Table of contents

After successfully held for two consecutive years, the 2021 3rd International Conference on Electronic Engineering and Informatics (EEI 2021) was successfully held in Dali, China during June 18-20, 2021. EEI 2021 is to bring together innovative academics and industrial experts in the field of Electronic Engineering and Informatics to a common forum. The primary goal of the conference is to promote research and developmental activities in Electronic Engineering and Informatics, and another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. The conference will be held every year to make it an ideal platform for people to share views and experiences in Electronic Engineering and Informatics and related areas.

The conference model was divided into two sessions, including oral presentations and keynote speeches. In the first part, some scholars, whose submissions were selected as the excellent papers, were given 15 minutes to perform their oral presentations one by one. Then in the second part, keynote speakers were each allocated 30-45 minutes to hold their speeches. In this conference, we have invited Prof. Quanxin Zhu, from Hunan Normal University, China and Assoc. Prof. GHAMGEEN IZAT RASHED, from Wuhan University-School of Electrical Engineering and Automation to serve as our Conference Chairmen. And we were honored to invite 6 sophisticated keynote speakers to deliver keynote speeches during the conference. Prof. Yue Yang, from Nankai University, College of Electronic Information and Optical Engineering. He is engaged in basic and applied research in the fields of intelligent photonics, optical communication systems and networks, optical interconnection, detection and imaging display technologies, integrated photonics, optical fiber and free space optics. The next keynote speakers, Prof. Quanxin Zhu, from Hunan Normal University, China. His main research interests include Markov process, stability and control of stochastic systems. Prof. Philip T Moore, from School of Information Science and Engineering, Lanzhou University, China. The other keynote speakers as follow: Prof. Hiroshi Watanabe, from National Yang-Ming Chiao-Tung University/Dept. Electrical and Computer Engineering; Assoc.Prof. Kai-Sheng Chen, from National Central University, Taoyuan, Taiwan; Assoc. Prof. Anwar Ali, from Politecnico di Torino, Italy.

We are glad to share with you that we received lots of submissions from the conference and we selected a bunch of high-quality papers and compiled them into the proceedings after rigorously reviewed them. These papers feature following topics but are not limited to: Electronic Technology, Information and Communication. All the papers have been through rigorous review and process to meet the requirements of international publication standard.

We would like to thank the organization staff, the members of the program committees and reviewers. They have worked very hard in reviewing papers and making valuable suggestions for the authors to improve their work. We also would like to express our gratitude to the external reviewers, for providing extra help in the review process, and the authors for contributing their research result to the conference.

Lastly, we would like to warmly thank all the authors who, with their presentations and papers, generously contributed to the lively exchange of scientific information that is so vital to the endurance of scientific conferences of this kind.

The Committee of EEI 2021

List of Committee members are available in this pdf.

All conference organisers/editors are required to declare details about their peer review. Therefore, please provide the following information:

• Type of peer review: Double-blind

• Conference submission management system: AI Scholar System

• Number of submissions received: 185

• Number of submissions sent for review: 179

• Number of submissions accepted: 101

• Acceptance Rate (Number of Submissions Accepted/Number of Submissions Received X 100): 54.6%

• Average number of reviews per paper: 2

• Total number of reviewers involved: 60

• Any additional info on review process:

• Step 1. Each of selected paper will be reviewed by two/three professional experts in the related subject area.

• Step 2. Review Reports received from the experts will be judged by one of the editors either Review Reports are logical or not?

• Step 3. If not logical, then editor can assign new reviewer or can also judge at his/her own.

• Step 4. If logical, then Review Reports will be sent to authors to modify the manuscript accordingly.

• Step 5. Authors will be required to revise their papers according to the points raised.

• Step 6. Revised version will then be evaluated by the editor for the incorporation of the points raised by the reviewers.

• Step 7. Then the editor will send the revised manuscript to the reviewers again for re-evaluation.

• Step 8. If the reviewers approve the revise version of the manuscript, then will be accepted for publication.

• Contact person for queries:

Xuexia Ye

publication@keoaeic.org

AEIC Academic Exchange Information Centre

The signal generator has a wide range of applications in the fields of communication, measurement and control, navigation, radar, and medical treatment. At present, most of the signal generators in the laboratory are purchased precision instruments, which are not only expensive, but also can not fully perform their functions, resulting in a waste of resources [1]. Based on the analysis of the working principle of the existing signal generator, this paper takes the programmable DDS integrated chip as the core, and designs a sine wave and square wave signal generator that is simple in structure, high in accuracy, small in size, and suitable for laboratory requirements. The precision and error analysis are carried out on it. The signal generator is composed of a power supply system, a single-chip computer system, a DDS waveform generation module, an amplitude adjustment module, a square wave generation module, and a relay output module. A multiplier is used to multiply the sine signal and the analog signal of the single-chip microcomputer to achieve the purpose of amplitude modulation of the waveform. Compared with the general signal source, the signal generator has the advantages of small output signal frequency error, high resolution, full digital realization, easy integration, small size, light weight, convenient use, stable work, etc.

When a nurse uses a syringe pump to infuse the patient, the nurse needs to contact the patient several times at a close range. This article proposes a method to detect the infusion of the syringe pump to reduce the frequency of contact between the nurse and the patient and reduce the labour intensity of the nurse. Using machine vision technology, filter and Prewitt operator are combined to process the acquired syringe pump pictures to obtain the accurate liquid level position. The image is captured by an industrial camera. After grayscale processing and image filtering, the Prewitt edge detection algorithm is used to obtain a clear edge image, and then the corner detection algorithm and pixel coordinate display are used to detect the liquid level of the syringe without external auxiliary measuring equipment. After performing multiple tests on 26 different liquid level images of a 50ml syringe, the results show that proposed method is effective to measure the liquid level in a non-contact way. The test result shows that the relative error is When the scale is 2ml to 16ml, the relative error range is -66% to -0.63%. When the scale is 18ml to 50ml, the relative error range is -1.86% to -1.19%. Among the 26 pictures, the absolute error of 22 pictures is within ±1ml, and the absolute error of 19 pictures is within ±0.5ml.

At present, in terms of clinical temperature measurement in China, most hospitals use traditional mercury thermometers to obtain patient temperature data through human readings and records. In order to improve the work efficiency of medical staff and reduce the frequency of their contact with patients, machine vision is adopted. A scale recognition method of non-electronic thermometer based on image features is proposed. The reading data of clinical thermometers is calculated through pixels. The automatic reading record of the clinical thermometer is realized, and the relative error does not exceed 0.25% in the temperature range of 35.5 to 37.5°C, which has certain practical significance for the research in the field of intelligent medical treatment.

