bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on Human Pose Estimation Based on High-resolution Network
Authors: Ji Xu , Niu Yanmin 
Published: November 2023

Abstract
The problem addressed in this paper is the increase in the parameter quantity of existing human body pose estimation network models when the depth of the network is scaled up to improve forecast precision. To tackle this issue, an optimization network model of the new human body pose estimation called BDENet is proposed, inspired by high-resolution detection networks. This model incorporates a bottleneck structure and dilated convolution to reduce parameters and incorporates the ECA lightweight attention mechanism to enhance precision. Compared with HRNet, the proposed model achieves a 21.4% reduction in parameter quantity on the MSCOCO dataset while scaling up precision by 1.4%. The experimental findings strongly suggest that the modified network significantly improves network precision along with lowering the number of parameters.
Temporal-difference Adaptive Graph Convolutional Network for Skeleton-based Action Recognition
Authors: Liu Fuchun , Huang Shengfeng 
Published: November 2023

Abstract
In action recognition based on the skeleton, graph convolutional networks (GCNs) have shown great superiority based on the design of making the skeleton in the video a spatiotemporal map and extracting features from the spatiotemporal map. However, the topology of the skeleton in GCN-based methods is pre-designed according to prior knowledge, which limits the capacity of the network to learn high-level topology about the skeleton. To improve this deficiency, we design a temporal-difference adaptive graph convolutional network (TDA-GCN) that can learn the potential topology of the human skeleton from the input data, which is augmented using the channel attention module. Experiments show that TDA-GCN achieves state-of-the-art performance on two large-scale skeleton datasets, NTU-RGBD and Kinetics-Skeleton.
Fisheries Water Quality Monitoring Improvement System
Authors: Jia Junle , Luo Chun , Hou Zhengyi , Xia Qiqi , Ma Xuanhang , Pan Xiang , Ma Awen , Zheng Yuru 
Published: November 2023

Abstract
In this paper, the system of dynamic identification and monitoring of water bodies and intelligent allocation of pharmaceutical discharge is designed. At present, aquaculture technology in our country is relatively traditional, and the water environment-bearing capacity will often be ignored. This paper aims to realize the efficiency of equipment in the multiple stages of aquaculture through the design system, the remote control of motion software device, and strive to combine intelligent equipment and the basic process of aquaculture, so as to make the aquaculture industry gradually upgrade. Through the test, our device can dynamically identify and detect the water body, and ensure the fishery output and water quality at the same time, bringing economic and environmental benefits to a great extent.
An airborne object detection and location system based on deep inference
Authors: Hu Xiao , Pan Shenfu , Li Dongdong , Feng Long , Zhao Yuan 
Published: November 2023

Abstract
In recent years, with the development of sensors, communication networks, and deep learning, drones have been widely used in the field of object detection, tracking, and positioning. However, there are inefficient task execution and some complex algorithms still need to rely on large servers, which is intolerable in rescue and traffic scheduling tasks. Designing fast algorithms that can run on the airborne computer can effectively solve the problem. In this paper, an object detection and location system for drones is proposed. We combine the improved object detection algorithm ST-YOLO based on YOLOX and Swin Transformer with the visual positioning algorithm and deploy it on the airborne end by using TensorRT to realize the detection and location of objects during the flight of the drone. Field experiments show that the established system and algorithm are effective.
Design and Research of AGV Indoor Positioning System Based on Visual and Ultra Wideband Combination Positioning
Authors: Li Xudong , Wu Ruiming 
Published: November 2023

Abstract
Aiming at the problems of cumulative error in monocular visual positioning and Non-Line-of-Sight (NLOS) error in UWB positioning for the automated guided vehicle (AGV) in indoor environments, a combined method of vision and Ultra-Wide Band (UWB) is proposed for indoor AGV positioning. Firstly, the overall structure and system of the AGV are designed to achieve indoor navigation and positioning functions. Secondly, the monocular visual and UWB positioning data are fused using the Error State-Extended Kalman Filter algorithm (ES-EKF) to obtain the optimal pose estimation of the AGV. Finally, the AGV is used as a mobile platform to conduct positioning experiments in different indoor environments. The experimental results demonstrate that the navigation and positioning system has high accuracy and robustness in indoor environments with obstacles, and no significant drift or discontinuity phenomena occur during the positioning process, indicating its practicality in indoor settings.
English Pronunciation Quality Evaluation System Based on Continuous Speech Recognition Technology for Multi-Terminal
Authors: Wu Xianxian , Zhang Yan , Feng Bin 
Published: November 2023

