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5th IEEE International Conference on Dielectrics, ICD 2024

作者： Xin, Yuepeng Liu, Yong Feng, Guangming Wang, Minxin Guo, Yufeng Jiao, Jingyi Du, Boxue School of Electrical and Information Engineering Tianjin University Tianjin China Suzhou Nuclear Power Research Institute Co. Ltd. Suzhou China North China Electric Power University Department of Computer Science Baoding China

ISBN: (纸本)9798350308976

The aging discrimination method of composite insulators has always been the focus of research in the electric power field. This paper obtained the SEM data set (CIS-SEM data set) by collecting 550 composite insulator samples in operation in a coastal area in China. By analyzing SEM images, this paper determined the aging characteristics of the SiR surface of composite insulators at different aging stages. Then, based on different aging characterizations, this paper divided the aging degree of composite insulators into 6 levels from the micro-level. This paper improved the basic YOLOv8 and added the improved CBAM to achieve better determination of dense targets. For small object detection, we proposed a four-head ASFF prediction head, which can be replaced according to the characteristics of the data set. The results show that the detection accuracy (mAP) of the IC-FHA-YOLOv8 algorithm on the CIS-SEM data set can reach 98.6%. The new algorithm can achieve higher detection accuracy at the expense of less detection speed, which can also well balance the accuracy and speed of the algorithm. It is of great significance to identify the aging of composite insulators from the micro-level. © 2024 IEEE.

关键词： ageing composite insulator IC-FHA-YOLOv8 micro-detection SEM

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An Improved Method for Identifying SSVEP Single-Channel Target Frequency for BCI Systems 3

An Improved Method for Identifying SSVEP Single-Channel Targ...

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3rd International Conference on Emerging Trends in electrical, Control, and Telecommunication engineering, ETECTE 2024

作者： Wahab, Adeel Khan, Umar Shahbaz Nawaz, Tahir Akbar, Hassan Shah, Syed Tayyab Hussain Khan, Zulfiqar Hasan Department of Mechatronics Engg National University of Sciences and Technology IslamabadH-12 Pakistan National Centre of Robotics and Automation National University of Sciences and Technology IslamabadH-12 Pakistan Department of Basic Sciences and Humanities National University of Sciences and Technology IslamabadH-12 Pakistan Faculty of Electrical Engineering Ghulam Ishaq Khan Institute of Engineering Sciences and Technology Topi Pakistan

ISBN: (纸本)9798331504861

Steady-state visual evoked potential (SSVEP) is a brain response to flickering visual stimuli in the occipital area. SSVEP detection methods usually utilize multichannel configurations, which can be intricate and uncomfortable. Conversely, single-channel configurations are simple and user-friendly, but attaining the necessary accuracy is difficult, requiring the development of a reliable and accurate single-channel technique. For this purpose, this study introduces a hybrid VMD-LGBM approach to single-channel SSVEP detection. The proposed technique utilizes VMD as a preprocessor that decomposes the SSVEP signal into harmonic, intrinsic mode functions (IMFs), and noisy IMFs. To separate harmonic IMFs from noisy IMFs, the crest factor of the cross-correlation function was introduced. Then the restored SSVEP signal is used to extract features using power spectral density analysis (Welch's approach), followed by classification using a Light Gradient Boosting Machine. Our proposed approach performs better than available techniques in terms of classification accuracy and information transfer rate. The proposed single-channel approach provides better efficiency and user-friendliness for practical applications. ©2024 IEEE.

关键词： Harmonic analysis

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Retinal Malady Classification Using AI: A novel ViT-SVM combination architecture 6

Retinal Malady Classification Using AI: A novel ViT-SVM comb...

