bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Novel 5G-advanced Core Network Intelligent Operation and Maintenance System
Authors: Zhang Xue , Li Huanan , Wang Dong 
Published: June 2022

Abstract
The 5G core network adopts Network Functions Virtualization technology, which forms a variety of virtual resources for general computing, storage, and network hardware to achieve dynamic and flexible deployment of network functions and resources based on needs. With large-scale commercial deployment of cloud-native 5G core network with network function virtualization technology, the operation and maintenance of 5G core network is facing new challenges. This paper describes the architecture and deployment characteristics of 5G core network, and analyses the challenges brought to operation and maintenance by new network characteristics such as SBA, NFV, MEC and separated UPF, as well as the difficulties of operation and maintenance of virtual deployed 5G core network. Combined with the architecture evolution and function enhancement of 5G-Advanced, the architecture and scheme of A Novel Intelligent 5G-Advanced Core Network Operation and Maintenance System are proposed. The architecture and scheme of 5G core network operation and maintenance system construction were proposed, and suggestions on the organizational structure of 5G core network cloud-network integration operation and maintenance were put forward, so as to provide reference for 5G core network cloud-network integration operation and maintenance. The proposed scheme improves the performance of operation and maintenance of 5G core network significantly.
Design IoT-based Collaborative Framework and Routing Method in Complex Emergency Situation
Authors: Zhu Xiaoguang , Chen Fengzhao , Zhang Yu 
Published: June 2022

Abstract
Emergency management affords a crucial responsibility to protect the lives and properties of our society through disaster prevention and emergency responses. Current research applied Internet of Things(IoT) and intelligent models to improve the efficiency of emergency responses. However, in a complex emergency, the responses require more dynamic and collaborative strategies to prevent an emergency at the starting point. Therefore, this paper proposes a collaborative framework and routing method to facilitate the combination of IoT systems and social forces. Firstly, we construct a framework through the induction of current collaborative emergency systems. Secondly, based on multi-modal sensors and directors, we propose a routing method to harness complex emergencies with route optimization and local communication. The complete system could be completed on light equipment and crowding data that are green and sustainable.
A Generalized Projetion Gradient Algorithm for Mathematical Programs with Complementary Constraints
Authors: Zhang Cong , Sun Limin , Xiao Ya 
Published: June 2022

Abstract
Against the shortcomings that many existing algorithms for solving the standard smoothing nonlinear programming would fail if they were used directly to solve the mathematical programs with complementary constraints( MPCC). By using a complementarity function and the idea of smoothing approximation method, the MPCC problem was transformed into a smoothing nonlinear programming. Combined with the supermemory gradient idea, a generalized projection gradient algorithm is proposed and its global convergence is obtained.
Mask Wearing Detection Based on Inceptionv4 and Multi-Scale Retinex Image Enhancement Algorithm
Authors: Zhang Hongfei , Liu Chun , Ho James , Zhang Zhiwei 
Published: June 2022

AbstractThe novel coronavirus is a contagious virus with a high mortality rate, and the international health emergency due to COVID-19 has never stopped since the outbreak, due to this situation, wearing masks has become a basic recommended public epidemic prevention approach for many countries. In the current shortage of medical human resources, we urgently need a non-artificial mask-wearing detection method. In this paper, the multi-scale Retinex algorithm is involved as the preprocessing step of the input image. The mask-wearing detection is based on the InceptionV4 convolutional neural network model. During the experiment, we compared and verified the superiority of the Inception part of the InceptionV4 model compared with the Stem structure of the GoogLenet model, and from LFW (Labeled Faces in the Wild), RMFD (Real-World-Masked-Face-Dataset) more than 10,000 samples were selected from the public datasets for model training. Finally, the precise rate reaches 97.3 %.
Adhesive Abrasive Detection for Diamond Images based on Improved Watershed Algorithm
Authors: Lin Yanfen , Fang Congfu , Gao Lizhen 
Published: June 2022

