bluuebunny/crossref_metadata_2025 huggingface dataset:
Defect detection of automotive injector valve seat based on feature fusion
Authors: Zhu Zonghong , Li Chungui
Published: August 2020

Automobile fuel injector seat is a device that injects gasoline into the automobile cylinder. It plays a very important role in the control of automobile fuel quantity. However, due to the small parts and susceptibility to processing technology, in the production process of automobile fuel injector seats, it is inevitable to leave scratches, defects, rust spots, white spots and other defects. This paper will use the depth detection technology to complete the flaw detection of the injector seat, the depth detection algorithm model Faster R-CNN is improved. Defect detection can be seen that when extracting features, the Faster R-CNN algorithm model only uses the features of the last layer of convolution output, and has a large loss and affects the effect of small target detection. In order to improve the detection ability and solve the problem of missing detection caused by multi-scale and small targets, we introduce the idea of multi feature fusion in the stage of feature network extraction, and compares the improved algorithm model with the original Faster R-CNN model on the data set of injector seat. It is found that the improved model can be better applied to the flaw detection of automobile injector seats.
Short-term wind power prediction based on nutrosophic clustering and GA-ELM
Authors: Ye Zijun , Ding Yunfei
Published: August 2020

Wind farm NWP data has regularity and difference, and making full use of the information contained in NWP data is the key to wind power prediction. A short-term forecasting method for wind power based on nutrosophic clustering and GA-ELM is proposed. Firstly, the wind farm NWP data is divided into several weather types by the Chinese wisdom clustering method, and then the GA-ELM model is established for different weather types. The Gaussian index method is used to classify the forecast data, and then the different types of forecast data are substituted into the corresponding model predictions. Taking a 14MW wind farm in Northeast China as an example, the experiment shows that the nutrosophic clustering method reduces the influence of boundary points and abnormal points on the clustering center. Compared with the traditional method, the method has higher precision and universality.
Design and analysis of intelligent retrieval system for drilling data and completion data based on cloud platform
Authors: Zhao Yifan , Wang Kuisheng , Chen Lianguo
Published: August 2020

In the context of the accelerating cloud platform construction in the oil industry, this paper solves the problem of difficulty in drilling and completion data retrieval by classifying and sorting drilling data and completion data to construct an intelligent retrieval model for drilling and completion data. Based on the cloud platform environment, this paper studies the method of constructing an retrieval system for drilling data and completion data through the microservice architecture. This system provides a unified retrieve page for structured data and unstructured data of drilling and completion operations. By using the ElasticSearch full-text search engine to build a retrieval model, it provides users with fast, efficient, and convenient comprehensive query and retrieval services, and lays a foundation for the intelligent construction of drilling and completion platforms.
Application Analysis of Computer Effect Drawing in Landscape Design
Authors: Xie Xuan
Published: August 2020

With the progress of modern science and technology, computers are gradually applied to various fields, greatly improving the efficiency of work, in which the effect drawing of landscape design is an example. In the design of landscape effect drawing, the designer makes a simple conception plan of the design drawing by observing the entity project, and then uses the computer to draw his own ideal effect drawing. Such landscape effect drawing integrates the designer’s design soul, not only let the expert understand deeply, but also make the layman have a good understanding. Therefore, this paper first describes the definition and function of computer effect drawing in landscape design, then analyzes the common software for drawing computer effect drawing in landscape design from four aspects, and finally expounds the four steps of drawing computer effect drawing in landscape design.
Wavelet Adaptive Control for Robotic Manipulator With Input Deadzone
Authors: Sun Yongfu , Zhao Dequan , Wang Yuchao
Published: August 2020

In this paper, the adaptive wavelet neural network (WNN) tracking control problem is investigated for robotic manipulator with input deadzone. The WNN is used to approximate the unknown nonlinear function and the derivative of virtual control in the system, which avoids the problem “explosion of complexity” in the traditional backsteppinng control methods, the requirement of input instruction signal is reduced. The robust term is designed to compensate the approximation errors of WNN and external disturbance. Since wavelet functions are used in WNN, its learning capability is precede to the traditional neural network for system identification. It is proved that the proposed controller can guarantee that all signals of the closed-loop system are uniformly ultimately bounded. Simulation results demonstrate the effectiveness of the proposed approach.
Study on Fast Response of Semiconductor Laser Driven by Impulse Current
Authors: Qing Shi , Gentai Shi , Tao Zhang , Zhongmin Xing
Published: August 2020

A simulation model based on single-mode rate equations of semiconductor laser and its typical parameters shows that, the photon stimulated emission rate at the early turn-on time of the semiconductor laser is increased with the increase of the injection current, and the corresponding rise time is reduced with the increase of injection current. However, for an output power is fixed semiconductor laser, increasing the injection current to reduce the rise time of the transmitted pulse leads to increase in temperature of semiconductor laser. We show that adding an impulse current in the front of the normal luminous pulse current can reduce the rise time of the transmitted pulse and ensure the stable output of the semiconductor laser. This method is verified by simulation and an experiment using PLTB450B semiconductor laser. The simulation and test results show that for an output power is fixed semiconductor laser, the rise time of the transmitted pulse can be reduced significantly by adding impulse current.
Design of Intelligent Levelling Control System for Grader
Authors: Xiong Z G , Liu Z , Wang H Y
Published: August 2020

