检索结果-内蒙古大学图书馆

5th IEEE Information technology, Networking, Electronic and automation Control Conference, ITNEC 2021

作者： Yang, Liu Zhu, Xing Xi, Hewei He, Zhaoqing Zhu, Qingsong Chengdu University of Technology State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Chengdu610059 China Chengdu University of Technology College of Nuclear Technology and Automation Engineering Chengdu610059 China

ISBN: (纸本)9781665415989

The previous landslide image acquisition system adopts a continuous image acquisition and transmission method, which has high consumption and produces many redundant data. Therefore, a new landslide image acquisition system is developed in this paper. The system adopts seismic geophone to gain landslide motion data, and then the dual limit comparator filters out the landslide motion data and forms a trigger signal to wake up the system. In the end, after being awakened, the embedded micro-controller collects and transmits the image. With the intermittent image acquisition and transmission method, the equipment keeps in a low-power consumption for a long time when the landslide movement is not severe. The equipment will be awakened only when the landslide movement is violent. It turns out that compared with the continuous acquisition method, the power consumption of the system can be reduced by about 66%, and the data amount can be reduced by about 60KB when the system is triggered only once in a minute. © 2021 IEEE.

关键词： Landslides

来源：评论

学校读者我要写书评

暂无评论

Study on Energy calibration of LaBr3(Ce) Scintillation Detector 15

Study on Energy calibration of LaBr3(Ce) Scintillation Detec...

引用

15th IEEE International Conference on Electronic Measurement and Instruments, ICEMI 2021

作者： Jiang, Zheng Guo, Siming Yu, Tao Qie, Xiaoyu Wu, Jinjie Lai, Wanchang The College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China Division of Ionizing Radiation Metrology Beijing China School of Science Hebei University of Science and Technology Shijiazhuang China

ISBN: (纸本)9781665444910

The energy calibration of LaBr3(Ce) detector is carried out by using the experimental methods of standard radioactive source, K fluorescence X-rays source and crystal diffraction monochromatic X-rays source, and the energy calibration curve is given. The calibration results using K fluorescence X-rays source and crystal diffraction monochromatic X-rays source are close to the calibration results of standard radioactive source, which verifies the rationality and reliability of the two experimental methods for the detector energy linear calibration. Using the fitting formula obtained by K fluorescence X-rays source and crystal diffraction monochromatic X-rays source, the relative error between the energy fitting value and the real value of Pb-210, Am-241, Cd-109 and Co-57 radioactive sources is less than 3.5%. For the detection of the energy range of (30-120) keV, the LaBr3(Ce) detector can basically determine the energy of the measured ray. © 2021 IEEE.

关键词： Fluorescence

来源：评论

学校读者我要写书评

暂无评论

Hybrid Energy Storage Power Sharing Scheme of Small Hydro-Power Station Based on Ceemdan And Hilbert Spectrum

SSRN

引用

SSRN 2023年

作者： Yan, Qun-Min Ma, Rui Ma, Rui-Qing Dong, Xin-Zhou An, Chen College of Automation Northwestern Polytechnical University Shaanxi Xi’an710072 China Department of Electrical Engineering and Applied Electronics Technology Tsinghua University Beijing100084 China College of Electrical Engineering Shaanxi University of Technology Shaanxi Hanzhong723001 China

The auto regulation capacity of runoff small hydro-power which is easily affected by climate is weak, so that high penetration of small hydro-power interconnection will threat the security and stability of the operation of electric power system. The influence of a sudden change in the hydro-power output power on power system can be reduced using the spatiotemporal translation and rapid response characteristics of energy storage devices to electricity. With the standard of effect of suppression of small hydro-power fluctuations, a power sharing method for hybrid energy storage system (HESS) which is composed of super capacitor and lithium battery is proposed. By an algorithm of moving average and median average weighted filtering, in addition to the smoothness of small hydro-power output power, small hydro-power grid-tied power and HESS reference power are obtained. Using the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), the HESS reference power is decomposed into different intrinsic mode functions (IMF) from high to low frequency bands. Then, using the Hilbert transform (HT), the time-frequency curves of each IMF are extracted, with the high-frequency band absorbed by the super capacitor and the low-frequency band absorbed by the lithium battery, to allocate the internal power of the HESS. Finally, the effectiveness of the proposed strategy is verified through simulation based on actual sampling data from a small hydro-power station in a certain area. © 2023, The Authors. All rights reserved.

关键词： Intrinsic mode functions

来源：评论

学校读者我要写书评

暂无评论

A Novel All-phase Fast Fourier Transform-based Parameters Identification of High Frequency Oscillations

A Novel All-phase Fast Fourier Transform-based Parameters Id...

