bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identity and body temperature detection system based on image registration
Authors: Yao K , Chen Y , Zhang Z D , Li G , Zhai J B , Liu Y H , Zhou J L 
Published: June 2022

Abstract
In view of the normalization of epidemic prevention and control work, the low detection efficiency of traditional temperature measurement methods, and the existence of infection risks, an infrared thermal imaging temperature measurement system that can measure and identify the temperature of more than two people is designed. The system uses the Raspberry Pi as the core controller, using visible light and infrared cameras to capture identity and body temperature information. Identity recognition is based on OpenCv, using the Face Recognition face recognition framework to complete the identity recognition; body temperature detection is based on image registration, and the face position is mapped to the infrared image in real time through affine transformation, and finally the temperature of the human face area is obtained and displayed on the screen. The final experimental results show that it can simultaneously identify multiple people and detect body temperature with high accuracy, which can basically meet the requirements of rapid body temperature screening in intensive situations.
LADRC Based Digital Control DC-DC ASIC Design
Authors: Zhang Wangdong , Fan Bo , Lu Chao , Liu Huimin 
Published: June 2022

Abstract
The Internet of Things (IoT) systems require power management modules to have the characteristics of low power consumption, high conversion efficiency, high integration, stable output, and good dynamic response. Due to its ease of tuning and superior control performance, linear active disturbance rejection control (LADRC) is an attractive design option. Yet, to date, due to its high complexity, LADRC has been used in software systems, while little effort has been made in its hardware implementation. In this work, we investigate and explore efficient hardware implementation of the LADRC algorithm. A fully integrated digital LADRC controller for DC-DC Buck converters is synthesized with UMC 55 nm CMOS process. Its input voltage is 5V, stable output voltage is 2V, and rated operating current is 100mA. To our best knowledge, this is the first work to implement LADRC algorithms in hardware. Simulation results show that the LADRC controller is superior to the PID controller in the terms of start-up time, line regulation, load regulation.
Detection of Weak Pulse Signal under Chaotic Noise based on Fractional Maximum Correlation Entropy Algorithm
Authors: Su Liyun , Shi Lin , Li Fenglan , Quan Jing , Zhao Shengli 
Published: June 2022

Abstract
How to improve the detection accuracy of target weak signal is always the difficulty of signal processing. In this paper, based on fractional maximum correlation entropy algorithm and combined with the local linear model, a method for detecting weak pulse signal in chaotic noise background is proposed. Firstly, for the sensitivity of chaotic signal to initial values and short-term predictability, reconstruct the phase space of the observation signal, establish a local linear model, use the fractional maximum correlation entropy algorithm for parameter estimation, and perform a single-step prediction to obtain the prediction error. Then, in order to accurately detect the submerged weak pulse signal, a threshold is given. Finally, the simulation results show that the proposed model in this paper can effectively detect the weak pulse signal under the background of chaotic noise, and it is suitable for signals of different intensities, and the detection speed and accuracy are much better than other models.
Radio Frequency Identification target location based on the Unmanned Aerial Vehicle
Authors: Liu Yulin , Zhou Jian , Wang Lin , Wang Yu , Yin Yong , Ding Zhongjun 
Published: June 2022

Abstract
Due to the complex environment, the traditional Radio Frequency Identification (RFID) localization algorithm is cumbersome, the system localization accuracy is low, and the calculation time is relatively complex, an RFID localization algorithm based on sequential Kalman filtering has been proposed in this paper. Through the flight of sequential points, The Unmanned Aerial Vehicle (UAV) with the reader collects the Received Signal Strength Indication (RSSI) data dealt with mixed filtering of the target in the scene, after obtaining the coordinates according to the three-ball intersection method, and then using the Unscented Kalman Filter (UKF) algorithm to generate the estimation equation, thereby determining the position trajectory information to estimate. The results show that compared with other positioning methods the system has higher mobility and improved positioning accuracy with an average of 13.15%. At the same time, due to the real-time and flexibility of drones, this system can also be applied to more diverse scenarios. And the algorithm operation time is 1.15 s and it is suitable for UAVs scenarios.
A strategy dedicated to the concise and efficient development of the customized large-signal model for GaAs HEMTs
Authors: Zhu Huabing , Yan Zhihai , Tian Weiqian , Zhao Hong , Song Cheng , Zhang Lin , Hu Bin 
Published: June 2022

Abstract
In this letter, a strategy dedicated to the concise and efficient development of the customized large-signal models for GaAs HEMTs is proposed, which is specialized for MMIC designers. The core concepts of the strategy are a deconstruction of the original thought of model construction and dimension reduction of the objective functions of optimization algorithms. The development of an Angelov-based customized large-signal model following this strategy has been successfully applied to GaAs HEMTs in 70nm process. The results show that it takes less than five minutes to execute such a parameter extraction algorithm with a one-button extraction function and good agreement is achieved between the model simulation and device measurement up to 65GHz.
MIMO Radar Imaging Based on Two-dimensional Compressive Sensing Recovery Algorithm
Authors: Feng Junjie 
Published: June 2022