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6th International Conference on Computing Methodologies and Communication, ICCMC 2022

作者： Jha, Shashwat Luhach, Vishvaditya Poddar, Raju Birla Institute of Technology Mesra Department of Electrical and Electronics Engineering Ranchi India Maharaja Surajmal Institute of Technology Department of Computer Science and Engineering New Delhi India Birla Institute of Technology Mesra Department of Bio-Technology Ranchi India

ISBN: (纸本)9781665410281

Macular Holes, Central serous retinopathy and Diabetic Retinopathy are some of the most widespread maladies of the eyes responsible for either partial or complete vision loss, thus making it clear that early detection of the mentioned defects is detrimental for the well-being of the patient. This study intends to introduce the application of Vision Transformer and Support Vector Machine based hybrid architecture (ViT-SVM) and analyse its performance to classify the Optical Coherence Topography (OCT) Scans with the intention to automate the early detection of these retinal defects. © 2022 IEEE.

关键词： Support vector machines

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Safe Collective Control Under Noisy Inputs and Competing Constraints via Non-Smooth Barrier Functions

Safe Collective Control Under Noisy Inputs and Competing Con...

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European Control Conference (ECC)

作者： Clinton Enwerem John S. Baras Department of Electrical & Computer Engineering Institute for Systems Research University of Maryland College Park MD USA

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

We consider the problem of safely coordinating ensembles of identical autonomous agents to conduct complex missions with conflicting safety requirements and under noisy control inputs. Using non-smooth control barrier functions (CBFs) and stochastic model-predictive control as springboards, and by adopting an extrinsic approach where the ensemble is treated as a unified dynamic entity, we devise a method to synthesize safety-aware control inputs for uncertain collectives. Drawing upon stochastic CBF theory and recent developments in Boolean CBF composition, our method proceeds by smoothing a Boolean-composed CBF and solving a stochastic optimization problem where each agent's forcing term is restricted to the affine subspace of control inputs certified by the combined CBF. For the smoothing step, we employ a polynomial approximation scheme, providing evidence for its advantage in generating more conservative yet sufficiently-filtered control inputs than the smoother but more aggressive equivalents produced from an approximation technique based on the log-sum-exp function. To further demonstrate the utility of the proposed method, we present an upper bound for the expected CBF approximation error, along with results from simulations of a single-integrator collective under velocity perturbations. Lastly, we compare these results with those obtained using a naive state-feedback controller lacking safety filters.

关键词： Smoothing methods Upper bound Stochastic processes Control systems Polynomials Robustness Safety

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Photon pair generation with >600 coincidence-to-accidental ratio in the 4H-SiC-on-insulator platform

Photon pair generation with >600 coincidence-to-accidental r...

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Optica Quantum 2.0 Conference and Exhibition, Quantum 2.0

作者： Rahmouni, Anouar Ma, Lijun Wang, Ruixuan Li, Jingwei Tang, Xiao Gerrits, Thomas Li, Qing Slattery, Oliver National Institute of Standards and Technology 100 Bureau Dr GaithersburgMD20899 United States Department of Electrical and Computer Engineering Carnegie Mellon University PittsburghPA15213 United States

We demonstrate efficient photon pair generation via implementing spontaneous four-wave mixing in a compact, high-quality-factor microring resonator in the 4H-silicon-carbide-on-insulator platform. Photon pairs with co... 详细信息

ISBN: (纸本)9781957171272

关键词： Four wave mixing Nonlinear optical crystals Raman scattering Ring resonators Silicon carbide Tunable diode lasers

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Demonstration of a Vertically Stacked Junctionless Forksheet as Dielectric Modulated Biosensor 28

Demonstration of a Vertically Stacked Junctionless Forksheet...