An LNA for 8∼12 GHz is proposed in this paper. The amplifier uses a GaAs process with cost-effective, E-mode HEMTs with gate widths of 0.25 µm and 0.45 µm. The three stages of the LNA are powered by dual power supplies, with a drain operating voltage of +3V and a gate operating voltage of +0.7V. The simulation results of the schematic diagram show that the noise factor of the low-noise amplifier is less than 2.5dB in the frequency range of 8-12GHz, the in-band gain is greater than 30dB, the gain flatness is ±1.5dB, the 1dB compression point is 7dbm, the VSWRs are less than -10dB, and the LNA is absolutely stable in the X-band.

Traditional low-frequency antennas have larger volume and higher energy consumption. These characteristics make the traditional antennas easy to be destroyed by the enemy and expensive to maintain. In this paper, a mechanical antenna based on triangular array of rotating permanent magnets is introduced, and a prototype is made according to the proposed theoretical assumptions. Different from the traditional electric antenna, the mechanical antenna adopts the way of motor driving the permanent magnet to rotate, which realizes the miniaturization of the low-frequency transmitting antenna. In this paper, the analytical model of the rotating magnetic dipole is presented. By comparing the simulation results and the experimental data with the theoretical calculation results, it is proved that the mechanical antenna based on the rotating permanent magnet array can emit low-frequency sinusoidal electromagnetic waves, which has a broad application prospect in the Ultra-Low-Frequency/Very-Low-Frequency (ULF/VLF) communication field.

The line spectrum detection method based on coherent power spectrum estimation is one of the important research directions of weak signal line spectrum detection. For the purpose of resolving the problem of phase compensation inaccurate introduced by limited frequency search accuracy with the existing coherent power spectral estimate method, a modified line spectrum detector is proposed. The zero padding is used to improve the line spectrum frequency search accuracy in discrete Fourier transform (DFT) for phase compensation calculations, thereby obtaining more accurate line spectrum frequencies and phase compensation, which further improves Line spectrum detection performance. The detection performances of three detections based on Welch's method, coherently averaged power spectral estimate(CAPSE) and modified method are compared each other by computer simulations. The results show modified line spectrum detection can obtain a gain of 2-3dB, which verifies the effectiveness of the modified method.

In electronic warfare, airborne multiple input multiple output (MIMO) radar must not only accurately detect the Angle of moving target, but also ensure the low interception performance of radar. In order to solve this problem, a low interception bistatic MIMO radar with improved coprime array is proposed in this paper. By expanding the coprime array of the bistatic MIMO radar, the array spacing is further expanded to form a sparse array, which reduces the hardware and software cost and improves the anti-jamming capability. In addition, based on the two-dimensional MUSIC algorithm to detect the Angle of the maneuvering target, Taylor expansion method is added to realize the Angle estimation under low SNR. The research results show that, compared with the joint DOD and DOA estimation in a bistatic MIMO radar, the improved method in this paper increases the estimation accuracy, reduces the computational cost of the algorithm, applies to low SNR environment, and ensures low interception performance.

With the rapid development of China's transportation, higher requirements are put forward for the handling capacity of traffic accidents. Therefore, it is of great practical significance to study the effective monitoring methods of high-speed traffic accidents for timely guiding the traffic and saving the lives of the injured. The VMD is used to decompose the vehicle vibration signal, and the cross-correlation coefficient is used as the index to screen the components, and the KICA algorithm is used to extract the components of the screened component matrix, so as to further eliminate the environmental noise. The signal is recombined by the denoised components to highlight the time-domain statistical characteristics of the signal. The feature vector based on time-domain statistical parameters is constructed, and the recognition model is built by using the support vector mechanism optimized by genetic algorithm. The experimental results show that the accuracy of the method for vehicle driving state can be 95.5%.

In order to discover in time the potential interference coupling relationship caused by the installation of multiple types of frequency-using equipment and antennas on an aircraft or spacecraft platform, and to improve the rationality and compatibility of the antenna layout. The antenna isolation must be simulated at the beginning of the aircraft or spacecraft platform design, and the antenna isolation must be tested before the antenna is installed. In this article, the simulation and test results of the real case show that the model construction error during simulation, the actual spatial attenuation, the actual diffraction attenuation, the actual occlusion factor and the test error during the test process have formed the preliminary error relationship between simulation results and test results.

Electrostatic potential testing is an important parameter for characterization of the electrostatic source. An electrostatic dynamic potential test device based on the principle of "signal virtual shielding-distributed parameter coverage" is proposed for the large sensor volume, complex signal processing and network transmission in current electrostatic dynamic potential tester. The problems of linear distortion and frequency response are solved. The basic principle of electrostatic dynamic potential test is introduced. The design requirements are defined.The hardware and software design and implementation process of electrostatic dynamic potential test device are described in detail. Finally the test verification and application of the device are given.

Conventional beamforming fail to derive the full-rank covariance matrix due to the existent of coherent interference in the spatial domain. Most of the existing methods suppress the correlation interference by sacrificing the degree of freedom (DOF). In this paper, we develop a new adaptive beamforming for coherent interference without the loss of DOF, and the process of this new algorithm is as follows. First, the steering vector of the interference signal is estimated through convex optimization. Then we estimate the interference signal power by decomposing the covariance matrix and reconstruct the interference plus noise covariance matrix (INCM). Finally, the array weights are obtained based on the maximum SNR criterion. The proposed method has no loss of DOF and the array gain is adjacent to the ideal value. The feasibility of the technique is proved by theoretical derivation, and the effectiveness of the method is also verified by numerical results.

Synthetic Aperture Microwave Radiometer (SAMR) can be carried on the satellite to realize the global large-scale measurement of ocean salinity and soil moisture. As a key component of SAMR, the multi-channel digital correlator has been introduced in this paper from three aspects: an improved method to implement multi-channel correlation, the correlator design and the test results of the correlator. The improved method which effectively reduces the FPGA resource utilization and system complexity is applied to the multi-channel digital correlator system which consists of three signal collectors and one signal processor. The design of multi-channel digital correlator can ensure the real-time signal sampling and processing of 144 ADC channels. The results demonstrate that the measurement accuracy of correlation coefficient can exceed 0.99.

In the process of transformer equipment operation and maintenance, power companies encounter some problems, including of unstructured text data difficult to use, full caliber data difficult to deeply integrate and shallow equipment knowledge application. Based on artificial intelligence technology such as semantic web, knowledge map, natural language processing, etc., this paper studies the key technologies of equipment intelligent service, and proposes a knowledge intelligent technology framework for transformer. This framework includes three components: unstructured text intelligent recognition and extraction, device centered device knowledge representation and storage, and device knowledge intelligent application.