Abstract
Diamond images have characteristics of adhesive abrasives besides much background noise, irregular abrasive shapes and different abrasive size, which brings big challenges to accurate diamond abrasive detection. Therefore, an improved watershed algorithm is put forward to detect adhesive abrasive in this work. Firstly, the diamond abrasive image is filtered by Gaussian to suppress the background noise, and then the pre-processed diamond abrasive image is reconstructed by morphology. Through the distance transform of the reconstructed image, marking features for subsequent abrasive detection can be obtained. Finally, the watershed algorithm and extended-minima transform are used to finely detect diamond abrasives and separate adhesive abrasives, respectively, so as to realize the accurate detection of adhesive diamond abrasive image. According to the results of detection experiments, the proposed method based on improved watershed algorithm and extended-minima transform can accurately detect adhesive diamond abrasive images, the recall rate of abrasive is 94.8%, which indicates good recognition accuracy and robustness of the proposed method. The accurate detection results can be further used for subsequent image analysis and abrasive feature parameter extraction.
Applications and Current Status of AI in the Medical Field
Authors: Feng ZHAO , Hua XU 
Published: June 2022

Abstract
Artificial intelligence has developed very rapidly in recent years, resulting in a huge impact on all sectors of society. People are also paying more and more attention to AI. Artificial intelligence application in the field of medical treatment are more common, this paper introduces the main applications of artificial intelligence in medicine, common applications include virtual assistant, AI auxiliary diagnosis and treatment, medical robots, etc, through in-depth analysis of the various applications, found applications in the field of artificial intelligence in the process of all kinds of problems,There are common problems such as lack of unified norms and shortage of artificial intelligence talents, and the above problems are discussed in detail.Finding and solving problems provides a strong guarantee for the development of artificial intelligence in the medical field.It is believed that AI will provide greater help to both doctors and patients.
Comparative Analysis of Optimization Schemes of Carry Look-ahead Adder
Authors: Chu Shunan 
Published: June 2022

Abstract
Conventional CLA adder has has a large number of transistors and high input impedance, which affects various performance aspects, resulting in high delay and power consumption. Therefore, to increase the performance and reduce delay, several optimized structures of CLA are proposed. From the perspective of structure and power, this paper selects four different design schemes and uses Cadence Virtuoso 90nm technology to compare and analyze the optimization results in aspects of circuit area, delay and power consumption. The analysis results show that the conventional 4-bit adder structure can be improved by designing the carry term Field Effect Transistor (FET) network and replacing the existing gate circuit with a hybrid Gate diffusion technology (GDI) gate, which can reduce the number of transistors and the design circuit area. They also contribute to improving the power consumption, delay, power delay product (PDP) and other performance parameters. Pipeline technology and multi-layer CLA block technology are suitable for carry look-ahead adder with more bits and longer carry chain, which can shorten carry propagation time, further optimize processor performance and improve CPU computing efficiency.
Research on Influence of Battery Energy Storage System on Voltage Transient Stability
Authors: Liu Xinke , Li Peiqiang , Zhang Zhongkai , Zeng Jingjie 
Published: June 2022

Abstract
In view of the current transient stability of the grid voltage, this paper studies the reactive power support of the access point when the energy storage system is connected to the power grid by studying the four-quadrant working mode of the energy storage system. Using the energy storage system built in the Power System Analysis Software Package PSASP and the CEPRI36 node example, the transient stability changes of the power system voltage before and after the energy storage connection are simulated and compared. The results show that the energy storage has a restraining effect on the voltage fluctuation.
Research on accuracy performance evaluation technology of Beidou GBAS reference receiver
Authors: Liu Ruihua , Yang Huanfa 
Published: June 2022

