bluuebunny/crossref_metadata_2025 huggingface dataset:
Correction of Tunnel Wireless Propagation Model Based on TD-LTE
Authors: Yan Rui , Zheng Yunshui , Liu Yang
Published: July 2021

Because WLAN uses the open frequency band of 2.4GHz or 5.8GHz and does not need to be approved by the radio management department, it is inevitable that it will interfere with the wireless transmission of rail transportationt vehicles. The rail transit system of some cities introduces TD-LTE into the CBTC system, but the path loss generated during the transmission has a non-negligible impact on the urban rail transit network propagation plan. Therefore, the accuracy of the radio wave transmission model has an impact on the urban rail transit system. The importance of transportation is self-evident. This paper selects the SPM propagation model for correction, and uses the PSO algorithm to make up for the problem of BP easily falling into local optimality, and obtains the corrected propagation model and the measured data is closer.
Layout guide for Journal of Physics: Design and Research of Distributed Educational Resource Sharing Platform Based on IPFS
Authors: Zhou Qinghe , Lu Ju , Yin Hongjie , He Dong
Published: July 2021

In the age of information network, blockchain technology has become a key focus. With the integration of new technologies, blockchain covers many fields such as finance, social welfare, agriculture, smart cities, and education. At the same time, education has undergone fundamental changes along with the continuous advancement of technology, and under the impetus of blockchain and other technologies, “technology better empowers education” is an important goal of education informatization workers. Therefore, this article will explore its application scenarios in the field of “blockchain + education” based on blockchain and IPFS-related technologies and elaborate on how IPFS technology can improve the efficiency of educational resource sharing, optimize the process of sharing and dissemination of educational resources, promote the improvement of the quality of science education and build the application prospects of science education resource sharing.
Error Self-Detection of Smart Electric Meter Base on DFT processing
Authors: Wu Zhongxing , Zhu Enguo , Lin Fantao , Xu Yuelou
Published: July 2021

The paper proposes a high frequency signal (975 HZ) through superposition method for error self-detection. The feasibility of 975Hz superposition signal is illustrated and verified. According to the Nyquist sampling theorem, the sampling data are processed by DFT theorem. And through the self-detection error and metering error analysis judgment, it is concluded that scheme design of the self-detection error can be used as report and the early warning mechanism of smart IoT electric meter. It lays a good foundation for realizing the transformation of smart electric meter from regular replacement to state replacement, and provides a theoretical basis for ensuring the accuracy of metering.
Design of Movie Data Visualization System Based on Web Crawler
Authors: Zhang Nannan
Published: July 2021

This paper uses Python’s requests, beautifulsoup, Jieba and fontools to obtain the relevant data of all public films in 2015-2020 and analyze them. Finally, the data results are displayed graphically through Ajax technology, layui framework and eckards.
Acoustic field simulation of phased array in borehole in layered formation
Authors: Gan Tian
Published: July 2021

Horizontal stratified strata is a common geological model, and it needs to be simulated numerically in order to get the propagation law of sound waves in it, usually using the finite-difference time-domain method. However, for hundreds of meters underground well section, how to improve the calculation efficiency is a question that we need consider. In this paper, a dynamic method is proposed to obtain the computational domain, which can minimize the computational domain when the simulation results are reliable. When the transmitter is located below the receiver and the nearest delamination boundary is more than 2.0 m below the instrument, all delamination media below the instrument can be ignored in the calculation. A similar strategy is used for the layered boundary located above the array receiver. In this paper, the method is used to simulate the response of phased array acoustic logging in multi-layer media.
Installation and Debugging of Pneumatic Sorting Station in Flexible Automatic Production Line
Authors: Li Songtao , Zhou Xueguang , Liu Xuxuan
Published: July 2021

Vocational and technical colleges attach great importance to practical teaching. Automatic production line is an important equipment for practical teaching of required courses for mechanical and electrical majors and non-mechanical and electrical majors. On the basis of analyzing the composition of flexible automatic production line and training objectives, this paper gives the structure and workflow of pneumatic sorting station, summarizes pneumatic components, and gives installation and debugging steps.
Projectile wireless setting and Mechanical testing technology
Authors: Zhang Mingyue , Fang Liqing , Shi Yonglei
Published: July 2021

This paper discusses the mechanical testing technology used in the wireless setting system of projectile, mainly including sensor, signal processing, system analysis, error analysis and data processing theory. The circuit simulation and system analysis are carried out by using Multisum, and the magnetic field simulation is carried out by using CST. The wireless setting scheme based on electromagnetic induction is designed, and the scheme is analyzed and improved. Finally, the data of range and firing angle of the projectile in high-speed motion can be set quickly.
Application Research of Electronic Technology in Communication Engineering in Communication Engineering
Authors: Liao Xianbi
Published: July 2021