Specific emitter identification is one of the important technologies of electronic countermeasures. The convolutional neural network (CNN) has a strong ability to process image classification. To solve the problem that the bispectral feature of the radiation source does not perform well in the specific emitter identification, this paper proposes a method of combining the two-dimensional bispectrum of the radiation source and CNN. In order to test the performance of the method, this article designed a semi-physical system to collect the radiation source signal. It is verified by experiments that this method has a 92.4% correct rate for identifying different radiation source signals. Compared with other algorithms that combine bispectral features, the proposed method has advantages in accuracy and complexity.

To correct installation errors of star sensors, we propose an error calibration method based on the measurement information from fine guidance sensors (FGS). This work established an extended Kalman filter model by using the measurement information of FGS as the observation to estimate position errors. Simulation experiments are presented to assess the effectiveness of the proposed star sensor calibration technique, and the results demonstrate the improved error estimation accuracy.

The single event effect brings great risks to spacecraft operating in special environments such as space. In response to this phenomenon, single-particle tests for evaluating its radiation performance are becoming more and more frequent. This article introduces a single event effect test system. The design method of the single event effect test system is introduced from the system architecture, test principle, and software and hardware design. The system is used for single event effect irradiation test research. And finally analyzed the experimental results.

An important feature of future spaceborne synthetic aperture radar (SAR) is the adoption of large mesh reflectors fed by arrays. The main advantage of this SAR sensor is the provision of large antenna apertures and reconfigurable feed excitation. A large deployable mesh-reflector antennas combinaed with feed arrays is designed for the application of spaceborne SAR on geosynchronous orbit. To decrease the transmit power of feed element and increase the flexibility, a large scale of two-dimensional feedarray is adopted. An approach based on defocused reflector is used to broaden the beams from feed element, so almost all the feed elements can participate in the pattern synthesis in the complete angular domain. This paper presents a new optimization method of the defocused reflector system. The method aims at getting high gain and low sidebobes by optimizing the reflector parameters together with the feed array. The differential evolution algorithm(DE) is used to get globally optimal solution. The performance of the reflector after optimization is computed to demonstrate the effective of the method presented.

This paper presents a wearable antenna for Wireless Body Area Network communication. A 3×3 array artificial magnetic conductor structure (AMC) is loaded at the bottom of the antenna to reduce the backward radiation and improve the antenna gain. The simulated results show that the antenna can completely meet the working requirements in the bent state. After the addition of AMC array, the maximum gain reaches 7.53 dB, and the SAR value of human tissue can be reduced by about 94%. In addition, we have also processed and tested the antenna. The measured results are in good agreement with the simulated results, and its working bandwidth includes the low-frequency band of the ISM frequency band for WBAN communication, which can meet the working requirements of the antenna.

An analytical method for electromagnetic scattering characteristics of complex unmanned aerial vehicle targets by using hybrid multilevel fast multipole algorithm (MLFMA)-physical optics (PO) and short-time fourier transformation (STFT) is proposed in this paper. By constructing accurate electromagnetic models of unmanned aerial vehicle (UAV) target with inlet, the aspect and polarization characteristics of radar cross section (RCS) and time-frequency representation (TFR) are studied. To validate the influence of the inlet, the monostatic and bistatic RCS at specific angles, RCS statistical characteristics and TFR correlation are simulated and compared. It is concluded that the inlet should be sufficiently considered to calculate the accurate scattering characteristics.

By analyzing the discontinuous character in time domain, a jamming suppression method is propose to counter Interrupted sampling reperter jamming(ISRJ, which is an effective coherent jamming to wide-band linear frequency modulation signal. The discontinuous character of ISRJ and the instantaneous frequency change rule after stretch is firstly analyzed. Secondly, by controlling the adjustment parameters, the generalized S transform is utilized to obtain the time-frequency grayscale image of received signal. Then, the grayscale image can be segmented by using genetic algorithm to construct a time-domain filter, and the time-domain filter can be used to extract the echo band without jamming signal. Finally, the extracted signal is used as compressed data to construct a compressed sensing minimization model, and the compressed sampling matching pursuit algorithm is used to reconstruct the target echo signal. Simulation shows that this method has good jamming suppression performance.

Because of friction and assembly clearance, the accuracy of traditional rigid parallel mechanism cannot be maintained for a long time. Compliant mechanism has the advantages of light weight, high precision and low wear. Combining the characteristics of the two mechanisms, this paper designs a series-parallel compliant manipulator structure, and studies its forward and backward kinematics. Finally, it uses MATLAB software to study its workspace. Motion analysis was carried out.

The condenser of 550kV RIP oil-gas bushings is in the solid structure of resin-epoxy impregnated paper(RIP), which has large difference with the oil-immersed one (OIP). Oil-gas bushings has compact configuration and heat conduction condition is harsh, while temperature distribution has direct relationship with bushings' long-term stable operation performance, so it's essential to carry out research in radial temperature within condenser during production of RIP oil-gas bushing prototype. In this paper, radial temperature distribution principle of bushing condenser under linear material conditions has been summarized by building electrothermal coupling theoretical model of bushing condenser. The model has been generalized by electro-thermal coupling finite element mode under nonlinear material conditions, and electrothermal coupling iterative computation process has also been proposed, then experimental measurement study in local temperature points of bushing condenser has been carried out. The study shows that plate model has advantages of high accuracy and simple form in calculating radial temperature distribution of bushing condenser; the hot-spot temperature of 550kV RIP oil-gas bushings is about 95°C which appears near the center conductor; radial temperature of bushings under nonlinear material conditions is lower than that under linear material conditions and the thermal breakdown voltage of condenser under rated current is 538kV which is higher than the maximum operation phase voltage. This paper provides theoretical foundation for radial temperature computation within RIP bushing condenser and has some reference value for the design of HVAC RIP bushings.

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.

In the research of the power cable anti-theft problem, the demand for high-precision positioning of the cable manhole cover is proposed. For this reason, a wireless sensor WSN node with ranging function is studied. The system uses the Stm32 chip as the MCU core, uses 433MH radio frequency signals and ultrasonic signals to implement a ranging circuit based on the TODA principle of arrival time difference, and sends data to the cloud server through the NB-IoT module to achieve the purpose of alarming. The system has the characteristics of good real-time performance and high positioning accuracy. It can be applied to the theft prevention of cable manhole covers, and can also be extended to the detection of indoor moving objects.