Abstract
The ground based augmentation system (GBAS) uses ground subsystems including reference receivers to provide differentially correction Global Navigation Satellite System (GNSS) data to improve the overall accuracy and integrity of the system. The accuracy of the GBAS ground subsystem is measured in the pseudo-range domain, so it is necessary to perform pseudo-range domain accuracy testing of the GBAS ground equipment. Based on the B-value method, this paper presents the evaluation process of GBAS pseudo-range domain accuracy based on the BDS-3 new frequency points of B1C and B2a. The B-value methodology is based on broadcast pseudo-range correction data, which covers the differential correction data of all reference stations and considers ground system monitoring, and can reflect the impact of the multipath synthesis effect of different receiver combinations on the accuracy of the pseudo-range domain. The real-collected data shows that the built test system can reach a GAD-B3 accuracy level, and the B-value method can effectively evaluate the pseudo-range domain accuracy of BDS-3 GBAS reference receivers.
Research on customer’s electricity consumption behavior pattern
Authors: Wang Yi , Yang Zhengyu , Wang Yaojian , Gu Jie 
Published: June 2022

Abstract
The fine-grained customer load data provides a large amount of information for the analysis of customer’s electricity consumption behavior pattern. Therefore, this paper proposes an algorithm for identifying the electricity consumption patterns of electric power users based on k-means algorithm. Our method is verified on the electricity consumption data of Irish residents and Shanghai Southern Industrial and Commercial users. The experimental results show that our method can divide the curves with similar electricity consumption patterns efficiently.
Reserch on Optimization of Electronic Optical System of X-band Klystron
Authors: Liu Qiang , Shen Bin , Gu Honghong , Liang Yuan 
Published: June 2022

Abstract
This paper has completed the simulation of the X-band 1 MW klystron electronic optical system, and optimized the electron gun and focusing system respectively. The electron gun adopts a single electron beam scheme. The voltage and current of the beam is 80 kV and 45 A respectively, the perveance is about 2.0 μP , and the average emission current density of the cathode is 6.81 A/ cm
2. The focusing system adopts the design of electromagnetic focusing, and the maximum magnetic field in the uniform area is about 0.33 T. The calculation results show that the distribution of the electric field lines in the electron gun area is uniform, the fluctuation of the electron beam is uniform, and the DC pass rate of the electron beam reaches 100%, which meets the design requirements.
Harmonic source identification method based on sinusoidal approximation
Authors: Gao Peng , Tian Mingxing , Wang Lixun 
Published: June 2022

Abstract
The proportion of nonlinear electronic devices such as electric arc furnace is increasing day by day, and the proportion of harmonic content in power grid is also more and more cannot be ignored. Therefore, the identification of harmonic source has received the attention of experts and scholars in the industry at present. Therefore, how to accurately locate and reduce harmonic content from power system source becomes the first step to improve power quality. This paper firstly analyzes the causes of harmonics and points out that nonlinear load is the fundamental cause of harmonics in power system. Secondly, the load equivalent model, the composition of the model and the method to determine the model parameters are established. Meanwhile, the current distortion coefficient is introduced to determine the harmonic source. Finally, an example is designed to verify the feasibility and rationality of the proposed method. Compared with the existing analytical methods at present, the proposed method has significantly improved the accuracy of harmonic source identification.
Recognition of Active Deception Jamming for LFM Radar Based on Hyperdimensional Computing
Authors: Dong Hao , Wang Yan , Hu Wen 
Published: June 2022

Abstract
Active deception jamming is one of the common means to jam radar signals. How to effectively recognize active deception jamming is a challenge of modern radar technology. To address the accuracy and real-time of radar active jamming recognition in practical applications, we propose a fast recognition method of radar active deception jamming based on hyperdimensional computing. First, to address the high feature dimensions, we use the sparse representation of time–frequency diagrams as the input, which time–frequency diagrams are constructed by the jamming plus echo signals in multiple consecutive pulse periods. Second, to achieve a high accuracy and real time of recognition, we employ the hyperdimensional computing to map the input to hyperdimensional space for training and recognition. Last, in the recognition stage, the Hamming distance is adopted to measure the similarity of samples. We validate our method on nine types of radar active deception jamming. The experimental results show that compared with the existing mainstream machine learning-based methods, the proposed method greatly shortens the training time on the premise of maintaining a high recognition accuracy.
Control strategy of DC/DC converter for photovoltaic-storage-DC microgrid based on improved LADRC
Authors: Liu Fengyi , Guo Kunli , Hao Yifan , Cai Weizheng , Li Bohao , Lv Jiajun , Liu Luhao 
Published: June 2022

