bluuebunny/crossref_metadata_2025_split huggingface dataset:
According the data analyse to study of the Frost Resistance of Corrugated Metal Pipe Culverts in Permafrost Regions
Authors: Wang Xu , Yu Tianlai 
Published: February 2023

Abstract
In this paper, we mainly studied the stress variation law of corrugated pipe culvert in permafrost regions under the influence of external load and temperature field, and formulated the corresponding experimental arrangement and observation scheme, in order to reveal the mechanical characteristics and action mechanism of corrugated metal pipe culverts.At the same time, we studied the law of the upper limit variation of permafrost foundation under corrugated pipe culvert, established the finite element model of corrugated pipe culverts, and for which we conducted mechanical analysis, frost heave analysis, and solution(thawing) settlement analysis; measured the variation of earth pressure and temperature field around pipe wall during and after filling soil.
Research on the generalization of resident load Identification based on Hybrid Branch Network
Authors: Tan Zhukui , Xu Yutao , Xiao Xiaobing , Zhang Qiuyan , Liu Bin 
Published: February 2023

Abstract
Household energy consumption has become an important part of energy consumption, and improving its utilization plays an important role in solving the global energy crisis. As an effective means, load identification technology promotes energy saving on the user side by providing detailed power consumption information. In this paper, aiming at the generalization of power supply voltage fluctuation in load identification, electrical appliances are classified into four categories: time-varying load, linear load, constant power load, and other nonlinear loads. A load identification model with many kinds of neural network branches is proposed. According to the characteristic differences of different types of loads, different branches are selected for different types of electrical appliances for identification. Finally, compared with the recognition accuracy of other common models in different environments, it is concluded that the method in this paper has higher recognition ability and generalization ability.
Neural Networks with the Correlative Layer for Multi-label Classification
Authors: Liang Lixin , Li Ning , Li Yihong , Lin Lin 
Published: February 2023

Abstract
Multi-label classification is a very significant but challenging task. Correlation between labels often exists, so recent works have paid much attention to using the correlation between labels to improve the classification performance. However, how to effectively learn the correlation is still a problem. In this paper, a general framework, i.e., the neural network with the correlative layer (CLNN), is proposed, where the correlative layer is used to express the dependencies between labels. Different from existing work, CLNN first trains a neural network without the correlative layer to obtain rough classification results and then trains the whole neural network to adaptively adjust all the weights including those of the correlation layer. Thus CLNN could learn both positive/negative and strong/weak relationships between labels. We test CLNN with three typical neural networks, and experimental results show that neural network can achieve better performance by adding the correlative layer, which demonstrates that the CLNN framework is very effective.
Statistical Learning Based Wireless Channel Parameter Estimation for Power Internet of Things
Authors: Tan Chong , Chen Jinshan , Sun Xin , Qi Qi 
Published: February 2023

Abstract
With the rapid increase in the number of sensors in Power Internet of Things (PIOT), the data volume surges and efficient communications are needed. Precise estimation of delay spread is critical to improve the communication performance. In this paper, we propose a statistical learning (SL) based root mean square delay spread (RMSDS) estimation method, which consists of offline training and online estimation. During the offline training process, the instantaneous delay spread (IDS) for each data frame is firstly computed based on the known pilots. The acquired IDS is a random variable and its statistical parameter is related to the actual RMSDS, which is preset and known during offline training. Then, the functional relationship between the statistical parameter and the preset RMSDS is acquired through the SL algorithm. The acquired functional relationship can be used in the online estimation process to accurately estimate the RMSDS. Simulation results indicate that the proposed method can accurately estimate the RMSDS and greatly improve the bit error rate performance.
Research on Intelligent Elevator Based on ZigBee
Authors: Wang Lei 
Published: February 2023

Abstract
With the rapid increase of the number of elevators, the safety of elevators has attracted more and more attention of the public. How to improve the safety of elevators and how to reduce the occurrence of elevator failures has become the focus of attention of all parties.With the development of science and technology and the continuous improvement of the intelligent degree of elevator, intelligent elevator comes into being.This paper proposes a ZigBee-based intelligent elevator and its management method, aiming to help the elevator supervision department, user unit, maintenance unit, insurance company, ect., establish a new elevator use management mode, and reduce the occurrence of accidents such as elevator failure.
Application of terahertz spectroscopy in medical microbiological detection
Authors: Ruan Xiaohu , Ruan Xiaofu , Huang Hai 
Published: February 2023

