural heritage, teaching reform, scientific research and innovation. Based on the major colleges and universities, this paper aims to explore the improvement of university archives management in the information age. It uses the literature review method, research method, experimental method, and object-oriented method to analyse. This paper analyzed the current situation of university archives management work, summed up the problems existing in archives management work, improved the archives management system of colleges and universities, and implemented it by means of management information system.
MSF-MAC: A Multi-Channel MAC Protocol for Long-distance and Anti-interference in Wireless Sensor Networks
Authors: Hao Ma , Jian Wu
Published: June 2020

On-site monitoring in the energy industry such as photovoltaic power stations is one of the main application areas of wireless sensor networks, with long distances, many nodes, long deployment cycles, and large communication interference. Aiming at these data collection characteristics, we propose a multi-channel MAC protocol which is capable of optimizing the allocation of multiple users for parallel transmission at a low data rate based on the SFs, named MSF-MAC. Based on the channel characteristics and flow characteristics of the data distribution of the acquisition nodes, the traffic adaptive slot allocation and the rate-based multi-spread-spectrum channel allocation algorithm are used to perform real-time coordinated scheduling of network nodes. At the same time, the protocol combines CSMA / polling mechanisms to design a multi-channel MAC protocol for long-distance and anti-interference in WSNs. Simulation experiments in NS2 confirm that the MSF-MAC has similar characteristics to 802.11 in the case of single-channel, and has a better system throughput and a lower average delay than 802.11 in the multi-channel scenario, which reduces the overhead of collisions and retransmissions, and improves the interference immunity of intra-cluster communication.
Empirical Research on Intelligent Upgrade Technology for Small and Medium-sized Logistics Enterprises
Authors: Chunfang Wang , Jilu Liu , Weibing Tan
Published: June 2020

The project uses key technologies such as PLC controller, inverter and sensor technology, integrated mechanical transmission, and motor drive to upgrade the equipment of a small enterprise, thereby realizing the intelligent automation of logistics sorting operations in the enterprise. The project research used interview method, observation method, and empirical analysis method. The research team went to the company’s site to investigate and study. After careful observation, it found that the company’s sorting system had problems. The misjudgement of the information of the sorting operator is the key reason for the picking error. Pushing the goods by manpower is the reason for the inefficiency. The project combines the principles of the related control system to redesign the operation of the original sorting operator. The intelligent control system and automatic code scanning system are connected to the relevant equipment of the operation line. The project realizes the connection between the intelligent control system and the automatic code scanning system on the existing transmission equipment. The combination of related technical function modules used in the project improves the maintainability of the equipment, which is a major improvement for enterprises to improve production efficiency and achieve capacity upgrades. Production innovation.
Research on practical calibration compensation method of MIMU
Authors: Zhao Renjie , Hu Baiqing , Tian Jiayu , Lv Xu
Published: June 2020

The Micro-inertial measurement unit (MIMU) is affected by the processing, installation and environment during its working process, which will produce large errors, resulting in low measurement precision, therefore, error calibration compensation is necessary. In this paper, a practical calibration compensation method of MIMU based on the error model of gyroscope and accelerometer was studied. The practical method uses a three-axis multi-functional turntable, which can provide high-precision angular rate and spatial position benchmark, to design the angular rate and six-position calibration scheme, and computes twenty-four error parameters of the MIMU, including zero bias, scale factor and installation error coefficient. The analysis of the experimental result shows that the precision of MIMU after calibration compensation can be improved by 1-2 orders of magnitude, which proves the effectiveness of the calibration compensation method.
A Four-point three-dimensional spatial localization algorithm based on RSSI
Authors: Ma Li , Cao Ning , Mao Minghe , Zhang Jianping
Published: June 2020