Abstract
Conventional sparse signal recovery-based MIMO radar imaging method rearranges the received two-dimensional (2D) signals into a vector, However, transforming the two dimensional equation to one dimensional equation then solving linear equation based sparse signal recovery problem requires huge memory and computational budget. A two-dimensional compressed sensing MIMO radar imaging algorithm based on improved smooth L0 norm is proposed in this paper. Firstly, a two-dimensional MIMO radar imaging model is established to transform the imaging problem into a sparse optimization problem. Then, the two-dimensional negative exponential function sequence is used as the smoothed function sequence to approximate the L0 norm. The two-dimensional imaging of MIMO radar is realized by cyclic iteration and gradient projection algorithm. Simulation results show that the proposed algorithm has advantages over the traditional compressed sensing algorithms.
A test method for active reflection coefficient of array antenna
Authors: Zhao Hongyi , Shi Guangqin , Ma Fengjun , Zhang Yi , Wei Yinyu 
Published: June 2022

Abstract
The mutual coupling effect of array antenna can usually be characterized by the dominance of active reflection coefficient. A test method of active reflection coefficient is proposed in this paper. the theory of antenna active reflection coefficient is analyzed, and the array antenna modeling and active reflection coefficient simulation results are introduced by HFSS. the hardware composition and function of antenna active reflection coefficient test system are introduced. the comparison between test results and simulation results is analyzed. The results are in good agreement. Compared with the traditional test methods, the designed test system has the characteristics of intuitive test results, fast measurement speed, high sensitivity, large dynamic range, small measurement error and strong expansibility.
Compensation of Position Estimation Error in PMSM Sensor-less Control Based on High Frequency Square Wave Injection
Authors: Zhao Xince , Su Jianyong , Wang Shuai , Yang Guijie 
Published: June 2022

Abstract
The high-frequency square-wave injection method is widely used to estimate rotor position at low speed. However, the accuracy and reliability of the method are greatly affected by the dead-time effect. The specific expression of position error is deduced. On this basis, a dead zone error reduction method based on second-order general integrator (SOGI) is adopted to improve the accuracy of position estimation. Besides, low-pass filter needs to be introduced into the current loop, which will bring delay to the system. Aiming at this problem, a delay compensation algorithm is adopted, which can effectively improve the accuracy of position estimation. Results of simulation verify the effectiveness of the methods and their applicability to PMSM sensorless control systems.
An Efficient Multi-dimensional Data Aggregation Scheme for Fog-Assisted Wireless Body Area Network
Authors: Fan Hongbin , Luo Yiheng 
Published: June 2022

Abstract
The rapid development of wireless body area network and monitoring technology has brought new opportunities for the later rehabilitation of patients. Due to the limited computing power and power of wireless body area network (WBAN) sensor nodes, combining WBAN with fog computing is one of the feasible solutions for remote monitoring. Wireless body area network can exchange medical information in real time, which is an effective way to improve medical services. The WBAN is inefficient and vulnerable to attacks, leading to leakage of user privacy information. This paper proposes an efficient data aggregation scheme for fog-assisted WBAN. The analysis shows that the scheme can resist the existing attack. The security analysis shows that the scheme meets the privacy and security requirements of data aggregation in WBAN. Compared with existing schemes, this scheme has an efficiency advantage.
Numerical Calculation of Vibration Characteristics of Transformer Core under Inter-harmonics
Authors: He Qiang , Fan Chao , Yang Guang , Li Huiqi , Li Jiadong , Chen Xiaogang 
Published: June 2022

Abstract
In this paper, a numerical model that can simulate the vibration of the transformer core under arbitrary inter-harmonic excitation is established. On this basis, the influence of interharmonics on core vibration is studied. First, based on the multi-physics coupling software, by deriving the differential equations of the physical fields, a coupling model of the circuit, magnetic field and solid mechanics is established. Then the magnetostriction curve is used to calculate the magnetic flux density and vibration displacement of the transformer core model under power frequency sine and interharmonic excitation. The work of this paper lays a theoretical foundation for studying the vibration problems of power transformers and other equipment under inter-harmonics.
Research on Short-term Load Forecasting Based on GWO-BILSTM
Authors: Liu Zhaosu , Yang Jianfeng 
Published: June 2022