Electronic technology has positive significance for strengthening communication engineering quality. Its applications under big data context is mainly reflected in communication engineering resource allocation. It can establish an electronic communication resource intelligent allocation model, which is also the basis of communication engineering to complete massive data transmission. This article summarizes the combination of electronic technology and communication engineering based on past work experience.
Temperature Control System of Medical Instrument Based on Dual Threshold Hysteresis Comparison Circuit
Authors: Ding Zeyu , Hu Chunzheng , Miao Fushuai , Gong Wei
Published: July 2021

The paper presents a design method of temperature control system of medical instrument based on dual threshold hysteresis comparison circuit. The system adopts a negative temperature coefficient thermistor as the temperature sensor and a thermoelectric cooler as the control object. By means of this method, the working temperature in the medical instrument ranges from two degrees centigrade to four degrees centigrade accurately. According to the test results the design scheme is optimized and improved. The design method is scientific, effective and economic by experiments.
A New 2-Correspondences Monocular Vision Navigation Method Under Planar Motion
Authors: Yu Yingjian , Sun Xiangyi , Guan Banglei
Published: July 2021

Vision navigation has non-contact, high-precision and low-cost characteristics compared with other navigation method. This paper proposes a vision navigation method for planar moving platform in known scene based on two 2D-3D correspondences. Taking account of the arbitrary direction of camera and the relative pose between the camera and the platform, we propose a linear solver with unique solution, whose minimal number of requirement correspondences is 2 and can cope with arbitrary number of correspondences bigger than 2 directly. Our method is evaluated on both synthetic data and real-world data. The experimental results demonstrate that our method is high-accuracy and fast for vision navigation of planar moving platform.
Functional safety certification method for in-use escalators
Authors: Zhang Xupeng , Yong Zhao
Published: July 2021

As an emerging technology, functional safety technology has been widely used in escalators. In this article, the background and application of functional safety are briefly introduced, the definition of functional safety is given, and the method of documenting functional safety certification is a very effective and simple method, and the specific application of escalators in use is proposed. By providing reasonable safety certification documents in compliance with the prescribed procedures, risks can be effectively reduced, and the overall safety and reliability of the escalator can be improved. The content, scope, and development procedures of the escalator safety function certification document and the on-site verification of the escalator safety function were discussed.
A blockchain-based access control scheme for smart home
Authors: Zhang Wentai , Yan Huaizhi
Published: July 2021

With the advancement of technology and economy, the scale of the smart home industry has exploded. While improving people’s lives, smart home systems are facing threats to privacy leaks, malicious attacks, and structural security. Effective security mechanisms are very important for protecting valuable data in smart home systems. Access control helps information systems prevent malicious access, thereby reducing the risk of privacy leakage. Blockchain can provide security support for the Internet of Things system due to its advantages of decentralization and immutability. Therefore, in this paper, a smart home access control scheme based on blockchain is proposed. The scheme uses Hyperledger Fabric and implements access control strategies through smart contracts. By designing a hybrid access control model based on dynamic attribute-based access control and static access control matrix, the remote access control initiated by the user through the Internet and the access control between local devices are well guaranteed at the same time. Through safety analysis and performance evaluation, the feasibility of the proposed scheme is demonstrated.
Adaptive loop pipeline control mechanism for Coarse-Grained Reconfigurable Block Cipher Array
Authors: Qu Tongzhou , Dai Zibin , Lin Chen , Yin Anqi
Published: July 2021

Coarse-grained Reconfigurable Array (CGRA) is a new processor architecture suitable for Block Cipher calculation. However, it has the problems of complex control mechanism and poor support for loop pipeline mapping. Based on the CGRA architecture designed for Block Cipher algorithms, this paper proposes a scenario jump model which can describe the process of loop pipeline running. Based on this model, a control structure supporting Block Cipher loop pipeline mapping was designed on the process platform CGCLA (Coarse Grain Cipher Logic Array), which could automatically complete the control functions described by virtual instructions in the model driven by the configuration flow to realize the adaptive control. Compared with similar process structures, CGCLA platform has more complete control functions. The mapping results of AES algorithm show that the proposed technique can achieve 2.15times performance improvement and reduce the amount of algorithm configuration information by about 25%.
Research on Precise Control Technology of Explosion Point Based on Ballistics
Authors: Shi Yonglei , Fang Liqing , Zhang Mingyue , Guo Deqing , Zhang Sa
Published: July 2021

According to the characteristics of small caliber grenade, this paper establishes its internal and external ballistic model, and studies the characteristics and basic rules of internal and external ballistic of grenade. The key factors affecting the accuracy of the distance model are analyzed, and the techniques and methods for determining the parameters of the distance model are studied. The measuring system and wireless setting system for the precise control of small caliber grenade blast point are designed. The theoretical method of controlling the blast point of projectile by DSP chip and improving the accuracy of distance determination is described. Finally, a wireless setting system is constructed based on related theories and sensors.
A Total Dose Irradiation Test System
Authors: Zhang Kun , Yan Na , Yang Fan , Zhao Xiaodong
Published: July 2021

