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Optics Continuum 2025年第4期4卷 789-803页

作者： Esteban Farfán-Guillén, David Camporez, Higor Silva, Jair Adriano Lima Castellano Rodriguez, Juan Camilo Pohl, Alexandre De Almeida Prado CPGEI–Graduate Program in Electrical Engineering and Computer Science Federal University of Technology Paraná Curitiba80230–901 Brazil Graduate Program in Electrical Engineering Federal University of Espírito Santo Vitória29075-960 Brazil

Visible light communications (VLC) enable wireless data transmission using existing light-emitting diode (LED) illumination. This experimental study evaluates the performance of multiple input and multiple output (MIMO) configurations in indoor VLC systems by analyzing their impact on both communication and illumination. Various MIMO setups (2 × 2, 3 × 2, and 4 × 2) are compared against single input single output (SISO), and single input multiple outputs (SIMO) schemes, using commercial LED luminaires as transmitters. While the 4 × 2 MIMO configuration demonstrates superior overall performance, intermediate configurations like 3 × 2 or 2 × 2 MIMO offer an attractive trade-off between system complexity and performance enhancement, particularly in scenarios with space or cost constraints. The results show that MIMO configurations significantly outperform SISO systems, achieving reliable communication (BER ≤ 10−3) at practical indoor distances of up to 2 meters while maintaining illumination levels above 300 lux, where conventional SISO setups do not meet these dual requirements. These findings demonstrate the practical feasibility of MIMO-VLC systems for indoor deployments. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Frequency division multiplexing Modulation techniques Multiple input multiple output Quadrature amplitude modulation Signal processing Visible light communications

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Compact Model Build Upon Dynamic Weighting Artificial Neural Network Approach for Complementary Field Effect Transistors

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IEEE Transactions on Electron Devices 2024年第1期71卷 246-253页

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation The Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program The Institute of Communications Engineering the Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan

In this work, a dynamic weighting-artificial neural network (DW-ANN) methodology is presented for quick and automated compact model (CM) generation. It takes advantage of both TCAD simulations for high accuracy and SPICE simulations for cost-effectiveness. This methodology is developed for gate-all-around (GAA) silicon (Si) nanosheet (NS) complementary field effect transistor (CFET), a potential candidate for future CMOS technology due to its innate properties. The critical process variation (PV) sources that severely degrade the CFET performance are estimated using DW-ANN. It reduces the computation cost and predicts the effects of PV sources with less than 1% error. Furthermore, a compact DW-ANN-based Verilog-A model has been developed that captures the dc as well as transient behavior accurately for circuit-level analysis. CFET-based circuits such as inverter, 6T-static random access memory (SRAM), and ring oscillator (RO) are characterized and implemented using DW-ANN-based CM. The overall average error of the model is reported as less than 2%. Therefore, the proposed device and circuit modeling approach provides a feasible solution for the rapid compact modeling of new emerging devices with good convergence and high accuracy. © 1963-2012 IEEE.

关键词： Neural networks

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An Expanded Latent Space Autoencoder for Land Cover Classification of Remote Sensing Images from EuroSAT 16

An Expanded Latent Space Autoencoder for Land Cover Classifi...

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16th Brazilian Symposium on Robotics and 15th Workshop on Robotics in Education, SBR-WRE 2024

作者： Vilar Oliveira, Emerson Garcia Gonçalves, Luiz Marcos Graduate Program in Electrical and Computer Engineering Universidade Federal do Rio Grande do Norte Natal Brazil

ISBN: (纸本)9798350391084

Image classification has been instrumental in the interpretation and labeling of images in the field of remote sensing, computer vision, and in robotics applications. Machine learning and artificial intelligence algorithms, particularly artificial neural networks, are extensively utilized for this purpose. In this work we propose the Expanded Latent Space Autoencoder (ELSA) with a case use application to classify land cover data. The main idea on the ELSA network structure is to utilize the latent spaces of multiple internal autoencoders in order to create an expanded latent space. This expanded latent space extracts more information from the input data, and serves as input features for a more simpler classifier network. In order to evaluate the proposed network’s ability to extract features and classify complex and multispectral images we employed it to the EuroSAT dataset. The results demonstrate a remarkable capacity for feature extraction using the ELSA network, with lower complexity, trained with a reduced number of images. The classifier network achieved a final accuracy of 98.7%, matching or exceeding the performance of more complex state-of-the-art models. ©2024 IEEE.

关键词： Neural networks

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Quality Analytics for Latin American and Brazilian Robotics Symposiums 16

Quality Analytics for Latin American and Brazilian Robotics ...