For the problem of grader intelligent levelling control system with much uncertainty and serious nonlinearity, precise mathematical model based traditional Proportional Integral-Derivative (PID) controller cannot meet the requirements of angle control. In order to improve dynamic performances of grader intelligent levelling control system in the laser transmitter platform of laser sources positioning system based on dynamic triangle principle, the obliquity sensor to detect the angle of laser transmit platform, and angle sensor data processed based on the data fusion algorithm through federal Kalman fusion, which is compared with Kalman algorithm. And the Radial Basis Function (RBF) Neural Networks based PID control strategy is proposed for the grader level control in this paper. This method can identify the mathematical model of the grader levelling angle via the RBF neural networks, and then the PID parameters can be optimized automatically to accommodate the characteristic variation of the process. The simulation results show that the PID controller designed based on the RBF neural networks has good control performance on the steam generator level control.
EMC improvement of CAN bus in automotive bus
Authors: Huan LI , Qinzhu Wang
Published: August 2020

With the increase in the car above the electronic products, automotive interior complex and a wide range of electrical systems will produce all kinds of magnetic field, from the cause of EMC problems, from the perspective of traffic safety considerations, with the increase of automotive electronic components and lead to an increase in the complexity of the system, in order to eliminate all kinds of such electromagnetic fields, it will increase the cost of all kinds of unnecessary. The content of this paper is to improve the electromagnetic compatibility and working stability of the CAN bus in the automotive network system by improving the design of the system and routing rules.
Parasitic Effects Analysis of Bonding Wires Bonding Parameter of Intelligent Power Modules for Three-Phase Motor Control Applications
Authors: Wang Chunxing , Zheng Jiaxing , Wang Gongtang , Gao Wen , Hua Qing
Published: August 2020

Parasitic parameter analysis is the focus of intelligent power module switch performance research. This paper will utilize the model of 600V/30A intelligent power module and extract the part of circuit layout bonding wires parasitic parameter by Ansys Q3D Extractor, expedition the relationship between physical bonding parameter and parasitic parameter in the intelligent power module circuit. An exact three-phase circuit module of high voltage intelligent power module and bonding wires package module is established. Through Ansys Q3D Extractor, test a series of bonding parameters from the three-phase circuit layout module and extract the parasitic parameters of the bonding wires. The experimental results of the parasitic parameters are analysed and compared, and the influence degree of the bonding parameters on the parasitic parameters is discussed. An improved solution is proposed for the bonding wires of the intelligent power module to reduce the voltage spike that the MOSFET chip during the turn-off process.
A 5-13GHz Power Amplifier for UWB Applications in 40 nm CMOS Technology
Authors: Zhu Jie , Liu Zhangfa
Published: August 2020

A two-stage power amplifier using current multiplexing technology and resistor shunt feedback technology to flatten gain and expand bandwidth is designed in this paper. In this paper, the SMIC 40nm CMOS process is used. The power amplifier proposed works in the 5-13GHz frequency range, providing more than 10dB of the gain at the voltage of 1.0V, and has good input and output matching. The return loss is lower than -30dB. The stability factor Kf is maintained at about 1.1, and Bf is greater than 0. The peak power added efficiency of the power amplifier can reach 24%.
Differential filtering algorithm for robot welding seam image enhancement
Authors: Liu Ying , Huang Qingjiu , Sato Kentaro
Published: August 2020

The low resolution of the welding seam recognition image during robot welding will affect the welding accuracy, and the cost of high-resolution cameras is higher. Therefore, in this paper, the geometrical processing of the bilinear interpolation method for the welded seam pictures taken by the low-resolution camera was used to obtain a high-resolution image. This paper proposed a differential filtering algorithm based on Gaussian filtering and bilateral filtering, to eliminate the fine lines, noise and enhance the weld feature value for the obtained high-resolution image, thereby ensuring the welding accuracy. Finally, through the image processing experiment of increasing the 1.25 million pixel weld image to 5 million pixel weld accuracy, the effectiveness of the image enhancement method proposed in this paper was proved.
Speech Synthesis of Children’s Reading Based on CycleGAN Model
Authors: Jia Ning , Zheng Chunjun , Sun Wei
Published: August 2020