The three-dimensional positioning of nodes is a major and basic problem in wireless sensor networks. It has an important application value in areas such as search and rescue, target tracking, disaster reduction and intelligent environment. This paper presents a three-dimensional four-point centroid location algorithm based on RSSI. Based on signal strength between unknown nodes and known nodes, a received signal strength indicator (RSSI) propagation model in shadow mode is established. The Gaussian model is employed to RSSI. The signal strength is rectified to obtain a more accurate ranging model. In a three-dimensional space, a reasonable detection point is selected, and the centroid iteration algorithm is used twice. The weighted centroid algorithm is utilized for the first time and the average centroid algorithm is used for the second time to find the target. The coordinates of the nodes realizes the three-dimensional spatial positioning of the unknown nodes. Through simulation experiments, the positioning algorithm has improved accuracy and stability compared with the least square method and weighted centroid algorithm.
Research on Badminton Sports System Based on Wireless Sensor Network
Authors: Li Yunwei
Published: June 2020

Wireless sensor network is a self-organizing network system composed of nodes through multi-hop wireless communication. Deploying a wireless sensor network in the monitored area can complete sensing, data collection, and data processing in real time, and transmit the data processing results to the network terminal. This article studies the structure of the badminton sports system from the design perspective, and analyzes its technical characteristics and node software structure, wireless sensor network node structure, sports system architecture and functional characteristics. The system is deployed in the badminton sports venues to collect the movement parameters of badminton players in real time and perform timely and effective analysis to provide support for scientific decision-making in badminton training.
Transaction Data Management System based on Distributed Storage Architecture
Authors: Ji Yuan , Xia Tian , Zhang Honglue , Chen Gang
Published: June 2020

With the continuous development of application requirements and technologies, the differences between distributed storage architectures and traditional storage architectures are becoming increasingly apparent. The distributed storage architecture not only has the advantages of small fault impact range, high scalability, and large throughput, but also is widely used in many application systems. In the transaction data management system based on the distributed storage architecture, a large amount of transaction data information is transmitted and stored using the distributed storage architecture, which can effectively ensure the accuracy and consistency of the data. At the same time, the stability of the transaction data management system will be enhanced.
Design and Implementation of University Intelligent Library Based on Cloud Computing
Authors: Zhang Bin , Zhang Yuping , Zhang Shengjun , Yu Bing
Published: June 2020

With the development and wide application of the internet, the cloud computing technology with powerful functions has been initially applied in the fields of industry, agriculture, scientific research, medical treatment and so on. Its technical advantages undoubtedly bring the development power to the library. Intelligent library is the advanced form of intelligent library. Cloud computing service makes the user’s data storage and application software in the operation of the internet server, which makes the library network data high integration, intelligent and efficient. On the basis of discussing the basic meaning of cloud computing, we build a cloud service platform of Intelligent library and put forward the architecture design of modern and information-based intelligent library in the cloud computing environment. This paper discusses the function realization of university intelligent library based on cloud computing to provide some references for the innovative paths of university reader service in the new era.
RETRACTED: Application of artificial intelligence in computer network technology under the background of big data era
Authors: Xu Hao
Published: June 2020

The development of computer network technology is the trend of future social development, and the integration of artificial intelligence and computer technology, while enriching people’s daily life, has also become an inaccessible part of people’s daily life. Artificial intelligence technology is relying on computers The technology-based development was established, and because of its high intelligence, it has become one of the most promising technologies in computer networks. In order to accelerate the application of artificial intelligence in social production and life, and to facilitate production and life. Starting from the importance and necessity of artificial intelligence applications, the application status and its development advantages are introduced, and specific applications of artificial intelligence in computer networks are proposed.
Design and Implementation of Embedded Database Security and Reliability
Authors: Gao Zhang
Published: June 2020

This article analyzes the classification of common embedded databases, including SQLite embedded database, Berkeley embedded database, eXtreme DB embedded database, OpenBASE Lite, etc. By studying data replication and backup, embedded database recovery, embedded database backup design, detailed backup design and implementation, the purpose of this article is to improve the security of the database application process and the integrity of the information stored in the database.
Research on the Security Strategy and Technology of Information Resource Network of Chinese Academy Library
Authors: Zhou Donghua
Published: June 2020