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16th Brazilian Symposium on Robotics and 15th Workshop on Robotics in Education, SBR-WRE 2024

作者： Garcia Gonçalves, Luiz Marcos Electrical and Computer Engineering Graduate Program Universidade Federal do Rio Grande do Norte Natal Brazil

ISBN: (纸本)9798350391084

We bring historical findings related to the most important Latin American and Brazilian Robotics Symposiums including their quality analytics regarding all papers published since their creation. For this quality analysis, we first provide a little of history and then we apply a methodology based on a systematic mapping of the literature using Scopus (from Elsevier) and Web of Science. The quality analysis includes variables as citations metrics, and also other historical variables as participation per countries, per states, per universities, and contributed areas among others. We use metadata and tools available in the most commonly used digital libraries, for a fair comparison. To the end, with basis on the results of our methodological approach, we point out that the community has followed the right path for establishing a high quality event, mainly regarding the decision of publication of the proceedings at IEEE Xplore, and recently in the Brazilian computer Society Library (Sol-SBC), all together. Also, our analysis corroborate to verify the modi operandi that have been used in the events execution, including joining in the Workshop of Robotics in Education (WRE) and the competitions (RCB, OBR, MNR, CBR, LARC). Besides happening jointly, each event keeps their original event structure and characteristics. ©2024 IEEE.

关键词： Taxonomies

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Correntropy-Based Data Selective Adaptive Filtering

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IEEE Transactions on Circuits and Systems I: Regular Papers 2024年第2期71卷 754-766页

作者： Chien, Ying-Ren Wu, Sheng-Teng Tsao, Hen-Wai Diniz, Paulo S.R. Adaptive and Autonomous Communication Laboratory Department of Electrical Engineering National Ilan University Yilan City260007 Taiwan College of Electrical Engineering and Computer Science Graduate Institute of Communication Engineering National Taiwan University Taipei10617 Taiwan Program of Electrical Engineering Department of Electronics and Computer Engineering COPPE/Poli Universidade Federal do Rio de Janeiro Rio de Janeiro68504 Brazil

Data selection can be used in conjunction with adaptive filtering algorithms to avoid unnecessary weight updating and thereby reduce computational overhead. This paper presents a novel correntropy-based data selection method as an alternative to conventional data selection mechanisms based on squared error values. We developed a variable correntropy sensing algorithm to maximize the instantaneous correntropy function for the Gaussian kernel function to mitigate the impact of impulse noise and other forms of noise that can be disregarded in data selection. The proposed data selection mechanism can be implemented with any adaptive filtering algorithm. In simulations, the proposed method (implemented with the least mean squared algorithm) outperformed comparable error-based data selection schemes in terms of hit rate and miss rate, and the resulting weight updating ratio was close to the expected weight updating ratio. © 2023 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.

关键词： Adaptive filters

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Real Time Chest X-Ray Interpretation Applying Vision Transformer for Tuberculosis Detection

Real Time Chest X-Ray Interpretation Applying Vision Transfo...

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2024 International Conference on computer engineering, Network and Intelligent Multimedia, CENIM 2024

作者： Irhamsyah, Muhammad Roslidar Yunidar Al Lail Qadrillah, M. Nasaruddin Arnia, Fitri Munadi, Khairul Universitas Syiah Kuala Post Graduate Program in Engineering Banda Aceh2311 Indonesia Faculty of Engineering Department of Electrical and Computer Engineering 2311 Indonesia

ISBN: (纸本)9798350368802

Tuberculosis (TB) is an infectious disease that can attack the lungs and other organs. In the diagnosis of TB, the interpretation of X-ray radiological images requires special skills from medical specialists. However, the lack of experience of medical personnel and focus on X-ray examinations can be a challenge for radiologists because it has the potential to cause diagnostic errors in image interpretation. Therefore, we proposed a web-based application of real-time chest X-ray interpreter by integrating the deep learning model of Vision Transformer (ViT) to interpret chest X-ray images. The inference model was trained and tested on 652 normal and 652 tuberculosis X-ray images. The data preprocessing of Contrast Adaptive Histogram Equalization (CLAHE) was implemented to increase chest X-ray image contrast as well as inference model performance. The proposed real time system can inteprete the tested chest x-ray images with an accuracy of 95% and with simulation duration time of 4.7 seconds. © 2024 IEEE.

关键词： Diagnosis

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An Ensemble-Based Classifier to Determine the Harmonic Contribution Responsibility Between Utility’s Grid and Microgrids

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IEEE Access 2025年 13卷 85873-85881页

作者： Mella, Matheus C. Fernandes, Ricardo A.S Barbosa, Daniel Federal University of São Carlos Graduate Program in Electrical Engineering São Carlos Brazil University of São Paulo São Carlos School of Engineering Department of Electrical and Computer Engineering São Carlos Brazil Federal University of Bahia Department of Electrical Engineering Salvador Brazil

The integration of nonlinear loads and distributed energy resources in microgrids (MG) has increased the levels of harmonic distortions in distribution feeders. Identifying the responsibility for the harmonic distortions measured at the MG’s point of common coupling (PCC) is essential for managing the power quality. For this purpose, the present paper aims to determine whether the responsibility predominates from the utility’s grid or the MG itself. Thus, an ensemble-based approach was proposed, comparing the behaviour of Random Forest and XGBoost classifiers to identify the side with the predominant harmonic contribution. In order to validate the proposed approach, scenarios were simulated in the IEEE 34-node test feeder using the ATP/ATPDraw software, considering the harmonic sources located at different nodes of the feeder. Three-phase voltage and current signals were acquired at MG’s PCC to train and validate the ensembles. However, a feature extraction stage was performed to obtain time and frequency features used as inputs to the predictive models. The results demonstrated that the proposed approach effectively identified the contribution side, achieving an average F1-score above 99% for both ensembles, representing a feasible solution for determining the harmonic distortion responsibilities at the MG’s PCC. © 2013 IEEE.