The generation of emotional speech is a challenging and widely applied research topic in the field of speech processing. Because the design method of effective speech feature expression and generation model directly affects the accuracy of emotional speech generation, it is difficult to find a general solution of emotional speech synthesis. In this paper, the CycleGAN model is used as the starting point, and the improved convolution neural network (CNN) model and identity mapping loss scheme are used to achieve effective timing information capture. At the same time, we learn the positive mapping and the reverse mapping to find the best matching design scheme, and retain the speech information in this process, without relying on other audio data. Experiments show that the emotional speech can be accurately recognized by comparing the speech emotion before and after the improvement on the speech corpus of children’s reading. By comparing with the common emotional speech generation model, the advantages of the model proposed in this paper are verified.
A precision pose measurement technique based on multi-cooperative logo
Authors: Guo JianPo , Wu PeiZhang , Wang WeiRu
Published: August 2020

The use of image recognition technology to complete the precise pose measurement of objects has always been a difficulty in the field of computer vision. This paper proposes a precision pose measurement technology based on multi-cooperation logo, which uses OpenCV and Aruco to complete the generation of cooperative logo. Through the uPnP algorithm to complete the relative pose detection of the camera and the cooperation logo, and then the precise pose measurement of the multi-cooperation sign is completed by Gaussian filtering and iteration of the nearest neighbor. Compared with the traditional positioning method, it has higher accuracy and robustness. This technology has important reference value in robot positioning.
Study on foundation selection and economy of 220kV four circuit narrow base steel tube tower
Authors: Yaning Ren , Lihuan Wang , Yantao Xie
Published: August 2020

Through the practice of a certain urban line project in Hebei Province, the common forms of steel tube tower foundation with narrow base are introduced, and make a comparison from the basic form, technical economy and other aspects, and recommend the foundation form suitable for the corresponding situation. It is expected to be a reference for the foundation design of steel tube tower with narrow foundation.
Research on JOB SHOP Scheduling Problem
Authors: Yongsuo Zi , Caimeng Zhang , Yinsheng Hong , Pengrui Qiu , Wangjiao Shu
Published: August 2020

Aiming at the dynamic job shop scheduling problem with extended process constraints, this paper constructs a mathematical model of job shop scheduling problem with the objective of minimizing the maximum completion time. Genetic algorithm is used to solve the minimum maximum completion time, and the results are compared with those obtained by WSPT, EDD, FCFS, LPT and Cr. Through computer simulation, it is verified that the minimum maximum completion time obtained by genetic algorithm is better than that by SPT, EDD, FCFS, LPT and Cr.
Mixed LFM Signal Estimation Based on Radon-Wigner Transform and Matching Pursuit
Authors: Wang Dong , Tang Hong
Published: August 2020

Parameter estimation of mixed signals is a key problem in electronic reconnaissance. Based on Radon-Wigner transform (RWT) and Matching Pursuit (MP) algorithm, a parameter estimation method for mixed LFM signals is proposed in this paper. The core of the method is to separate signal components from the mixed signal and estimate their parameters one by one. Firstly, a rough parameter estimation of the strongest signal is obtained by RWT. After that an optimized estimation based on MP algorithm is performed to fine-tune the estimation result. Then, the strongest signal component is reconstructed with the optimized estimation, and it is separated from the mixed signal. Therefore, by iteratively estimating and separating the stronger signal within the residual mixed signal, all of the signal components can be precisely estimated. Experimental results show that the proposed method is able to achieve satisfactory performance on a lower signal-to-noise ratio.
An intrusion tolerant scheme of crosstalk attack based on multi-evidence trust model in multi domain optical networks
Authors: Wu Qiwu , Li Fang , Jiang Lingzhi
Published: August 2020

In order to improve the survivability of multi-domain optical networks, an intrusion tolerant scheme of crosstalk attack based on multi-evidence trust model in multi domain optical networks was proposed. By collecting and processing evidence and classified crosstalk attacks, the reputation of nodes and links in the intra-domain and inter-domain were calculated, and the application framework of the multi-domain optical networks crosstalk attack tolerant intrusion scheme was proposed. The analysis and experimental results showed that compared with the typical tolerant intrusion scheme, this scheme had better tolerant intrusion capability when multi-domain optical networks suffer from crosstalk attack.
Knowledge-aided sparse recovery STAP algorithm with off-grid self-calibration for airborne radar
Authors: Gao Zhiqi , Wu Zhixia , Huang Pingping , Xu Wei , Zhang Zhenhua
Published: August 2020

Space-time adaptive processing (STAP) for airborne radar may cause lattice mismatch during sparse recovery processing, which is the off-grid problem. The off-grid problem may lead to degradation of STAP performance. To cope with this problem, this paper proposes a knowledge-aided sparse recovery STAP algorithm with off-grid self-calibration (AO-SR-STAP). The snapshots are decomposed by sparse processing firstly. The off-grid of spare dictionary is calibrated and dense interferences are removed according to the knowledge of clutter distribution. A standard steering vector set is constructed by the prior knowledge of clutter distribution, which is used to calibrate the off-grid of sparse dictionary. The dense interferences in snapshots are removed with knowledge of clutter distribution. Hence, the clutter information of snapshots is estimated accurately and the target in cell under test can be detected completely. The advantage of this algorithm is that the off-grid of sparse dictionary can be calibrated, and dense interferences are filtered effectively. Simulation experiments verify the effectiveness and robustness of the proposed algorithm.
Design of an Unmanned Boat System for Floating Garbage Salvage and Water Quality Monitoring Based on OneNET
Authors: Xing Aoyu , Fang Jing , Gao Mengjie , Zhang Chenyang
Published: August 2020

