bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pipelined Memristive neural network analog-to-digital converter
Authors: Wang Weihe , Yu Hongqi 
Published: November 2023

Abstract
This paper designs a pipelined memristive neural network ADCs. Cascade the sub stages of memristive neural network ADC with pipeline structure to improve the conversion accuracy of memristive neural network ADC. First, the signal flow of the pipeline architecture is optimized, and the compatibility between the 4 bit memristive neural network ADC and the pipeline architecture is solved. Secondly, the application of random disturbance circuits in pipeline architecture was analyzed. Combining the calibration circuit with the pipeline DAC to reduce the power consumption of the calibration circuit. Finally, the circuit model of memristive neural network ADC is built and compared with the existing memristive neural network ADC. The results indicate that the pipeline structure ADC designed in this chapter has the advantage of adaptive calibration in terms of calibration function.
Spreading Factor and Coding Rate Allocation Method for LoRa Network
Authors: Li Ruyan , Tang Xiaoqing , Xie Guihui 
Published: November 2023

Abstract
Aiming at the problems of frequent packet loss and high energy consumption in large-scale LoRa networks, this paper proposes a joint allocation method of Spreading Factor (SF) and Coding Rate (CR). Firstly, we establish the effect relationship of SF and CR on Frame Error Rate(FER), and pre-allocate SF and CR based on the node position to minimize the energy consumption of the node while meeting the FER requirement. Then, according to the collision model, the collision probability of each SF group is calculated, and the sequential water injection method is used to equalize the collision probability within each SF group, to improve the average packet arrival rate of the entire network. The simulation results show that compared to mainstream algorithms, the proposed algorithm obtains a 13% increment in terms of the network average packet success probability, and a 104% one in terms of the average energy efficiency. The proposed algorithm has high application value in many application scenarios such as smart agriculture and smart cities.
Insulator Defect Detection Method upon Fused Attention Mechanism and Bidirectional Feature Fusion
Authors: Chen Yiming 
Published: November 2023

Abstract
Insulators are important components for achieving electrical insulation and mechanical support, but they are prone to various defects in harsh operating environments, which can damage their mechanical strength and insulation performance. This article proposes the Shuffle YOLOv7 model based on the YOLOv7 algorithm for insulator defect detection, aiming to solve the weakness of low precision in traditional object detection algorithms when facing complex backgrounds and small-sized defects. To address the issue of low attention to flashover faults in traditional algorithms, the ShuffleAttention fusion attention mechanism is supplied to concentrate on both intra-channel and inter-channel deep features, and the original PANet structure is replaced with a pyramid which has a bidirectional feature fusion structure to enhance the network’s feature extraction ability. The Focal-EIOU LOSS optimization method focuses on high-quality prior boxes to improve model accuracy, and the effectiveness of the optimization method is verified through ablation experiments. These results of the experiment show that the proposed algorithm achieves varying degrees of performance improvement in terms of precision, recall, average precision, and overall loss compared to mainstream object detection algorithms in detecting insulator damage and flashover.
Intelligent Vehicle Systematic Design Based on Arduino and Raspberry Pi
Authors: Liu Yulin , Liu Xiaolu , Lu Chunguang , Song Lei , Cui Guoyu , Qian Haifeng , Tan Nick Nianxiong 
Published: November 2023

Abstract
The intelligent vehicle designed in this paper can realize functions, such as safety detection, visual identification, remote control and manipulator grasping, and so on. Arduino MEGA is used as the main control board to send signal messages to drive vehicles. Wi-Fi module is used to receive messages to remote control vehicles. The ultrasonic and infrared module is used to realize object detection around vehicles. To realize complex route movement, raspberry pie is used for visual recognition and path planning. Data is sent to Arduino for judgment in real time. Finally, it is verified that the design effectively improves the path-planning ability and obstacle-avoidance function in a sample vehicle.
Power Equalization Strategy Based on Adaptive Virtual Impedance
Authors: Lv Xiong , Zhang Baoge , Tian Hao , Ren Yongquan , Cui Fuhong 
Published: November 2023

Abstract
Due to the differences in the line resistance of each distributed generation unit, conventional sag control does not allow for precise distribution of power, which also reduces the problem of system reactive power accuracy. To address this problem, this paper analyzes the power equalization and distribution conditions. A method for adaptive adjustment of virtual resistance by system output power feedback is submitted. Reducing the variance among the original line resistances aims to solve the problem of power not being evenly divided and improve the equalization of reactive power. By building a Simulink parallel simulation model of the inverter, it is verified that the power feedback-based fetching and the improved droop control is effective.
Multi-pedestrian Tracking Method Fusing Two-stage Matching
Authors: Deng Xin , Zhao Lijun , Li Ruifeng 
Published: November 2023

