检索结果-内蒙古大学图书馆

Iranian Conference on Electrical engineering (ICEE)

作者： MohammadReza Fazli Nasser Masoumi Hamid Rahimpour School of Electrical and Computer Engineering University of Tehran Tehran Iran Physics & Accelerators Research School Nuclear Science and Technology Research Institute Tehran Iran

ISBN: (数字)9798350376340

ISBN: (纸本)9798350376357

Digital pulse processing systems have become crucial in a wide range of scientific, industrial, and medical applications, particularly in the context of spectroscopy. This paper presents a novel approach to pulse shaping for gamma-ray and x-ray spectroscopy using a combination of CR and RC filters in digital signal processing. The proposed design aims to overcome challenges associated with exponential decay inputs and introduces a scaling factor to achieve a consistent amplitude scale in the filtered output. Specifically, the design tackles the issue of undershoot arising from exponential decay inputs, a significant limitation in existing CR-RC filter implementations. This is achieved through a novel post-processing step. This conversion ensures clean, semi-Gaussian pulse shapes free from distortion, leading to improved accuracy in subsequent analysis. Furthermore, the proposed approach introduces a scaling factor that guarantees a consistent 1-to-1 ratio between input and output amplitudes. This unique feature simplifies subsequent signal processing pipelines and ensures accurate energy measurements, crucial for spectroscopic applications. The effectiveness of this novel method is demonstrated through experimental evaluations using real data acquired from an HPGe detector. The experimental results successfully demonstrate the correction of undershoot and a consistent 1-to-1 ratio between input and output amplitudes, validating the effectiveness of the proposed method in enhancing the accuracy of digital pulse shaping systems in spectroscopy.

关键词： Spectroscopy Accuracy Shape Pipelines Gamma-rays Energy measurement Detectors

来源：评论

学校读者我要写书评

暂无评论

Exploring the Impact of Preprocessing Techniques on Retinal Blood Vessel Segmentation Using a Study Group Learning Scheme

Exploring the Impact of Preprocessing Techniques on Retinal ...

引用

2023 IEEE Signal Processing in Medicine and Biology Symposium, SPMB 2023

作者： Bashir, S. Rohail, K. Sadak, F. Hadi, M.U. Muneer, A. Ragab, M.G. Awais, M. Qureshi, R. National University of Computer and Emerging Sciences Karachi Campus Pakistan Bartin University Department of Mechanical Engineering Turkey Ulster University School of Engineering Belfast United Kingdom Universiti Teknologi PETRONAS Computer Science Department Seri Iskandar Malaysia MD Anderson Cancer Center Department of Imaging Physics HoustonTX United States

ISBN: (纸本)9798350341256

The segmentation of retinal vessels in retinal images is vital for automated diagnosis of retinal diseases. This is a challenging task because it requires accurate manual labeling of the vessels by expert clinicians and the detection of tiny vessels is difficult due to limited samples, low contrast, and noise. In this study, we explore the use of preprocessing techniques such as contrast-limited adaptive histogram equalization (CLAHE), grad-cam analysis and min-max contrast stretching to improve the performance of a study-group learning (SGL) segmentation model. We evaluate the impact of these preprocessing techniques on the accuracy, sensitivity, specificity, AUC, IoU, and Dice scores using four publicly available datasets, DRIVE, CHASE, HRF and IOSTAR. Our findings indicate that the utilization of the Min-Max technique resulted in a notable enhancement in the accuracy of both the DRIVE and CHASE datasets, with an approximate increase of 3% and 2% respectively. Conversely, the impact of the CLAHE method was discernible solely in the DRIVE dataset, demonstrating an improvement in accuracy of 1%. In addition, our results demonstrated superior accuracy performance for both the DRIVE and CHASE datasets compared to the findings of the reviewed studies. The GitHub repo for this project is available at Link. © 2023 IEEE.

关键词： Medical imaging

来源：评论

学校读者我要写书评

暂无评论

Multimode Strong Coupling of Thermal Radiation for Graphene/hBN Atomic System

Multimode Strong Coupling of Thermal Radiation for Graphene/...