In view of the serious floating garbage on water surface and the drawbacks of relevant cleaning equipment, an unmanned boat system for floating garbage salvage and water quality monitoring based on OneNET IOT platform is designed. The design of hardware, software and cloud platform application of the system are introduced in detail. The system is mounted on a small remote-control boat, which monitors water quality data through various sensors and uploads the data to the cloud platform while collecting garbage, and sends warning emails when water quality data exceeds the threshold value. The experimental results show that the system has realized the transmission of monitoring video in real time, remote control of floating garbage salvage, water quality information collection and release, and warning of monitoring data over threshold value. The system has a certain application prospect in water quality monitoring and protection of small-scale water area.
Research on Random Virtual IP Address Redistribution Technology Based on OpenFlow
Authors: wang Hai , wang Yi , luo Bingbing , zhang Baoying
Published: August 2020

In view of the shortcomings of traditional network defense measures and the dynamic defense needs of existing network security, a random virtual IP address redistribution technology based on OpenFlow protocol is proposed, which realizes the conversion between real IP address space and random virtual IP address space. The technology can increase the randomness of IP addresses in two dimensions of time and space, and increase the difficulty of network sniffing and network attacks. It provides new solutions and ideas for the implementation of dynamic defense at the network level.
Analysis of Factors Affecting FWM Inter-Channel Crosstalk Based on VPI
Authors: Liu Xueyue , Wu Qiwu , Liu Jiaqi , Jiang Lingzhi
Published: August 2020

To study the effect factors of inter-channel crosstalk caused by FWM in optical fiber communication and improve communication system performance, we build a simulation system on VPI, observe the changes of optical spectrum of the output, signal power diagrams and the eye diagrams of receiving channels, analyze the effects on FWM produced by different fiber parameters, channel spacing and optical signal power. The results show that the crosstalk between four wave mixing channels will be more serious with the increase of optical signal power, however, increasing the optical fiber’s dispersion coefficient and the effective area of the core can suppress FWM effectively, at the same time, increasing the frequency channel spacing can also reduce the FWM.
Relative pose estimation of cooperative target based on monocular vision
Authors: Wang Weiru , Liu Jiasheng , Wu Peizhang , Guo Jianpo
Published: August 2020

With the vigorous development of the global logistics industry, warehousing automation has become a popular applied research direction in computer vision. In this paper, the fork and the fork hole’s relative posture during the forklift picking process were taken as the research object. The relative position of the two is solved based on the Aruco cooperative logo PnP algorithm. In this paper, the initial values of the relative poses of the two are addressed by the linear algorithm DLT, and the relative poses are further optimized by Bundle Adjustment (BA). The iterative error observation function is constructed based on the visual pose estimation model, and the Gauss-Newton method is adopted. The least-square fitting iterative process is carried out many times, and the relative position and posture of the fork and the fork hole with high precision are finally obtained.
Research on Edge Detection Method Based on Improved HED Network
Authors: Lou Li , Zang Shasha
Published: August 2020

Aiming at the problem of rough and fuzzy edges generated by the current edge detection technology based on HED network, an improved edge detection method for HED network is proposed. First, the useful information captured by each convolutional layer of HED becomes rougher as the size of the acceptance field increases. The improved HED network makes use of all the information of the convolution layer to capture more targets in a larger range, or make the local boundaries of the targets possible. The improved HED makes full use of the multi-scale and multi-level information of the target to obtain high-precision and high-quality edge maps, which lays a good foundation for image segmentation.
Research and Implementation of Passive Wireless Communication System Based on Ambient Backscatter
Authors: Li Yue-zhong , Zhan Xiao-bo , Cao Jie
Published: August 2020

The ambient backscatter technique has attracted a lot of attention in passive communication systems. This device achieves wireless communication through radio frequency signals in backscattering Environment. In this paper, we focused on how to improve energy collection efficiency, communication rate and communication distance of passive wireless communication system. An ultralow power multi-antenna decoding algorithm and 5-stage charge pump booster rectifier circuit were proposed. The environment electromagnetic wave energy collection module, passive transmitter and passive receiver were designed. The experimental results show that communication rate of the passive wireless communication system can reach 50kbps and communication distance can reach 6 feet.
A method for source number estimation with density-based clustering algorithm
Authors: Li Qi , Ning Jinzhi , Dou Jiao
Published: August 2020