Abstract
In short-term power load forecasting, changes in external multi-dimensional factors will have a certain impact on the accuracy of load forecasting. In response to this problem, this paper proposes a prediction model GWO-BILSTM that combines the Grey Wolf Optimizer (GWO) and the bi-directional long short-term memory (BILSTM) network. Taking the real power load data as the data set, the high correlation parameters are selected as the input through the Pearson correlation analysis, the hyperparameters of BILSTM are optimized by the GWO algorithm, and finally the GWO-BILSTM prediction model is established based on the optimized parameters to predict the data set. The experimental results show that the mean absolute percentage error, root mean square error and mean absolute error index of the GWO-BILSTM model are better than other comparison models, which effectively improves the prediction accuracy of multi-dimensional power load data.
Analysis and calculation of beam-wave interaction in 220GHz gyrotron resonator
Authors: Su YunFeng , Zhao Ding , Liu Qiang 
Published: June 2022

Abstract
In this paper, the beam-wave interaction of the 220GHz gyrotron resonator is analyzed. The design scheme of the physical structure of the TE36,17 cylindrical open resonator is given. According to the beam-wave coupling coefficient, the center radius of the electron beam guidance of the resonator is obtained, and the working parameters of the resonator are determined by the start current. The single-mode self-consistent nonlinear theory in the frequency domain of the resonator is deduced, and the output characteristics of the resonator are studied by using MATLAB.
Analysis of FAST’ Best Working Paraboloid
Authors: Xiao Haitao , Wang Hanyun , Li Wenzhi , Yang Shanshan 
Published: June 2022

Abstract
FAST consists of an active reflector, a signal receiving system (feedback source cabin) and other devices, where the reflector is an adjustable sphere composed of a main cable net, reflective panel, actuator and other main parts. It obtains an ideal paraboloid for operation in line with the position of the heavenly bodies, and meanwhile, a reflective panel regulating model by fitting the paraboloid as much as possible based on this ideal paraboloid, and calculates the absorptance of the cable according to the reflection model of electromagnetic waves.
Offloading Strategy in Satellite-Ground Network
Authors: Li Yang , Wei-dong Ma , De-bin Wei 
Published: June 2022

Abstract
Subject to other constraints such as economic costs, limited ground network coverage and insufficient network service capabilities in remote areas have resulted in some unloading requests being rejected. In this paper, the satellite network is used as the supplement of the terrestrial network, and the satellite-ground fusion multi-layer MEC network is constructed to study the offloading strategy and resource allocation for multi-type tasks. Firstly, the priority of task unloading is divided, and then the optimization function is constructed with the goal of minimizing the system overhead, and the improved tabu search algorithm is used to solve the problem. Finally, the feasibility and superiority of the algorithm are verified by experimental simulation.
A Hybrid Particle Swarm Optimization and Single-Objective Slap Swarm Optimization Algorithm Based MPPT Strategy
Authors: Huang Ronggeng 
Published: June 2022

Abstract
Under inhomogeneous irradiance conditions, multiple peak characteristic of P-V curve reduces the efficiency of conventional trackers like incremental conductance control. A hybrid particle swarm optimization and single-objective slap swarm optimization algorithm (PSO-SOSSOA) based which is applied to maximum power point tracking (MPPT) strategy is presented. The PSO-SOSSOA adopts the particle swarm optimization algorithm in the early period of the algorithm operation and a modified single-objective slap swarm optimization algorithm (SOSSOA) in the remaining period. The simulation results reveal that the PSO-SOSSOA can successfully deal with global MPPT and exhibits performance advantages in terms of efficiency, search speed, and power oscillation compared with the SOSSOA.
Acoustic modeling of transformer combined with multi physical field coupling
Authors: Wu Zhengyang 
Published: June 2022

Abstract
To realize the state diagnosis of transformer by detecting the running sound signal of transformer, it is necessary to obtain the sound pressure distribution of transformer in normal state. Because the amplitude of the sound signal changes obviously during the operation of the transformer, this paper studies the overall operation noise of the transformer and verifies it with the sound signal collected on site. The multi physical field coupling analysis software COMSOL multiphysics is selected to solve the vibration acceleration and sound pressure distribution of dry-type transformer under rated state. By comparing the solution with the field data, the sound pressure law of the transformer under normal operation is studied.
A Group Learning based Optimization Algorithm Applied to UWB Positioning
Authors: Zhang XiuWei , Zheng WenYi , chen Yong 
Published: June 2022

