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2023 IEEE International Conference on Dependable, Autonomic and Secure computing, 2023 International Conference on Pervasive Intelligence and computing, 2023 International Conference on Cloud and Big Data computing, 2023 International Conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023

作者： Nicolas, Dowens Figueroa, Henry Wang, Yi Elmannai, Wafa Giakos, George C. Manhattan College Electrical and Computer Engineering Department New York United States

ISBN: (纸本)9798350304602

The paper investigates the use of AI in power systems to improve monitoring, control, and optimization. For successful classification tasks on various datasets, ML models are critical, boosting power system dependability and efficiency. The research focuses on ML model designs in AI-driven power systems for binary, triple, and multiclass classification. Misclassifications can destabilize grid stability, underlining the importance of precise classification in decision-making processes. To combat this, this research proposes a DNN model that uses specific parameters that were fine-tuned for greater accuracy in classification tasks. Model correctness is an important performance metric that can be improved by architecture design and fine-tuning. For successful optimization, three essential loss functions (binary cross-entropy, categorical cross-entropy, and sparse categorical cross-entropy) are investigated. We have achieved great results with utilizing the sparse categorical cross-entropy loss function to minimize the error during training periods. The study underscores the critical relevance of correct categorization and the possibility for robust AI applications in power systems, which contribute to grid stability and sustainability. © 2023 IEEE.

关键词： Classification (of information)

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Enhancing sound pressure output in graphene-based hybrid bone conduction hearing aids through electromagnetic and electrostatic integration

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Nano Research 2025年第4期18卷 425-434页

作者： Dong-Kwan Lee Hyunwoo Baek Byung-Ho Kang § Jongchan Yoo Kun-Woo Nam Sang Hyun Lee Illsoo Sohn Eunjung Han June Choi Sung-Hoon Park Department of Mechanical Engineering Soongsil UniversitySeoul 06978Republic of Korea Department of Otorhinolaryngology-Head and Neck Surgery Korea University College of MedicineAnsan HospitalAnsan 15355Republic of Korea School of Electrical Engineering Korea UniversitySeoul 02841Republic of Korea Department of Computer Science and Engineering Seoul National University of Science and TechnologySeoul 01811Republic of Korea

Bone conduction hearing aids(BCHA)actively serve patients with conductive hearing loss or external auditory canal problems,including auditory canal atresia,ossicular dislocation,*** are typically categorized into surgically implanted devices,embedded directly into the skull,and adhesive devices,which transmit sound through the *** latter are advantageous for being noninvasive and suitable for children under ***,adhesive devices,due to their sound transmission method,require enhanced sound output performance compared to implanted ***,known for its low mass density yet excellent mechanical and electrical properties,finds application in various electronic ***,it serves as a diaphragm in electroacoustic transducers,enabling stable vibrations across broad frequency *** electroacoustic transducers of BCHA are typically driven by electromagnetic methods,which may be effective in low-frequency ranges but not in high-frequency *** study successfully introduced a hybrid approach that combines the complementary advantages of both electromagnetic and electrostatic modes by utilizing a graphene sheet as the diaphragm for a hybrid graphene *** electrostatic mode,which performs better in highfrequency ranges compared to the electromagnetic mode,was implemented in this hybrid *** to the measured frequency response data,the hybrid mode showed up to an 11 dB improvement compared to the electromagnetic mode and up to a 21 dB improvement compared to the electrostatic mode,exhibiting a relatively flat shape over a wide frequency ***,the device’s effectiveness as a BCHA is confirmed through experiments on rabbits,showcasing its potential in auditory aid advancement.

关键词： graphene bone conduction hearing aid loudspeaker frequency response

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Average Current Control Design of Active Power Decoupling Converter with Low Filter Inductance Based on Double Sampling Techniques for PV Microinverter

Average Current Control Design of Active Power Decoupling Co...