Almost all high-performance spatial spectrum estimation algorithms for direction of arrival (DOA) estimation are based on accurate source number estimation. Applied with features of covariance matrix eigenvalues of received data and compared with commonly-used K-means algorithm, this article proposes to use a density-based clustering algorithm, which is ordering points to identify the clustering structure (OPTICS) and its detailed steps, to estimate the accurate source number. The experimental results applying with OPTICS algorithm demonstrate better performance on source number estimation over other algorithms under the same conditions.
Research on Correction Method of Wind Measurement based on Platform Attitude
Authors: Zhi-qian Li , Ni Wang , Sui-ping Qi , Zhi-wei Zhang , Jia Sun , Dong-ming Wang
Published: August 2020

On the moving platform, the accuracy of wind measurement is also affected by the attitude of the platform. The influence of platform attitude on wind measurement is analyzed. Based on the coordinate system transformation in mathematics, the compensation and correction model of wind measurement based on platform attitude is deduced, and the verification method is designed. The sea test results show that the method can effectively restrain the influence of low frequency attitude movement of ship platform on wind measurement, and effectively improve the accuracy of wind measurement on the moving platform.
Target Signal Separation of Missile Group Based on Micro-motion Frequency Correlation
Authors: Tao Zhongtao , Yang Shaoqing
Published: August 2020

Object micro-motion feature extraction method for isolated targets is relatively mature, but the resolution and micro-motion feature extraction method for group targets still needs further research. Ballistic missiles in the middle of the throw-off process is taken to be the example, when the false target is released. A method of target separation by micro-Doppler frequency is proposed, and the target is modeled. A parameterized expression is given. The narrow band echo is processed by STFT and the time-frequency plane is obtained. After that, the BM3D algorithm is used to filter and reduce noise to smooth the curve. The improved Viterbi algorithm is used to extract the micro-Doppler curve of the group target. Finally, the Fourier transform is performed. According to the frequency correlation, the group target is separated, and the simulation verified this method.
Depth Image Inpainting method based on sparse gradient prior
Authors: Wu J , Li Z
Published: August 2020

This paper solves the inpainting problem of single depth images. depth images are regarded as natural images without texture. Because of the sparsity property of natural images and the textureless property of depth images, we propose a similar group-based sparse model with sparse gradient regularization. For one thing, the similar group-based sparse model can better represent the local smooth and nonlocal self-similarity. For another, the sparse gradient regularization can better represent the textureless properties. The proposed algorithm takes advantage of the properties of depth images. The experimental results show the effect of the proposed algorithm.
Capacity Analysis for Cooperative Vehicular Networks with Different Fading Channels
Authors: Zhu Hexiang , Zou Dan , Liao Longxia
Published: August 2020

The cooperative vehicular networks (CVNs) enable vehicles to obtain information of remote infrastructures through cooperative vehicles. Nevertheless, the tradeoff between the cooperative vehicular ratio and transmission capacity of CVN is a challenge. In this paper, an analytical framework is developed to study the impacts of cooperation, interference and channel fading on the system capacity. Moreover, based on the proposed analytical framework, a closed-form expression is derived to reveal the relationship between transmission capacity and other network parameters, such as outage probability, vehicular density and adjacent infrastructures distance. Numerical results show that an optimal cooperative vehicular ratio leads to the maximum capacity. The results can also provide a preferable guidance for the design of CVNs.
High Efficient Real-time Calculation Method of here Large FFT with High Overlapping Rate
Authors: Gao-xiang Xing , Tian-qi Yin
Published: August 2020

In order to meet the needs of large number of overlapping samples in sequential fine feature extraction, this work proposes a frame by frame (segment) iterative algorithm based on the “sparse” feature of incremental data to achieve efficient real-time calculation of large FFT, which breaks through the hardware bottleneck of real-time computing platform such as DSP platform in high-resolution spectral analysis. The proposed algorithm makes use of the sparseness of incremental data to make the computation burden of segment iteration lighter than that of standard FFT, and has the potential of parallel computation. The simulation results show that the new algorithm is more efficient than the standard FFT when the number of segments is large.
Antenna Performance Test Method and Result Analysis for V2X Communication of Connected Vehicle
Authors: Feng Jiaxu , Jiang Guokai , Ding Yifu , Zhang Xu , Liu Haiming , Fan Yan
Published: August 2020

This paper proposes an antenna performance test method for vehicle-level to ensure the stable communication capability for vehicular networking technology and application. Firstly, considering the large size and heavy weight of characteristic for the vehicle, a spherical near-field test for the vehicle antenna test is then proposed in the paper. Secondly, the impact of the vehicle body on the antenna performance is analysed by comparing the different performance between different vertical angles and antennas. Finally, the experimental results verify the validity and correctness of this method.
EMC Reliability Evaluation of Networked Vehicle (V2X) In Laboratory
Authors: Fan Yan , Jiang Guokai , Ding Yifu , Zhang Xu , Feng Jiaxu , Zhang Jie
Published: August 2020

