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2023 7th International Conference on Mechanics, Mathematics and applied Physics, ICMMAP 2023

作者： Zhu, Ying Hao X.C., Wei X.Y., Jiang The College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu610059 China Chengdu University of Traditional Chinese Medicine China

Target positioning has always been a hot research topic in the field of sensors. In recent years, radar detection technology has become increasingly mature, resulting in a large number of radar sensors have begun to be used in traffic, security, medical and other fields for target detection. This paper mainly studies the super-resolution localization problem of FMCW FMCW in moving scenes. It analyzes the echo data by mathematical modeling to obtain the distance and angle information of the object to find the place of the object. To restore the motion trajectory of objects more realistically and achieve super-resolution positioning, a super-resolution radar positioning model based on Kriging interpolation based on the Fourier spectrum is established. By constructing a frame of intermediate frequency data Fourier spectrum tensor space, Fourier spectrum analysis is used to obtain the spectral characteristics of spatiotemporal changes when objects move. The Fourier spectrum surface is reasonably predicted through the statistical method - kriging interpolation. More Fourier spectrum information of objects in the time dimension can be obtained, and then more object points can be restored to achieve super-resolution positioning. This is widely used in the automotive field, which develops autonomous driving systems to help drivers better control the vehicle and reduce the probability of car accidents. © Published under licence by IOP Publishing Ltd.

关键词： Spectrum analysis

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Enhanced Brain Tumor Detection Using Transfer Learning with Fine-Tuned Efficientnet-B3 Blocks and Graph-Based Spatial Attention Capsule Networks 21

Enhanced Brain Tumor Detection Using Transfer Learning with ...

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21st International Computer Conference on Wavelet Active Media technology and Information Processing, ICCWAMTIP 2024

作者： Aggrey, Esther Stacy E.B Zhen, Qin Kodjiku, Seth Larweh Fiasem, Delali Linda Sey, Collins Ejiyi, Chukwuebuka Joseph Ntia, Nsikakabasi Williamson School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China School of Computer Science and Technology Zhejiang Gongshang University Hangzhou China College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China

ISBN: (纸本)9798331519254

Brain tumors are critical medical conditions that require timely and accurate diagnosis to improve survival outcomes. This research proposes a cutting-edge framework for brain tumor classification, combining fine-tuned EfficientNet-B3 blocks with graph-based spatial attention capsule networks. By addressing challenges such as limited data availability, overfitting, and the complex nature of tumor structures, the framework employs partial transfer learning, advanced feature extraction, and attention mechanisms to effectively model spatial relationships in MRI images. Evaluated on a dataset of 3,064 contrast-enhanced brain MRI images, the model demonstrated exceptional performance, achieving 99.85% classification accuracy and notable improvements in precision, recall, and F1 scores for glioma, meningioma, and pituitary tumours. The use of advanced data augmentation techniques significantly improved the model's ability to generalize, while its computational efficiency makes it well-suited for clinical diagnostic applications. © 2024 IEEE.

关键词： Dynamic contrast enhanced MRI

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The Impact of Neutron Energy on Laser Simulation technology in Transient Synergistic Damage 3

The Impact of Neutron Energy on Laser Simulation Technology ...

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3rd International Symposium on Semiconductor and Electronic technology, ISSET 2024

作者： Zhang, Fuwang Tang, Ge Zhu, Siji Liu, Jingrui Zhao, Wenjiao Zhang, Zhenkang Li, Mo College of Nuclear Technology and Automation Engineering Chengdu University of Technology Sichuan610059 China School of Electronic Science and Engineering University of Electronic Science and Technology of China Pidu Sichuan Chengdu611731 China

ISBN: (纸本)9798350390285

The study explores the impact of neutrons with different energies on laser simulation of silicon bipolar junction transistors (Si BJTs) under transient synergistic damage. By simulating the energy deposition distribution and transient current response of low-energy and high-energy photons at different neutron energies (ranging from 1 e V to 2 MeV), the following results are revealed: For high-energy neutron surroundings (energy > 100 keV), low-energy photons can effectively simulate high-energy photons to cause transient synergistic damage effects with neutrons. In contrast, for low-energy neutron surroundings (energy © 2024 IEEE.

关键词： Photons

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Real-Time Monitoring of Meteorological Data at In-Situ GCW Remediation Sites

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Journal of Geoscience and Environment Protection 2024年第9期12卷 152-166页

作者： Qinghai Wu Xiaofeng Yang Jun Liu Ruiqi Wang Quanyou Fu College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China