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2024 International Conference on Sustainable Energy: Energy Transition and Net-Zero Climate Future, ICUE 2024

作者： Shen, Yidi Hasnain, Arafat Zakzewski, Daniel Resalayyan, Rakesh Khaligh, Alireza University of Maryland College Park Department of Electrical and Computer Engineering The Institute for Systems Research College ParkMD United States

ISBN: (纸本)9798331517076

Active power decoupling (APD) converter is a power dense and reliable solution in dc-ac power conversion systems to balance the fluctuating ac-side power and constant dc-side power. In boost type APD converter, filter inductor with low inductance can be beneficial in achieving efficient and compact designs or allows the implementation of zero voltage switching (ZVS) based modulation. On the other hand, the reduced inductance increases the difficulty of controller design due to reduction of the average current control loop phase margin and higher requirement in low-pass-filter (LPF). This paper proposes an average current control based on double sampling techniques to reduce the phase delay of LPF and improve the current tracking performance under low inductance. The implementation of double sampling in the digital signal processor (DSP) and the design of control loops are discussed. The proposed approach is experimentally verified using a 40 V, 400 W APD converter prototype. © 2024 IEEE.

关键词： Low pass filters

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Solar thermal application and optimization of a staircase-shaped resonator broadband solar absorber

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Optical and Quantum Electronics 2024年第12期56卷 1-14页

作者： Alsharari, Meshari Muheki, Jonas Surve, Jaymit Armghan, Ammar Aliqab, Khaled Patel, Shobhit K. Department of Electrical Engineering. College of Engineering Jouf University Sakaka72388 Saudi Arabia Department of physics Biological and medical physics University of Houston HoustonTX United States Department of Electrical Engineering Marwadi University Gujarat Rajkot360003 India Department of Computer Engineering Marwadi University Gujarat Rajkot360003 India

The development of efficient energy absorbers is essential for optimizing solar energy utilization, particularly for applications such as thermophotovoltaics and other solar energy harvesting technologies. Current research typically focuses on improving the efficiency of the solar absorbers with low-cost materials. This study addresses this limitation by introducing a broadband solar absorber with a staircase-shaped resonator structure. The absorber employs tungsten as the substrate due to its high thermal conductivity and stability, with a GaInAsP layer forming the staircase resonator. Simulations using finite element methods demonstrate that the proposed two-layered structure achieves over 90% absorption within the 200–3000 nm wavelength range, including ultraviolet and visible spectra. This broad absorption range maximizes solar energy capture and conversion efficiency. A parametric examination demonstrates how geometric factors like substrate depth and resonator dimensions affect the absorption effectiveness. The unique staircase shape of the resonator enhances light trapping and absorption across the full spectrum. Under real-world conditions, the absorber effectively captures solar energy across various angles and polarizations. These findings contribute to the advancement of energy absorber design and offer insights for future innovations in solar energy harvesting. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Stairs

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Wavelet-Transformed K-NN Pipeline for EEG-Based Eye Blink Classification with Time Wrapping 2nd

Wavelet-Transformed K-NN Pipeline for EEG-Based Eye Blink C...

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2nd International Conference on Data Science and Network engineering, ICDSNE 2024

作者： Priyadharshini Jayadurga, N. Chandralekha, M. Saleem, Kashif Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India Department of Computer Sciences and Engineering College of Applied Studies and Community Service King Saud University Riyadh Saudi Arabia

ISBN: (纸本)9789819783359

An innovative pipeline integrating wavelet transform, k-nearest neighbors (k-NN), and temporal wrapping approaches is presented in this work for the classification of eye blinks in electroencephalogram (EEG) recordings. The proposed process commences with raw EEG data preprocessing followed by wavelet treatment to extract significant time and frequency domain properties. These characteristics are subsequently utilized by a k-NN classifier to enhance the accuracy of eye blink recognition by using spatial relationships within EEG signals. Notably, the integration of a novel time wrapping technique deals with temporal dynamics, supplying the model with resilience to fluctuations in eye blink patterns across time. The pipeline’s enhanced efficiency can be observed through validation using a customized EEG dataset, particularly when navigating the time complexity associated with eye blink events. Evaluations performed against current techniques demonstrate the efficacy of the proposed solution. The outcomes not only demonstrate the methodology’s accuracy, but also its possible use in real-world settings featuring clinical diagnostics and human-computer interactions. This work conveys a strong basis for the discipline of EEG-based eye blink classification, having implications to enhance neuroscience and facilitating beneficial uses in healthcare and assistive technologies. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Wavelet transforms

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An EfficientNet to Classify Monkeypox-Comparable Skin Lesions Using Transfer Learning

An EfficientNet to Classify Monkeypox-Comparable Skin Lesion...