In this paper, a set of generalized test system for total dose irradiation test is designed. Through the establishment of related hardware platform and related test chip according to the adaptation requirements, the device can be observed in real time under the radiation environment. The total dose test was irradiated with the 60Co source, and it worked normally when different total doses were selected. In this article, a unit library test chip based on 130nm SOI technology is selected for testing. During the test, the system works stably and functions normally.
Analysis of Influencing Factors on the Capability of Ground Safety Remote Control Omnidirectional Antenna
Authors: Zhao Mei , Lin Yiyong , Hu Yuming
Published: July 2021

Aiming at the capability of the ground-safe remote control omnidirectional antenna, the factors affecting its signal coverage are analyzed. The calculating method of antenna working boundary combining the width of the antenna beam is proposed. The determination of the effective working hours of the omnidirectional antenna is realized.
Research on Man-Machine Service Reliability of New Generation Power System
Authors: Yin Xia , Li Lulu , Lv Zhimeng , Yan Zhen , Xu Hua , Zhao Kun , Huang Kun
Published: July 2021

With the rapid growth of smart grid dispatching business scale, the traditional fat client mode power system has a large degree of business coupling, which limits the power grid dispatching business. But the lightweight man-machine cloud terminal and man-machine service framework have greatly reduced the coupling degree of the grid dispatching system business. The appearance of man-machine service reduces the development cost of client, and makes the unified browsing of multi system and multi terminal equipment easier. However, how to ensure the reliability and stability of man-machine interaction service is a question worthy of discussion. How to adapt to the interaction of a lot of clients and to adapt to the requests of different clients put forward higher requirements for man-machine service. This article describes the man-machine service architecture and key technologies to ensure reliability, introduces technologies such as load balancing and thread pools that adapt to the characteristics of power grid human-computer interaction, introduces in detail the distributed job scheduling management mechanism within the man-machine service, and describes the standardized request and return result of man-machine service. Finally, through sample testing and on-site operation, demonstrate the reliability of the man-machine service.
Application of mapping geographic information in emergency mapping
Authors: Liu Yuhua , Song Wenjie , Sun Jiuhu , Qu Tonglei , Tian Dan
Published: July 2021

With the continuous development of geographic information surveying and mapping technology, emergency surveying and mapping puts forward higher requirements for surveying and mapping work. Whenever an emergency occurs, emergency investigation and geographic mapping provide effective and reliable information for the emergency situation. In addition, emergency surveying puts forward higher requirements for mapping geographic information. Analyzing the application of surveying and mapping geographic information technology in emergency surveying and mapping, such as the application of data collection technology and virtual reality technology, can effectively enhance the role of geographic information technology in emergency surveying and mapping, and improve the ability of emergency response. This paper mainly analyzes the application of geographic information in emergency surveying and mapping and related technical fields, and explores the main application trends of emergency surveying and mapping.
Research on the Construction Method of Knowledge Ontology Facing the Field of Substation Maintenance
Authors: Zhang Bowen , Qian Ping , Li Cheng , Gao Fei , Yang Ning
Published: July 2021

Starting from the definition and classification of knowledge, this paper gives the definition and classification of substation maintenance knowledge. Based on the “seven-step method”, it proposes a method of constructing knowledge ontology for narrow fields, including 9 steps, and establishes substation maintenance knowledge Ontology, including 13 concepts and 60 attributes, lists the concepts and attribute descriptions of the ontology, laying the foundation for the next step of building a knowledge navigation map.
Research on Calibration Technology of TEV Partial Discharge Smart Sensors
Authors: Shao Hongming , Tang Zhiguo
Published: July 2021

TEV partial discharge detection is an important method to judge the insulation status of the switchgear. However, the quality of TEV smart sensors produced by different manufacturers on the market is uneven. Some TEV smart sensors that have been put into operation have deficiencies in measurement sensitivity, data stability, and long-term operational reliability. In response to these problems, this paper proposes a TEV smart sensor calibration method and builds a test platform, which is composed of program-controlled signal source, signal coupling device, protocol conversion device, host computer and corresponding integrated control software. On the basis of the existing standards such as sensitivity and linearity, the evaluation of the data stability, reliability and battery lifetime of the TEV smart sensor has been added. It provides a more comprehensive and effective implementation plan for TEV smart sensor performance verification in power grid access test.
Research on SLAM based on RBPF algorithm in indoor environment
Authors: Li Qiang , Kang Jia , Cao Xiaofang
Published: July 2021