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28th International Symposium on VLSI Design and Test, VDAT 2024

作者： Gandhi, Navneet Jaisawal, Rajeewa Kumar Kondekar, P.N. Dixit, Ankit Kumar, Naveen Georgiev, Vihar Bagga, Navjeet PDPM-IIITDM Vlsi Lab Electronics & Communication Department Jabalpur India University of Glasgow Device Modelling Group James Watt School of Engineering United Kingdom Indian Institute of Technology School of Electrical and Computer Sciences Bhubaneswar India

ISBN: (纸本)9798350380101

In this paper, we demonstrated the performance metrics of a Junctionless vertically stacked Forksheet FET for biosensing applications. Through the use of well-calibrated TCAD models, the N-and P-side of a Forksheet FET is designed with a cavity region where the presence/absence of the biomolecule is sensed using a permittivity modulation approach. The label-free electrical detection of different biomolecules, including streptavidin (K=2.1), biotin (K=2.63), APTES (K=3.57), and keratin (K=8) is obtained by analyzing the variations in threshold voltage, OFF current, and the ION/IOFF ratio as sensing performance metrics. The proposed Junctionless sensor exhibits superior electrical characteristics and sensitivity at lower metal gate work functions compared to other available Junctionless devices operating at higher metal gate work functions. Thus, the study underscores the potential of the proposed Junctionless Forksheet FET for efficient and accurate biosensing applications. © 2024 IEEE.

关键词： Biomolecules

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Real-time Glass Recycling Quality Assurance and Contamination Reduction with IoT and Random Forest algorithm 7

Real-time Glass Recycling Quality Assurance and Contaminatio...

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7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Balasubadra, K. Shadaksharappa, B. Seeni, Senthil Kumar Sridevi, V. Thamizhamuthu, R. Srinivasan, C. R.M.D. Engineering College Department of Information Technology Chennai Tamil Nadu Kavaraipettai India Sri Sairam College of Engineering Department of Computer Science And Engineering Bengaluru Karnataka Anekal India Cognizant Technology Solutions Department of Mobile Application Development Buffalo GroveIL United States Academy of Maritime Education And Training Deemed To Be University Electrical And Electronics Engineering Tamil Nadu Chennai India Srm Institute of Science And Technology Department of Computing Technologies Kattankulathur Campus Chennai Tamil Nadu Chengalpattu India Saveetha University Saveetha School of Engineering Saveetha Institute of Medical And Technical Sciences Department of Computer Science And Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350359299

The recycling industry is crucial to environmental protection and resource conservation. Glass recycling has great sustainability potential, but quality assurance and contaminant reduction are major challenges. Integrating the Internet of Things (IoT) with the Random Forest algorithm, this work offers a new solution to these difficulties. IoT devices are used in glass recycling collection, transportation, sorting, and processing. These devices measure glass quality, contaminants, temperature, humidity, and other parameters in real-time. Data is sent to a central system for analysis and decision-making. Random Forest, a machine learning method that handles complicated, multidimensional datasets, powers the system. This algorithm learns from past data and updates with real-time data. It detects contaminants, foreign elements, and faults in recycled glass. This permits fast remedial action, enhancing recycled glass quality and decreasing contamination. Application of this mechanism yields two outputs. First, it improves glass recycling efficiency and produces high-quality glass for remanufacturing. Second, it significantly minimizes the environmental and economic implications of contamination and low-quality glass, which may limit recycling yields and increase waste disposal. In comparison to traditional approaches, the proposed approach that utilizes the IoT and the Random Forest algorithm reduces contamination and ensures the quality of glass recycling by 30%. © 2024 IEEE.

关键词： Internet of things

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How to turn your camera into a perfect pinhole model

arXiv

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arXiv 2023年

作者： De Boi, Ivan Pathak, Stuti Oliveira, Marina Penne, Rudi InViLab University of Antwerp Groenenborgerlaan 171 Antwerp2020 Belgium Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Coimbra3004-531 Portugal