In order to study the damage effect of continuous laser on optical detectors, an equivalent experimental method of laser irradiated optical detectors was designed and constructed in the laboratory. The damage mechanism and phenomenon of the laser are analyzed through experiments, and the power density of the laser to the target and the size of the saturated spot on the surface of the detector are measured, and the corresponding relationship between the saturation of a single pixel of the detector and the power of the laser to the target is obtained, which reveals the influence of laser power on detection The influence law of the interference characteristic of the device. The experimental results show that under the condition that the diameter of the laser beam and the distance to the target are the same, as the power of the laser to the target increases, the saturated spot size of the detector (that is, the number of saturated pixels) increases, and the saturated spot size increases with the power within the error range. The relationship is approximately linear; for a typical optical detector, the laser power at which the pixels are disturbed by saturation is a fixed value. Increasing the laser power can increase the number of saturated pixels, and the area disturbed by laser saturation is further expanded.

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.

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.

In order to maximize the multiple-beam performance in a specific service area, a new optimization design method of shaped single-aperture single-feed multiple-beam antenna was proposed. The contradiction between the layout of satellite platform and the performance of specific service area was solved by comprehensively optimizing the reflector and feed position. As the reflector surface and the feed position were taken as optimization variables, the objective function was constructed by the gain and XPD in the service area, and then the artificial bee colony algorithm was used for optimization, so as to obtain the optimal performance of the whole service area. Finally, an optimization design example was given, and the simulation results indicated the effectiveness of the optimization method.

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.

Among many important equipment and instruments, in order to obtain a stable HVDC output, a high voltage multiplier power supply is usually used. With the development of science and technology, higher requirements are put forward for the performance parameters of high voltage multiplier power supply. In this paper, the core part of the high voltage multiplier power supply - voltage doubling circuit as the focus of research. Firstly, the principle of various voltage doubling circuits are analyzed, the steady state analytical formula under ideal state is obtained and their advantages and disadvantages are analyzed. According to the above analysis and comparison, this paper proposes that the topological structure of the voltage doubling circuit for the 500kV HV power supply is the symmetrical CW multiplier circuit. Then the ripple expression of the symmetrical CW multiplier is deduced, the reason of voltage sag is analyzed, and the calculation expression is given. Finally, a simulation model of the voltage doubling circuit of the HV multiplier power supply was built in ANSYS Simplorer. The validity of the analytical design is verified by experimental simulation.

Small current source module has low accuracy, big ripple and cannot be used for multi-channel expansion and isolated output. In view of this, a high-precision isolated current source module for multi-channel expansion is designed. The current source module consists of an isolated power supply circuit, an A/D conversion circuit, a linear current stabilizer circuit, and a digital isolation circuit. MCU can implement control of the module through only three ordinary IO ports, and one MCU can simultaneously control multiple current source modules to complete multi-channel isolated output. The output accuracy of each channel can reach a level of 0.001mA.

With the development of chip design technology, the complexity of the chip is getting bigger and bigger, and various IP (Intellectual Property) is integrated to form SoC (System on Chip). In order to improve the efficiency of designing SoC, IP reuse technology is often used, so the development of IP has a wide range of significance and use value. The SPI bus is a bus protocol often used in chip communication and has many application scenarios. Therefore, this research mainly develops the SPI bus IP. During the development process, the SPI bus design is carried out, then based on the UVM verification methodology the designed IP has been functionally verified, and finally, a fully functional SPI bus design is obtained.

In recent years, computer vision technology in the field of science and technology has been stubbornly high, making a lot of scientific and technical personnel involved in the research gate technology. Depth learning, artificial intelligence in recent years, often around our ears, vision technology is occupying a place in the field of artificial intelligence. This paper mainly studies the recognition and localization of robots based on vision. The mobile robot is detected by the background difference method, and the background model is established by the Gaussian background modeling. Recognizing the color and number tags on the robot for matching the robot's features. Real-time positioning of the robot under the premise of the same background.

The complexity of research and development process and the diversity of research methods of intelligent connected vehicles increase the difficulty of establishing, integrating and verifying of virtual simulation experiments. In order to solve the problem of how to quantify the impact of weather environment changes on the virtual lidar in the simulation experiment, this paper first uses the derivation of the lidar range model and the analysis of the influence of atmospheric attenuation on the lidar range. Then, with the help of the empirical model of the attenuation coefficient of rain, snow, and haze, the curve fitting method is used to simplify the influence relationship so that it can be applied to the virtual simulation software of autonomous driving. Finally, the scene verification and evaluation of the quantification method of the lidar in the virtual environment affected by weather changes are carried out. The results show that this method effectively improves the restoration degree of the virtual simulation sensor while ensuring the calculation efficiency.

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.

A model based on multidimensional features and GRNN was designed for electronic nose (eNose) in the paper. It can be applied to distinguish hepatocellular carcinoma from normal controls. Hepatocellular carcinoma patients have altered composition of exhaled gas due to abnormal metabolism. Thus, we can detect them by the exhaled gas. In the paper, the exhaled gas signals of hepatocellular carcinoma patients and health controls were first collected with eNose. And then the features were extracted and the multidimensional combined features were achieved. Furthermore, the PCA method was applied to optimize the features. Next, the classification model based on GRNN was constructed for training and generalization ability testing. Finally, the constructed model was adopted to predict the test and the performance was calculated. The result shows that, with the limited training set, the performance of the GRNN model is better than the BPNN model. The prediction accuracy could reach to 91.3%. Therefore, the proposed model is well suited for the classification detection with small training set and this will contribute to the study of the practical application of the eNose in the clinic.

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.

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.

Based on the Australian wildfire in 2019, this paper obtains the grid risk coefficient through the cellular automata model, and linear model and uses the cluster gravity method to select the location of EOC. Finally it gives the two-layer interconnection model constructed by SSA UAV and radio repeater UAV and the UAV system model of UAV two-layer interconnection coverage planning. It aims to create a safe and economic disaster monitoring system. The security, that is, the connectivity coverage rate of UAV system and the economy, that is, the total number of UAVs, are taken as the objective functions. The constraints are the minimum standard limit of coverage rate and connectivity rate, the limit of divided area, the limit of divided area inspection cycle, and the limit of the relationship between the built-in battery consumption and the number of on-the-job UAVs. According to the PSO-ACO fusion algorithm, the optimal number and combination of the two types of UAVs are obtained. The adaptability of the model to extreme fire events in the next ten years is verified by grey weight Markov prediction.

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.