Abstract
In dealing with optimization problems, metaheuristic algorithms have attracted much attention due to their simple structure and flexible characteristics. Inspired by the principle of teaching students in accordance with their aptitude, this paper proposed a novel metaheuristic algorithm——Group Learning based Optimization (GLBO) Algorithm, this algorithm is suitable for continuous optimization problems. The main idea of this method is to divide a class into three study groups according to their scores, and formulate different study strategies for them according to the characteristics of each group, so as to improve the scores of the whole class. To verify the performance of the algorithm, it is tested on the CEC21 Benchmark suit and applied to UWB positioning. The results show that the proposed method has excellent performance when dealing with continuous optimization problems.
Research on graph classification based on improved metric learning
Authors: Dai Miaomiao , Zhang Xiaohui , Chen Wenxia 
Published: June 2022

Abstract
Few-shot graph classification is to learn valuable information from limited labelled graph data for graph classification. However, although the traditional graph neural networks (GNNs) have been widely used in graph classification tasks, the problem of insufficient graph sample of many domains is ignored. At present, using meta learning method can greatly solve the problem of low data in many fields. However, when facing the new few-shot graph classification task, there are still fundamental difficulties in using the existing methods. In this paper, a novel loss function compared with prototype networks is proposed which takes both inter-class and intra-class distance into account, is applied to solve the problem of graph classification under the condition of few samples. In addition, combined with the existing idea of considering the structural features of graphs, using this idea can extract a more accurate representation of graph sample features, so as to improve the classification accuracy of the model. Extensive experiments on two data sets Chembl and TRIANGLES verify the effectiveness of our proposed method.
A New Black Widow Algorithm for Discontinuous Optimization in Cloud Task Environment
Authors: You Die , Zheng WenYi , Chen Yong 
Published: June 2022

Abstract
Task scheduling in cloud environment has received extensive attention due to its complex characteristics, and most of the previous methods ignore the discontinuity problem of workflow scheduling. Therefore, a new black widow optimization algorithm (NBWO) is proposed. NBWO proposed a new reproductive strategy to select excellent male individuals and female individuals to obtain better offspring. In NBWO, the number of female individuals is fixed, and males obtain mating rights through competition; NBWO improves the mutation strategy, which makes the exploration ability and development ability of the algorithm more balanced. Applying NBWO to cloud computing task scheduling, the experimental results show that NBWO has excellent performance in dealing with discontinuous optimization problems.
Development and application of data mining method for synthetic aperture radar image ship inspection based on big data application technology
Authors: Chang Ruili 
Published: June 2022

Abstract
Synthetic aperture radar belongs to the radar signal working in microwave band, which has the characteristics of strong penetrating performance, large area imaging, all-weather and so on, and is widely used in the civil field and military field. Especially in the background of the information era, synthetic aperture radar imaging technology has developed to different degrees, and the resolution of synthetic aperture radar images has been significantly improved, which is highly valued by the target detection field, and the detection of naval targets through the reasonable use of synthetic aperture radar images has become an important application direction in the field of marine remote sensing. Based on this, this paper analyzes the characteristics of ship targets in SAR images, analyzes the differences between them and optical images from different aspects, and then concentrates on the most common statistical models and prediction methods of clutter analysis in SAR images, proposes the most reasonable way of clutter distribution simulation, and then uses the experimental way to accurately evaluate the complex sea clutter in SAR images, so as to propose the similar characteristics of the ship detection method‥
Design of low-power CIC decimation filter based on nibble serial arithmetic
Authors: Gao Min , Yu Zongguang , Wan Shuqin , Shao Jie 
Published: June 2022

Abstract
Aiming at the problem of large area and high power consumption of traditional CIC (Cascade Integral Comb Filter) decimation filter, a folded multistage cascade CIC decimation filter is designed. The nibble-serial arithmetic and multiplexing technology are used to reduce the operation and storage logic unit, lower the cost and improve the utilization efficiency of system resources. The folded multistage cascade CIC decimation filter has a programmable structure of down sampling factor and can dynamically realize 1∼16 times extraction. It is suitable for communication systems with multiple channel bandwidths. In addition, the designed truncation module can optimize the effective accuracy of the final stage output.
Power Grid Multi-protocol Network Topology Based on Data Exchange Strategy
Authors: Qian Kejun , Li Yafei , Liu Yi , Zheng Zhong 
Published: June 2022

Abstract
With the combination of Internet of Things technology and smart grid, there are more and more application scenarios of Internet of Things in power system, which makes the whole power system more informationized and intelligent. In this paper, an intelligent data switching technology for power communication network based on multi-protocol label is proposed. The link structure model of mobile core network is constructed, and the TDMA protocol of the multi-protocol intelligent data switching node is designed by using route detection method. The dynamic routing decision and node rotation scheduling of the mobile core network are realized, and the intelligent data exchange performance is improved. Finally, the simulation experiment of the intelligent data exchange protocol is carried out, and the comparative experiment between the proposed method and other methods is carried out, which shows the superior performance of the proposed method in improving the intelligent data exchange capability of the mobile core network.