Abstract
In recent years, pathogenic bacteria and other microorganisms are still a very important aspect of human health. Nowadays, with the rapid development of information science, it has become a new research idea to explore scientific problems from the perspective of interdisciplinary integration. The research on the biomedical application of Terahertz (THz) wave is a hot frontier of the intersection between physical optics and bio-medicine. Based on the background of terahertz spectrum application, this paper introduces the application and progress of terahertz technology in medical microorganism detection, analyzes the characteristics of terahertz and the application technology in medical microorganism detection. Secondly, it tries to comprehensively summarize the application research results of terahertz technology in the field of microbial bio-medicine. Finally, it analyzes and prospects the shortcomings and advantages of the application of terahertz technology in the field of biomedical science.
A time-space coding metasurface and potential applications
Authors: Zhang Zhongzheng , Li Hongwei , Noman Khandaker , Li Yongbo 
Published: February 2023

Abstract
Compared with the deepening development of time-space coding metasurfaces in the electromagnetic and acoustic field, the research on time-space coding metasurface in the field of elastic vibration is still in the infancy. In order to enrich the designed schemes of spatiotemporal coding for elastic vibration, a time-space coding metasurface based on the random modulation strategy of wavefront phase is proposed in this paper. Compared with traditional homogeneous materials with highly correlated vibration transmission, the proposed coding metasurfaces with homogeneous materials realizes extremely low correlated vibration transmission in different vibration directions, which provides a physical realization for the measurement matrix in compression sensing. Furthermore, combined with compressed sensing technology, the potential application value of the proposed time-space coding metasurfaces in single-sensor vibration location and impact identification is verified through simulation.
Research and application of deep learning in image recognition
Authors: Zhao Xingzhi 
Published: February 2023

Abstract
In recent years, deep learning technology has been one of the most important representatives of progress in the field of artificial intelligence technology in China. It has made great achievements in many fields, such as language recognition, natural language processing, image processing and video analysis. This paper further discusses the application research and practice of deep learning technology in modern digital image recognition. Deep learning technology has played a more and more important role in modern digital image recognition.
Research on PMSM control system based on high order sliding mode method
Authors: Wang Zhicheng , Li Zhiyuan 
Published: February 2023

Abstract
A high-order sliding mode viewer using the stator current and rotor magnetic chain as state quantities is designed and implemented, which is based on the fourth-order state equation and can directly output the observed values of the rotor magnetic chain. To avoid the phase change of the magnetic chain due to the introduction of a low-pass filter, a vector equation of state filtering method is proposed to filter the dither signal through the magnetic chain equation by taking the observed deviation of the current as the sliding mode surface and inputting the equivalent control signal directly into the magnetic chain equation. Simulation results show that the designed extended sliding mode observer is able to accurately estimate the rotor position and speed at lower speeds without accurate compensation of the observed values for rotor information collection present in the counter potential and the rotor magnetic chain. The sensorless vector control system is characterized by robustness, wide speed range, and higher feasibility and effectiveness.
Research on non-time-series data filling methods based on feature evaluation
Authors: Yang Fengyu , Fan Yongjian , Xie Lingze , Zhong Yihui 
Published: February 2023

Abstract
With the rapid development of the information age, a large amount of data is used in popular research areas such as data mining. Missing data has a very serious impact on both the process and the result of data mining, and it is important to find out how to fill the missing values accurately and efficiently. In this paper, we propose a method to optimally fill the missing values based on the backpropagation of evaluation functions for non-time-series data. Based on both the target value error and its own error after filling, four classical filling methods, namely mean, interpolation, model prediction, and K-nearest neighbor, are considered for selection. Finally, single-model padding and multi-model weighted padding schemes are compared, and the results show that the padding method with the highest fitness value is selected to work best for data with different degrees of missingness in different datasets.
3D Laser Scanning Acquisition and Modeling of Tunnel Engineering Point Cloud Data
Authors: Shi Fangzhe , Yang Jingxin , Li Qiuyi , He Junjie , Chen Boning 
Published: February 2023

Abstract
For tunnel deformation analysis using traditional measurement methods to obtain tunnel section data, there are problems such as small data coverage and low efficiency. 3D laser scanning technology has the advantages of automatic, high precision and high efficiency in collecting the point cloud data of the target object, and can completely and accurately express the target entity. Based on the tunnel point cloud acquired by 3D laser scanner, the tunnel engineering modeling research is carried out in this paper. Firstly, the engineering survey and 3D reconstruction technology of shield tunnel were carried out based on 3D laser scanning technology. The total station layout control was used to scan the subway platform and tunnel interval, and the high-precision laser point cloud data were obtained. Secondly, a random sampling consistency algorithm is proposed to extract engineering measurement results such as tunnel axis and cross section. Finally, the 3D modeling of the tunnel is established by using the stretching setting out modeling method. Taking Yuzhu Tunnel planning and acceptance project as an example, the experimental results show that the method can effectively visualize the overall deformation of the tunnel, and provide accurate and scientific spatial data for tunnel engineering measurement, operation and maintenance.
Research on the Development and Application of Acoustic Testing Technology
Authors: Liu Feng 
Published: February 2023