Abstract
Multi-pedestrian tracking is one of the hot topics in computer vision. For an intelligent mobile robot, multi-pedestrian tracking from a first-person perspective can provide information for navigating through a crowd and ensure safety. Most of the existing methods cannot deal with occlusion and trajectory overlap well. In this paper, a multi-pedestrian tracking method fusing two-stage matching is proposed. Firstly, the detection and the corresponding feature values of the pedestrians are obtained by a multi-task learning network based on CenterNet. Then the detected pedestrians are matched with feature values by greedy strategy. When dealing with the reappearance of pedestrians caused by occlusion or trajectory overlap, the sample database is established to update the samples in real time. The color histogram and HOG feature are calculated for each sample. When the pedestrian disappears, the direction of disappearance and the last position is recorded for the selection of trajectory. Finally, the KM algorithm is used for cross-frame matching. Our method is compared with some recent methods on MOT data sets. The result shows that our method has a significant improvement in the main evaluation index MOTA.
Face and Background Deepfake Detection Algorithm
Authors: Zhang Xinjun , Liu Jia , Sang Yu 
Published: November 2023

Abstract
The paper proposes the Face and Background Deepfake Detection (FBDD) algorithm to detect both face forgery and background forgery. Multiple key frames of the video are extracted as the input of the FBDD Transformer, and the inter-frame information is also considered to obtain four feature vectors of the person, background, head, and face to improve the detection efficiency and accuracy. FBDD distance is proposed to determine the type of video forgery. Constructing a rich dataset of video forgery methods containing face forgery and background forgery improves the accuracy of the model on different datasets. The FBDD algorithm was experimented on several commonly used and article-constructed datasets and has higher accuracy and stronger image degradation generalization compared to frontier detection algorithms.
Prior Knowledge-guided Hierarchical Action Quality Assessment with 3D Convolution and Attention Mechanism
Authors: Zhou Haoyang , Hou Teng , Li Jitao 
Published: November 2023

Abstract
Recently, there has been a growing interest in the field of computer vision and deep learning regarding a newly emerging problem known as action quality assessment (AQA). However, most researchers still rely on the traditional approach of using models from the video action recognition field. Unfortunately, this approach overlooks crucial features in AQA, such as movement fluency and degree of completion. Alternatively, some researchers have employed the transformer paradigm to capture action details and overall action integrity, but the high computational cost associated with transformers makes them impractical for real-time tasks. Due to the diversity of action types, it is challenging to rely solely on a shared model for quality assessment of various types of actions. To address these issues, we propose a novel network structure for AQA, which is the first to integrate multi-model capabilities through a classification model. Specifically, we utilize a pre-trained I3D model equipped with a self-attention block for classification. This allows us to evaluate various categories of actions using just one model. Furthermore, we introduce self-attention mechanisms and multi-head attention into the traditional convolutional neural network. By systematically replacing the last few layers of the conventional convolutional network, our model gains a greater ability to sense the global coordination of different actions. We have verified the effectiveness of our approach on the AQA-7 dataset. In comparison to other popular models, our model achieves satisfactory performance while maintaining a low computational cost.
Performance Analysis and Vibration Test of Hot Melt Bonder
Authors: Peng Fang , Xu Cheng , Lei Ming , Jiang Xinghui , Kong Xiangrui 
Published: November 2023

Abstract
In this paper, the performance analysis, strength simulation, and vibration test of the structure of the hot-melt bonding machine are carried out. This paper firstly analyzes the structure and performance of the new hot-melt adhesive machine from the functional analysis of the product, then uses the knowledge of mechanical design to analyze the strength and stability of the whole machine, and uses Solid Works to build a three-dimensional model and the simulation software Ansys Workbench. The strength simulation and evaluation of the model were carried out. Finally, the samples were made and vibration tests were carried out. The hot melt adhesive machine has passed the transportation simulation vibration test and met the functional requirements of transportation stability. The simulation and testing methods in this paper provide a technical reference and solution for engineers.
Angle-only Autonomous Terminal Guidance and Navigation Algorithm for Asteroid Defense based on Meta-reinforcement Learning
Authors: Pu Yuhao , Bei Chao 
Published: November 2023

Abstract
This paper presented a robust angle-only guidance and navigation algorithm for asteroid defense missions based on meta-reinforcement learning. A recurrent neural network, trained via proximal policy optimization, is used to map the line-of-sight angles captured in real-time by the onboard camera to the optimal thrust. The neural network effectively replaces the roles of the navigation and guidance system while simultaneously removing the dependence on dynamic and observation models. The guidance and navigation model is tested on numerical simulations of a simulated mission directed to asteroid Bennu. The objective is to enable the spacecraft to hit the asteroid precisely, despite the presence of scattered initial conditions, uncertain model parameters, thruster control error, and attitude control and measurement error.
Optimization and verification of mechanical design for small total reflection optics
Authors: Dong Shuai , Xu Yangbo , Ma Youwei , Li Libin , Han Shengsheng 
Published: November 2023