Under the background that electronic products have been developing in the direction of being smaller, lighter and cheaper, the packaging of chip components has also been continuously improved. Fan-out panel-level package (FOPLP) is one of the latest development trends in microelectronics package, which can achieve higher productivity and lower costs. A planar toroidal spiral transformer is designed based on Fan-Out Panel Level Package technology. The transformer is constructed by two RDL layers provided by the packaging process. The size of the proposed transformer is 434um×434um. The simulated primary and secondary inductance is 2.5nH and 2.5nH respectively. The coupling factor of the transformer is 0.845. The quality factor of the transformer is higher than 800 during the entire working frequency range. The self-resonant frequency of the present transformer is 20 GHz. Compared to the on-chip counterpart, the transformer designed based on Fan-Out Panel Level Package technology can achieve higher coupling factor and quality factor. Therefore, the proposed transformer can save chip size and reduce the cost through avoiding using area hungry passive on chip transformer.

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.

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.

In this paper, we propose and demonstrate an indoor positioning scheme based on phase ranging with Bluetooth low energy (BLE). It is to deal with the contradiction between the cost and accuracy of today's indoor positioning system. The experiment is based on BLE multi-carrier phase ranging, and the DA14695 BLE module from Dialog Semiconductor is selected as the experimental hardware module. The linearized pseudo range observation equation and least square estimation are used to construct a positioning platform to verify its positioning effect. The experimental results show that the indoor positioning method based on BLE phase-based ranging has high positioning accuracy, and in view of the low-power and low-cost advantages of BLE itself, it shows that this indoor positioning scheme is feasible and has further research value.

Researching an electric energy router and analyzing the control and operation characteristics are of significant importance for bi-high power system. In this study, a multi-modal two-level coordinated control strategy of multi-port electric energy router is proposed to achieve fast and flexible regulation of power flow. a prototype of multi-port energy router is trial-produced with an energy storage system, a sending-end power grid and a receiving-end power grid. Furthermore, a comprehensive dynamic test for the prototype of multi-port energy router is completed. The results show that the dynamic performance of the multi-port energy router in power step test is found to conform to the test standard. The charging and discharging modes of the energy storage unit under multi-modal control strategy are switched correctly. During the energy exchange process, multi-port AC/DC voltage operates stably. It can be applied to multi-port, multi-cascade, multi-flow distribution network.

As a new technology, functional safety technology has been widely used in escalators. Functional safety inspection is the basis of escalator maintenance operations. This paper introduces the distribution and application of escalator functional safety, proposes a functional safety inspection method for escalator functional safety based on functional safety theory, and constructs a technical framework for escalator functional safety maintenance operation guidance, including data integrity, working environment, and daily inspection, Sensors, cabinets and control panels, wires and connectors, etc. and inspection methods. On this basis, taking the overspeed inspection of the escalator as an example, the escalator function safety maintenance operation guidance technology is explained.

In this paper, we investigate the acceleration properties of fine-grain parallel large-scale MOSFET circuit simulation using multi-core CPU. Several CPU have been tested for understanding maximum possible accelerations. A parallel circuit simulator, MOSTIME, is used to simulate experimental circuits. Performing tests on CPU and MOSTIME, we find that more advanced accelerations on large-scale fine-grain parallel circuit simulation would rely on time-saving software techniques and GPU (Graphic Processing Unit) cards. A newly implemented time-saving technique for MOSTIME has been tested to show promising effects.

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.

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.

By analyzing a variety of traditional wave spectrum models, combining the actual wavelength and wave surface displacement to compare the electromagnetic field propagation process, the P-M (Pierson-Moscowitz) spectrum is used to theoretically derive the electrical characteristics of the rough sea surface and its influence on the propagation process of high-frequency electromagnetic waves. Based on the bilinear superposition algorithm and Matlab numerical calculation software, the electrical characteristics of rough seas and the theoretical results of electromagnetic wave propagation in rough seas are simulated and verified. The results show that the modeling of rough sea surface based on P-M spectrum has the advantages of high reducibility and stable frequency spectrum.

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%.

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.

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.

In visual object tracking, robust scale estimation is always a challenging problem. Because of the fast movement of the target, the background, the relative distance and relative azimuth angle between the target and the background usually change greatly. However, traditional correlation filtering tracking method cannot track the target accurately or even lose the target when the target scale and aspect ratio change. To address these problems, this paper adds two independent filters for the length and width scale estimation to complete the adaptive tracking on the basis of the translation filter. The experimental results in the public data set show that: compared with the original trackers, our method improves the tracking accuracy significantly, and meets the needs of real-time target tracking.

With the continuous development of the power system and the rapid growth of the scale of the power grid, the information that needs to be monitored, inquired, and maintained in the power grid dispatching system is increasing. The traditional way of understanding the realtime operation status of the power grid through dispatching workstations is increasingly unable to meet the requirements of modern power grids for monitoring, operation and maintenance in real-time, timeliness, and anywhere. In the face of such a huge business demand market, how to develop mobile applications that meet customer needs with minimal investment in resources and efficient development efficiency has become our research direction. This paper discusses a release management technology of the mobile application for electricity dispatching that meets the above requirements. This technology adopts the design mode of "shared application + personalized page", without too much intervention by developers, Users can edit and compress their own personalized pages, then upload to the version server and update the main page on the mobile devices themselves; this technology improves the efficiency of opening graphics file and the response time of operation through caching the graphic files and only refreshing the operation area mechanisms; through the publish/subscribe message bus mechanism, the hot update effect of the main page is realized; the service is restored through one-click, which provides users with more operating space.

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.

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.

Attribute-based access control is an effective cryptographic mechanism that allows a data owner to perform attribute-level access control over users' access capabilities. In the application background of blockchain, it is urgent to use attribute-based access control to solve a series of security problems. Although there exist several similar schemes, they do not consider attribute revocation. By adopting the attribute revocation technique based on binary trees, we extended Waters' ciphertext policy attribute-based encryption (CP-ABE) scheme into a revocable CP-ABE (RCP-ABE) scheme. By combining our RCP-ABE with blockchain, we constructed a revocable attribute-based access control system. The new system supports expressive access control policies and allows the attribute authority to revoke users' attributes or part of their attributes. The security analysis shows that the new system satisfies several ideal properties, i.e., forward security, backward security, confidentiality, and integrity.

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.

In order to realize long-term, continuous, stable and reliable operation of wheeled robot without intervention, the principle of autonomous charging technology is analyzed, and the common and key technologies of wheeled robot autonomous charging are introduced. Aiming at the disadvantages of traditional autonomous charging system. A robot automatic charging docking method based on the combination of infrared radiation sensor, photoelectric tube tracking sensor and ultrasonic distance sensor is adopted. through the data fusion of Kalman filter algorithm for the distance value obtained by ultrasonic sensor, a high precision distance estimation value is obtained, which makes up for the lack of measurement accuracy in traditional infrared method. Experimental tests show that the docking accuracy between robot and charging seat is high. The docking is completed well.