Abstract
Taking the commonly used acoustic detection technology as the research object, the working principle of different types of acoustic detection technology and the application of adverse geological forecasting and nondestructive testing in the geotechnical field are described, and the advantages and disadvantages of different types of acoustic detection technology are pointed out through the discussion of the development of acoustic detection technology.
Research on Multi-axis Synchronous Test Technology based on GLINK Bus
Authors: Yu Zikou , Shen Li , Liang Yuchen , Guo Yunqi , Li Zhanye , Zhang Xian , Kang Ping 
Published: February 2023

Abstract
As a rocket engine for thrust vector control system of high reliability and redundancy, high precision, and the requirements of lightweight, servo system for test system can quickly test a certain level and fast data processing of the test location, transient, and frequency characteristic indexes, a rocket motor thrust vector control system using GLINK as control bus. Moreover, the first level servo is an all-in-one machine with four drives and controls, so the test system is required to have the ability to control and test four actuators simultaneously under the GLINK main line. This paper discusses the hardware knowledge of the test system based on the GLINK bus: GLINK bus technology, communication topology of GLINK station card and network card; software function of the test system; multi-axis synchronous test function, and synchronous data processing function developed by LabVIEW.
Ultra-short-term PV prediction based on LSTM with a multi-head attention mechanism
Authors: Zhu Xiaoming , Wang Liang , Gu Jiaru , Wang Peng , Tang Jigang , Hao Jinbao , Xiang Min , Lu Yangwen , Lu Xincheng 
Published: February 2023

Abstract
With the increasing penetration and installation of renewable energy such as photovoltaic (PV) generation, ultra-short-term PV output prediction is necessary to guarantee the stability of the power system. However, the traditional methods cannot capture the important features of PV power data, and prediction accuracy cannot be guaranteed. Focusing on these problems, this paper presents a novel PV prediction method based on LSTM with a multi-head attention mechanism. The mechanism can make the matrix operation run in parallel. At the same time, the model assigns weight to different features of the input data to improve the prediction. To show the effectiveness, this paper constructs four scale types for PV power prediction. Case studies show that the multi-head attention mechanism can improve the prediction performance, and the prediction accuracy decreases following the increase of time scale.
Analysis of Impurities in Sulfur Hexafluoride Gas via Gas Chromatography Based on Enhanced Plasma Detector
Authors: Luo Zongchang , Zhang Longfei , Tang Bin , Liang Qinqin , Pan Jiqi , Hu Mengzhu 
Published: February 2023

Abstract
An analytical method for detecting impurities in high-purity sulfur hexafluoride (SF6) gas is established by using gas chromatography (GC) based on the enhanced plasma detector (EPD). The concentration of impurities (hydrogen, oxygen, nitrogen, methane, carbon monoxide, carbon dioxide, carbon tetrafluoride, hexafluoroethane, and octafluoropropane) can be quantitatively detected through one-time sampling and external standard method, and the minimum detection limit of each component is calculated to be about 0.1ppm, the RSD of the test results is less than 3%. This method can meet the requirements of detecting the purity of SF6 gas used in electrical equipment.
Research on the Automatic Control System of Coolant Circulation in Laboratory
Authors: Li Xin , Tian Xiaodi , Zhai Guifei , Liu Jixu 
Published: February 2023

Abstract
This paper introduces a design method of an automatic control system for coolant circulation in the laboratory, which can use a “pneumatic pump + valve control” manual in place of “manual pressing + manual liquid filling + manual collection”. Then this paper analyzes the system principle and has carried out the application in a practical laboratory, which had solved the problems of low efficiency, environmental pollution, and waste of resources of the existing manual operation mode.
Target Recognition Network Based on Improved Convolutional Regression Network
Authors: Zhang Shuang , Song Jinyu , Li Weiwei 
Published: February 2023

Abstract
For refine the regression precision and speed of convolutional neural recognition network, propose improved detection and identification algorithm on the basis of deep learning algorithms, mainly aiming at improving the accuracy and speed of regression prediction of target recognition. Firstly, the acquired images are preprocessed in batches to obtain image datasets with different sizes of detection objects, that is, the enhancement of small sample images. Secondly, the one-stage target detection network SSD algorithm is improved. ResNet50 network is used to extract features, while FPN is fused with the main algorithm to ameliorate the detection network, which purpose is to improve the target detection accuracy. The test results on remote sensing datasets show that the actual accuracy was elevated to about 0.9% compared to the conventional algorithm. The speed in the actual measurement is also increased by 0.6 frame/s.
Baihetan - Jiangsu engineering soil and water conservation online monitoring data system
Authors: Lei Lei , Song Ji Ming , Wang Jin , Hai Zheng Shu , Yi Li Feng , Wan Hao 
Published: February 2023