Camera calibration is a first and fundamental step in various computer vision applications. Despite being an active field of research, Zhang's method remains widely used for camera calibration due to its implementation in popular toolboxes like MATLAB and OpenCV. However, this method initially assumes a pinhole model with oversimplified distortion models. In this work, we propose a novel approach that involves a pre-processing step to remove distortions from images by means of Gaussian processes. Our method does not need to assume any distortion model and can be applied to severely warped images, even in the case of multiple distortion sources, e.g., a fisheye image of a curved mirror reflection. The Gaussian processes capture all distortions and camera imperfections, resulting in virtual images as though taken by an ideal pinhole camera with square pixels. Furthermore, this ideal GP-camera only needs one image of a square grid calibration pattern. This model allows for a serious upgrade of many algorithms and applications that are designed in a pure projective geometry setting but with a performance that is very sensitive to nonlinear lens distortions. We demonstrate the effectiveness of our method by simplifying Zhang's calibration method, reducing the number of parameters and getting rid of the distortion parameters and iterative optimization. We validate by means of synthetic data and real world images. The contributions of this work include the construction of a virtual ideal pinhole camera using Gaussian processes, a simplified calibration method and lens distortion removal. Copyright © 2023, The Authors. All rights reserved.

关键词： Pinhole cameras

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Path Loss Modelling for UAV Communications in Urban Scenarios with Random Obstacles

Path Loss Modelling for UAV Communications in Urban Scenario...

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European Conference on Antennas and Propagation, EuCAP

作者： Abdul Saboor Zhuangzhuang Cui Evgenii Vinogradov Sofie Pollin WaveCoRE of the Department of Electrical Engineering (ESAT) KU Leuven Leuven Belgium Autonomous Robotics Research Center Technology Innovation Institute Abu Dhabi UAE

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

Path Loss ( $PL$ ) is vital to evaluate the performance of Unmanned Aerial Vehicles (UAVs) as Aerial Base Stations (ABSs), particularly in urban environments with complex propagation due to various obstacles. Accurately modeling $PL$ requires a generalized Probability of Line-of-Sight $(P_{LoS})$ that can consider multiple obstructions. While the existing $P_{LoS}$ models mostly assume a simplified Manhattan grid with uniform building sizes and spacing, they overlook the real-world variability in building dimensions. Furthermore, such models do not consider other obstacles, such as trees and streetlights, which may also impact the performance, especially in millimeter-wave (mmWave) bands. This paper introduces a Manhattan Random Simulator (MRS) to estimate $P_{LoS}$ for UAV-based communications in urban areas by incorporating irregular building shapes, non-uniform spacing, and additional random obstacles to create a more realistic environment. Lastly, we present the PL differences with and without obstacles for standard urban environments and derive the empirical PL for these environments.

关键词： Base stations Shape Urban areas Buildings Layout Line-of-sight propagation Autonomous aerial vehicles Propagation losses Millimeter wave communication Standards

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Time-Resolved FMRI Shared Response Model Using Gaussian Process Factor Analysis 48

Time-Resolved FMRI Shared Response Model Using Gaussian Proc...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Ebrahimi, MohammadReza Calarco, Navona Hawco, Colin Voineskos, Aristotle Khisti, Ashish University of Toronto Department of Electrical and Computer Engineering TorontoON Canada Centre for Addiction and Mental Health TorontoON Canada University of Toronto Department of Psychiatry TorontoON Canada University of Toronto Institute of Medical Science TorontoON Canada

ISBN: (纸本)9781728163277

Multi-subject fMRI studies are challenging due to the high variability of both brain anatomy and functional brain topographies across participants. An effective way of aggregating multi-subject fMRI data is to extract a shared representation that filters out unwanted variability among subjects. Some recent work has implemented probabilistic models to extract a shared representation in task fMRI. In the present work, we improve upon these models by incorporating temporal information in the common latent structures. We introduce a new model, Shared Gaussian Process Factor Analysis (S-GPFA), that discovers shared latent trajectories and subject-specific functional topographies, while modeling temporal correlation in fMRI data. We demonstrate the efficacy of our model using the time-segment matching experiment on the publicly available Raider dataset. We further test the utility of our model by analyzing its learned model parameters in the large multi-site SPINS dataset, on a social cognition task from participants with and without schizophrenia. © 2023 IEEE.

关键词： Multivariant analysis

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