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2023 IEEE International Conference on Omni-Layer Intelligent Systems, COINS 2023

作者： Hossen, Md. Rifat Alfaz, Nazia Sami, Adnan Tanim, Sharia Arfin Bin Sarwar, Talha Islam, Md. Kamrul Department of Computer Science and Engineering Dhaka Bangladesh Department of Computer Science Dhaka Bangladesh College of Computing and Applied Science Universiti Malaysia Pahang Faculty of Computing Pekan Malaysia

ISBN: (纸本)9798350346473

Monkeypox is an infectious illness caused by the DNA-based monkeypox virus, which has raised public health concerns due to its rapid transmission to over 50 countries. Direct physical interaction with infected humans or infected animals is the main reason behind the spread of this virus. The appearance of skin problems such as smallpox and rashes are the most frequently reported symptoms of this virus. Since cases of monkeypox are increasing rapidly around the world, stopping the spread of this zoonosis by providing early diagnosis and treatment is crucial before the emergence of a pandemic similar to COVID-19. In this study, we aim to propose a transfer learning-based approach using the EfficientNet-B0 architecture to identify monkeypox subjects by using skin lesion image samples. However, distinguishing monkeypox from other comparable infectious skin illnesses like chickenpox and measles is challenging. Therefore, additionally, this study identifies other diseases that also cause blisters and rashes on the skin, like chickenpox, and measles. During the data distribution phase, 5-fold cross-validation is used to validate the work's reliability by assuring that every sample is utilized for training and validation. For the evaluation of the model's classification performance, accuracy and loss are recorded for each training epoch. Moreover, precision, recall, F1-score, and confusion matrix are generated upon completion of the model training. This proposed approach is experimented on a public dataset and has shown remarkable performance by providing an overall 96.53% classification accuracy, 96.57% precision, 96.53% recall, and 96.52% F1-score. © 2023 IEEE.

关键词： Viruses

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Dynamic Model Reduction for Decentralized Learning in Heterogeneous Mobile Networks 20

Dynamic Model Reduction for Decentralized Learning in Hetero...

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20th IEEE International Conference on Mobile Ad Hoc and Smart Systems, MASS 2023

作者： Lee, Sangsu Zheng, Xi Hua, Jie Yu, Haoxiang Julien, Christine University of Texas Department of Electrical and Computer Engineering Austin United States Macquarie University School of Computing Australia

ISBN: (纸本)9798350324334

Collaborating with nearby devices to train and personalize deep learning models opens the potential to support new mobile application scenarios. In emerging decentralized learning algorithms, devices communicate over a peer-to-peer network to share knowledge obtained from local data. However, communication bandwidth, computing power, and the duration for which these connections are available are limited and heterogeneous. In this paper, we explore the feasibility and efficacy of adaptive model reduction strategies for decentralized learning algorithms (Dynamic Reduction (DR)). For this study, we use as an exemplar an existing opportunistic learning algorithm (OppCL) that relies on device-to-device model exchanges to iteratively train a local model based on encounters. In layering model reduction on OppCL, when a device encounters a potential learning partner, it dynamically constructs a model reduction suitable for given computation and communication budget by quantizing weights and building a dropout version of a neural network. We term our new approach DR-OppCL and show that DR-OppCL leads to faster convergence with minimal effort in tuning hyperparameters related to model reduction, using both simulated and real-world mobility traces. While we demonstrate our DR approaches in the context of OppCL, they are generic and can be easily applied to other decentralized learning algorithms. © 2023 IEEE.