Community detection is one of the most important attributes to reveal the hidden structure of complex networks. The way of community detection based on the intelligent optimization algorithm has been widely used. Aiming at the initialization problem of the solution, the paper uses the density peaks clustering (DPC) algorithm to obtain a stable and high-quality solution. Aiming at the search strategy, state transition simulated annealing algorithm (STASA) is proposed. On the basis, three types of operators are designed: vertex replacement operator, community fusion operator and cross mutation are designed. In the initial optimization stage, the vertex substitution operator is used to generate diverse solution. The community fusion operator speeds up the optimization in a certain sense. The introduction of the cross mutation operator in the later optimization stage is only suitable for high-quality solution and enhances the local search ability of the algorithm. Finally, the experimental results on the GN benchmark and the real-world networks show that the algorithm is superior to other classic community detection algorithms in terms of stability and accuracy.

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.

In adaptive systems, the least mean square error (LMS) adaptive algorithm is widely used. The variable step size LMS algorithm (SVSLMS) based on the Sigmoid function has greatly improved the convergence speed, and the normalized LMS algorithm is stable Sexual performance has certain advantages. Therefore, improvement is made on this basis, the SVSLMS algorithm is normalized, and the iteration speed is increased by changing the iteration factor, and the stability of the algorithm is also improved. This paper uses MATLAB simulation tools to verify the superiority of the new algorithm. Finally, the improved algorithm is applied to beamforming to estimate the azimuth of arrival of the simulated sound source signal at the partial discharge point of the submarine power cable.

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.

Optical tracking of small and weak targets in space, has problems such as a large and unknown number of targets, dense clutter, close measurement of neighboring targets, and false detection and missed detection. In this paper, a Gaussian mixture cardinalized probability hypothesis density (GM-CPHD) filtering algorithm assisted by luminance information is proposed. By establishing the luminance likelihood function, the luminance information is introduced into the CPHD filtering process, and the Gaussian mixture implementation method is given. The simulation results indicate that the proposed algorithm can effectively adapt to the dense clutter environment, and compared with the traditional GM-CPHD filtering algorithm, its tracking accuracy for multiple targets is significantly improved.

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.

There are a large number of similar or even identical webpages on the Internet. These webpages will cause unnecessary loss of network resources, including waste of storage space, decreased web search speed, and decreased user experience. And some malicious mirror websites will become tools for criminals to carry out illegal activities such as phishing attacks. In this paper, the autours analyzed the mainstream text similarity detection algorithms and webpage deduplication algorithms, and proposed an improved webpage deduplication algorithm based on Simhash. The algorithm converts the text collection into Simhash fingerprints for storage through mapping, and calculates the similarity of the two fingerprints through Hamming distance, thereby obtaining the similarity of the webpage. Experiments show that the algorithm proposed in this paper has a higher accuracy rate and recall rate, and can be better applied to the identification and detection of malicious mirror websites.

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.

In the large-capacity FBG sensor network demodulation system, the process of collecting the light source is often accompanied by noise interference. Signal denoising is an important factor that affects the accurate demodulation of the FBG sensor system. Aiming at the problem of constant deviation of soft and hard threshold functions in denoising of traditional wavelet threshold algorithm and the shortcomings of modal aliasing easily in empirical mode decomposition, a modified semi-soft threshold-VMD denoising algorithm is proposed. The simulation results show that the function in this paper is better than the traditional threshold function in continuity and signal reduction degree, and has achieved good results.

In order to solve the problems of the traditional GNSS multipath signal simulation methods, such as the complexity increases linearly with the number of multipath signals, inconvenient parameter updating and long operation time, a GPU based GNSS multipath signal parallel simulation method is proposed. Based on Farrow variable fractional delay filter, an independent parallel computing model of multi-channel filter coefficients is established, and a large number of floating-point units in GPU are used for parallel computing and filtering. Aiming at the performance bottleneck of this method, the optimization strategy of asynchronous parallel execution is given. The computer simulation results show that the complexity and operation time of the proposed method will not increase with the increase of the number of multipath signals. For the GNSS direct signal with sampling rate of 75MHz and time length of 1s, the maximum time consuming of the proposed method to generate 50 ∼ 1000 multipath signals is 158.6ms. Compared with the method of serial simulation on CPU, the proposed method speeds up to about 9.5 times, and the real-time simulation of multipath signals in complex environment can be realized.

Port logistics, as an important carrier supporting the trade exchanges of countries around the world, has a positive driving effect on economic growth. This paper adopts the DEA-Malmquist index evaluation model and takes the panel data of my country's top ten coastal port logistics from 2012 to 2019 as the research object for empirical research. By constructing a reasonable evaluation index system, using DEA method to conduct static analysis of port logistics efficiency, and using Malmquist index method to conduct dynamic analysis of port logistics efficiency. Finally, according to the results of the logistics efficiency evaluation, targeted countermeasures and suggestions are put forward to provide reference for the improvement of my country's port logistics efficiency.

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 characteristics of terahertz communication technology, such as large capacity, high speed and high security, make it stand out among many wireless communication technologies. For future space communication application scenarios, the link performance and beam pointing accuracy of the terahertz communication system were analyzed. The beam adjustment angular acceleration index were analyzed through STK.

As an important part of modern machinery, gears are safe and reliable directly related to the normal operation of the mechanical system, and when the gears are abnormal, it is very important to carry out fault diagnosis in time and effectively. Wavelet transform is effective in signal time-frequency analysis and fault diagnosis. Based on the wavelet analysis method, this paper first filters and de-noises the vibration signal data of a certain type of gear, and then performs fault analysis. Time-frequency analysis of time-domain signals has a better effect on gear fault diagnosis.

With the aim at improving the efficiency of satellite communication spectrum utilization, this paper proposes a non-continuous orthogonal frequency division multiplexing (NC-OFDM) satellite communication model based on convolutional code and LDPC code. We further analyze the bit error rate performance of the NC-OFDM system and evaluates the interference of the authorized system. Simulation experiment results show that NC-OFDM model can significantly improve the spectrum utilization of satellite communication, which can achieve spectrum compatibility with authorized users by adopting adaptive channel access and spectrum sensing technologies.

An improved multi-target tracking algorithm for automotive radar is proposed in this paper. In the application of automotive radar, in addition to the motion generated by the target maneuver, the maneuver of the radar-equipped vehicle will also cause the target to move relative to the radar. A single motion model for the target cannot accurately describe the motion state of the target relative to the radar. To solve the above problems, the nonlinear state equations of various motion models and their process noise covariance matrix are derived, and the Interacting Multiple Model (IMM) algorithm, the Joint Probabilistic Data Association (JPDA) algorithm and the Unscented Kalman Filter with Doppler measurement (DUKF) are combined. At the same time, the correlation coefficient of range measurement error and velocity measurement error of Frequency Modulated Continuous Wave (FMCW) radar is derived, and the relationship between it and FMCW radar parameters is studied. By simulation, its influence on target tracking is assessed, final results indicate the reference value for the application of automotive radar in intelligent driving.