In order to realize the simultaneous localization and mapping (SLAM) of robots in indoor environments, a SLAM method for four-wheel mobile robots based on RBPF algorithm and lidar is proposed. The mobile robot realizes its own positioning during the movement. The lidar scans the location of indoor obstacles, updates the map in real time, and gradually realizes the construction of a local map to a global map through data association. Aiming at the particle barrenness that may occur when the RBPF algorithm realizes SLAM during resampling, an adaptive resampling method is adopted to ensure that there are enough particles to realize SLAM every time. The experimental results show that when the linear velocity and angular velocity of the four-wheel mobile robot are small, indoor SLAM can be better realized.
Single Image Defogging Algorithm Based on Sky Region Segmentation
Authors: Xu Shufang , Fu Yaowen , Sun Xiaoyi
Published: July 2021

The visibility, contrast and color fidelity of images acquired under foggy weather will decrease to a certain extent, image defogging is an important part of image processing. Since the dark channel prior is not applicable to the sky area, which results in the color distortion and some noise of the restored fog-free image. Based on the segmentation of the sky region, it is proposed to separately estimate the atmospheric light value and transmission map according to different regions, and finally generates a defogging image using the optimized synthetic global map. In order to divide the sky domain and the non-sky domain more accurately, the two results obtained by the threshold segmentation method for the dark channel map and the improved threshold segmentation method for the original foggy image are considered at the same time. In the step of estimating the transmittance of the sky domain, the dark channel map of sky domain is obtained based on HSI color space, making the sky area more natural after defogging. Experimental results show that the algorithm can achieve good defogging effect, smooth edge transition between regions, and the defogging images are more natural and clear.
Studies on the influence of speckle density on the accuracy of digital image correlation method based on numerical simulation
Authors: Junyao Song , Zibin Liu , Chuan Luo
Published: July 2021

Digital image correlation method is a high-precision non-contact modern optical mechanics method whose measurement accuracy is directly affected by the quality of the speckle pattern used. In this paper, a numerical simulation experiment is designed to measure and analyze the accuracy of DIC method using speckle patterns which are generated with different speckle densities. The results show that the measurement error of DIC decreases first and then increases with the increase of speckle density, and the error is minimum when the duty ratio is about 60% to 70%. The result show that in practical application the duty ratio of speckle on the specimen surface should be appropriately high, preferably between 60% and 70%. This study is helpful for speckle selection and related research in practical application.
The influence analysis of Active Distributed Jamming on radar detection probability
Authors: He Ailin , shi Feng , Li xiaobin
Published: July 2021

In this paper, we studied the influence of active distributed suppression jamming on radar detection probability. Firstly, the radar detection probability models of three kinds of target echo signals, namely, deterministic signal, Swerlling type I and II signal, Swerlling type III and IV signal, are established under the condition of active distribution; Then, the influence of distributed jamming on the detection probability of three kinds of target echo signals is simulated and analyzed in two kinds of scenarios of distributed support jamming and long-distance distributed support jamming. The simulation results show that the noise power entering the main lobe has the greatest influence on the radar detection probability, but when the noise power in the main lobe increases to a certain extent, the influence on the radar detection probability is not obvious.
Resource-aware fluid scheduling with time constraints for clustered many-core architectures
Authors: Yin Anqi , Guo Yuanbo , Tang Di
Published: July 2021

With the rise of many-core processors, real-time applications processing obtains better performance acceleration and parallelization freedom. A validate schedule is able to minimize system resource consumption under the time constraints, which has become a focus recently. This paper establishes an accurate fluid task model and an optimal integer linear programming (ILP) model further. These models not only realize the flexible parallel scheduling, but also achieve co-scheduling between computing and communication resources. Moreover, a heuristic algorithm is presented to generate near-optimal solutions within polynomial time. The experimental results show that the proposed approach is validate and capable to balance the time and resource consumption effectively. It leads the improvement of schedulability and validity up to 68.67% and 24.67% respectively, with 13.16% reduction of the system density averagely.
Analysis of data crawling and visualization methods for recruitment industry information
Authors: Zihan Song , Yanhong Yang , Hongtai Guo
Published: July 2021

With the popularity of the Internet, major job boards have become the main way for job seekers to obtain information, but the current job boards generally lack clear information display, overall industry trend analysis and data visualization, which makes job seekers fall into confusion. In this paper, we first crawl the job boards based on Scrapy framework, store the data in EXCEL after cleaning, explore the potential connection between different data through Apriori algorithm, and finally visualize the different job information in a targeted way. In this paper, we take the job information of printing industry as an example for implementation, extract key information, and propose a suitable visualization method for different types of job information. The method proposed in this paper can not only help job seekers understand the current talent demand of the industry in a simple, intuitive and fast way, but also has some guiding significance for the talent training program of universities.
Single image dehazing based on fusion of sky region segmentation
Authors: Li Simeng , Zhou Qinghua
Published: July 2021