Abstract
Aiming at the problem that the DC bus voltage is easily affected by nonlinear noise of the converter, photovoltaic output power and load disturbance, a bidirectional DC/DC converter control strategy based on the improved Linear Active Disturbance Rejection Control is designed. Firstly, establish the mathematical model of the bidirectional DC/DC converter, and analysis of existing problems in traditional LADRC. On this basis, a new state variable is introduced to observe the differential of the total disturbance to improve its rapidity; Then a lead-lag correction link is connected on the total disturbance observation channel to suppress the problem of high-frequency noise amplification. Finally, the Bode diagram is used to analyze the performance indicators of the improved LADRC. The simulation results show that, compared with the traditional LADRC, the control strategy in this paper reduces the bus voltage amplitude fluctuation by 63%, the adjustment time by 59%, and the inductor current ripple by 66%, which is more superior to suppressing the DC bus voltage fluctuation.
Dual-frequency Hexagonal Helical Microstrip Slot Antenna Loaded with Resonant Ring
Authors: Shan Zhiyong , Gao Mingrong 
Published: June 2022

Abstract
A hexagonal helical microstrip slot dual-frequency antenna loaded with resonant ring is presented in this letter. By loading the resonant ring and slot, the dual frequency of the antenna is realized and the antenna gain is improved. The best performance of the antenna is obtained by the optimization experiment. The simulation results show that when the reflection coefficient of the antenna is less than -10dB, the impedance bandwidth is 1.45GHz-1.78GHz and 2.39GHz-2.52GHz, the corresponding relative bandwidths are 20.4% and 5.3% respectively, and the maximum gain is 3.54dB. The antenna has better performance, it can be used in modern communication systems such as global positioning system (GPS), bluetooth, wireless local area network (WLAN) and WIFI.
Infrared target detection method using adaptive feature fusion
Authors: Zheng Lu , Zhou Tongtong , Peng Yueping , Ye Zecong 
Published: June 2022

Abstract
As the key technology of low altitude airspace security and air attack, vision-based air target detection has better concealment and lower cost compared with radar, radio and other detection methods. Based on yolov3, this paper proposes an air infrared target detection algorithm using adaptive feature fusion, which can effectively improve the accuracy of air infrared multi-scale target detection. Firstly, the construction of air infrared target detection data set is completed, and the target characteristics in the data set are statistically analysed. Secondly, the output layer of backbone is adjusted, and the four times down sampling feature map is used to replace the eight times down sampling feature map to enhance the detection ability of small targets. Thirdly, aiming at the problem of weakening feature expression caused by cross-scale feature fusion in FPN, a pixel level feature adaptive fusion module is designed. Finally, two improved SPP modules are added to neck to enrich the expression ability of feature map through the fusion of local features and global features. Experimental results show that compared with yolov3, our algorithm improves the map from 86.53% to 90.26% while keeping the detection speed basically unchanged.
Direction-of-Arrival Estimation Under Coexistence of both Circular and Strictly Non-Circular Signals in Coprime Linear Array
Authors: Xu Haiyun , Li Hao , Cui Weijia , Yu Zhenhua , Quan Mengjiao 
Published: June 2022