To optimize the self-organization network, self-adaptation, real-time monitoring, remote management capability, and equipment reuse level of the meteorological station supporting the portable groundwater circulation wells, and to provide real-time and effective technical services and environmental data support for groundwater remediation, a real-time monitoring system design of the meteorological station supporting the portable groundwater circulation wells based on the existing equipment is proposed. A variety of environmental element information is collected and transmitted to the embedded web server by the intelligent weather transmitter, and then processed by the algorithm and stored internally, displayed locally, and published on the web. The system monitoring algorithm and user interface are designed in the CNWSCADA development environment to realize real-time processing and analysis of environmental data and monitoring, control, management, and maintenance of the system status. The PLC-controlled photovoltaic power generating panels and lithium battery packs are in line with the concept of energy saving and emission reduction, and at the same time, as an emergency power supply to guarantee the safety of equipment and data when the utility power fails to meet the requirements. The experiment proves that the system has the characteristics of remote control, real-time interaction, simple station deployment, reliable operation, convenient maintenance, and green environment protection, which is conducive to improving the comprehensive utilization efficiency of various types of environmental information and providing reliable data support, theoretical basis and guidance suggestions for the research of groundwater remediation technology and its disciplines, and the research and development of the movable groundwater cycling well monitoring system.

关键词： Groundwater Circulation Well Weather Station Real-Time Monitoring Embedded Web Server

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An Improved Convolutional Networks Model for Carbon Emission Prediction in Power Systems

An Improved Convolutional Networks Model for Carbon Emission...

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2024 IEEE IAS Industrial and Commercial Power System Asia, I and CPS Asia 2024

作者： Cai, Dongsheng Acen, Caroline Ukwuoma, Chiagoziem C. Zhang, Nan Liu, Wei Zhang, Zhenyuan Huang, Qi College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China School of Computing and Cyber Security Chengdu University of Technology Chengdu China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China School of Information Engineering Southwest University of Science and Technology Mianyang China

ISBN: (纸本)9798350352290

In response to the imperative need for carbon reduction, tracking the carbon footprint of power systems has emerged as a critical concern. Traditional methods have struggled to accurately capture the nuances of carbon emissions, necessitating a fresh approach. To address this gap, the study introduces a pioneering deep learning-based model. We contend that the rapid advancement of deep learning offers a solution by harnessing neural network models, particularly the temporal convolutional networks (TCN) and gated recurrent units (GRU). These models are adept at handling the intricate patterns and dependencies inherent in carbon emission data, which exhibit both short-term fluctuations and long-term trends. Sequel to that, we propose a novel TCN-GRU-ATT neural network model designed explicitly for carbon footprint data. This innovative model combines TCN, GRU, and attention mechanisms to comprehensively capture both short-term variations and long-term dependencies within carbon emission patterns. Using power generation data from a gas-fired unit within the power grid as a foundation, the model calculates carbon emissions across various time intervals. Results demonstrate the model's exceptional performance, with a low Mean Absolute Percentage Error (MAPE) of 1.7123%, a Root Mean Square Error (RMSE) of 8.8436 kg/CO2, and a high Coefficient of Determination R2 of 0.9802. © 2024 IEEE.

关键词： Low emission

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Exploring the Performance Test of Smart Substation Auxiliary Control System Test Platform Based on B/S Architecture 4th

Exploring the Performance Test of Smart Substation Auxiliary...

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4th International Conference on Power and Electrical engineering, ICPEE 2023

作者： Feng, Fuyong Cai, Dongsheng Chang, Zhengwei Wu, Jie Bamisile, Olusola Huang, Qi The College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China State Grid Sichuan Electric Power Company Electric Power Research Institute Chengdu China

ISBN: (纸本)9789819716739

Smart substation is an important infrastructure for the development of the power industry, in which the auxiliary control system plays a vital role, and the performance of the auxiliary control system of smart substations affects power security. Aiming at this problem, this paper uses the object-oriented programming language Java technology to develop a set of smart substation auxiliary control system test platforms based on the IEC61850 protocol, which is used for performance tests of auxiliary control system. By using Jmeter to simulate the multi-sensor data interaction test environment, the test platform tests the stability, response speed, and data processing capability of the auxiliary control system. The test data results indicate that the response time of the system is basically less than 80 ms, with a maximum deviation of only 10.05. The auxiliary control system testing platform designed in this article has shown satisfactory performance in different concurrent data interaction testing environments, providing a solid guarantee for the reliability and stability of the equipment. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Control systems

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Automatic Fruit Detection Based on Robotic Vision 5

Automatic Fruit Detection Based on Robotic Vision

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5th International Conference on Big Data and Artificial Intelligence and Software engineering, ICBASE 2024

作者： Chen, Yiran Yao, Rui Liu, Haoran Liu, Bingqi Liu, Mingzhe Wenzhou University of Technology School of Data Science and Artificial Intelligence Wenzhou China Chengdu University of Technology College of Nuclear Technology and Automation Engineering Chengdu China Norla Institute of Technical Physics Chengdu China

ISBN: (纸本)9798331506612

Automatic fruit detection has greatly reduced labor costs and crop damage rates, contributing to the progress of agricultural modernization. It involves real-time assessment of the surrounding environment and recognition of target fruit categories. However, fruit detection faces challenges due to the similarities in shape, color, and other features among different types of fruits, as well as the impact of environmental factors such as inadequate lighting, occlusion, and background variations on recognition accuracy. This project focuses on the simulation of the robotic fruit harvesting process, which includes environmental image acquisition, image processing, and robot control. The robot utilizes its integrated camera to capture real-time images of the surrounding environment. These images are then processed on a computer, employing color recognition based on traditional algorithms. The images are segmented based on the identified color regions and subjected to object detection using YOLO v5. By discerning the presence of the target objects, the results are transmitted to the robot, which responds accordingly. The real-time performance is enhanced by filtering and narrowing down the target regions, reducing the time required for object recognition. © 2024 IEEE.