In order to solve the problem of image sharpening with sky region, a single image dehazing method combining sky region segmentation was proposed. Firstly, a fusion sky segmentation method combining OTSU algorithm with Canny operator edge detection is proposed to divide foggy image into sky region and non-sky region. Secondly, a linear index was constructed for the sky region using the dark channel prior sky transmittance to modify the sky region transmittance. For the non-sky region, a fast guided filter was used to optimize the dark channel prior non-sky transmittance. The two were combined to obtain the final transmittance, and the atmospheric light value was optimized by means of average estimation. Finally, combined with the atmospheric scattering model, the image is reconstructed dehaze. The experimental results show that the proposed method can segment the sky more accurately, estimate the atmospheric light value and transmittance more accurately and efficiently, and has the advantages of high contrast, natural color and clear details.
Deep Program Representation Learning Analysis for Program Security
Authors: Li Na , Zhang Haoyu , Hu Zhihui , Kou Guang , Dai Huadong
Published: July 2021

As the scale of software and the complexity of programs continue to grow, it is hard to meet development of modern computer technology only by manually extracting program features. In recent years, deep learning has achieved rapid development in different fields. Program representation learning based on deep learning has been widely used in many works, such as software vulnerability analysis, program analysis and malware detection. And it has gradually become a hot research direction in information security. After the deep analysis of existing research work on automatic program security detection, we catalog deep program representation learning for program security based on data representation and provide a comprehensive overview of deep program representation learning for program security under different application scenes. Then, we propose a deep program representation learning framework for program security. Finally, we conduct comparative analysis and summarize the challenges in deep program representation learning for program security.
An Analysis on the Crisis of “Chips shortage” in Automobile Industry ——Based on the Double Influence of COVID-19 and Trade Friction
Authors: Wu Xiling , Zhang Caihua , Du Wei
Published: July 2021

The COVID-19 pandemic and various infection control measures have made a great impact on the regular operation of global integrated circuit companies,which caused the“Chips shortage” Phenomenon in the automotive industry. Based on data collected from official channels, industry associations, SIA and enterprises, this paper performed an empirical analysis on the structure of global integrated circuit market, and studied supply and demand in the market. The results of the analyses showed that:1) the pandemic control measures and the re-allocation of market resources are the short-term factors unbalancing the supply and demand for automotive chips. 2) the global shortage of Chips of the automotive industry may continue and the risk of breaking the industrial chain is increasing. Because it is a long industry chain which relies on efficient cross-border collaboration, but it is lack of international prevention and control cooperation mechanism altogether. The current situation presents both challenges and opportunities to China. This paper proposes that China should take efforts in strengthening international cooperation; and improve the core competitiveness of China’s chip industry by the top-level designing and encouraging domestic enterprises to invest in research and development,and to improve their technical performance.
Hyperspectral image classification based on composite kernel relevance vector machine
Authors: Sun Cheng , Liu Donghao , Han Jie Guo , Yang Bei , Cheng Zhaoxiang
Published: July 2021

This paper presents a composite kernel Relevance Vector Machine(RVM) algorithm, for enhanced classification accuracy of hyperspectral images. This paper constructs three forms of composite kernels based on properties of kernels. The spatial feature is extracted using multi-scale morphological method from the image after principal components transform. The final classification is achieved by composite kernel RVM classifier. The proposed approach is tested in experiments on AVIRIS data. Compared with spectral kernel RVM, the OA and Kappa coefficient of composite kernel RVM increased obviously. However, the training time dose not increased. Meanwhile, composite kernel RVM has ability to get high accuracy with relative small training set. The proposed method has practical use in hyperspectral imagery classification.
Image recognition and detection based on fast area convolutional neural network
Authors: Zhang Hanwen , Qin Zhen , Xie Hua
Published: July 2021

Nowadays, image recognition and detection technologies based on traditional artificial neural networks and convolutional neural networks are slightly inadequate in terms of training and recognition time and accuracy, and are difficult to deploy on devices with limited hardware resources. Therefore, this article proposes a recognition and detection technology based on fast regional convolutional neural networks. We use RPN (Region Proposal Network) instead of Selective Search method to rebuild the network, and add a new ROI pooling layer before the fully connected layer of CNN. Determine the category. The average detection accuracy on our data set can reach 83.8%, and the training time is only 0.34 hours.
Nodes detection in CDN with enhanced naive bayes tree
Authors: Hou Ruijjie , Guo Changyong , Zhang Zhaoxin , Li Ning
Published: July 2021