引用

2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Huang, Jiayao Ye, Feng Deng, Fu Liu, Xuanyi Fu, H.Y. Zhang, Shengdong Li, Qian School of Electronic and Computer Engineering Peking University Shenzhen518055 China Department of Physics The Hong Kong University of Science and Technology Kowloon Hong Kong Tsinghua Shenzhen International Graduate School Tsinghua-Berkeley Shenzhen Institute Tsinghua University Shenzhen518055 China

We demonstrate the Graphene/hBN atomic system to manipulate strong coupling of thermal radiation between plasmons and phonons, which explores quantitative understanding of energy exchange, mode evolution and coupling ... 详细信息

ISBN: (纸本)9781957171258

关键词： Heat radiation

来源：评论

学校读者我要写书评

暂无评论

Lensless Light-field Imaging with Angular Resolution Improvement

Lensless Light-field Imaging with Angular Resolution Improve...

引用

2022 International Conference on Optical and Photonic engineering, icOPEN 2022

作者： Mo, Chen Cai, Zewei Xi, Jiangtao Tong, Jun Liu, Xiaoli Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen518060 China School of Electrical Computer and Telecommunications Engineering University of Wollongong WollongongNSW2522 Australia School of Electronic and Optical Engineering Nanjing University of Science and Technology Jiangsu Province Nanjing210094 China

ISBN: (纸本)9781510661905

Lensless light-field imaging is the process to encode the light field information of object through an optical encoder, and then recover the light field information of object through a reconstruction algorithm. In traditional lens-based light field imaging, each microlens in microlens-array corresponds to an angular sampling, and it needs to adjust the microlens-array to alter the angular resolution. In this paper, a commercial holographic diffuser is used as an optical encoder, and a flexible overlapping segmentation method of angular sampling is proposed for the point spread function (PSF). The surface microstructures of holographic diffuser allow any region of it to encode and recover light information of object independently, corresponding to an angular sampling. Calibration of PSF for the lensless imaging system is done firstly, and encoded image of object is captured;then the PSF is divided into different regions as sub-PSFs, corresponding to different angular samplings;after that, light field images of object is reconstructed with corresponding sub-PSFs through reconstruction algorithm;with these light field images, digital refocusing can be achieved finally. Different from evenly segmentation of angular sampling in microlens-array, the overlapping segmentation method divides PSF into sub-PSFs while adjacent sub-PSFs overlap each other. This improves angular resolution of imaging system and ensures low error in reconstruction of light field images. Experiments show that, the overlapping segmentation method can guarantee the reconstruction accuracy of lensless light-field imaging system while flexibly adjusting and improving the angular resolution. © 2022 SPIE.

关键词： Optical transfer function

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Based Corona Discharge Severity Classification for High Voltage Equipment

Deep Learning Based Corona Discharge Severity Classification...

引用

Annual Conference of Industrial Electronics Society

作者： Maher Messaoudi Sayed Mohammad Kameli Shady S. Refaat Haitham Abu-Rub Mohamed Trabelsi Department of Electrical and Computer Engineering Texas A&M University at Qatar Doha Qatar School of Physics Engineering and Computer Science University of Hertfordshire Hatfield United Kingdom Electronics and Communications Engineering Department Kuwait College of Science and Technology Kuwait

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

Discharges, such as partial discharges (PDs) and corona discharges (CDs) are the most common faults that occur in insulation materials used in high voltage (HV) equipment. A high repetition rate of discharge activity indicates the severity of the defects that shorten the lifetime of electrical equipment, leading to insulation failure. To solve this, this paper proposes an efficient classification technique for corona discharge defect intensity using features obtained from statistical parameters such as the ignition voltage of CDs. The Recurrent Neural Network (RNN) is proposed to identify the intensity of corona discharges. A comprehensive experimental evaluation is conducted, to demonstrate the capabilities of the proposed solution. The exceptional predictive abilities of the long short-term memory (LSTM) method are the primary benefit of the proposed approach presented, with a potential for enhancing the performance of CD detection systems. The obtained results demonstrate the accuracy of the proposed model, indicating its potential for deployment in practical applications. The innovative approaches utilized in this paper will help engineers and operators quickly determine the severity (sharpness and curvature) of the protrusions or surface defects that cause CDs, solely based on measurements of the ignition voltage.