This article briefly analyses the Security Strategy and Technology of Information Resource Network of Chinese Academy Library. At present, every country in the world is paying very close attention to the management of library Information resource network (IRN). Library Information Resource System is an important part of the information technology category. There are many risks in the library’s information resource system. In order to provide the users with the information accurately and timely, we need to develop a reliable and stable defense strategy.
Analysis of the Application of Machine Learning Algorithms in Data Mining
Authors: Xiaojun Chen , Jiang Bian
Published: June 2020

In the context of the era of big data, it is necessary to process information data more quickly to further develop various industries. At present, traditional data processing and calculation methods can no longer meet the requirements of modern big data calculations. With the increase of the amount of information data, the calculation and analysis methods of data are also growing, and machine learning algorithms are one of them. This article mainly expounds and analyzes the application of its learning algorithm in data mining.
Research on Practice Reform and Implementation of European Music History Course in Colleges and Universities Based on Music Feature Extraction Technology
Authors: Zhou Jie
Published: June 2020

The history of European music is one of the required subjects for music majors in colleges and universities, involving many cross-disciplines. As a part of the basic education curriculum of higher music discipline, the reform of European music history curriculum is imperative. As a part of the basic music education curriculum, the European music history curriculum is undergoing this transformation and will certainly find its own new development direction and space. The current music history curriculum practice reform is another important measure put forward under the background of the basic education curriculum reform. The development of the teaching practice reform of higher music education and the need of the development of the European music history curriculum itself require that the students’ participation in the practice teaching should be given full attention. The application of modern educational technology is an effective solution to improve the malpractice and quality of traditional music history teaching. Based on the technology of music feature extraction, this paper analyzes the reform and implementation of European music history curriculum in Colleges and universities.
Research on AGV Scheduling Optimization Based on Hungarian Algorithm
Authors: Liu Jiancheng , Wu Jian , Zhang Chengcheng
Published: June 2020

Aiming at some problems in the mode of intelligent warehouse multi-selection and order outbound, this paper proposes to optimize the picking station assignment order task and order task assignment AGV in a “serial” or “parallel” manner to realize the synchronous scheduling of order tasks and AGV. The improved Hungarian algorithm is used to solve the optimal assignment solution. Simulation proves that this strategy can effectively improve the order picking efficiency and avoid buffer blockage, thereby improving the efficiency of the dispatching system.
Research on Chaos Characteristics of Nonlinear Systems with Fractional Exponential
Authors: Lei Teng-fei
Published: June 2020

In this paper, a chaotic system with fractional exponential term is proposed according to the classical chaotic system. The bifurcation diagram, LE and attractor phase diagram of the system are analyzed by Matlab software. The numerical simulation results show that the system has rich dynamic characteristics, which provides a theoretical basis for the parameter selection of the system when applied to image encryption.
Chaos Analysis of Fractional-order System with Delay Based on Adomian Decomposition
Authors: Cao Feng , Lei Teng-fei
Published: June 2020

In this paper, fractional-order Lü chaotic system with nonlinear delay term is proposed, and the fractional-order Lü chaotic system with time-delay is numerically decomposed by Adomian decomposition. At the same time, the influence of fractional-order number on the system is verified. Then the bifurcation diagram, complexity and attractor phase diagram of the system are analyzed by Matlab software. The numerical simulation results show that the 0.9order system has rich dynamic characteristics, which provides a theoretical basis for parameter selection when fractional order delay system is applied to multimedia encryption.
Advanced Chinese Character Detection for Natural Scene Based on EAST
Authors: Zhang Jianxin , Feng Yunhai
Published: June 2020

