A5004611294- Air Quality and Health Impacts
- Atmospheric chemistry and aerosols
- Energy Load and Power Forecasting
- Air Quality Monitoring and Forecasting
- Solar Radiation and Photovoltaics
- Wind and Air Flow Studies
- Machine Fault Diagnosis Techniques
- Fault Detection and Control Systems
- Vehicle emissions and performance
- Atmospheric aerosols and clouds
- Engineering Diagnostics and Reliability
- Quantum Computing Algorithms and Architecture
- Artificial Intelligence in Law
- Complex Systems and Time Series Analysis
- Hybrid Renewable Energy Systems
- COVID-19 diagnosis using AI
- Water Quality Monitoring and Analysis
- Meteorological Phenomena and Simulations
- Ethics and Social Impacts of AI
- Quantum Information and Cryptography
- Hydrological Forecasting Using AI
- Wind Energy Research and Development
- Seismic Imaging and Inversion Techniques
- Geography and Environmental Studies
- Gas Dynamics and Kinetic Theory
Serviço Nacional de Aprendizagem Industrial
2018-2025
University of Surrey
2022-2025
Universidade Federal de Pernambuco
2024
Mathematics Research Center
2019-2023
NSF National Center for Atmospheric Research
2021
Universidade Federal do Espírito Santo
2014-2020
Instituto Brasileiro de Informação em Ciência e Tecnologia
2016
This work presents a novel transformer-based deep neural network architecture integrated with wavelet transform for forecasting wind speed and energy (power) generation the next 6 h ahead, using multiple meteorological variables as input multivariate time series forecasting. To evaluate performance of proposed model, different case studies were investigated, data collected from anemometers installed in three regions Bahia, Brazil. The model was compared an LSTM (Long Short Term Memory)...
The evolution of low-cost sensors (LCSs) has made the spatio-temporal mapping indoor air quality (IAQ) possible in real-time but availability a diverse set LCSs make their selection challenging. Converting individual into sensing network requires knowledge research disciplines, which we aim to bring together by making IAQ an advanced feature smart homes. this review is discuss home automation technologies for monitoring and control through networked pollution LCSs. key steps that can allow...
Short-term wind speed forecasting for Colonia Eulacio, Soriano Department, Uruguay, is performed by applying an artificial neural network (ANN) technique to the hourly time series representative of site. To train ANN and validate technique, data one year are collected tower, with anemometers installed at heights 101.8, 81.8, 25.7, 10.0 m. Different configurations applied each site height; then, a quantitative analysis conducted, statistical results evaluated select configuration that best...
Greenhouse gas (GHG) emissions, especially CO2, represent a global concern. Among those responsible for CO2 buildings stand out due to the consumption of energy from fossil fuels. In this sense, initiatives decarbonization and construction tends contribute achievement target defined in Paris Agreement limiting increase temperature 1.5 degrees Celsius above pre-industrial levels, as well achieving Sustainable Development Goals (SDG) Triple Bottom Line (TBL). This article aimed identify...
The majority of current approaches for bias and fairness identification or mitigation in machine learning models are applications a particular issue that fails to account the connection between application context its associated sensitive attributes, which contributes recognition consistent patterns metrics. This can be used drive development future models, with attribute acting as connecting element these Hence, this study aims analyze several metrics identifying fairness, applying...
Recent advancements in Artificial Intelligence have yielded promising results addressing complex challenges within Natural Language Processing (NLP), serving as a vital tool for expediting judicial proceedings the legal domain. This study focuses on detection of similarity among documents an inference group, employing eight NLP techniques grounded transformer architecture, specifically applied to case Brazilian system. The transformer-based models utilised — BERT, GPT-2, RoBERTa, and LlaMA...
Industry 4.0 has introduced new maintenance management paradigms, demanding innovative training and implementation solutions. This article proposes a system architecture integrating sensors, IoT devices, data analysis, condition-based techniques to serve as demonstration learning platform. The proposed methodology involved four steps, culminating in the system's prototyping. enables visualization of how Maintenance technologies impact performance, cost, compliance indicators. study concludes...