In this paper, a networked vehicle is taken as the research object. The system construction and test method of V2X EMC reliability evaluation in the laboratory are studied, and the experimental demonstration and analysis are carried out for the specific V2X scenes. The research results show that the V2X EMC reliability test system built in the laboratory can effectively verify the network connection performance, functional stability and reliability of the vehicle, making up for the shortcomings of the actual road test process, such as low efficiency, large impact of the external environment and the failure is not easy to reproduce. In general, the system verify the feasibility of the V2X EMC test and evaluation ideas built in the laboratory.
Research on Identity Authenticated Encryption System for Application Services of the New Generation Dispatch Control System
Authors: Wang Jing , Liang Ye , Guan Yi , Liu Yong
Published: August 2020

This paper designs an identity authenticated encryption system for application services based on the problems of identity authentication and communication encryption of application service in the new generation dispatch control system, combined with the security protection requirements of dispatch control system. When the application is started, it will actively initiate authentication to the authentication center and obtain the application ID according to the national encryption algorithm after the authentication is passed. When the application makes a service invocation, the application directly sends the application ID to the service. The service verifies that the application ID is correct to provide the service without complicated bi-directional authentication and key agreement. At the same time, the session key for encryption in communications is automatically generated based on the information related to the application ID, which effectively reduces the impact of security authentication on service invocation performance while improving the security of service invocation.
Integration time interpolation control of space-borne TDICCD
Authors: Cai Shuai , Zhang Xu , Zhu Yajie , Li Liang , Bo Shu , Fu Shuai
Published: August 2020

Spacecraft orbits around the earth are basically elliptical orbits. That the altitude varies with motion of the remote sensing satellites results the ground resolution varies. Adjusting the integration time of image sensor can remain the accurate ground resolution.Similarly, the change of the satellites attitude leads to the variation of the ground resolution, which can be correct by adjusting the integration time of the image sensor. This paper presents an integration time interpolation arithmetic, which increases the adjustment rate of integration time of image sensor to make the space borne image sensor adapt to changes in orbit timely to ensure ground resolution. The arithmetic is implemented in FPGA, and this paper describes the results in the end.
A denoising strategy for the improvements of PPGi’s signal-to-noise-ratio
Authors: Deng Fubo , Zhang Jizhao , Jia Yunfang
Published: August 2020

Photoplethysmographic imaging (PPGi) is a burgeoning technology to monitor physiological parameters. Under the background of information technologies’ development, both the PPGi signal’s collecting set-ups and its data processing methods have been widely studied. However, the unsatisfactory signal-to-noise-ratio is still an obstacle to its productization. For this problem, an appropriate denoising strategy would be a feasible solution. Therefore, through the analysis and screening of Butterworth Low Pass filter, Butterworth High Pass filter, Median filter, Wavelet Transform, Hilbert-Huang Transform and Independent Component Correlation Algorithm, three of them are combined to form 3 tactics, their effects in improving signal-to-noise-ratio of PPGi signals are evaluated. It is found, the integration of Butterworth Low Pass filter, Median filter and Wavelet Transform (BMW) can acquire the best signal-to-noise-ratio (31.42dB) in the designed strategies. Furthermore, these denoised PPGi signals by the three tactics are used to calculate the blood pressure (BP) and heart rate (HR). The comparisons with the actually BP and HR data which are measured by a commercial sphygmomanometer also indicate that the close-to-actual BP and HR are obtained from the BMW denoised PPGi signals.
Research on the Development and Application of “Blockchain+” Education
Authors: Jiayan Li
Published: August 2020

As Internet technology registers rapid development, “Blockchain+” comes into being and is considered to be one of the most important inventions in the Internet era. “Blockchain+” has found its way into various fields, such as education, finance, economics, music, culture, management and other fields, thus changing the working methods in these fields considerably and leading to fruitful results. “Blockchain+” Education is a combination of the blockchain technology with education, featuring uniqueness, openness, and security. This study briefly introduces the blockchain technology and its development status in education, analyzes the classification of “Blockchain+” and its application value in education, with specific focus on its application in education.
Performance of Different Graph Neural Networks on Graph Classification
Authors: Zhan Zikang
Published: August 2020

In recent years, machine learning has become a common approach for solving problems of artificial intelligence, which is developing at a high speed. Convolutional Neural Network (CNN) is popular on solving image problems for its believable accuracy. However, it does not mean that other neural networks are useless on these problems. In this paper, performance of Convolutional Neural Network (CNN), Multilayer Perceptron (MLP) and Recurrent Neural Network (RNN) in the same database are presented. Performance of different types of networks are compared, and a conclusion is given that recurrent neural network might be able to classify pure black and white images at high accuracy, and that convolutional neural network performs better than multilayer perceptron on graph classification problems.
RETRACTED: Research on Computer Network Security Problems and Protective Measures under the Background of Big Data
Authors: Luo Guoyu
Published: August 2020