Currently in the field of image vision processing, text detection and text recognition under natural scenes is a challenging task. At present, most of the research on text positioning is mainly aimed at English, and the detection and recognition of Chinese characters is relatively few. EAST text detection algorithm is simple in structure and high in accuracy. However, because of the feature extraction network, there is a small sense field, which cannot be well adapted to the text detection of Chinese characters. In order to adapt it to the natural scene Chinese character text detection, the feature extraction network of the modified EAST algorithm is Mobilnet-V2 and Resnet50, which increases the depth of the network and extracts more image features. The modified algorithm is tested on the dataset MSRA-TD500, and the obtained accuracy shows that the improved network performance is better than the original algorithm.
A 3D reconstruction method of image sequence based on deep learning
Authors: Liu Yun-peng , Yan Xing-peng , Wang Ning , Zhang Xin , Li Zhe
Published: June 2020

Camera calibration, image feature detection, matching and other aspects have become barriers that traditional 3D reconstruction methods are difficult to break through. The important role of deep learning in data detection and classification has a deep impact on the real world, and has become a research hotspot at home and abroad to deal with this problem. In this paper, a 3D reconstruction method of image sequence based on depth learning is proposed. Firstly, the principle and method of 3D reconstruction are introduced. Then, the new method of 3D reconstruction based on image is studied and discussed in combination with deep learning theory. Finally, the conclusion and prospect are given.
Multifaceted sentiment analysis of public comments on the Dianping.com
Authors: Sui Liying , Shang Lu , Guo Xiaochao , Zhang Dexue
Published: June 2020

Emotional analysis of text has always been a hot topic in natural language research. In view of the long-term dependence of recurrent neural networks and the fact that most models do not consider the correlation between input and output, this paper proposes a bidirectional LSTM model based on attention mechanism to judge the comment emotion. This method vectorizes the semantics of comments into the LSTM model, improves the relevance of input and output through the attention mechanism, fuses the aspect category and aspect Term, and outputs the results through the classifier. The experimental results of Dianping.com review data set provided by AI Challenger competition show that the improved method adopted in this paper is better than the common deep learning method.
Cycle Fusion Network for Multi-Person Pose Estimation
Authors: Wang Yuanxiang , Wang Teng
Published: June 2020

Multi-person pose estimation has been largely improved with the development of convolutional neural network, which however remains a challenging task in computer vision. The challenge is particularly pronounced in high flexibility of occlusion, camera angles, imaging-caused body limbs. Existing methods are mostly based on networks with deep architectures, which are capable of inferring the semantic labels with high accuracy while suffering from positioning accuracy degeneration caused by the loss of the spatial information. To address these problems, we present a novel network called cycle fusion network to improve the pose estimation accuracy in multi-person environments. The cycle fusion network has a two-stage structure. In the first stage, a cycle-path feature fusion is used to increase the semantic information for low level layers and the spatial information for high level layers respectively. In the second stage, a cross-scale feature fusion is used for refining the positions of keypoints. Equipped together with RFB module and multi-level supervision, the proposed method has shown the state-of-the-art performance on the large-scale MS COCO benchmark with extensive experiments.
Analysis and simulation of rainfall clutter of primary surveillance radar for civil aviation Air Traffic Control
Authors: Zhang Huaicai , Yang Yuhang , Du Hui , Luo Qiming , Zhang Ye
Published: June 2020

To evaluate the influence of rain clutter on the detection performance of Air Traffic Control (Hereinafter referred to as ATC) primary surveillance radar (Hereinafter referred to as PSR), paper takes the scattering area of rainfall clutter as the object of study. By using the equivalent sphere as the equivalent model, the RCS mathematical statistical model of rainfall clutter at different levels is quantitatively analyzed in combination with the rainfall clutter sign. At the same time, from the angle of the rainfall clutter itself and the wet radome with different thickness of water film, the influence of the detection distance of ATC PSR under rainfall condition is analyzed and studied.
Binocular vision mechanical arm system based on salient region target recognition
Authors: Li Ronghua , Wang Ruiliang , Tian Xueying
Published: June 2020