关键词： Learning algorithms

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Random hyperbolic graphs in d+1 dimensions

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Physical Review E 2024年第5期109卷 054131-054131页

作者： Gabriel Budel Maksim Kitsak Rodrigo Aldecoa Konstantin Zuev Dmitri Krioukov Faculty of Electrical Engineering Mathematics and Computer Science Department of Physics Network Science Institute Department of Computing and Mathematical Sciences Department of Physics Department of Mathematics Department of Electrical & Computer Engineering

We consider random hyperbolic graphs in hyperbolic spaces of any dimension d+1≥2. We present a rescaling of model parameters that casts the random hyperbolic graph model of any dimension to a unified mathematical framework, leaving the degree distribution invariant with respect to the dimension. Unlike the degree distribution, clustering does depend on the dimension, decreasing to 0 at d→∞. We analyze all of the other limiting regimes of the model, and we release a software package that generates random hyperbolic graphs and their limits in hyperbolic spaces of any dimension.

关键词： Network formation & growth Network structure

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AI-EgyVent: Artificial Neural Network Assisted Control based Low-Cost Ventilator Implementation in Response to COVID-19 Pandemic

AI-EgyVent: Artificial Neural Network Assisted Control based...

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2023 International Telecommunications Conference, ITC-Egypt 2023

作者： Abotaleb, Abdelrhman M. Mohammed, Ahmed Abdellatif Saber, Mohammed Taha Riad, Mohamed Cairo University Communications and Electrical Engineering Department Egypt Cairo University Computer Engineering Department Egypt Military Technical College Electrical Engineering Department Egypt

ISBN: (纸本)9798350326062

It has become crucial to develop low-cost ventilators as the demand for these life-saving devices has increased during the COVID-19 pandemic. A pneumatic system of four ventilation modes is implemented with an overall cost under $400. The proposed design utilizes sensor fusion to achieve precise flow values even if low-accuracy sensors are used. Fluke biomedical monitoring device is used to verify the functionality correctness of the ventilator. An Artificial Neural Network (ANN) is used to enhance the PID control process of the ventilator, providing better accuracy and faster response times. The ANN is trained using a dataset generated from the ventilator system using two test lungs with different compliance values. The proposed ANN achieves a high determination coefficient of 87.97% and a low mean absolute error equals to 3.26 while maintaining a low number of parameters equals to 70, to be feasible for the hardware implementation. © 2023 IEEE.

关键词： COVID-19

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Design of Miniature UWB-Based Antenna by Employing a Tri-Sectional SIR Feeder

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computer Systems Science & engineering 2022年第6期41卷 1157-1172页

作者： Ehab Dh.Hussein Yaqeen S.Mezaal Oguz Bayat Electrical and Computer Engineering Department Altinbas UniversityIstanbulTurkey Medical Instrumentation Engineering Department Al-Esraa University CollegeBaghdadIraq

A novel ultra-wideband(UWB)-based microstrip antenna is presented in this work by using a slotted patch resonator,a tri-sectional stepped impedance resonator(SIR)feeder,as well as a reduced ground *** whole structure was realized on an FR4 *** impact of incorporating several cases of ground planes on the input reflection has been thoroughly investigated under the same tri-sectional SIR feeder and by employing a slotted patch *** the complete ground plane presents an inadequate frequency response,by reducing the ground plane,the induced UWB responses are apparent while the antenna exhibits higher impedance *** impact of both the uniform impedance resonator(UIR)as well as the SIR feeder on the input reflection has also been examined by following the same adopted reduced ground technique and using a slotted patch *** a result,the UIR feeder exhibits a dual-band frequency response,when a wide notched band is incorporated in the range from 4.5–6.5 *** dual-band response of the bi-sectional SIR feeder is still apparent with a narrower notched band in the frequency range from 4–5 *** far as the tri-sectional SIR feeder is concerned,the UWB response is discernible without recording the existence of a notched ***,the antenna displays a higher impedance bandwidth compared with the previously reported *** proposed antenna configuration is designed with highly compact dimensions and an overall size of 14×27.2 ***,it operates under the impedance bandwidth of 2.86–10.31 GHz that can be leveraged for numerous applications where wireless systems are *** approach presents several advantages compared with the other reported UWB-based antennas in the literature,whereas the measured S11 pattern is in good agreement with the simulated one.

关键词： Microstrip antenna reduced ground plane slotted patch radiator tri-sectional stepped impedance feeder ultra-wideband

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