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Electronic Information engineering and Computer Communication (EIECC), International Conference on

作者： Yang Liu Mingxing Xu Guangxi Wang Yufeng Yang College of Nuclear Technology and Automation Engineering Chengdu University of Technology Cheng Du China Applied Nuclear Technology in Geosciences Key Laboratory of Sichuan Province (Chengdu University of Technology) Cheng Du China

ISBN: (数字)9798331534622

ISBN: (纸本)9798331534639

This paper designs a baseline estimation digital energy spectrum measurement system using a parallel full-comparison method, aimed at reducing the impact of baseline drift on the energy resolution of the digital energy spectrum measurement system. The system consists of two parts: an analog baseline adjustment circuit and a digital baseline estimation module. The digital module first performs baseline estimation, then transmits the results to the frontend circuit to adjust the baseline, thereby correcting drift caused by circuit noise and signal pulse stacking. The system is mainly composed of a DAC baseline adjustment circuit, an ADC sampling circuit, and an FPGA-based digital multi-channel analysis system, in which a parallel full-comparison mean baseline estimation method is deployed to calculate the baseline adjustment amount. To verify the reliability of the system, NaI detectors were used in this study, and the energy resolution and response of the system were tested using dual-source 137 Cs and 60 Co. The experimental results show that the linear response fitting of the digital multi-channel energy spectrum measurement system exceeds 99.99%. Under high counting rates, the energy resolution without baseline recovery was 8.83% (@0.662 keV), while the energy resolution with the parallel full-comparison baseline recovery method was 7.57% (@0.662 keV), improving by 0.92%. In conclusion, compared to the system without baseline recovery, the parallel full-comparison baseline recovery method effectively alleviates the baseline drift issue of the NaI detector under high counting rates, thereby improving the energy resolution of the system.

关键词： Spectroscopy Energy resolution Stacking Estimation Energy measurement Linearity Detectors Software Software measurement Signal resolution

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A lightweight image segmentation algorithm based on mobilenetv3 and global context block attention mechanism 4

A lightweight image segmentation algorithm based on mobilene...

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4th International Conference on Computer Vision, Application, and Algorithm, CVAA 2024

作者： Qian, Songcheng Li, Jiajun Yao, Xiaozhou College of Energy Chengdu University of Technology Chengdu610059 China School of Automation Engineering University of Electronic Science and Technology of China Chengdu611731 China Institute of Communication UniversitéLumière Lyon-2 Bron Lyon69500 France

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

Image segmentation is a crucial task in computer vision that involves dividing an image into distinct regions, with each region containing pixels that share similar attributes. Traditional methods like Otsu, Sobel, and Canny often suffer from high computational complexity and sensitivity to parameters. To address these limitations, this paper proposes a lightweight image segmentation algorithm that integrates MobileNetv3-Small with a global context block attention mechanism. MobileNetv3 leverages depthwise separable convolutions and optimized architecture to significantly reduce computational load and parameter count. To further improve segmentation accuracy, a deformable convolutional network is employed during feature extraction, while the global context block attention mechanism enhances focus on target regions. The proposed algorithm not only improves segmentation performance but also offers a lightweight solution suitable for resource-constrained environments. © 2025 SPIE.

关键词： Convolutional neural networks

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Dual-Channel Non-Contact Continuous Blood Pressure Measurement Based on Millimeter-Wave Radar 6

Dual-Channel Non-Contact Continuous Blood Pressure Measureme...

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6th International Conference on Frontier Technologies of Information and Computer, ICFTIC 2024

作者： Li, Shangxun Ma, Guangji Li, Yuting Gao, Suzhen Sun, Haiyang Liu, Yongjie Yingcai Experimental College University of Electronic Science and Technology of China Uestc Chengdu China School of Life Science and Technology University of Electronic Science and Technology of China Uestc Chengdu China School of Automation Engineering University of Electronic Science and Technology of China Uestc Chengdu China School of Integrated Circuit Science and Engineering University of Electronic Science and Technology of China Uestc Chengdu China

ISBN: (纸本)9798331541750

Traditional blood pressure measurement methods are mostly contact, cumbersome and easy to bring discomfort to patients, and the measurement results are likely to be affected by psychological factors, which is inconvenient for home physiological health monitoring in the aging society. Based on the above problems, we use millimeter wave radar to collect the echo signals from the human chest and wrist veins, and then obtain the specific value of blood pressure through machine learning. This method collects and processes ECG and PPG signals and performs pre-processing, filtering, mathematical analysis and other operations on the signals to finally calculate systolic and diastolic blood pressure. The feasibility of non-contact blood pressure parameter measurement was verified by conducting experiments on 30 subjects and comparing the measurement results of the non-contact method with those of the traditional method, and the errors were within the controllable range [1]. © 2024 IEEE.

