[HTML][HTML] Artificial intelligence of things applied to assistive technology: a systematic literature review

MP de Freitas, VA Piai, RH Farias, AMR Fernandes… - Sensors, 2022 - mdpi.com
According to the World Health Organization, about 15% of the world's population has some
form of disability. Assistive Technology, in this context, contributes directly to the overcoming …

[HTML][HTML] The sustainability concept: A review focusing on energy

RN Muniz, CT da Costa Júnior, WG Buratto, A Nied… - Sustainability, 2023 - mdpi.com
The concept of sustainability, with a focus on energy, has emerged as a central tenet in
addressing the mounting global challenges of environmental degradation and resource …

[HTML][HTML] Optimized hybrid ensemble learning approaches applied to very short-term load forecasting

MY Junior, RZ Freire, LO Seman, SF Stefenon… - International Journal of …, 2024 - Elsevier
The significance of accurate short-term load forecasting (STLF) for modern power systems'
efficient and secure operation is paramount. This task is intricate due to cyclicity, non …

Aggregating prophet and seasonal trend decomposition for time series forecasting of Italian electricity spot prices

SF Stefenon, LO Seman, VC Mariani, LS Coelho - Energies, 2023 - mdpi.com
The cost of electricity and gas has a direct influence on the everyday routines of people who
rely on these resources to keep their businesses running. However, the value of electricity is …

Machine fault detection using a hybrid CNN-LSTM attention-based model

A Borré, LO Seman, E Camponogara, SF Stefenon… - Sensors, 2023 - mdpi.com
The predictive maintenance of electrical machines is a critical issue for companies, as it can
greatly reduce maintenance costs, increase efficiency, and minimize downtime. In this …

Optimized EWT-Seq2Seq-LSTM with attention mechanism to insulators fault prediction

ACR Klaar, SF Stefenon, LO Seman, VC Mariani… - Sensors, 2023 - mdpi.com
Insulators installed outdoors are vulnerable to the accumulation of contaminants on their
surface, which raise their conductivity and increase leakage current until a flashover occurs …

[HTML][HTML] Hypertuned temporal fusion transformer for multi-horizon time series forecasting of dam level in hydroelectric power plants

SF Stefenon, LO Seman, LSA da Silva… - International Journal of …, 2024 - Elsevier
This paper addresses the challenge of predicting dam level rise in hydroelectric power
plants during floods and proposes a solution using an automatic hyperparameters tuning …

On forecasting cryptocurrency prices: A comparison of machine learning, deep learning, and ensembles

K Murray, A Rossi, D Carraro, A Visentin - Forecasting, 2023 - mdpi.com
Traders and investors are interested in accurately predicting cryptocurrency prices to
increase returns and minimize risk. However, due to their uncertainty, volatility, and …

[HTML][HTML] Ensemble learning methods using the Hodrick–Prescott filter for fault forecasting in insulators of the electrical power grids

LO Seman, SF Stefenon, VC Mariani… - International Journal of …, 2023 - Elsevier
Electrical power grid insulators installed outdoors are exposed to environmental conditions,
such as the accumulation of contaminants on their surface. The contaminants increase the …

Video-based human activity recognition using deep learning approaches

GAS Surek, LO Seman, SF Stefenon, VC Mariani… - Sensors, 2023 - mdpi.com
Due to its capacity to gather vast, high-level data about human activity from wearable or
stationary sensors, human activity recognition substantially impacts people's day-to-day …