关键词： Fruits

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Applicability of denoising-based artificial intelligence to forecast the environmental externalities

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Geoscience Frontiers 2024年第3期15卷 469-483页

作者： Dongsheng Cai Ghazala Aziz Suleman Sarwar Majid Ibrahim Alsaggaf Avik Sinha The College of Nuclear Technology and Automation Engineering Chengdu University of TechnologySichuan Province 610059China Department of Business Administration College of Administrative and Financial SciencesSaudi Electronic UniversityJeddahSaudi Arabia Department of Finance and Economics College of BusinessUniversity of JeddahJeddahSaudi Arabia Management Development Institute Gurgaon India

The current study attempts to compare the hybrid artificial intelligence models to forecast the environmental externalities in Saudi *** have used the denoising based artificial intelligence models to construct hybrid *** comparing the denoising techniques,the CSD-based denoising has ***,we have used the CSD-based hybrid ***-ANN and CSD-RNN are used for denoising-based artificial intelligence models,whereas CSD-ARIMA is used for denoising-based traditional *** these models are used to check and compare their performance in terms of level and direction of prediction for PM_(10).The results show that the CSD-based ANN model has a higher predictability for PM_(10) levels in Saudi Arabia due to low error values and higher Dstat *** comparing original and forecasted data,the superiority of CSD-ANN is evident in predicting the PM_(10) in Saudi ***,this hybrid model can predict the environmental externalities for non-linear and highly noised ***,the findings can be useful in achieving the sustainable development goal.

关键词： Hybrid artificial intelligence Forecasting Saudi Arabia Environment PM_(10)

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Thin-film approximate point scattered function and its application to neutron radiography

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nuclear Science and Techniques 2022年第9期33卷 1-9页

作者： Jun Qin Jia-Yu Ni Lin-Feng Ye De-Hong Gao Wei-Jun Jiang Department of Nuclear Engineering and New Energy Technology The College of Engineering and Technology of Chengdu University of TechnologyLeshan 614000SichuanChina Society for Theoretical and Computational Physics The College of Engineering and Technology of Chengdu University of TechnologyLeshan 614000SichuanChina

A simpler and improved utility approximate point scattered function for thin-film converters currently used in neutron photographic devices is proposed as a correction method to produce clearer,more realistic *** validity of the model was demonstrated through a simulation *** on the results,an error analysis was carried out,certain corrections were made to the original model,and the final model achieved a very low relative error in the simulation *** model can also be optimized for quantitative neutron photographic analysis using iterative algorithms to obtain realistic neutron photographic images more *** the end of the article,the model is extended to consider the case of energy spectrum hardening by introducing a temperature correction parameter.

关键词： Neutron radiography Point scattered function Image processing

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Targets capture by distributed active swarms via bio-inspired reinforcement learning

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Science China(Physics,Mechanics & Astronomy) 2025年第1期68卷 206-217页

作者： Kun Xu Yue Li Jun Sun Shuyuan Du Xinpeng Di Yuguang Yang Bo Li Institute of Biomechanics and Medical Engineering Applied Mechanics LaboratoryDepartment of Engineering MechanicsTsinghua UniversityBeijing 100084China Institute of Nuclear and New Energy Technology Tsinghua UniversityBeijing 100084China Shanghai Aerospace Control Technology Institute Shanghai 201109China Shanghai Key Laboratory of Aerospace Intelligent Control Technology Shanghai 201109China College of Automation Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China

Natural swarms arranged from cells to herds are usually decentralized but display intriguing collective intelligence in coordinating individuals across large scales to efficiently achieve their common *** from nature may provide new strategies for controlling collective dynamics of synthetic swarms to accomplish specific ***,we present a bioinspired computational framework that steers distributed active swarms to collectively capture and merge targets via reinforcement *** exploit collective milling structures of natural herds to cage the targets,and adopt a switching control policy inspired by sperms’chiral dynamics to optimize the trajectories of individuals,through which the active swarms can selforganize to enclose single or multiple distant targets in a dynamical,adaptive and scalable *** exists a critical swarm size,beyond which the excessive competition between agents would generate large mechanical forces,leading to capture instability but enabling the transition from short-distance to long-distance merging capture of multiple *** work provides physical insights into distributed active swarms and could offer a multilevel,decentralized strategy toward controlling swarm robotics in wide applications such as bio-medical devices,machine immunity,and target clearance.

关键词： swarm intelligence robotics multi-tasks artificial intelligence bionics

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