Abstract
Mechanical performance assurance is one of the key concerns in the design of small total reflection optics. This article addresses the issue of insufficient strength margin in the design of a total reflection optics for a space photoelectric sensor. Firstly, structural design optimization research was conducted on the optics, and the effectiveness of structural improvement was verified through finite element analysis; Secondly, a concave analysis was conducted under mechanical test conditions to further reduce the risk; Afterwards, the accuracy of the simulation results was verified by comparing the simulation with the experiment through small-scale random vibration tests; Finally, sine vibration tests, random vibration tests, shock tests, acceleration tests were conducted on the entire machine, and optical tests were conducted before and after the tests. The experimental and testing results indicate that the entire machine has passed the mechanical test assessment at the appraisal level and maintained good optical performance. The total reflection optics optimized by mechanical design meets the requirements of engineering applications.
Marangoni convection in a C-shape enclosure with partially heated walls
Authors: Siri Zailan , Al ‘Idrus Sharifah Nuriza S M N 
Published: November 2023

Abstract
A numerical study was carried out to investigate Marangoni convection of nanofluid in a C-shape cavity with partially heated walls. The opposite sides of the walls are cooled at constant temperature while the rest of the partitions are kept adiabatic. The governing equations and boundary conditions are then introduced to describe the fluid flow and temperature distribution within the enclosure before the equations are non-dimensionalised and solved using the finite element method. The solutions, presented as streamlines, isotherms, local Nusselt and average Nusselt for varying Marangoni number, Rayleigh number, and depth, are then discussed.
Assessing the potential of CO2 huff ‘n’ puff technology for enhanced oil recovery and CO2 sequestration in tight oil reservoirs
Authors: Yu Longhui , Li Hangyu , Liu Junrong , Liu Shuyang , Wang Zhiqiang , Tan Qizhi 
Published: November 2023

Abstract
Fossil fuels utilization will produce a large amount of CO2, which causes a series of environmental problems. However, the exhaust CO2 can be used to achieve oil recovery improvement (CO2 EOR), while simultaneously allowing for the geological storage of CO2. For the unconventional reservoir, CO2 huff ‘n’ puff (HNP) is a potential technology showing promising results in laboratory experiments, while its effectiveness in enhancing oil recovery and CO2 sequestration at the reservoir scale remains uncertain. Thus, further research is needed to evaluate the CO2 HNP performance for its implementation. In this paper, we conducted a numerical simulation of the CO2 HNP process in a real tight oil reservoir (1800 m × 350 m × 10m in size) to assess its potential for improving oil recovery, CO2 injectivity, and CO2 sequestration. The results show that the accumulative oil production increased by more than 20% after the implementation of CO2 HNP. Meanwhile, CO2 HNP in tight oil reservoirs is proven capable to achieve CO2 injectivities of more than 4×107 SCm3 and CO2 storages of more than 5×106 SCm3. We designed 3 CO2 HNP schemes and found that the largest CO2 storage does not occur in the optimal scenario for oil production. A new type of CO2 HNP evaluation system considering oil production and storage capacity needs to be established. The results of the article suggest that CO2 HNP can achieve an oil production increase and CO2 storage in tight reservoirs, which has a positive significance for the sustainable development of environmental protection.
Application of DEKF algorithm for SOC estimation of lithium batteries
Authors: Yang Xiong , Yao Xiong 
Published: November 2023

Abstract
A technique based on a double-extended Kalman filter (DEKF) is created to estimate the SOC of a lithium-ion battery pack in real time. The Kalman filter technique and the Thevenin battery model are used to develop a state-space expression for the battery model. Improved accuracy and a more faithful representation of the battery’s internal state are achieved using the least squares approach and the DEKF algorithm to determine the model’s parameters. Experiments are developed for testing batteries that adhere to the presented idea of the online estimate of charge status using the DEKF algorithm. The results of the experiments demonstrate the algorithm’s excellent accuracy and environmental flexibility in calculating SOC online in various settings. The greatest error is less than 4.5 percent. The DEKF method is shown to successfully address the issues of erroneous initial estimates and cumulative errors and to have strong convergence and resilience.
Study on Life Prediction of Li-MnO2 Battery
Authors: Wang Xiao’er , Dong Li , Jiang Pei 
Published: November 2023

Abstract
In order to predict the life of lithium-manganese dioxide batteries, 32 lithium-manganese dioxide batteries were taken as the research object, and temperature is selected to be the battery life accelerated stress. Based on the test results, the Arrhenius model is used as the accelerated life model to predict the storage life of lithium batteries. It is provided a new method of normal temperature storage life prediction of lithium primary batteries, which provides theoretical support for the maintenance in the determination of the lithium battery storage period. It has a certain reference value for the storage reliability accelerated life test of other types of lithium primary batteries.
Intelligent Perception of Distribution Network State Based on Multi-source Data Fusion
Authors: Zhang XiaoSong , Zuo Zhiping 
Published: November 2023