In view of the data problems restricting the joint intelligent simulation, this paper constructs a data classification system. By mining and sorting the data, rules and models in cases and experiences, and combining with the basic data and ability data of the relevant system simulation model, it carries on the digital and systematic annotation, constructs the conceptual model, establishes the segmentation and part of speech standards, and adopts the methods of concept mining, attribute mining and instance mining. The data system of joint intelligent simulation is established by mining and instance mapping, and the multi-layer logical template and intelligent matching rules are used to solve the data problems of joint intelligent simulation.

This paper introduces the technical characteristics and end-to-end typical application systems of NB-IoT, puts forward the overall network architecture of NB-IoT. Based on the development status of the industry, the network deployment scheme and relevant development suggestions are proposed, providing reference for the innovative development and commercial implementation of 5G IoT in radio and television industry.

Convolutional neural network (CNN) is widely used in Natural Language Processing (NLP) and has achieved relatively good results. Since the convolutional layer of CNN can be initialized by encoding important semantic features, CNN can extract important semantic features in the convolutional layer. The pooling layer of CNN uses the feature of max-pooling to filter the features, but it does not consider the key information in the sentence and the context semantic information in the text. Therefore, a novel neural network algorithm combining with the attention mechanism and the pooling layer is proposed in this paper to make the model pay attention to the keywords in the sentence and automatically maintain the most meaningful text message, thereby improving the performance of text classification. Our paper uses important information features to initialize the convolution filter so that the model can notice the important semantic features. The resulting feature is enhanced by combining the attention mechanism in the pooling layer, so that the model can maintain the important information features of the text. Experiments show that the proposed model achieves excellent results for multiple text classification tasks, including sentiment classification and topic classification.

Through the simulation modeling of the generalized sidelobe cancellation system, the influence of the interference signal and expected signal at different incident angles on the system is analyzed. The results show that the cancellation ratio is affected by the expected signal, the interference signal and the original beam pattern, and the expected signal loss factor is affected by the angle of incidence of the expected signal. At the same time, the influence of the angle deviation of the interference signal on the system is simulated, and the result shows that the angle deviation of the cancellation ratio is very sensitive to the angle deviation from the beginning to the later.

Compared with the traditional pedestrian detection technology, the pedestrian detection technology based on deep learning has achieved overwhelming advantages. However, due to the large scale of deep convolution network, the demand for dedicated processor limits the popularization of pedestrian detection system. To solve these problems, this paper proposes a deep convolution network model with moderate network scale, which improves the universality of the detection model on the premise of ensuring the detection accuracy. Based on the low dimensional shallow convolution neural network, the optimal network structure is found from three aspects of network layer number, sensor field size and characteristic graph, and the final network parameters are determined by guiding experimental evaluation. The pedestrian image to be detected is input into the above network model, and the pedestrian detection result is obtained. The pedestrian detection results on several popular pedestrian databases such as Daimler, MIT and INRIA show that the network structure designed in this paper not only has moderate network size, but also has good detection performance. Cross experiments also verify the robustness and generalization of the algorithm. The work of this article is funded by the undergraduate training program for innovation and entrepreneurship (202010373050, 202010373051, 202010373046).

The linear frequency modulation signal is widely used in radar, sonar detection and communications as a typical non-stationary signal. In order to better analyse the linear frequency modulation signal received by the receiver, it is necessary to perform denoising processing on the received signal. As a new type of time-frequency analysis method, empirical mode decomposition algorithm is very suitable for processing non-stationary signals. However, due to the large bandwidth of the linear frequency modulation signal, more noise will be retained when the traditional empirical mode decomposition algorithm is used to denoise the linear frequency modulation signal. Under above background, this paper proposes a denoising method based on the window function and the empirical mode decomposition to achieve further denoising of the linear frequency modulation signal. According to the simulation results, when the signal-to-noise ratio is about 0dB, the method proposed in this paper improves the signal-to-noise ratio by about 1.5dB compared with the traditional empirical modal decomposition algorithm.

Conventional direction-of-arrival (DOA) estimations perform poorly in coherent signals due to the rank loss of spatial covariance matrix, and most of the existing methods solve the problem at the expense of Degree of Freedom (DOF) or accuracy. In this paper, a novel DOA estimation technique for coherent signal is presented based on virtual array. The method comprises three steps: Firstly, the covariance matrix is generated according to the output signals of the array. Then, the first row and first column are selected from the matrix according to the data model of each element of the covariance matrix, which can be regarded as a uniform and continuous single snapshot signal of virtual array. Finally, the forward and backward spatial smoothing is used to achieve decorrelation of the single snapshot signal of the virtual array element. The proposed method has no loss of DOF and maintains high accuracy for low signal-to-noise ratio (SNR) conditions. The feasibility of the proposed method is proved by theoretical derivation, and its effectiveness is also verified by numerical results.

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.

The similarity measurement of high-dimensional data is an important research content in data mining and other fields. Aiming at the shortcomings of the traditional similarity measurement algorithms, a new measurement algorithm is proposed. The results of comparison with traditional algorithms show that new algorithm can quantitatively and intuitively reflect the similarity of two sets of high-dimensional data, and has strong adaptability and superiority.

It is easy to understand that presentation maintenance can prolong the lifecycle of the equipment. Due to the lack of an efficient maintenance management platform for Printing Press equipment, we develop a cloud-based platform to record routine inspections, to notify management information, and to remind replacement with a monitoring analysis model. In that case, the producer of the printing press could master the data of prevention maintenance and provide better after-sales service. The platform consists of equipment data sensing analysis workflow, routine inspection, and equipment warning/failure detection. This enables effectively extending the service life of the equipment, reducing the maintenance costs of equipment, and providing on-demand access to computing resources. In the future, new artificial intelligence models could be added to provide smarter manufacturing solutions.

Electrostatic charging and discharging have an important impact on the safety and reliability of electronic products, and human static electricity is one of the important sources of electrostatic hazards in the production and use of electronic products. In order to analyze the electrification law of human walking and explore the electrostatic protection measures of human body, the theoretical model of human walking electrification is further deduced on the basis of previous studies. The electrification law of human walking under typical conditions is analyzed, and the influence of maximum foot lifting height on potential is studied. When the maximum lifting height is small, the potential oscillation approximately conforms to the sine law, and with the increase of the maximum lifting height, the sine law is no longer satisfied. When the maximum foot lifting height is small, the actual peak potential cannot reach the saturation potential. Therefore, on the basis of taking electrostatic protection measures, reducing the foot lifting height when walking is helpful to prevent electrostatic hazards.