Robotic arms have been widely used in the sorting of manufacturing lines. During the sorting process of the robot arm, the captured speed and accuracy are core problems. In order to improve that, this paper proposes a binocular vision sorting robot arm system based on the target identification of significant regions. First, establish the target artifact training set and the Faster R-CNN algorithm is imported. A binocular camera is used to take pictures of the workpiece in the tray, and then deep learning algorithm is used to extract the significant area where the object is located. Image processing is performed on this region. Then, the three-dimensional coordinates of the workpiece centroid are calculated and passed to the manipulator for grasping and sorting. Because the significance area is extracted, the amount of calculation by the image processing algorithm is greatly reduced, and the speed is significantly improved. Finally, the picking and sorting experiment was designed. The results show that the system has high accuracy, strong robustness and strong portability.
Research on Geomagnetic Reconstruction Based on LSTM Neural Network
Authors: Wei He , Jing Wang
Published: June 2020

Geomagnetic observation data has unique academic research significance, and it is also an important national basic strategic resource. Based on the correlation and temporal characteristics of surrounding stations in geomagnetic observation data, this paper proposes the use of LSTM neural network method to predict the missing data of the target station based on the data of the reference station, and it is compared with the traditional BP neural and CNN neural network method. The results show that the LSTM neural network is superior to the BP neural network and CNN neural network in geomagnetic data reconstruction, and the predicted geomagnetic data has higher accuracy.
Multi-robot task assignment algorithm based on improved self-organizing mapping network
Authors: Guo Zhenyu , Liu Dan
Published: June 2020

In order to solve the problem of slow convergence speed and easy task conflict, a multi-robot task assignment algorithm based on improved self-organizing mapping network is proposed in this paper. Considering the redundancy generated in the solution, the self-locking factor is introduced to optimize. The neuron is then reselected when the path intersects to avoid the risk of collision. The simulation results show that the proposed algorithm can effectively reduce the solution time and the distance of multi-robot navigation compared with the traditional algorithm.
Design of Remote Monitoring System for Limb Rehabilitation Training Based on Action Recognition
Authors: Hu Wentao , Zhang Jiashuo , Huang Bailiang , Zhan Weida , Yang Xue
Published: June 2020

Aimed at the high cost of domestic rehabilitation medical care, the limited number of doctors, the shortage of training venues, and the lack of follow-up tracking for patients who recovered better after rehabilitation training, and a remote monitoring system to understand the patient’s rehabilitation situation, a kind of motion recognition-based Remote monitoring system for physical rehabilitation training based on motion recognition was proposed. From the perspective of machine learning and intelligent classification, the system uses the wavelet transform principle and Support Vector Machine (SVM) algorithm to inject intelligence into the remote monitoring system for limb rehabilitation training, so that doctors can receive patients walking and running energy characteristic and their movement distance data in the rehabilitation center, and based on this data to determine the patient’s recovery and rehabilitation training plan, the doctor can make a diagnosis for dozens or even hundreds of patients even if they never leave home, which greatly improves the efficiency of treatment, saves the corresponding manpower and material resources for the country and society t, and benefits the people.
Mission planning of multi base UAV Based on improved artificial bee colony algorithm
Authors: Zhang Xiaomeng , Hu Yongjiang , Li Wenguang , Yu Mingxin , Wang Jianyin
Published: June 2020

Aiming at the constraint that the take-off and landing position of Unmanned Aerial Vehicle (UAV) varies from time in maritime operations, a cooperative attack model of multi-base UAV is established. An improved artificial bee colony algorithm based on coding operation pool is proposed, which retains the basic idea of standard artificial bee colony algorithm, It draws lessons from RNA coding operation and introduces coding operation pool to ensure that the algorithm has better global search ability. The simulation results show that the cooperative attack model of multi-base and multi-UAV complies with the characteristics of modern maritime unmanned combat missions, and the proposed algorithm has strong optimization efficiency and optimization ability.
Data analysis and strategy evaluation in national defence science and technology tracking
Authors: Li Kan
Published: June 2020