关键词： Blood pressure

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Practical prescribed-time fuzzy tracking control for uncertain nonlinear systems with time-varying actuators faults

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Journal of automation and Intelligence 2024年第1期3卷 40-49页

作者： Shuxing Xuan Hongjing Liang Tingwen Huang College of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China Science Program Texas A&M UniversityDoha 23874Qatar

The paper investigates the practical prescribed-time fuzzy tracking control problem for a category of nonlinear system subject to time-varying actuator *** presence of unknown nonlinear dynamics and actuator faults makes achieving tracking control within a prescribed-time *** tackle this issue,we propose a novel practical prescribed-time fuzzy tracking control strategy,which is independent of the initial state of the system and does not rely on precise modeling of the system and *** apply the approximation capabilities of fuzzy logic systems to handle the unknown nonlinear functions and unidentified actuator faults in the *** piecewise controller and adaptive law constructed based on piecewise prescribed time-varying function and backstepping technique method establish the theoretical framework of practical prescribed-time tracking control,and extend the range of prescribed-time tracking control to *** of the initial conditions,the proposed control strategy can guarantee that all signals remain uniformly bounded within the practical prescribed time in the presence of unknown nonlinear item and time-varying actuator *** example is presented to demonstrate the effectiveness of the proposed control strategy.

关键词： Prescribed-time tracking control Adaptive fuzzy control Actuator faults Uncertain nonlinear system

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Distributed Energy Management for Ship-Integrated Energy System Considering Economic and Environmental Benefits 14

Distributed Energy Management for Ship-Integrated Energy Sys...

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14th International Conference on Information Science and technology, ICIST 2024

作者： Zhang, Yuxin Shan, Qihe Liu, Haoran Li, Tieshan Navigation College Dalian Maritime University Dalian China School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798350353334

To decrease the dependency of fuel-based resources in the shipping industry, the energy management problem is analyzed in this paper. Firstly, the development of shipboard energy system is reviewed from radiation pattern, ring pattern, two-end pattern to the ship-integrated energy system. Moreover, for ensuring the secure sailing, a multi-objective energy management model is established with the consideration of economic and environmental benefits. Meanwhile, the requirements of supply-demand balance, velocity, voltage security and so on are considered as well in the energy management. Then, a distributed energy management strategy based on ADMM algorithm is proposed. Finally, simulation results of a 5-node test system proves the effectiveness of the constructed energy management model and the distributed algorithm. © 2024 IEEE.

关键词： Energy development

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An Improved Wildfire Identification Method Based on Yolov7 and Attention Mechanism 3

An Improved Wildfire Identification Method Based on Yolov7 a...

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3rd International Conference on Artificial Intelligence, Virtual Reality, and Visualization, AIVRV 2023

作者： Yang, Qiang Yu, Fan Zhang, Gexiang Jin, Xiaozhao Guo, Dequan Wang, Ping Yao, Guangle Liang, Kai College of Computer Science and Cyber Security Chengdu University of Technology Chengdu China School of Automation Chengdu University of Information Technology Chengdu China School of Network & Communication Engineering Chengdu Technological University Chengdu China

ISBN: (纸本)9781510671485

Wildfires, also called forest fires, are a common natural disaster that often occur in forests and are difficult to control. Detecting and suppressing them at an early stage, primarily through monitoring smoke and fires, is crucial in reducing losses. Thanks to the efforts of researchers, wildfire detection technology has advanced significantly, from traditional manual monitoring to target detection, sensor detection, and infrared detection. However, the various detection methods still have some issues, including low accuracy, high costs, slow detection speeds and susceptibility to interference. This paper presents an improved approach to identifying wildfires based on YOLOv7 with CBAM. Our experimental results indicate that our approach achieves a mean Average Precision (mAP) of 95.77%, surpassing VGG-SSD with CBAM by 0.53%, MobileNetv2-SSD with CBAM by 0.37%, and Faster R-CNN with CBAM by 2.1%. Thus, our method offers a highly accurate approach to wildfire identification. © 2023 SPIE.

关键词： Smoke

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Fractal Converters with Boundless Current and Voltage Ratings 3

Fractal Converters with Boundless Current and Voltage Rating...

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3rd International Conference on Power Systems and Electrical technology, PSET 2024

作者： Fang, Jingyang Jiang, Qin Yang, Hanqing Shandong University School of Control Science and Engineering Jinan China Sichuan University College of Electrical Engineering Chengdu China University of Electronic Science and Technology of China School of Automation Chengdu China

ISBN: (纸本)9798350353204

Extremely high current/voltage stresses challenge power electronics. This paper proposes a novel series of power converters, collectively referred to as Fractal (F) converters. F converters consist of several identical layers, which further comprise many identical cells or submodules. Salient benefits of F converters include but not limited to 1) modularity and scalability;2) boundless current and voltage ratings;3) high power quality;4) unified control applied to various layers;5) high reliability;6) control flexibility, e.g., for efficiency optimization. F converters will quickly find their applications in 1) high-voltage dc/ac transmissions;2) renewable energy generation;3) power quality enhancement equipment;4) electric vehicles;5) marine and aircraft propulsion;6) medical applications such as noninvasive magnetic stimulators;7) high-frequency high-power power supplies;8) plasma applications;9) future distributed power grids. For validations, simulation results are presented, demonstrating that F converters operate well as high-voltage and high-current inverters as well as arbitrary pulse generators. © 2024 IEEE.