引用

Annual Meeting Industrial and Commercial Power Systems Technical Conference

作者： Feiyu Sun Dongsheng Cai Zhenyuan Zhang Qi Huang College of Nuclear Technology and Automation Engineering Chengdu University of Technology China Sichuan Provincial Key Lab of Power System Wide-Area Measurement and Control 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 P.R. China

ISBN: (数字)9798350345308

ISBN: (纸本)9798350345315

Wind and solar energy inverter-based resources (IBRs) has been employed extensively with the aim of carbon neutrality. Power systems also make extensive use of power electronic converters, leading to interactions between IBRs and with the grid, causing high frequency oscillation (HFO) problems. It damages equipment and jeopardizes the security of the system. To identify HFO components above 100 Hz, this research use Phasor Measurement Unit (PMU) instantaneous value data to determine the HFO associated characteristics. To reduce the influence of spectral leakage and the fence effect, as well as to improve the identification accuracy of the related parameters, this paper adopts the RV self-convolutional window based Discrete Fourier Transform (DFT) and the Hanning double-window based all-phase Fast Fourier Transform (apFFT) hybrid algorithm to identify the HFO modal parameters. We take into account the identification accuracy in complex cases, such as non-nominal frequencies, with noise effects and multiple HFO modes. The simulation results show that the proposed method has high identification bandwidth, accuracy and strong flexibility.

关键词： Accuracy Wind energy Simulation Discrete Fourier transforms Noise Bandwidth Hafnium oxide

来源：评论

学校读者我要写书评

暂无评论

Applying Energy-Dispersive X-Ray Fluorescence Analysis to Detect Tungsten Inclusions in nuclear Fuel Rod End Plug TIG Welds

引用

Journal of Spectroscopy 2021年第1期2021卷

作者： Gu, Runqiu Cheng, Jianfeng Lai, Wanchang Wang, Guangxi College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu610059 China

This study proposes a new method of detecting tungsten inclusions in nuclear fuel rod upper-end plug welds using energy-dispersive X-ray fluorescence (EDXRF) analysis. The Monte Carlo simulation method was used to simulate the process of detecting tungsten inclusions in nuclear fuel rod upper-end plug welds by the EDXRF. The detectable tungsten particle diameters in the zirconium alloy at different depths in welds and the detection limits of the trace tungsten dispersed in welds were obtained. Then, we constructed an experimental device that uses a CdTe detector with an X-ray tube. The results showed that the relative standard deviation of the net count rate of tungsten K-series characteristic X-rays [W (Kα)] was 1.46%, and the optimum parameters are a tube voltage of 150 kV and current of 0.5 mA. These values were used to perform energy-dispersive X-ray fluorescence analysis. These results were compared to the X-ray radiographic results, which were broadly similar. Furthermore, the results of EDXRF analysis were more legible and reliable than those from X-ray radiographic inspections. This study demonstrates the feasibility of applying EDXRF analysis to detect tungsten inclusions. © 2021 Runqiu Gu et al.

关键词： Monte Carlo methods

来源：评论

学校读者我要写书评

暂无评论

Influence of Production Line Environmental Factors on the Accuracy of X-Ray Thickness Measurements

SSRN

引用

SSRN 2023年

作者： Su, Zhe Zhou, Rong Wang, Zhonghai Zhang, Jinglong Qiao, Zhongtao Ding, Dejia Sun, Shu College of Physics Sichuan University Chengdu610065 China College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu610059 China Shenzhen Dacheng Precision Equipment Co. LTD Shenzhen518000 China

Lithium battery cathode thickness measurements using X-rays are influenced by various environmental conditions such as changes in air temperature, cathode position, and cathode inclination angle. To understand these effects, Monte Carlo simulations using GEANT4 were conducted. The polynomial fitting method was employed to calculate mass thickness accurately. The results show that every 10°C rise in air temperature leads to a decrease in measured mass thickness by an average of 0.26 g/m2. As the cathode moves away from the detector by 5mm, the measured mass thickness increases by approximately 0.07%. Additionally, a rising inclination angle also increases the measured mass thickness. © 2023, The Authors. All rights reserved.

关键词： Thickness measurement

来源：评论

学校读者我要写书评

暂无评论

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

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

引用

International Conference on Wavelet Active Media technology and Information Processing (ICWAMTIP)

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

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.

关键词：

来源：评论

学校读者我要写书评

暂无评论

ATEDU-NET: An Attention-Embedded Deep Unet for multi-disease diagnosis in chest X-ray images, breast ultrasound, and retina fundus

引用

Computers in Biology and Medicine 2025年 186卷 109708-109708页

作者： Ejiyi, Chukwuebuka Joseph Qin, Zhen Agbesi, Victor K. Ejiyi, Makuachukwu Bennedith Chikwendu, Ijeoma A. Bamisile, Oluwatoyosi F. Onyekwere, Favour Ezinne Bamisile, Olusola O. College of Nuclear Technology and Automation Engineering Chengdu University of Technology Sichuan 610059 China Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Sichuan Chengdu China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Pharmacy Department University of Nigeria Nsukka Enugu State Nsukka Nigeria School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China