Abstract
Baihetan - Jiangsu ± 800kV UHVDC project can improve the power supply stability of the hydropower station, which has very important economic significance. The construction of power transmission projects will affect the water and soil conservation situation along the site. Currently, the commonly used monitoring methods are based on manual data collection with low accuracy and a large workload. Therefore, the government vigorously promotes the development of intelligent water conservancy and strives to improve the digitalization degree of water and soil monitoring systems. In this paper, the traditional chain pin method was improved, using the photosensitive chain pin and ultrasonic chain pin instead of the ordinary chain pin. Then calculated the soil erosion modulus by collecting the soil loss index of the measured point, and uploading it to the cloud for analysis by the radio transmission device, so that the monitor system obtained accurate soil loss data. Finally, the system is applied to the baihetan-Jiangsu soil and water conservation monitoring project, and the monitoring data of soil and water conservation of the two stations are obtained. Combined with the local meteorological conditions, we can analyze the causes of soil and water loss, and give the corresponding prevention measures.
Design of Multi-sensor Fusion Positioning and Navigation Method Based on Federated Kalman Filter for Low-Speed Rotorcraft of Atmospheric Detection
Authors: Yu Binggang , Chen Lei , Fatin Fatihur Rahman Mohammad 
Published: February 2023

Abstract
A rotorcraft needs to accurately sample the predetermined path at a low flight rate when performing atmospheric sounding tasks; thus, it is particularly critical to obtain accurate positioning and navigation information in real-time. Hence, this paper designs a multi-sensor fusion positioning and navigation algorithm for atmospheric detection of low-speed rotorcraft. The multi-sensor fusion positioning and navigation algorithm for velocity and spatial position are presented based on the Federated Kalman Filter combined with the accelerometer, Global Positioning System (GPS), and barometer. The experimental results show that the fusion algorithm result of the velocity and spatial position is closer to the actual position than a single sensor. In conclusion, this paper’s multi-sensor fusion positioning and navigation algorithm overcomes the problems of low positioning accuracy of a single sensor and cumulative errors and effectively improves positioning accuracy, real-time, and stability.
Research on Tip Clearance Measurement Technology of Aero-engine Blade Based on Optical Fiber Sensing System
Authors: Ma Huiping , Wang Xiaoming , Zhang Xiaoguang , Liu Yongmeng 
Published: February 2023

Abstract
A novel non-contact detecting method of aero-engine blade tip clearance based on an optical fiber sensing system is presented. To eliminate the sensor measurement error caused by the slight change of the reflectivity value of the mechanical end face when the light source angle fluctuates and rotates, a three-coil coaxial fiber bundle sensor is proposed. Relevant experimental results show that the system has the advantages of high measurement sensitivity, small sensing probe volume, strong electromagnetic interference resistance, and high reliability. The application of this technology provides an effective method for dynamic radial gap detection of high-speed rotating machinery.
Study on Measurement Method of β Radioactivity in Environmental Water by Liquid Scintillation Spectrometers
Authors: Qi Yelin , Lai Yongfang , Zhang Xuan , Huang Weiqi 
Published: February 2023

Abstract
Compared with other methods for measuring radioactivity in water, liquid scintillation measurement has the outstanding advantages of fast sample pretreatment, simple measurement method and high detection efficiency. Based on liquid scintillation spectrometer (SIM-MAX LSA3000B), 14C and 90Sr-90Y are selected as typical nuclides to study the change of TDCR quenching correction curve under different activity concentrations, and the basic method for measuring radioactive water samples with different activity concentrations is proposed, which is applied to the measurement of lake water, mountain spring water, tap water, mineral water and rainwater. The measurement results show that the total time of this method is less than 60 minutes, and the measurement error is less than 20%, which is obviously superior to the existing water sample radioactivity measurement method under nuclear emergency conditions.
Research on Time Synchronization and Spatial Calibration Algorithms of Radar and Camera
Authors: Song Shiping , Dong Changqing , Qin Kongjian , Hou Xintian , Zhao Xiong , Tian Xiaodi , Wang HuaSen 
Published: February 2023

Abstract
The intelligent connected vehicle can detect 360° full coverage around the vehicle by installing multiple radars and cameras. However, the sampling frequency of each sensor is different and each sensor outputs the target motion state information based on its coordinate system. the accurate and rapid realization of time synchronization and spatial position alignment between sensors is very important for multi-sensor data fusion. This paper presents a method of radar and camera time synchronization based on least squares cubic spline curve fitting. Based on time synchronization, a fast space joint calibration method of radar and camera is proposed based on the longitudinal symmetry plane of the vehicle. The validation data of the target object show that the proposed algorithm is accurate and simple.