关键词： Software testing

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Enhancing Local Area Power Stability: Integrative Oscillation Damping with PV Systems and BESS

Enhancing Local Area Power Stability: Integrative Oscillatio...

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2024 International Conference on Technology and Policy in Energy and Electric Power, ICT-PEP 2024

作者： Akbar, Ilham Zakaria, Ariesa Budi Muljadi, Eduard Graduate Program PLN ITB PLN Corporate University Auburn United States Electrical and Computer Engineering Auburn University Auburn United States

ISBN: (纸本)9798331518646

This research delves into enhancing local area power stability by integrating battery energy storage systems (BESS) with photovoltaic (PV) systems to address and accelerate the damping of post-fault oscillations following short-circuit disturbances within power grids incorporating variable renewable energy sources. Focused on implementing a power oscillation damping (POD) mechanism within PV plants, this study aims to mitigate post-fault oscillations effectively within a specified timeframe. The proposed POD within the PV plant is strategically designed to augment the grid's resilience by supplying additional active and reactive power in response to system demands post-disturbance. The integration of a 25 MW BESS has demonstrated a significant enhancement in the system's recovery speed, reducing oscillation duration from 60 seconds to 45 seconds. Moreover, a configuration with double PV systems and a 50 MW BESS further reduced the oscillation duration to 42 seconds. Utilizing PSCAD software, this study presents an innovative approach to visualize the system's behavior post-short-circuit disturbances, confirming the efficacy of BESS integration in improving system stability and reliability. These results pave the way for further exploration of optimal BESS sizing and placement strategies to maximize grid resilience. © 2024 IEEE.

关键词： Renewable energy

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High impedance fault classification in microgrids using a transformer-based model with time series harmonic synchrophasors under data quality issues

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Neural Computing and Applications 2024年第23期36卷 14017-14034页

作者： Cieslak, Dionatan A. G. Moreto, Miguel Lazzaretti, André E. Macedo-Júnior, José R. PPGEEL - Graduate Program in Electrical Engineering Federal University of Santa Catarina UFSC R. Eng. Agronômico Andrei Cristian Ferreira s/n Santa Catarina Florianópolis88040-900 Brazil CPGEI - Graduate Program in Electrical and Computer Engineering Federal University of Technology - Paraná UTFPR Av. Sete de Setembro 3165 Paraná Curitiba80230-901 Brazil PPGEELT - Graduate Program in Eletrical Engineering Federal University of Uberlândia UFU Av. João Naves de Ávila 2121 Minas Gerais Uberlândia38408-100 Brazil

Recent advances in distribution networks, driven by the integration of renewable energy sources, have spurred the emergence of microgrids, elevating concerns regarded reliability and stability. In this context, precise monitoring of events, particularly those elusive to detection like high-impedance faults (HIFs), becomes imperative. The development of phasor measurement units (PMUs) with their harmonic synchronized measurements has enhanced the monitoring task and fostering the application of synchrophasors even on microgrids. This work introduces a novel method for event classification in microgrids, utilizing combined low-rate PMU data and harmonic synchrophasor time series. Central to our approach is the usage of a state-of-the-art transformer neural network, based on the attention mechanism, to effectively discern HIFs from other faulty and non-fault events. Notably, this methodology accounts for prevalent PMU data quality issues, including noise, missing data, and synchronism errors. Results from real-world HIF data demonstrate a robust performance, with an accuracy rate of approximately 98% in event classification. This harmonic synchrophasor-based strategy showcases promise as an original approach for handling commercial PMU data, offering sufficient robustness for deployment in real-world applications. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Phasor measurement units

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Metasurfaces for next-generation wireless communication systems

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National Science Review 2023年第8期10卷 17-19页

作者： Younes Ra'di Nikita Nefedkin Petar Popovski Andrea Alù Department of Electrical Engineering and Computer Science Syracuse University Photonics Initiative Advanced Science Research Center City University of New York Department of Electronic Systems Aalborg University Physics Program Graduate Center City University of New York

The pace of development in the world of 5G communication systems has proven to be much more demanding than previous generations, with 5G-Advanced seemingly around the corner [1]. Extensive research is already underway to structure the next generation of wireless systems(i.e. 6G), which may potentially enable an unprecedented level of human–machine interaction [2].

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