In the information age, human beings have entered the era of big data due to the large-scale data generated every day. Computer networks in people’s lives are very common. In the construction of social infrastructure and economic development, networks and information systems are essential core elements. When a network attack fails due to a malicious attack, it will bring about more serious security accidents, which will make the public interest and the national economy safe. Studying and strengthening the detection of cyberattacks to provide basic security for network infrastructure is the core link to ensure the controllability of core technical equipment and the construction of a national network security system. Therefore, this paper first analyzes big data, network security models and intrusion detection frameworks, and analyzes the key issues facing computer network security under the current circumstances. Protective measures are used to reduce the various security problems caused thereby, to prevent computer users from suffering major losses.
Application of Ear Detection in Non-frontal Face Recognition
Authors: Luo Yingjie , Shen Tianfei
Published: August 2020

Face gesture recognition is a research hotspot in the field of machine vision and pattern recognition.In this paper, we use the Haar-Like feature-based Gentle Adaboost algorithm to detect the ear of non-frontal face. An ear sample library for ear detection of non-frontal face images was constructed. Through zoom detection window and determining the ROI area, it can successfully detect ear and work better than the basic Adaboost algorithm. The detection rate of the algorithm in the experiment reached 82%. It is suitable for most of the non-frontal faces we photographed.It still has a good detection effect for images with a small amount of hair or eyeglass frame interference.Based on the contour information of the ear, an approximate method for determining the lower end of the ear based on edge detection and a head and neck boundary determination algorithm based on the lower end of the human ear are proposed, which is more complete than the previous algorithm based on the determination of the concave points on both sides of the neck. The face area is segmented to make the face contour finally applied on the fitted ellipse more accurate.
Suggestions on the implementation of the special planning of rural teaching network -Taking Xiushui County as an example
Authors: Sun Hailan , Fan Meng , Liao Jiayi , Yang Qing
Published: August 2020

The report of the 19th National Congress of the Communist Party of China puts forward “giving priority to the development of education”. Building a strong education country is a basic project for the great rejuvenation of the Chinese nation. We must give priority to the cause of education, speed up the modernization of education, and run education to the satisfaction of the people. The planning of rural teaching network in Xiushui county is of great significance to other rural areas in China. In order to speed up the solution to the current problems of “difficulty in entering the kindergarten” of preschool education in Xiushui County, the problems of “large school size” and “large class size” of primary and secondary schools, improve the layout of campus, promote the healthy and sustainable development of basic education, and promote the integrated development of urban and rural education as a whole, this project is carried out in accordance with the unified layout of Xiushui county Party committee and government, and in accordance with the planning requirements of education development, urban and rural planning and other industries suggestions for implementation are prepared.
Research on the Retrieval Algorithm of Speech Keyword Based on DTW
Authors: Li Zhi , Zhu Zhiyuan , Guo Jing
Published: August 2020

According to the query items entered by user, the speech retrieval is a data mining technology to retrieve and return the necessary results form massive audio data. In this paper, the history of speech retrieval is summarized and its necessity of studying is analyzed. On this basis, starting from the search of key words, the dynamic time regulation is derived in detail, and it is simulated by MATLAB. According to the results of MATLAB performance analysis, the optimization direction of speech keyword retrieval algorithm is explored.
Research on sparse channel estimation algorithm based on MIMO OFDM system
Authors: Xu Wei , Guo Tian
Published: August 2020

In the application of MIMO OFDM system, the traditional pilot-assisted channel estimation algorithm, such as LS, MMSE algorithm, does not take advantage of the characteristics of channel sparsity, which results in the reduction of spectrum utilization due to the use of a large number of pilots. Under the premise of compressed sensing, this paper uses channel sparsity to study the AMP channel estimation algorithm based on MIMO OFDM system, and introduces the principles and steps of the AMP algorithm in detail. Through theoretical analysis and simulation, it is shown that the AMP channel estimation algorithm proposed in this paper has a significant improvement in spectrum utilization and estimation performance compared with the traditional method, which is more effective and greatly reduces the calculation time.
Research on Clustering Algorithm Based on Web Log Mining
Authors: Xiang Haifei
Published: August 2020

People’s online business behaviour has become more and more frequent. Internet service providers are beginning to find ways to obtain the interests and hobbies of users in order to provide targeted services to users. Analysis of user behavior based on Web logs can obtain valuable information from users. User clustering based on Web logs can cluster users according to user behavior, and then analyze user access patterns, providing a good solution for problem solving. This article introduces the concept and process of data mining, the classification and process of Web data mining, and then analyzes the K-Means clustering algorithm. The class-centered algorithm avoids clustering and only obtains the local optimal solution, and it can reduce the algorithm iteration time and improve the clustering quality.
Ontology Based Semantic Understanding for 3D Indoor Scenes
Authors: Wang X H , Gao X , Zang K , Meng H J
Published: August 2020