Abstract
This article proposes an intelligent state perception method based on multi-source data fusion to address the issue of the difference between the state perception range and the actual range caused by the abnormal operation status of active distribution networks. In this paper, by combining Ant colony optimization algorithms and fusion rules, a multi-source data fusion model of the operation situation is constructed. The operation situation indicators, such as line loss rate and light load rate, are determined. Using multi-source data fusion information entropy to train samples, the range of abnormal operating states of the power grid is determined. By fusing multi-source voltage data and using the multi-source data fusion method to distinguish voltage data, four operating state perception results of voltage are obtained. Finally, the perception data is modified using Analytic Hierarchy Process to ensure that the state perception results meet the compatibility and consistency requirements with the actual results. According to the experimental results, the proposed method can accurately perceive the fluctuation of abnormal data within 40~50 ranges, which is consistent with the actual value fluctuation range, so as to obtain accurate perception results under different operating conditions.
Design and Application of Station Power Supply System for Lithium Iron Phosphate Battery Based on Power Exchange Operation
Authors: Li Yongjie , Wang Wenge , Lu Jizhao , Hou Huanpeng 
Published: November 2023

Abstract
Based on the engineering application design and development of the power supply system of lithium iron phosphate battery pack in the operation and maintenance mode, this paper conducts the application research from four aspects of battery quantity selection, capacity calculation selection, battery management system design, battery pack modular design, etc. The design scheme of the lithium iron phosphate power supply system is formulated, and the matching battery management system is designed. A universal lithium iron phosphate battery module with an “N+1” redundant configuration is developed to improve the maintenance efficiency of the battery pack. It reliably supports the substation power changing operation and maintenance mode and ensures the reliability and operation safety of the substation power supply system.
Internal flow characteristics of the valveless piezoelectric micropump with the diffusion/nozzle tube
Authors: Cai Shengchuan , Dong Min , Sun Wanxue , Li Caixia 
Published: November 2023

Abstract
A simulation was conducted to research the unsteady flow properties of the valveless piezoelectric micropump with diffusion/nozzle tube at different angles in the case of various driving frequencies using CFX software in this study. The purpose was to obtain the factors that affect the performance of the micropump under unsteady conditions. The results show that the rate of flow of the valveless piezoelectric micropump with different diffusion angles increases with the increase of frequency. The micropump with a diffusion angle of 10° has the best performance and the maximum rate of flow within the frequency range of 100 Hz~500 Hz, and the efficiency of the micropump can be reached 16.98%. The vortex motion generated due to flow separation has a notable effect on the performance of the micropump.
Design of Low Quality Heat Recovery and Utilization System for Fixed Discharge of Coal-fired Boilers
Authors: Hu Qiudong , Liu Xingli 
Published: November 2023

Abstract
In order to optimize the energy structure, increase the proportion of clean heat sources, and solve the problem of high energy consumption for heating, a waste heat recovery scheme is planned to be designed, which mainly recovers the waste heat of the 700MW boilers in the thermal power plant, which can be used to heat the condensed water of the steam turbine in summer., It can be used to heat the circulating water in the heating network in winter to achieve the goal of recovering heat and reducing energy consumption. In the design process, a lithium bromide absorption heat pump is used as the main system for low-quality heat recovery, and steam is used as a driving heat source to release heat in the generator to heat a dilute solution of lithium bromide to generate refrigerant vapor, thereby achieving high efficiency, energy saving and economic benefits. the goal of. At the same time, two booster pumps (one for transport and one for standby) are added to the condensate pipeline at the inlet of the low-low temperature economizer system to achieve the purpose of boosting the condensate. This design plan adheres to the concept of energy saving and environmental protection, and proposes a technical transformation route for low-quality heat recovery and utilization projects to achieve the goals of reducing production costs and increasing corporate benefits.
Harmonic analysis and filter design based on high power electromagnetic transmitter
Authors: Meng Qingke , Zhang Yiming , Wang Xuhong , Gao Junxia 
Published: November 2023

Abstract
In order to effectively suppress the higher harmonics contained in the output voltage of high-power electromagnetic transmitter, the waveform expression of the output voltage of bipolar pulse width modulation (SPWM) circuit is derived, which can accurately obtain the fundamental wave and each harmonic content in the inverter bridge transmission voltage, and provide a theoretical basis for the design of output filter. At the same time, a design method of output LC filter based on high power electromagnetic transmitter is proposed based on MATLAB simulation calculation and considering the fundamental voltage drop, inductor current ripple and reactive power capacity on the filter inductor. Finally, the feasibility of this design method is verified by the field experiment of transmitter, and the output filtering effect is good.