Abstract
This paper presents a novel approach for evaluating the pronunciation quality of English speech using continuous speech recognition technology. The research focuses on the application of artificial intelligence in speech recognition, utilizing web browsers on various terminal devices such as computers, mobile phones, and tablets to allow users to read the provided text aloud. The web program captures audio input from the microphone, records it in MP3 format, and uploads it to the server. The server employs the Whisper model to transcribe the audio into semantic text, which is then compared with the displayed text. By calculating the semantic distance and assessing the accuracy of pronunciation, the system provides an evaluation of pronunciation quality, marking correct and incorrect words. To achieve real-time processing, the compact tiny model is employed, and further optimization is performed using Ctranslate 2, resulting in significant performance improvements.
Development of a Testing System for High-efficiency Power Recovery Bag Accumulators
Authors: Hao Weigu , Ma Donghui , Xing Keli 
Published: November 2023

Abstract
Currently, most of the bladder-type accumulator test benches used have problems such as large installed capacity, severe energy loss, and incomplete testing functions. This article focuses on the research of the testing requirements and power recovery issues of bladder-type accumulators. A new type of hydraulic schematic and electrical control system for power recovery bladder type accumulator testing based on mechanical compensation with dual output shaft motor transmission, differential charging and discharging of dual accumulators, and parallel addition of oil replenishing accumulators has been designed. A measurement and control software based on the LabVIEW platform has been developed. The experimental results show that the system’s power recovery efficiency can reach 60.5% by adopting a scheme of mechanical compensation type power recovery, differential charging and discharging of energy accumulator group, and parallel addition of oil replenishing energy accumulator. The testing system can accurately, efficiently, and conveniently complete various performance tests of hydraulic bladder accumulators.
Noise Reduction of TBM Big Tunneling Data by Butterworth Filter
Authors: Xiao Haohan , Zheng Lifeng , Zhang Di 
Published: November 2023

Abstract
The location of a Tunnel Boring Machine (TBM) is prone to external environmental and internal system noise interference. To address TBM vibration characteristics, this study analyzed the sources of excavation data noise, the need for noise reduction, and the methods used, using excavation speed as the prime example. We validated the results through three actual tunnel projects. Our research showed that excavation parameters automatically collected by the TBM, such as excavation speed, cutter head thrust, and cutter head torque, contain noise and require filtering and noise reduction before data mining. Different cutoff frequencies correspond to varying filtering effects, and after considering both smoothness and accuracy, we recommend setting the Butterworth filter’s cutoff frequency to 0.1.
RGB and LiDAR Fusion-based 3D Semantic Segmentation for Autonomous Driving
Authors: Liu Jianguo , Jia Zhiling , Li Gongbo , Yan Fuwu , Wu Youhua , Sun Yunfei 
Published: November 2023

Abstract
Projection-based multimodal 3D semantic segmentation methods suffer from information loss during the point cloud projection process. This issue becomes more prominent for small objects. Moreover, the alignment of sparse target features with the corresponding object features in the camera image during the fusion process is inaccurate, leading to low segmentation accuracy for small objects. Therefore, we propose an attention-based multimodal feature alignment and fusion network module. This module aggregates features in spatial directions and generates attention matrices. Through this transformation, the module could capture remote dependencies of features in one spatial direction. This helps our network precisely locate objects and establish relationships between similar features. It enables the adaptive alignment of sparse target features with the corresponding object features in the camera image, resulting in a better fusion of the two modalities. We validate our method on the nuScenes-lidar seg dataset. Our CAFNet achieves an improvement in segmentation accuracy for small objects with fewer points compared to the baseline network, such as bicycles (6% improvement), pedestrians (2.1% improvement), and traffic cones (0.9% improvement).
Research and Implementation of 3D Object Detection Based on Autonomous Driving Scenarios
Authors: Chen Xi 
Published: November 2023

Abstract
Perception function, as an important part of autonomous driving, ensures the safety and intelligence of driving. We collect the surrounding environment of driving through hardware sensors, providing a basis for subsequent decision-making of autonomous driving. In recent years, deep learning has made breakthrough progress in object detection. Based on this, this paper uses lidar point cloud data, combined with deep learning theory and method, to carry out three-dimensional target detection tasks around lidar point cloud data, and carries out theoretical analysis, method verification, and result analysis. A 3D object detection method based on LiDAR point cloud data is proposed. The backbone network of the network model corresponding to the method is VoxelNet’s backbone network. After outputting the feature matrix, sparse point clouds are supplemented with point clouds, and then the feature matrix is decoded to generate candidate boxes. The model used in this paper on the KITTI data set can effectively solve the problem of 3D target detection in the process of autonomous driving and has good performance.
Research of a novel aerodynamic evaluation method for fixed-wing UAV
Authors: Wu Yansen , Liu Deshan , Wang Tiancheng , Zhao Anmin 
Published: November 2023