Science and technology tracking can provide powerful decision-making information support for science and technology management, and it is an important reference unit for national defence science and technology development planning and technical route. In the context of confidentiality, patent and industry competition, there are transmission barriers between organizations for systematic scientific and technological information, and a large amount of disorderly and excessive point information will lead to information disaster, lack of effective data and tracking methods for quantitative analysis, and the demand side is at a loss. Based on the combination of literature retrieval and data analysis, this paper selects the association between texts through co citation analysis, explains the relationship between tracking targets through co word analysis, and finally selects groups with similar or common characteristics as tracking targets. This paper explores a new way of science and technology tracking, which can provide reference for national defence science and technology tracking.
Empirical analysis of I-GBDT to improve the accuracy of mass appraisal method
Authors: Wang Jiaqi , Sui Jingqi , Zhang Ziyan , Qi Jiabao , Liu Nan , Lv Junna
Published: June 2020

The transactions related to real estate in social and economic activities need to appraise the market value of commercial housing. In order to improve the accuracy and efficiency of mass appraisal model (MA), the paper proposed the Improved-GBDT algorithm based on hybrid feature selection, which combines the concept of supervised learning and unsupervised learning, selecting appropriate features based on the impact of features on results and the changing trend of feature data. The feature weights can be calculated by Random Forest and XGBoost. Considering grey correlation analysis, the correlation degree among features can be calculated, and appropriate features can be selected. In the paper, we took the housing sales data from May 2014 to May 2015 in USA into simulation analysis. The simulation results show that IGBDT model has better accuracy and stability than SVR, RF and XGBoost. Compared with RF and XGBoost model under optimal parameters, IGBDT not only reduced the average absolute error of prediction by 98% and 11%, but also make the maximum relative error drop by 97% and 12%. The results show that IGBDT can provide a powerful reference in evaluating the property market value.
A Method of Searching for Optimal Coalition Structure for Solving Resource Scheduling Problem of Overall Load Balancing in Edge Computing Environments
Authors: Yanan Hu , Chunsheng Li , Kejia Zhang
Published: June 2020

The cooperative computing resource scheduling problem in the distributed computing environment is usually transformed into the problem about how to find the optimal coalition structure. However, affected by factors such as high node density and large number of concurrent tasks in edge computing environments, it is difficult to formulate resource scheduling schemes for overall load balancing in a large strategic space by traditional methods. In order to solve this problem, we proposed a method of searching for optimal coalition structure based on discrete particle swarm optimization (DPSO). Firstly, we converted the resource scheduling problem of edge computing into an optimization problem model, constructed a new structure of coalition structure to express the resource scheduling scheme, and gave key elements such as optimization objectives, decision variables, and constraint conditions. Secondly, we improved DPSO and designed M-ary discrete particle swarm optimization (MDPSO): improved particle state determination method for adapting to the new expression of the coalition structure, and proposed a power series-based inertia weight computing method to improve the optimization speed and the optimal solution quality. Finally, we simulated real application scenarios and designed comparative experiments on the optimization speed, the optimal solution quality, stability, etc., which verifies that the method proposed in this paper has obvious advantages in solving the resource scheduling problem of overall load balancing in edge computing.
Topological Data Analysis of Two Cases: Text Classification and Business Customer Relationship Management
Authors: Yue Bi
Published: June 2020

Topological Data Analysis (TDA) is a rising and burgeoning field of data science, which provides a set of new topological and geometric tools to extract relevant features out of complex high-dimensional data. In this paper, we mainly study two papers: Topological Data Analysis of Time Series Data for B2B Customer Relationship Management [1]; An Introduction to a New Text Classification and Visualization for Natural Language Processing Using Topological Data Analysis [2]. We briefly introduce the topological concepts involved in the two cases, then compare and analyze the corresponding topological solutions. Accordingly, we summarize the advantages of TDA and finally draw a conclusion with some improvements to optimize them.
Review of research on partial discharge detection techniques of high voltage switchgear
Authors: Chao Zheng , Yongkang Zheng , Jun Zhong , Yongfu Wang , Zhang Haiyang Zhao , Bo Ren
Published: June 2020