关键词： Partial discharges Voltage measurement Surface discharges Ignition Conductors Discharges (electric) Corona Surface roughness Rough surfaces Long short term memory

来源：评论

学校读者我要写书评

暂无评论

Glfnet: Global-Local (Frequency) Filter Networks for Efficient Medical Image Segmentation

Glfnet: Global-Local (Frequency) Filter Networks for Efficie...

引用

IEEE International Symposium on Biomedical Imaging

作者： Athanasios Tragakis Qianying Liu Chaitanya Kaul Swalpa Kumar Roy Hang Dai Fani Deligianni Roderick Murray-Smith Daniele Faccio School of Physics and Astronomy University of Glasgow Glasgow UK School of Computing Science University of Glasgow United Kingdom Department of Computer Science and Engineering Alipurduar Government Engineering and Management College West Bengal India

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

We propose a novel transformer-style architecture called Global-Local Filter Network (GLFNet) for medical image segmentation and demonstrate its state-of-the-art performance. We replace the self-attention mechanism with a combination of global-local filter blocks to optimize model efficiency. The global filters extract features from the whole feature map whereas the local filters are being adaptively created as 4 × 4 patches of the same feature map and add restricted scale information. In particular, the feature extraction takes place in the frequency domain rather than the commonly used spatial (image) domain to facilitate faster computations. The fusion of information from both spatial and frequency spaces creates an efficient model with regards to complexity, required data and performance. We test GLFNet on three benchmark datasets achieving state-of-the-art performance on all of them while being almost twice as efficient in terms of GFLOP operations. Our code is available here † .

关键词： Image segmentation Accuracy Frequency-domain analysis Computational modeling computer architecture Benchmark testing Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Enhanced Optimized Routing Technique for Data Aggregation in Wireless Sensor Networks

Enhanced Optimized Routing Technique for Data Aggregation in...

引用

2022 International Conference on Sustainable Computing and Data Communication Systems, ICSCDS 2022

作者： Ganesh, R. Karthik Robinson, Y. Harold Reeginal, Y. Scad College of Engineering and Technology Department of Computer Science and Engineering Tirunelveli India School of Information Technology and Engineering Vellore Institute of Technology Tamilnadu Vellore India Scad College of Engineering and Technology Department of Physics Cheranmahadevi India

ISBN: (纸本)9781665478847

The optimized routing procedure has been used to discover the optimum path in Wireless Sensor Networks (WSNs) as it also enhances the network lifetime using the consideration of the node's energy level. The Enhanced Optimized Routing Technique (EORT) is proposed in this paper for maintaining the data aggregation process and also enhancing the Quality of Service. Whenever a sensor node needs to deliver the data packet, it identifies the intermediate node as every node has the sensing area with similar energy level and routing speed. The cluster head is identified through the metrics of total hops within the sink and residual energy across the sink node. The network has been segregated into smaller areas while the forwarder node can deliver the data packet into the sink node. The simulation results proved that the proposed technique has produced the enhanced performances than the related methodologies. © 2022 IEEE.

关键词： Quality of service

来源：评论

学校读者我要写书评

暂无评论

The efficacy of deep learning based LSTM model in forecasting the outbreak of contagious diseases

引用

Infectious Disease Modelling 2022年第1期7卷 170-183页

作者： Nurul Absar Md.Nazim Uddin Mayeen Uddin Khandaker Md.Habib Ullah Department of Computer Science and Engineering BGC Trust UniversityBangladeshChittagong4381Bangladesh Centre for Applied Physics and Radiation Technologies School of Engineering and TechnologySunway UniversityBandar Sunway47500SelangorMalaysia Department of Physics Faculty of Science and TechnologyAmerican International University-Bangladesh(AIUB)Dhaka1229Bangladesh