Abstract
The aerodynamic parameters of unmanned aerial vehicles (UAVs) play an important role in the newly designed drone. For the purpose of the real-time measurement of the aerodynamic performance parameters of the UAV in flight status, based on the self-development connected-wing configuration airplane, a novel airborne aerodynamics test scheme is researched and verified in this work. The findings of this study indicate that the effectiveness of numerical calculations can be verified by comparison with both results of the numerical simulation and airborne flight test in the same conditions. The newly designed UAV equipped with this test system in the future, not only achieves quick and reliable results of aerodynamic performance and powered system efficiency but also can save the expense of wind tunnel experiments, which is of high potential to the UAV application.
Performance optimization design of wide-body aircraft pressure refueling system
Authors: Gong Hao 
Published: November 2023

Abstract
In order to reduce the wide body aircraft refueling process time-cost and improve the airport operation efficiency, pressure refueling system design strategy was innovated. The shutoff valves’ operation sequence in refueling process was optimized. The diameter of the orifices on the pressure refueling system fuel line was designed. Pressure refueling performance was simulated and analyzed at different scenarios. The results show that it can improve the pressure refueling system performance at different scenarios by optimizing the pressure refueling process strategy design including optimizing the fuel line orifice design and optimizing the wing tank inner side shut-off valve operation sequence.
Research on solar sail attitude maneuvering method based on adaptive sliding mode control
Authors: Wang Jie , Ma Tianyi , Song Haibo , Yu Ye 
Published: November 2023

Abstract
A solar sail is a spacecraft propulsion system that uses the pressure of light to push a spacecraft. It consists of a lightweight support structure that deploys a large area of flexible film. During attitude maneuvering in space, the solar sail will excite vibrations in the flexible support structure and film, which can affect the accuracy of the attitude control system. To address this issue, this article first establishes a rigid-flexible coupled dynamic model of the solar sail that includes attitude motion and flexible structure elastic vibrations. Then, based on an adaptive sliding mode control method, a solar sail attitude maneuvering method is proposed. Finally, a numerical simulation is conducted using a hexagonal-shaped solar sail as the object. The numerical simulation results show that the attitude maneuvering method has the performance of attitude tracking and attitude stabilization, can meet the requirements of large-angle attitude maneuvering for solar sail spacecraft, and has strong robustness to model parameter uncertainty.
Research on radial velocity and airspace position calculations of target in airborne active radar simulation
Authors: Zhang Wenguo , Gan Hanghua , Pan Xin , Tian Feng , Pan Li , Shao Peng , Jiang Xiangle , Zou Xiaobin 
Published: November 2023

Abstract
The detection of the target in the airborne active radar simulation is simplified to the calculations of the radial velocity, the maximum detecting range of the airborne active radar corresponding to the RCS, and the airspace position of the target. However, the coordinate transformations related to the calculations of the radial velocity and the airspace position are usually bewildering due to the different referenced coordinate systems. This paper introduces the radial velocity and airspace position calculations of the target in the airborne active radar simulation to illuminate the transformation process containing the specific rotation matrices, suggesting the unifying transformation to the north-up-east (NUE) rectangular coordinate system of the aircraft for both the radial velocity calculation and airspace position calculation of the target.
Effect of oxygen rich environment on detonation characteristics of pulse detonation engine
Authors: Yang M F , Qi S B , Bai H B , Gao S Y , Song J , Hu B W , Xu Z 
Published: November 2023

Abstract
The detonation tests of propane/air pulse detonation engine at normal temperature were carried out in this paper. The effects of chemical ratios on the detonation performance of propane/air pulse detonation engine in oxygen-rich environment were studied. The propagation modes and characteristics of detonation waves and the detonation characteristics of the engine under different conditions were analyzed. Detonation tests were conducted on propane/air mixtures with oxygen mass fraction of 20%, 25%, 30% and 35% respectively. The results showed that: In the detonation experiment of the propane/air mixture with oxygen content of 20%, 25% and 30%, the flame wave propagation velocity in the detonation tube is low, which fails to form a stable detonation wave. The detonation effect of the fuel mixture with oxygen content of 20% is the worst, and the propagation velocity of flame wave is 384.00 m/s. In the experiment of propane/air mixture with oxygen content of 35%, the detonation velocity and pressure obtained by pressure signal analysis are both greater than the theoretical CJ detonation velocity, and the detonation state is successfully reached.
Numerical simulation of rebar corrosion in track bed of shield tunnel under stray current
Authors: Yu Shuo , Sun Huajun , Wang Zijuan , Liu Changbao 
Published: November 2023