A scene understanding method of combining semantic segmentation and ontology description is proposed in this paper. The method not only obtains the object of each part of the scene but also gets the relationship between the parts of the scene. Firstly, to realize the semantic segmentation of indoor scenes for 3D point clouds, PointNet is used in this paper as a tool for processing point clouds, and the S3DIS as PointNet datasets for training and testing. Secondly, in order to combine semantic segmentation and ontology, an ontology to describe the relationship between objects and scenes of the semantic segmentation result is used in this paper. Finally, we build indoor scenes ontology based on IndoorGML and use Protégé to display the spatial position ontology of the indoor scene.
A Teaching Mode of PBL for Software Engineering Course Based on Integration of Industry and Education
Authors: Yu Jiujiu , Zhang Jishan , Chen Yun , Wu Ning , Mei Yingying , Zhang Deqing , Zhu Canglu
Published: August 2020

Problem-Based Learning (PBL) is a teaching mode which is suitable for key courses of software engineering major in universities. Based on the concept of PBL, this study takes engineering of Anhui Sanlian University as an example, and is committed to building a feasible PBL teaching mode of software engineering course. Furthermore, further work is put forward to promote the development of the PBL teaching mode for local teaching environment.
Reverse recognition of LDPC codes based on log-likelihood ratio
Authors: Liu Ren-xin , Zhang li-min , Zhong Zhao-gen , Sun Xue-li
Published: August 2020

With the development of Adaptive Modulation and Coding (AMC) technology, blind identification of channel coding parameters has recently attracted more attention. To reduce the computational complexity of the closed set recognition of problem low-density parity-check (LDPC) codes, this paper improves a closed set reverse recognition algorithm based on the maximum mean log-likelihood ratio. Before using soft decision information to make a decision, the check vector is first filtered to select some check vectors to reduce the computational complexity. The experimental results show that this method can complete the inverse identification of closed sets of LDPC codes in the case of low signal-to-noise ratio. Compared with the previous algorithm, the time complexity of the proposed algorithm is significantly reduced.
Research on Design Innovation Method Based on Multimodal Perception and Recognition Technology
Authors: kan Wu , Longlong Men
Published: August 2020

In order to solve the problems of low efficiency and poor robustness of single-mode speech emotion recognition, this paper uses a multi-mode fusion mechanism to fuse speech and visual information across modes to build an audio-visual speech recognition (AVSR) system. The results show that the modal attention mechanism can automatically adjust to a more stable and reliable state according to the quality of a single signal, so that the audio-visual multimodal perception is accurate and the recognition efficiency is high.
Text Retrieval Technology Based on Keyword Retrieval
Authors: Huang Chunhao , Zhu Zhiyuan , Guo Jing
Published: August 2020

In such an era of informatization and big data where the Internet has greatly enriched the sources of information of people and changed the way they get information, search engine is widely used and it results from the combination of text retrieval and Web. Based on the research on Boolean model, vector model and probability model, this paper deduces a text retrieval algorithm using keyword retrieval, which can realize keyword retrieval of text documents in text database.
Evaluation of ELINT system effectiveness based on Grey Relational Optimization Algorithm
Authors: Qiu Risheng , Pan Jifei , Zhao Jun , Shengli Zhang , Deheng Chu
Published: August 2020

Aiming at the problems and shortcomings of the current electronic intelligence reconnaissance system effectiveness evaluation methods, an ELINT system effectiveness evaluation algorithm based on grey correlation optimization algorithm is proposed. The algorithm firstly combines the principle of ELINT system to build its evaluation index system. Then, based on the subjective and objective attributes of the index, the algorithm combines the G1 sequence subjective weighting method with the CRITIC objective weighting method to obtain the combined weight of each index. Finally, the improved gray correlation optimization algorithm model is used to analyze the correlation of the index value of the system under test, and the system performance is determined by comparing each distance with the optimal system. Theoretical analysis and simulation results show that the method effectively combines qualitative and quantitative analysis and is feasible in the performance evaluation of ELINT system.
Nonlinear phase compensated OFDR based on Match Fourier Transform algorithm
Authors: Muping Song , Shouwang Zhuang , Yixuan Wang , Ge Chen
Published: August 2020

The nonlinear phase of beat signal in Optical Frequency domain Reflectometry(OFDR) has become a bottleneck to its utilization. In this paper, a method to compensate nonlinear phase based on Match Fourier Transform algorithm(MFT) is presented. The nonlinear phase of beat signal is represented as a polynomial phase function, then the coefficients of the polynomial phase function are obtained from an auxiliary interferometer through the polynomial regression algorithm. Finally, the nonlinear phase in main OFDR interferometer can be compensated by Match Fourier Transform algorithm. The experimental results show that the method can effectively suppress the side lobe of the reflection peak and achieve a spatial resolution of 0.2m at 4.3km. The experiment results verify the effectiveness of the proposed algorithm.