In recent years, Content Distribution Network (CDN) plays a critical and central part of Internet infrastructure. There are more and more studies on CDN. Nodes detection in CDN, as a key technology among them, has become a hot research topic. Current methods mainly focus on collecting one or some CDN vendors nodes by manually constructing features set. However, because CDN nodes detection is not restricted by specific CDN vendors, these methods are not applicable. In this paper, we proposed a novel machine learning algorithm, i.e. enhanced Naive Bayes Tree to identify CDN IP addresses. This algorithm makes full use of the advantages of Decision Tree and Naive Bayes algorithm, and further improves the performance through enhanced part. We build this classifier based on analysis of the characteristics of DNS resolutions, HTTP logs and WHOIS lookup. Experimental results show that our approach outperforms in terms of accuracy and amount of packages. Moreover, we separately tested the enhanced part and it performs well. We believe that this method could be applied to CDN IP addresses detection.
Anonymous node location based on clustering
Authors: Luan Jihai , Xia Yong , Xie Yuancheng , Zhao Dong , Zhang Zhaoxin , Li Ning
Published: July 2021

With the rapid development of network technology, the network’s scale is increasing and becoming more complex. It is imperative to understand the structure of the network for network management and network security. Therefore, the construction of the routing topology has become a top priority. Routing topology analysis is already a relatively mature technology, but anonymous nodes’ positioning has not received enough attention. Nowadays, the primary solutions to anonymous nodes are graph analysis and tomographic tree construction. Based on these two methods, this paper proposes a rough location of anonymous nodes based on the method of three-level clustering. They are the K-means clustering of data before anonymous identification, hierarchical clustering of feature values in anonymous identification, and central point calculation based on clustering ideas during anonymous positioning. Experiments have proved that performing the first-level K-means clustering before anonymous node identification can effectively improve anonymous positioning accuracy. And the three-layer clustering idea proposed in this paper can roughly get the location of anonymous nodes based on reducing the complexity of the original method.
Research on improvement of hybrid particle swarm algorithm in underwater active electric field positioning technology
Authors: Xu Tianyang , Cai Ding , Li Beiming
Published: July 2021

Since the underwater active electric field positioning algorithm based on the MP-MUSIC algorithm has a slower positioning search speed, the hybrid particle swarm algorithm is introduced to speed up the positioning search speed and positioning accuracy. This paper improves the particle swarm algorithm, adopts dynamic learning factors, and uses natural selection-hybrid particle swarm algorithm to improve the search speed and positioning accuracy of the positioning algorithm.
UWB/PDR integrated indoor positioning method based on robust adaptive square root cubature Kalman filter
Authors: Li Zhiyu , Zhang Lijie , Tian Guangliang
Published: July 2021

Aiming at the problem that the ultra wide band (UWB) wireless signal is easy to be interfered, a robust adaptive square root cubature Kalman filter (RA-SRCKF) is proposed to be used in UWB/PDR integrated indoor positioning. RA-SRCKF is based on square root cubature Kalman filter (SRCKF) and its statistical characteristic of measurement noise is updated with the method of first estimating and then modifying. The experimental results show that the proposed RA-SRCKF can effectively improve the accuracy and stability of UWB/PDR integrated positioning.
UWB/IMU integrated inspection robot positioning in underground substation
Authors: Zhang Xiaowei , Guo Xiucai
Published: July 2021

The task of the underground inspection robot is to detect the environment of the underground substation and the operating parameters of the electrical equipment in it, and precise positioning is the guarantee for the inspection robot to complete the above tasks. In order to solve the problems of large drift of inertial sensors based on micro-electro-mechanical systems, and susceptibility to NLOS errors in UWB positioning, a fusion positioning algorithm with extended Kalman filtering as the core was designed. The algorithm suppresses the drift of position information by estimating the deviation of the inertial device, and integrates the UWB ranging information to improve the long-term positioning stability of the carrier. Finally, a parallel window smoother is designed to smooth the fusion result. The simulation results show that the fusion algorithm has a strong ability to resist drift and non-line-of-sight errors. Compared with the traditional fusion algorithm, the error is reduced by 38%.
Object detection and recognition system based on computer vision analysis
Authors: Liu Haitao , Li Yuge , Liu Dongchang
Published: July 2021

Artificial intelligence based on deep learning enables the machine to have the ability of understanding and cognition, but the application of artificial intelligence technology in supermarket shopping scene is limited. In the post-epidemic era, the contactless self-checkout of unmanned supermarket is more in line with the development needs of modern society. We build Pytorch environment, first to collect pictures of a large number of commodities and labeling information, and training model is obtained by YOLO neural network algorithm, finally through a call to model to realize the recognition of goods. Neural network algorithm is used to improve the recognition rate of goods step by step and achieve the detection and recognition of objects. We have tested our model on the real supermarket commodity data set and the public data set ImageNet, and the results show that our model can achieve a certain practical effect.
A survey of offensive security research on PLCs
Authors: Ma Rongkuan , Wei Qiang , Wang Qingxian
Published: July 2021