Harris corner detection algorithm has been widely used in many computer vision allocations. However, it has low efficiency and accuracy, poor noise immunity and needs to set an artificial threshold. In this paper, an improved algorithm based on Canny edge detection and gray difference preprocessing is proposed. Firstly, Canny edge detection and gray difference preprocessing are used for corner prescreening to improve the detection efficiency, anti-noise, and rotation invariance. Secondly, non-maximum suppression is applied to the screened corners to reduce the number of false corners. Finally, the average of adjacent points method is used to solve the problem of corner cluster, and the detection results are compared the measurement accuracy is improved to sub-pixel level. Experimental results indicate that the proposed algorithm can accurately extract the corners in the image and remove the false corners and corner clusters. It achieves superior performance than existing methods.

Some studies have shown that haze not only poses a threat to people's health, but also affects the secretion of human hormones, making people depressed and endangering mental health. Microblog has the advantages of short content, rapid communication and convenient interaction. When the haze comes, a large number of topic microblogs related to the haze will be generated. Mining the topics of concern and psychological reactions contained in these microblogs is helpful for resource allocation and public opinion publicity in the case of haze. At present, the research of microblog topic mining in haze situation only involves a single research area, and few studies discuss the spatial differences of different regions. Based on this, this study collected the microblog data of seven provincial capitals in the severe haze areas in 2017, and used the community-based co word network method to complete a series of experimental steps, such as keyword extraction, co-occurrence matrix construction, co-word network construction and topic community detection. On this basis, we detected the topic community in the microblog data set, and analyzed the horizontal differences of topics in different cities. The results show that different cities have not only the same but also different concerns about haze. The results can provide theoretical guidance for the healthy development of cities.

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.

With the rapid development of information technology, single sign-on authentication systems have been adopted by organizations to protect their information management systems and other service platforms. With the single sign-on method, users just log in the authentication systems once to access all the information in systems, which are more convenience, but accompanied by user permissions vulnerabilities and information security risks. Users' browsing behaviors reflect the users' usage habits, purposes, and work contents. Risks of information leakage can be reduced by auditing the users' browsing behaviors. After analyzing the web logs of several service systems, we designed a user behavior audit system based on the Spark computing engine, which takes the real-time web log file as the data set. A possible preprocessing method for real-time web log data stream is proposed to extract users' web session data. we used the Spark computing engine and the corresponding analysis to mine users' behavior patterns. The online real-time detection and offline detection of user behavior are realized, and users are divided into three levels: normal, abnormal, and risky. The system administrators or auditors can view the calculation results of each stage online, manage the parameter configuration of the algorithm online, and adjust the user's access right in real-time.

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.

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.

The search requirements of users are usually vague and unclear, and the traditional keyword query method is difficult to obtain satisfactory query results. Therefore, the semantic query expansion technology uses semantic information to modify and extend the initial search requirements of users, to obtain more comprehensive and accurate query results. However, the construction cost of the extended query graph is high, and the existing research is difficult to adjust and optimize the user's query demand in time, resulting in a poor query effect. To solve the above problems, this paper proposes a semantic expansion method based on pay-as-you-go fashion for graph model: Firstly, the initial query graph is constructed according to the user's search requirements, and the semantic similarities between the search requirements and knowledge bases are calculated; Then, the extended sets of attribute-values and edges are generate by sorting the similarity value in descending order; Finally, all or part of the elements in the extended set are combined to generate the extended query graph. This method can dynamically adjust and optimize the initial query based on the relevant semantic information in time, and improve the query efficiency and effect.

Ship radiated noise recognition is one of the basic problems in underwater target recognition. To identify the number of ship types according to ship noise, the ship scale can be predicted in advance and the next step of processing can be carried out. Aiming at the problem of identifying the number of ship types based on ship radiated noise, a RK-Means (Recurrent K-Means) is proposed in this paper. According to the short-time energy characteristics of the target signal, the dimension of the feature data is reduced by principal component analysis; The K-Means algorithm is used to cluster and identify the dimension-reduced signals through cyclic iteration; A single connection algorithm is used to determine the appropriate clustering center, which reduces the similarity value of data objects between classes and makes the difference value between classes large. Furthermore, the algorithm can automatically determine the K value, which is the number of ship types. Verified by the experimental data, compared with the contrast algorithm, the K-value recognition result and clustering effect of the RK-Means clustering algorithm are better.

In order to solve the problem of spectrum fragment in elastic optical networks, a spectrum reconstruction algorithm based on resource partition allocation is proposed in this paper. Services are classified according to the different frequency of the services that occupy different number of frequency slots in the networks. Region division of spectrum resources is made according to the type of services and services are allocated in the corresponding spectrum partitions. When defragmenting in the networks, we reconstruct the spectrum for different regions with comprehensively considering the factors in time domain and frequency domain, integrating current resources and preventing the generation of spectrum fragment in the future. Simulation results show that the algorithm can reduce the degree of network fragmentation and reduce traffic blocking.

With the deepening of energy revolution, smart hydropower station (SHS) has become the demand and inevitable direction of technological revolution and upgrading development of hydropower industry in China. Under the background of power Internet of Things and SHS, the massive sampled data perceived by intelligent terminals of SHS poses a major challenge to the traditional cloud computing centralized processing mode. As an important supplement to cloud computing, edge computing has received extensive attention from the power system. According to the complementarity between edge computing and cloud computing, this paper proposes a cloud-edge collaborative framework based on the introduction of SHS. Secondly, orienting the application in SHS, the key technologies of cloud-edge collaborative are discussed. Finally, the solutions based on cloud-edge collaborative for two typical application are discussed.

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.

Modulation recognition of radar signals is an important part of modern electronic intelligence reconnaissance and electronic support systems. In this paper, to solve the problem of low recognition accuracy and low noise resistance of radar signals under low signal-to-noise ratio(SNR), a recognition method based on variational mode decomposition(VMD) and bispectrum feature extraction is proposed. Based on the feature that bispectrum can suppress Gaussian noise, the feasibility of signals modulation recognition under low SNR is analyzed and the noise item is introduced. Due to the interference of noise item, the noise suppression effect of bispectrum is worse under 0dB. An improved VMD algorithm based on artificial bee colony(ABC) algorithm optimization and envelope entropy evaluation is proposed to preprocess the signal to improve the SNR. Finally, we designed a convolution neural network(CNN) classifier to recognize signals of different modulation types. The simulation results show that this method has better noise resistance than traditional methods, and can effectively identify different types of signals under low SNR.

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.