bluuebunny/crossref_metadata_2025_split huggingface dataset:
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

Abstract
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

AbstractSpace-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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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

Abstract
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.