Industrial Control Systems (ICSs) are widely deployed in critical infrastructures, such as electric power, water filtration and distribution. Programmable Logic Controllers (PLCs) work as the core components of an ICS. The offensive security technology of PLCs has attracted the popular interests of both attackers and researchers. In this paper, we firstly abstract a 4-layers model of PLC’s implementation, and then summarize and classify attacks against PLCs into 5 types. Further, we point out the features and trends of the related attack studies, which is helpful to promote the research in the ICS security community and provide vital suggestions for defenders.
A novel quantization method combined with knowledge distillation for deep neural networks
Authors: Hu Zhou , Fan Chunxiao , Song Guangming
Published: July 2021

The massive parameters and intensive computations in neural networks always limit the deployment on embedded devices with poor storage and computing power. To solve this problem, a novel quantization algorithm combined with Knowledge Distillation (KD) is proposed to reduce the model size and speed up the inference of deep models. The proposed method consists of two phases, KD-Training and Quantization-Retraining. KD-Training attempts to train a compact student model with pre-quantized weights by the proposed pre-quantized constraint loss. In Quantization-Retraining, the pre-quantized weights are quantized to 2n and the first and last layers of the network are retained to make up for the accuracy loss caused by quantization. Experiments on the CIFAR-10 dataset show that the proposed method can obtain a low-precision (2-5bit) quantized student model with a compact structure, and the test accuracy even exceeds its full-precision(32bit) reference as the improvement of the generalization ability. It can get higher performance compared with that obtained by other quantization methods. Also, since the quantized weights are constrained in { ± 2n}, it is suitable for the acceleration of the network calculation in hardware.
A patch-based and multi-instance learning strategy for pneumothorax classification on chest X-rays
Authors: Tian Yuchi , Chang Yan , Yang Xiaodong
Published: July 2021

Pneumothorax is a lung emergency. Automated computer-aid pneumothorax diagnosis based on chest X-ray can help reduce the diagnostic time and save valuable time for the treatment. A total of 21,759 patient’s frontal-view chest X-ray images from one medical center are used in this study. The dataset is divided into two categories: pneumothorax and non-pneumothorax, which are evaluated by two radiologists with over ten years of practical experience. A two-stage training for pneumothorax classification based on multi-instance learning (MIL) are proposed, first training a patch-level classifier, followed by an image-level classifier training, which is initialized with the patch pre-trained weights. The image-level classifier initialized with patch pre-trained weights achieves good classification performance with the F1-score, accuracy and recall of 0.869, 0.915 and 0.843 respectively, which are larger compared to that of the model initialized without patch pre-trained weights (0.785, 0.878 and 0.783). The two-stage training strategy can improve the performance of pneumothorax classification and does not require too high GPU memory and long training time.
A diagnostic method of high myopia based on transfer learning
Authors: Chen Baibing , Wan Cheng
Published: July 2021

In order to promote the development of computer-aided diagnosis, improve the efficiency of high myopia diagnosis, and help healthcare workers assist in diagnosis, this paper uses 6571 fundus color images of high myopia and 6212 normal color images from the Geriatric Hospital of Nanjing Medical University as the dataset. The initialization parameters pre-training on ImageNet are loaded into the VGG-16, VGG-19, ResNet-50, ResNet-101, Inception-V3, and EfficientNet-B0 models, Learning rate changes dynamically according to the number of training epochs, and saving the model with the highest area under curve (AUC) value during the training process. Taking the best classification model from different networks, this paper achieves classification accuracy of 93.86%, sensitivity of 0.9126, specificity of 0.9677 and AUC value of 0.9866 on the test set. Each image takes 0.039 seconds, which is within the acceptable range meeting real-time of medically assisted diagnosis. Results show the fine-tuned ResNet-101 network meets the needs of medical assist diagnosis and can be used for screening high myopia, with high accuracy and real-time performance.
A key distribution protocol based on quantum entanglement swapping for unmanned surface vehicle
Authors: Qin Lingyu , Li Ying , Wang Shibo
Published: July 2021

Aiming at the problem of Unmanned Surface Vehicle’s (USV) secure communication, this paper proposes a key distribution protocol based on quantum entanglement swapping for USV. Compared with the current techniques, this paper uses the principle of quantum unclonability and quantum entanglement in quantum mechanics to realize the secure communication of USV. Meanwhile, in view of the low visibility at sea and the influence of weather such as wind and waves, this study adopts a key distribution architecture of quantum relay to realize the establishment of quantum channel between any two ships and obtain the absolutely secure key eventually. Therefore, the proposed method can provide long-distance, secure and reliable communication for USVs in the civil and military fields.
Analysis of sun-moon gravitational acceleration and engineering realization of space target
Authors: Huang Xiaobin , Zhang Yan , Xiao Rui , Lu Li , Jiang Yuan
Published: July 2021

