TEDE Communidade:https://tedebc.ufma.br/jspui/handle/tede/2792026-05-17T13:39:01Z2026-05-17T13:39:01ZMetodologia para cálculo de um índice de segurança energética em sistemas elétricos com fontes renováveis e armazenamento de energiaFREITAS, Raiane Rodrigueshttps://tedebc.ufma.br/jspui/handle/tede/69492026-05-11T19:23:49Z2026-03-27T00:00:00ZTítulo: Metodologia para cálculo de um índice de segurança energética em sistemas elétricos com fontes renováveis e armazenamento de energia
Autor: FREITAS, Raiane Rodrigues
Primeiro orientador: LIMA, Shigeaki Leite de
Abstract: The increasing complexity of electrical systems, coupled with the growing integration of
intermittent renewable sources, poses new challenges to energy security assessment. This
work proposes an Energy Security Index that integrates probabilistic and structural
indicators widely consolidated in the literature, including Loss of Load Probability
and Expected Energy Not Supplied, among others. This index should allow for the
simultaneous evaluation of reliability and matrix concentration aspects. In addition,
the index aims to capture the effect of technological diversification on the security of
electrical systems.The methodology used is based on Stationary Monte Carlo Simulation
for estimating probabilistic reliability metrics, and the Shannon entropy method was used
for the objective definition of the weights of the variables that make up the index. The
model is applied to the IEEE 14-bus system, used as a reference system, under different
scenarios of electrical matrix composition. The analyses consider variations in photovoltaic
generation penetration, inclusion of wind generation, presence of BESS, and different
loading levels, allowing for the evaluation of the system’s sensitivity to different operational
and structural conditions.The results demonstrate that the combination of dispatchable,
renewable, and storage sources presented the highest index values; therefore, maximizing
energy security depends not only on increasing the share of renewables but also on the
balance between technological diversity, capacity adequacy, and operational flexibility.
Instituição: Universidade Federal do Maranhão
Tipo do documento: Dissertação2026-03-27T00:00:00ZModelagem e análise dinâmica de um parque eólico dotado de geradores DFIG em uma rede de subtransmissão usando PSCAD/EMTDCFALCÃO, Caio Bruno Silvahttps://tedebc.ufma.br/jspui/handle/tede/69482026-05-11T19:10:18Z2026-03-16T00:00:00ZTítulo: Modelagem e análise dinâmica de um parque eólico dotado de geradores DFIG em uma rede de subtransmissão usando PSCAD/EMTDC
Autor: FALCÃO, Caio Bruno Silva
Primeiro orientador: OLIVEIRA, Denisson Queiroz
Abstract: The growing concern about climate change and the need to reduce global greenhouse
gas emissions have driven a profound transformation in the global energy sector.
In this context, wind energy has become one of the main renewable alternatives,
combining technological maturity, economic competitiveness, and low environmen
tal impact. Although wind power contributes to the diversification of generation
sources, it also introduces new technical challenges related to system stability and
power quality, requiring the improvement of grid integration standards and models.
In this scenario, the present study is motivated by the increasing participation of
wind energy in both the global and national energy mix, which demands a deeper
understanding of the dynamic behavior of generation systems and their interac
tion with subtransmission networks. This work aims to analyze the performance
of wind farms composed of Doubly Fed Induction Generators (DFIG) connected
to the electrical grid, through modeling and simulations in the PSCAD/EMTDC
environment, contributing to the understanding of transient phenomena associated
with wind power operation and providing technical insights to enhance the stabi
lity, control, and reliability of the integration of these renewable sources into power
systems.
Instituição: Universidade Federal do Maranhão
Tipo do documento: Dissertação2026-03-16T00:00:00ZDesenvolvimento de método em cascata para realização do cálculo do ângulo de Cobb em imagens de raio-x da coluna vertebralNASCIMENTO, Estephane Mendeshttps://tedebc.ufma.br/jspui/handle/tede/69092026-04-14T13:48:45Z2026-03-27T00:00:00ZTítulo: Desenvolvimento de método em cascata para realização do cálculo do ângulo de Cobb em imagens de raio-x da coluna vertebral
Autor: NASCIMENTO, Estephane Mendes
Primeiro orientador: SILVA, Aristófanes Corrêa
Abstract: Scoliosis is a spinal deformity that affects approximately 2 to 4% of the global population,
and its early diagnosis is essential to prevent disease progression and avoid severe cases,
which may only be reversible through corrective surgery. The diagnosis is usually performed
using x-ray images, in which the specialist measures the Cobb angle, a parameter used to
determine the severity of the deformity. In order to assist specialists in this process, this
work presents a method for the automatic estimation of the Cobb angle based on vertebral
segmentation. Initially, the region of interest (ROI) is extracted through spine segmentation,
followed by vertebrae segmentation from the image delimited by the ROI and, finally, the
Cobb angle is estimated for each obtained vertebral mask. The proposed method achieved
Dice coefficients of 92.14% and 83.23% for spine and vertebrae segmentation, respectively,
and a mean absolute error (MAE) of 8.72° in Cobb angle calculation.
Instituição: Universidade Federal do Maranhão
Tipo do documento: Dissertação2026-03-27T00:00:00ZClassificação de Exames PET de Corpo Inteiro usando Representações MIP e Aprendizado ProfundoSOARES FILHO, Celso Luiz Silvahttps://tedebc.ufma.br/jspui/handle/tede/69002026-04-10T19:18:10Z2026-03-13T00:00:00ZTítulo: Classificação de Exames PET de Corpo Inteiro usando Representações MIP e Aprendizado Profundo
Autor: SOARES FILHO, Celso Luiz Silva
Primeiro orientador: PAIVA, Anselmo Cardoso de
Abstract: Cancer is one of the greatest global public health challenges, with an estimated 35 million
new cases by 2035. In this context, Positron Emission Tomography (PET) is essential
for diagnosis and monitoring. However, the clinical interpretation of these exams is an
exhaustive task, subject to the specialist’s subjectivity and limited by the high complexity
of 3D volumetric data. This work proposes a method for the automatic classification of
whole-body PET scans of patients with lung cancer, lymphoma, melanoma, and healthy
individuals, using deep learning techniques applied to Maximum Intensity Projection
(MIP) representations. The method is structured in four stages: generation of MIP images
in the coronal and sagittal axes, preprocessing, feature extraction, and classification. Six
architectures for feature extraction (ConvNeXt, EfficientNet-B0, Swin, and VGG19) and
three classifiers (MLP, SVM, and XGBoost) were evaluated. The method achieved results
of 96.45% for the AUC metric, 91.98% for the accuracy, 91.63% for the F1-Score, 91.18%
for the sensitivity, and a precision of 92.08%. These results show that the use of MIP
representations, combined with a set of perspective-specific specialized architectures, allows
for satisfactory performance, approaching approaches that use 3D volumes and hybrid
examinations (PET/CT).
Instituição: Universidade Federal do Maranhão
Tipo do documento: Dissertação2026-03-13T00:00:00Z