Abstract
Direction-of-arrival (DOA) in coprime linear array involves the problem that existing algorithms have less taken signal features into consideration. Considering that there is coexistence of multiple both circular and strictly non-circular signals in communication systems, an approach to DOA estimation of high accuracy and degree of freedom is proposed in this letter. We first use the ellipse covariance matrix and matrix completion method to reconstruct the covariance matrix of a virtual linear array. This virtual matrix only concludes the components of noncircular signals. Then, we similarly use the covariance matrix and matrix completion method to reconstruct a new covariance matrix including all signals of another virtual linear array. We use the virtual non-circular covariance matrix to eliminate the non-circular components in another virtual matrix. Finally, this matrix only concludes the circular signals. And we apply multiple signals classification to obtain the DOAs of two kinds of signals separately. Simulation results show that the proposed algorithm can obtain a highest degree of freedom than existing algorithms and hold on a preferable accuracy.
Global Importance Analysis of Nodes Based on Complex Network Theory
Authors: Lin ShengNan , Li Shuai , Su Yang 
Published: June 2022

Abstract
Aiming at the effectiveness of global importance index of nodes in directed network, according to complex network theory, using degree index, intermediate centrality index, proximity centrality index and PageRank algorithm, the importance ranking of nodes is obtained,The global efficiency of the network and the number of nodes in the maximum connected subgraph are used as the criterion to attack the directed network with priority of node importance, analyzing the effectiveness of four indexes to evaluate the global importance of nodes.The global importance of nodes is studied by using the index with high effectiveness. By protecting the nodes with high global importance, the survivability and the overall efficiency of the directed network can be improved.
Parameter Estimation Processor for K-distribution Clutter Based on Deep Learning
Authors: Zhang Liang , Yang Wei , Zhi Shuaifeng , Yang Chen 
Published: June 2022

Abstract
This paper concerns the problem of parameter estimating of K-distribution. In previous work only the shape parameter of K-distribution is estimated from which the scale parameter is calculated. Therefore, the accuracy of the estimated scale parameter is largely determined by the accuracy of shape parameter estimation. In order to decouple the estimation of scale and shape parameters, in this work, deep learning is considered as the main tool to achieve K-distribution parameters estimation as a regression task. Specifically, a parameter estimation processor combining CNN with LSTM is constructed. The ground truth of the two parameters are taken as labels, and the weighted losses of the two parameters construct the total loss function of the network training. The effectiveness and superiority of the proposed estimation processor are verified on the simulated data and the real sea clutter data.
Performance analysis of empirical models of sea surface reflectivity based on measured data
Authors: Yang Boyu , Jiang Min , Wang Jianming 
Published: June 2022

Abstract
The empirical models of sea surface reflectivity have many categories and different applicable conditions. In order to solve the problem of how to select the best models in different environments, we make a systematic analysis of the performance of different models based on the measured data of sea surface and the meteorological observation data in the Northwest Pacific. The results show that the accuracy of the empirical models of sea surface reflectivity may be biased when only the sea state is used as the description of sea surface roughness. For low radar grazing angle, NRL and HYB models can obtain better performance. It is recommended to add a fixed offset for NRL model at medium grazing angles. Constant gamma model can get better fit at high radar grazing angle.
Dynamic Cache Replacement Strategy of Space Information Network Based on Cache Value
Authors: Cai Rui-yan , Qian Yang , Wei De-bin 
Published: June 2022

Abstract
With the development of space network communication technology, satellite cache becomes possible. However, due to the limited space on the satellites, content replacement has become a major factor affecting network performance. Aiming at the limited cache resources of space network nodes and the low cache hit rate of nodes, a space information network dynamic cache replacement strategy (SINDR) based on cache value is proposed. On the basis of considering the popularity of the content and the cost of caching, the strategy also calculates the caching value of the content by quantifying the entropy increase of the node, and assigns a reasonable weight to each factor according to the Analytic Hierarchy Process. The cache value function is reconstructed; finally, the content of the virtual node and the physical satellite node that will serve the area is replaced by combining the characteristics of the space network, so as to obtain the optimal utilization of satellite cache resources. The simulation results show that, compared with the existing cache replacement strategies, the cache replacement strategy proposed in this paper can effectively improve the average cache hit rate and reduce the average user acquisition delay in the space information network environment.