Space target orbit determination is a core function of space target surveillance radar, which involves very complicated mathematical principles, and it is very difficult for professional radar system designers with no orbital mechanics to develop corresponding software modules. The difficulty in developing orbit determination software is the calculation of perturbation acceleration, which is the basis for realizing high-precision numerical orbit calculations. To this end, this paper takes the solar-moon gravitational perturbation that cannot be ignored in the precision orbit determination of high-orbit satellites as an example, introduces its mathematical principles, gives the program design ideas for acceleration calculation, implements the interface function and integrates it into the author’s early development radar orbit determination library (RadarOrbDet). The simulation results verify the effectiveness of the interface function and show that the orbit determination function library can assist scientific researchers in radar system design. The research results of this paper can be used as a reference for the spacecraft orbit analysis of interplanetary flight.
Research on operating conditions of electric propulsion ships under transformer interturn short circuit
Authors: Ma Bo , Wu Xixiu , Ma Wenyu , Zhang Qichao , Hou Bowen , Wan Pengpeng , Feng Xiaotong , Hou Hui
Published: July 2021

Most ships currently use electric propulsion systems. In this system, the transformer plays a key role in power distribution. The probability of interturn short circuit occurs in the transformer is high, it will cause faults such as three-phase voltage imbalance and endanger the safe operation of the ship. The simulation model of ship electric propulsion system established in this paper includes propellers and transformers, and the influence of the interturn short circuit of a transformer on the sailing conditions is studied. The research results show that the transformer interturn short circuit will generate a huge inrush current and have a huge impact on the torque and speed of the propeller.
Research on the verification method of flyback high-frequency transformer (FHFT) based on field-circuit coupling model
Authors: Zhang Qichao , Wu Xixiu , Ma Wenyu , Ma Bo , Wan Pengpeng , Hou Bowen , Feng Xiaotong , Hou Hui
Published: July 2021

In view of the current status of research on verification of the correctness and effectiveness of FHFT design, a field-circuit coupling based FHFT design verification method is proposed in this paper. This paper proposes a FHFT design verification method based on field-circuit coupling. The steps of FHFT verification using field-circuit coupling method are elaborated in detail. A three-dimensional physical model of FHFT based on AP method is established. The calculation of FHFT flux density and the verifying of transformer output waveform are completed by using the field-circuit coupling method of alternating iteration of non-linear magnetic field solution and circuit. On the basis of completing the flux density calculation, the field circuit coupling method is used to verify the output waveform of the transformer. It is found that the output waveform of FHFT is not an ideal square wave, but has some distortion, which is caused by neglecting the leakage inductance of transformer in the design process. This shows that the influence of transformer leakage inductance is very important and should be paid attention to.
Multi-stage perforation and hydraulic fracture stage selection based on machine learning methods
Authors: Yu Yulong , Xu Jiafang
Published: July 2021

In unconventional oil and gas resources, especially shale oil and gas resources with extremely low permeability and porosity, in order to develop effectively, it is necessary to establish perforation and multi-stage fracturing. The machine learning algorithm k-means clustering was used to cluster the five features selected to describe reservoir properties: shale content, porosity, total organic carbon content and those reflecting rock mechanical properties: Young’s modulus and Poisson’s ratio. The data were classified in a high-dimensional space to determine different perforation fracture stages. The classification algorithm XGboost was then used to predict different perforation stages using four conventional logging curves GR, NPRL, VP and DEN. The K-means clustering algorithm based on Euclidean distance can well classify the selected features in the high-dimensional space. The Hopkins statistics of clustering trend is 0.94, showing a good clustering trend. When the classification algorithm is used for prediction, the average accuracy is 0.92, the average recall rate is 0.90, and the average F1 score is 0.90, which can predict different perforated fracture stages well and optimize the design of the perforated fracture stage.
Hardware in the loop simulation training system based on HLA architecture
Authors: Wu Tao , Zou Qiubai , Wu Jixiang , Wang Hong , Zang Mengyang
Published: July 2021

A simulation training system is designed, which uses HLA architecture to realize the coordinated operation of network simulation, hardware in the loop access and electromagnetic computing. The system uses the standardized virtual real access interface to make the communication equipment simulator share the equipment parameters and interactive data with the network simulation model. VRNET is used for network simulation and interacts with the electromagnetic calculation module to form a complex electromagnetic environment. The system can be used in communication simulation training, electromagnetic interference array analysis and other fields.
A wideband low phase noise VCO design
Authors: Cheng Ze , Zhang Dianwei , Li Weimin
Published: July 2021

A frequency synthesizer with high reliability and low noise was designed and manufactured by 0. 13um SiGe BICMOS process. The frequency synthesizer circuit is capable of generating 7. 5GHz-15GHz RF output signals (the entire VCO output band);The normalized phase noise of the frequency synthesizer reaches-230 dBC / Hz, and the VCO phase noise of the frequency synthesizer reaches-119dBC/Hz@1MHz at the oscillation frequency of 13GHz.