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Publicações

Publicações por CTM

2024

Determination of the spectral dispersion for the heart muscle - A Kramers-Kronig approach

Autores
Oliveira, M; Pinheiro, R; Oliveira, P; Carvalho, I; Tuchin, V;

Publicação
2024 International Conference Laser Optics, ICLO 2024 - Proceedings

Abstract
The refractive index of the pigs heart was measured at wavelengths between 255 and 850 nm to calculate the dispersion. The total transmittance and total reflectance spectra of the pig heart were measured between 200 and 1000 nm to calculate the spectral absorption coefficient. Using Kramers-Kronig relations, the dispersion of the heart was matched to experimental refractive index values. © 2024 IEEE.

2024

Precise Identification of Different Cervical Intraepithelial Neoplasia (CIN) Stages, Using Biomedical Engineering Combined with Data Mining and Machine Learning

Autores
Kruczkowski, M; Drabik-Kruczkowska, A; Wesolowski, R; Kloska, A; Pinheiro, MR; Fernandes, L; Galan, SG;

Publicação
Interdisciplinary Cancer Research

Abstract

2024

On the feasibility of Vis–NIR spectroscopy and machine learning for real time SARS-CoV-2 detection

Autores
Coelho, BFO; Nunes, SLP; de França, CA; Costa, DdS; do Carmo, RF; Prates, RM; Filho, EFS; Ramos, RP;

Publicação
Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Abstract

2024

Feature Extraction from EEG signals for detection of Parkinsons Disease

Autores
Souza, C; Viana, G; Coelho, B; Massaranduba, AB; Ramos, R;

Publicação
Anais do XVI Congresso Brasileiro de Inteligência Computacional

Abstract
The Electroencephalogram (EEG) is a medical tool that captures, in a non-invasive way, electrical signals from the brain activities performed by neurons. EEG signals have been the target of study as a biomarker of Parkinsons disease (PD), where several methods of analysis are applied. The present work aims to evaluate features extracted from EEG signals, through methodologies such as HOS, Haralick descriptors, and Fractal Features, as new biomarkers for PD identification. Data from 50 individuals, available at the Open Neuro repository, who underwent an attentional cognitive task were analyzed. RF and SVM algorithms were employed for the classification of the extracted features. The best accuracy achieved was 79.49% in differentiating between Parkinsons subjects and control subjects using Haralick descriptors and RF classifier, suggesting that these features can identify activations in brain areas caused by dopaminergic medication.

2024

Realistic Model Parameter Optimization: Shadow Robot Dexterous Hand Use-Case

Autores
Correia, T; Ribeiro, FM; Pinto, VH;

Publicação
OPTIMIZATION, LEARNING ALGORITHMS AND APPLICATIONS, PT II, OL2A 2023

Abstract
The notable expansion of technologies related to automated processes has been observed in recent years, largely driven by the significant advantages they provide across diverse industries. Concurrently, there has been a rise in simulation technologies aimed at replicating these complex systems. Nevertheless, in order to fully leverage the potential of these technologies, it is crucial to ensure the highest possible resemblance of simulations to real-world scenarios. In brief, this work consists of the development of a data acquisition and processing pipeline allowing a posterior search for the optimal physical parameters in MuJoCo simulator to obtain a more accurate simulation of a dexterous robotic hand. In the end, a Random Search optimization algorithm was used to validate this same pipeline.

2023

Trajectory-Aware Rate Adaptation for Flying Networks

Autores
Queirós, R; Ruela, J; Fontes, H; Campos, R;

Publicação
Simulation Tools and Techniques - 15th EAI International Conference, SIMUtools 2023, Seville, Spain, December 14-15, 2023, Proceedings

Abstract

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