关键词： Power converters

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Research on Distributed Sensor Network Faulty Recovery Method based on Attention Mechanism 3

Research on Distributed Sensor Network Faulty Recovery Metho...

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3rd International Conference on Artificial Intelligence and Computer engineering, ICAICE 2022

作者： Xing, Zheng Liu, Boya Guan, Haochen Zhang, Yiran Zhang, Ying Chengdu University of Technology The College of Nuclear Technology and Automation Engineering Sichuan Chengdu China Chengdu University of Technology College of Environment and Civil Engineering Sichuan Chengdu China Zhengzhou University of Light Industry International Education College Henan Zhengzhou China Hebei University School of Cyber Security and Computer Hebei Baoding China Northeast Petroleum University School of Electrical & Information Engineering Heilongjiang Daqing China

ISBN: (纸本)9781510663473

Faulty recognition and recovery is extremely essential component for existing sensor networks. However, current investigations concentrates on the recognition process and develop abundant advanced identification methods and existing recovery method is almost based on the multiple layers of neural network to achieve the recovery of sensor network, which would result in vast computation costs. Attention mechanism is proposed for neural network to focus some important neural nodes and perform high accuracy for training process with insignificant computation cost. In this article, we propose a novel neural network to recover the fault sensor network with attention mechanism. Thus, the developed mechanism can achieve rapid recovery of fault sensors network with reasonable computation costs and acceptable performance. From extensive experimental result, we can conclude that our proposed method can strictly process the fault sensor network and compared with existing fault sensor network recovery methods to illustrate the effective performance on recovery accuracy with reasonable costs of our proposed method. © 2023 SPIE.

关键词： Sensor networks

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The Influence of Radiation Distance on Microwave Coupling Efficiency in Microwave-assisted Rock Breakage

The Influence of Radiation Distance on Microwave Coupling Ef...

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Xiaoyun Zhao School of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China

ISBN: (数字)9798350375909

ISBN: (纸本)9798350375916

High power microwave early irradiation has a great potential in assisting excavators in breaking hard and abrasive rocks, radiation efficiency is a very important issue. The paper studied the radiation of standard rectangular waveguides on rocks at different working distances, obtained the minimum S 11 parameter through CST simulation, and determined the corresponding optimal radiation position, at a working distance of 0.31λ, the S 11 is minimum, which is the optimal position of the sample relative to the microwave antenna. Using this method, we can quickly and accurately obtain the efficiency of microwave coupling into rocks, can guide practical engineering applications.

关键词： Microwave antennas Couplings Radiation effects Horn antennas Rectangular waveguides Microwave theory and techniques Rocks

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Domain Contrastive Learning for Multi-Site Alzheimer's Disease Classification 20

Domain Contrastive Learning for Multi-Site Alzheimer's Disea...

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20th International Computer Conference on Wavelet Active Media technology and Information Processing, ICCWAMTIP 2023

作者： Fiasam, Linda Delali Rao, Yunbo Sey, Collins Aggrey, Esther Stacy E. B. Kodjiku, Seth Larweh Browne, Judith Ayekai Danso, Juliana Mantebea Ukwuoma, Chiagoziem C. Gyarteng, Emmanuel S. A. School of Information and Software Engineering University of Electronic Science and Technology of China China School of Computer Science and Technology Zhejiang Gongshang University China School of Computer Science and Technology University of Electronic Science and Technology of China University China College of Nuclear Technology and Automation Engineering Chengdu University of Technology China

ISBN: (纸本)9798350318982

In the field of medical imaging, accurately classifying Alzheimer's Disease (AD) poses a substantial challenge, primarily due to the inherent variability in imaging data across different clinical sites. This paper introduces a novel approach, Domain Contrastive Learning (DCL), to address this challenge by enhancing the robustness and transferability of AD classification models using multi-site Magnetic Resonance Imaging (MRI) data. DCL leverages a unique contrastive learning technique within an autoencoder's latent space, enabling the extraction of domain-invariant features essential for accurate diagnosis. We rigorously evaluate the proposed network on brain images from three distinct imaging sites, employing a Domain Generalization (DG) training protocol to ensure robustness and generalizability across varying data sources. Our model is evaluated on three binary classification tasks: AD vs. Normal Control (NC), AD vs. Mild Cognitive Impairment (MCI), and MCI vs. NC. Results demonstrate that DCL outperforms existing methods, especially in AD vs. NC classification, achieving higher accuracy, sensitivity, and specificity with 0.51%, 1.54% and 1.68% increments respectively. This underscores DCL's potential as a robust and generalizable method for enhanced AD diagnosis, marking a significant step forward in medical imaging challenges in a multi-site context. © 2023 IEEE.

关键词： Magnetic resonance imaging

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