The coronavirus disease that outbreak in 2019 has caused various health *** to the WHO,the first positive case was detected in Bangladesh on 7th March 2020,but while writing this paper in June 2021,the total confirmed,recovered,and death cases were 826922,766266 and 13118,*** to the emergence of COVID-19 in Bangladesh,the country is facing a major public health ***,the country does not have a comprehensive health policy to address this *** makes it hard to predict how the pandemic will affect the *** learning techniques can help us detect the disease's *** predict the trend,parameters,risks,and to take preventive measure in Bangladesh;this work utilized the Recurrent Neural Networks based Deep Learning methodologies like LongShort-Term ***,we aim to predict the epidemic's progression for a period of more than a year under various scenarios in *** extracted the data for daily confirmed,recovered,and death cases from March 2020 to August *** obtained Root Mean Square Error(RMSE)values of confirmed,recovered,and death cases indicates that our result is more accurate than other contemporary *** study indicates that the LSTM model could be used effectively in predicting contagious *** obtained results could help in explaining the seriousness of the situation,also mayhelp the authorities to take precautionary steps to control the situation.

关键词： COVID-19 LSTM Recurrent neural networks(RNN) Prediction RMSE

来源：评论

学校读者我要写书评

暂无评论

High-precision chaotic radial basis function neural network model:Data forecasting for the Earth electromagnetic signal before a strong earthquake

引用

Geoscience Frontiers 2022年第1期13卷 364-373页

作者： Guocheng Hao Juan Guo Wei Zhang Yunliang Chen David AYuen School of Mechanical Engineering and Electronic Information China University of GeosciencesWuhan 430074China School of Computer Science China University of GeosciencesWuhan 430074China Department of Mathematics Duke UniversityDurhamNC 27708USA Department of Applied Physics and Applied Mathematics Columbia UniversityNew YorkNY 10027USA

The Earth’s natural pulse electromagnetic field data consists typically of an underlying variation tendency of intensity and *** change tendency may be related to the occurrence of earthquake *** of the underlying intensity trend plays an important role in the analysis of data and disaster *** chaos theory and the radial basis function neural network,this paper proposes a forecasting model of the chaotic radial basis function neural network to conduct underlying intensity trend forecasting by the Earth’s natural pulse electromagnetic field *** main strategy of this forecasting model is to obtain parameters as the basis for optimizing the radial basis function neural network and to forecast the reconstructed Earth’s natural pulse electromagnetic field *** verification experiments,we employ the 3 and 6 days’data of two channels as training samples to forecast the 14 and 21-day Earth’s natural pulse electromagnetic field data *** to the forecasting results and absolute error results,the chaotic radial basis function forecasting model can fit the fluctuation trend of the actual signal strength,effectively reduce the forecasting error compared with the traditional radial basis function ***,this network may be useful for studying the characteristics of the Earth’s natural pulse electromagnetic field signal before a strong earthquake and we hope it can contribute to the electromagnetic anomaly monitoring before the earthquake.

关键词： Earth’s natural pulse electromagnetic field Chaos theory Radial Basis Function neural network Forecasting model

来源：评论

学校读者我要写书评

暂无评论

Study of Photonic Platforms for On-Chip Refractive Index Sensing

Study of Photonic Platforms for On-Chip Refractive Index Sen...

引用

Photonics North

作者： Raghi El Shamy Mohamed A. Swillam Xun Li Department of Electrical and Computer Engineering Faculty of Engineering McMaster University Hamilton Canada Department of Physics School of Science and Engineering The American University in Cairo New Cairo Egypt

ISBN: (数字)9798350366365

ISBN: (纸本)9798350366372

Here we present a rigorous study for the different integrated photonic platforms that can be used for on-chip refractive index (RI) sensing. The study includes the widespread silicon photonics platform, the silicon nitride platform and the silica platform. We compare these three platforms according to five parameters that determine the performance and reliability of the RI sensor. Finally, we conclude with the optimum platform for on-chip RI sensing according to the available technology and the aimed application.

关键词： Refractive index Silicon nitride Silicon photonics System-on-chip Sensors Reliability

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：