Partial discharge inside a high-voltage switchgear can cause serious accidents. Partial discharge detection can reduce the incidence of accidents. This article summarizes the current research status of common high-voltage switchgear partial discharge detection technologies (Transient Earth Voltage or TEV, Utrasonic or AE and Ultra-High Frequency or UHF), introduces the research status of partial discharge model identification and localization of PD source, and finally looks forward to future research directions.
Multi-objective Ensemble of Regression Chains Prediction Algorithm for Pose Correction Errors of Precise Vision-based Printing Equipment
Authors: Wu Qiang , Zhan Zhenhui , Yang Shilin , Zhang Xianmin , Yang Lixin
Published: June 2020

To accurately know the working condition of the Precise Vision-based Printing Equipment (PVPE) and improve its printing accuracy and stability, this paper proposes a multi-objective ensemble of regression chains algorithm to predict the pose correction (position and orientation) errors of PVPE’s alignment platform. Since this algorithm uses XGBoost as a base learner, it’s called XGBoost Ensemble of Regressor Chain (XGB-ERC) prediction algorithm. The algorithm is verified by a test set, which is constructed based on experimental data of PVPE. The experimental result shows that the Mean Absolute Percent Error (MAPE) of this algorithm for pose correction errors x, y and θ is 6.868%, 6.495% and 5.342%, which is 25.1%, 27.6% and 16.8% higher than that of the traditional XGBoost single-objective prediction algorithm. The predicted result of the proposed algorithm can be used to compensate the correction errors of the alignment platform, which will help improve the printing accuracy and stability of PVPE, and promote the development of the field of Surface Mount Technology (SMT).
Analysis of the Application Countermeasure of Virtual Reality Technology in the Vision Simulation System
Authors: Yonghui Wu
Published: June 2020

Virtual technology is a computer simulation system based on new technology and visual technology to realize the creation and experience of virtual world. It belongs to the use of information technology computer system function for environmental simulation, and it uses the combination of multi-information fusion and 3D dynamic visual interaction and physical behavioral experience to build virtual and real scenes to make the entire environment reality. It lets users feel the real environment and interact with them. At present, the application of visual simulation system for virtual reality technology has been gradually popularized. This article first introduces the development of virtual reality technology, and briefly describes the specific characteristics of virtual display technology, and finally puts forward some countermeasures for the application of virtual display technology in the visual simulation system.
Nowhere to hide: Anonymous User Recognition Based on Multidimensional Trajectory Set
Authors: Ma Manfu , Lei Yueshen , Li Yong , Wang Changqin
Published: June 2020

Anonymous user identification is one of the core issues in the field of information security and e-commerce applications. Accurately identifying the implicit characteristics of users’ online behavior and the unique identity is important, it has theoretical significance and commercial application value. Based on Massive online clickstream data, this paper proposed AUI algorithms and multidimensional trajectory set model (MTS) to verify the feasibility anonymous user identification. Through the AUI algorithm and vectorization method, a unique multidimensional trajectory set is created for each user. Experiments show that compared with the decision tree and user document methods, the multidimensional trajectory set based on the click data stream has improved the accuracy of recognition and provides an effective solution for user recognition.
Research and Design of Online Learning System Based on Cloud Platform
Authors: Daochun Xia
Published: June 2020

The traditional online learning platform has limited educational resources and isolated resources, so it is difficult to support the operation of massive data. This paper designs an online learning system based on cloud computing platform to effectively integrate resources, reduce operation and maintenance costs. The platform uses big data and distributed computing technology to collect and process user access history data and log data, and uses collaborative filtering algorithm to recommend courses, so as to improve the efficiency of learners.