In image segmentation for medical image analysis, effective upsampling is crucial for recovering spatial information lost during downsampling. This challenge becomes more pronounced when dealing with diverse medical image modalities, which can significantly impact model performance. Plain and standard skip connections, widely used in most models, often fall short of maintaining high segmentation accuracy across different modalities, because essential spatial information transferred from the encoder to the decoder is lost. Inspired by these limitations, the Attention-Embedded Deep UNet (ATEDU-Net) is presented here, an innovative framework designed and tested on diverse medical image modalities, including X-ray, breast ultrasound, and retinal fundus images. ATEDU-Net features a unique architecture that combines progressive context refinement modules (PCRM) and global context modules (GCM) within a U-shaped network structure with Convgroup blocks which facilitate the integration of convolutional operations. This allows ATEDU-Net to autonomously capture rich spatial details and crucial contextual information from input images. The GCM captures essential contextual information for informed decision-making, while the PCRM enhances feature attention, resulting in precise and robust segmentation. The experimentation and analysis demonstrate that ATEDU-Net promises to be a powerful tool for medical professionals, aiding in the early detection of chest-related diseases, accurate localization of breast tumors, and early identification of eye diseases. This, in turn, contributes significantly to the formulation of optimal therapeutic strategies, enhancing patient care and outcomes. The versatility of ATEDU-Net is further highlighted by its ability to analyze medical images across various modalities, making it well-suited for the complex task of medical image analysis in diverse clinical scenarios. © 2025 Elsevier Ltd

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

MPTA-Net: Multi-Scale Perception Network with Triple-View Attention for Polyp Segmentation 4

MPTA-Net: Multi-Scale Perception Network with Triple-View At...

引用

4th International Conference on Neural Networks, Information and Communication engineering, NNICE 2024

作者： Chen, Zhihong Yao, Lisha Liu, Yue Qiu, Bingjiang Han, Chu Tang, Haoyang Du, Yujia Liu, Zaiyi Fang, Gang Guangzhou University Institute of Computing Science and Technology Guangzhou China Guangdong Prov. Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application Guangzhou China South China University of Technology School of Medicine Guangzhou China Department of Radiology Guangzhou China Jiangxi College of Applied Technology School of Information Engineering Ganzhou China Guangdong Provincial People's Hospital Guangdong Academy of Sciences Guangdong Cardiovascular Institute Guangzhou China Southern Medical University Medical Research Institute Guangzhou China Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming China

ISBN: (纸本)9798350394375

Accurate segmentation of polyps in endoscopic images is pivotal for the early detection and diagnosis of colorectal cancer (CRC). Nonetheless, the varied appearance of polyp foregrounds and the intricate background interference significantly diminish the efficacy of pixel-level predictions. To address this issue, we propose a multi-scale perception network with triple-view attention (MPTA-Net) for polyp segmentation. The model primarily revolves around two core principles. The first integrates multiscale spatial information into the network's hierarchical encoding process to better preserve detailed polyp semantic information. The second introduces a triple-view attention mechanism that analyzes feature maps from three distinct perspectives to focus on and localize semantically relevant areas, thereby enhancing segmentation accuracy. Experimental results reveal that the proposed model outperforms existing mainstream segmentation models, effectively addressing under-segmentation, over-segmentation, and edge blurriness issues in polyp segmentation, thereby achieving better identification of challenging areas. © 2024 IEEE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Prediction of Fish School based on Neural Network and Gray Prediction 7

Prediction of Fish School based on Neural Network and Gray P...

引用

2020 7th International Conference on Computer-Aided Design, Manufacturing, Modeling and Simulation, CDMMS 2020

作者： Cai, MuZhen Dong, Bo Xiao, Yuhui College of Software Harbin Engineering University Harbin Heilongjiang150000 China School of Information Science and Engineering Dalian PolyTechnic University Dalian Liaoning116034 China The College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu Sichuan610059 China

Rising ocean temperatures affect the distribution of fish. The livelihoods of many small Scottish fishing companies have also been affected. We designed a fish migration prediction model, a system that predicts fish migration and helps small fishing companies make decisions. First, we creatively proposed the neural network algorithm modified to establish habitat evaluation model based on previous environmental data. Then, the gray prediction algorithm is used to predict the environmental data of each water area in the next 50 years, and the best habitat location of each year is evaluated by the evaluation model based on the environmental data. The migration route of the fish can be obtained by summarizing the best habitats each year in chronological order. We use the knowledge of graph theory to establish a "fishing judgment model"to determine whether small fisheries companies can catch fish in their fishing range. Then we use a triple nested loop to establish a continuous time calculation model, and use this model to discuss the continuous fishing time of a fishing company located in a certain place from a certain year in the future © Published under licence by IOP Publishing Ltd.

关键词： Fisheries

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：