Abstract
Track bed is the important support structure at the bottom of shield tunnel, during metro operation, the leakage of stray current will lead to corrosion of rebar in the track bed, which will affect the safe operation of metro. In this paper, the corrosion calculation model of track bed rebar under stray current is established, and the effects of stray current input mode and concrete resistivity on the corrosion rate of track bed rebar are studied. The result shows the corrosion rate of track bed rebar decreases nonlinearly with the increase of concrete resistivity, and the reduction gradient of corrosion rate in bilateral input mode is greater than that in unilateral input mode. With the decrease of concrete resistance, the corrosion area will cover the left half in unilateral input mode and cover both ends of track bed rebar in bilateral input mode. When the input point voltage increases by 40%, the corrosion current density in the middle of track bed will increase by about 61%.
Mixed Horizontal Well Pattern and Fracturing Parameter Optimization of Low Permeability Reservoir
Authors: Hu Qi-hao , Guo Fa-jun , Cao Hong-qiang , Wang Xiu-wei , Wang Ya-zhou , Wang Xia , Wang Hong-tao , Cao Jie-feng 
Published: November 2023

Abstract
Horizontal well fracturing development is significant in improving the development effect of low permeability reservoirs and is widely applied in many low permeability reservoirs of China. In this study, the reservoir numerical simulation is used to establish different mixed horizontal well networks of the target reservoir. The result shows that the best waterflood development effect is achieved when horizontal segment orientation and crack orientation are at an angle of 45°. The horizontal segment length and fracturing parameters of mixed horizontal well networks are optimized. It is considered that the rational horizontal segment length of the horizontal well is 400 m, the rational number of cracks is 3, and the optimal crack conductivity is between 180-200 mD.m. Through the study of mixed horizontal well network and fracturing parameter optimization, the low permeability reservoir efficient horizontal well fracturing development is well guided.
Design and engineering application of a new type of copper bar-embedded metering box based on DFA theory
Authors: Chen Zhiru , Zhao Xi , Zhang Zhi , Jing Zhen 
Published: November 2023

Abstract
Based on the design theory that products can be assembled, the optimal design of the electric energy metering box in the embedded copper bar and other aspects is realized, the product wiring is standardized and concealed, the assembly method is optimized, the assembly difficulty is greatly reduced, several problems in cost and quality are solved in industrial design, and objective score data from experts are obtained through perceptual experiments. It provides a new design method and evaluation idea for the field of power measurement and has great popularization value.
A Method for Estimating the System’s Maximum Effective Reserve under the Electricity Market
Authors: Liu Junlei , Chao Zhu , He Xiangzhen , Bao Bo , Duan Qinwei , Tang Xuchen , Xie Xiangzhong , Chen Huican , Su Xiangyang 
Published: November 2023

Abstract
System’s reserve is one of the important security constrains when conducting the day-ahead clearing calculation. Usually, the reserve requirement is determined by the local dispatching center based on their experience. However, this experience-based threshold may lead to two issues, i.e., the invalid reserve and the slow calculation speed under the electricity market condition. Based on the concept of effective reserve, a method for estimating the system’s maximum effective reserve is proposed in this paper. The main idea is to design an optimization algorithm to determine the operating unit set with the goal of maximizing the system’s effective reserve. The maximum value obtained can help the dispatching center to design the system’s reserve threshold, which is of great engineering significance. Simulation analysis verified the correctness and rationality of the proposed model through comparative analysis of multiple scenarios.
Regional electrical energy substitution potential prediction based on time series and improved back propagation neural network
Authors: Cai Ziwen , Xu Yutao , Xiao Yong , Chen Dunhui , Zhao Yun , Tan Zhukui 
Published: November 2023

Abstract
A combined time-series-based regression forecasting and GRA-IPSO-BP structure is proposed to forecast the electricity replacement forecasts using a time series model based on the triple exponential smoothing forecasting method. The forecast results are corrected using the GRA-IPSO-BP structure. The results of the algorithm show that using a combination of time series and GRA-IPSO-BP structure can significantly improve the forecasting accuracy of electricity replacement compared to single-method forecasting.
Analysis of annual power and electricity balance of hydro-thermal system in Yunnan province based on rolling dispatch with leading reservoir
Authors: Pan Hongyu , Zhao Zhenyu , Zhang Congtong , Chen Kai , Zhou Han , Liu Shuangquan , Yang Qiyu , Jin Tianyu 
Published: November 2023

Abstract
Renewable energy penetration presents challenges for power systems, including unit reconfiguration, resource allocation, and potential electricity shortage. In Yunnan Province, where hydropower is a dominant energy source, annual power and electricity imbalance is a serious issue due to insufficient hydropower regulation capacity and less scheduling flexibility. To address these problems, a rolling dispatch method is proposed to connect medium- and long-term scheduling with short-term scheduling, providing hourly start-stop statuses and output plans for units throughout the year and effectively solving power imbalance issues. Additionally, an economic benefit and electricity shortage analysis of the Longpan leading reservoir in the Jinsha River Basin is conducted, resulting in a 13 billion kWh annual power generation increase and approximately 4 billion yuan in direct economic benefits, greatly improving Yunnan Province’s adjustment ability from dry seasons to wet seasons.