TEDE Communidade:https://tedebc.ufma.br/jspui/handle/tede/2792026-08-13T20:50:47Z2026-08-13T20:50:47ZCompressão sem perdas de dados de telemetria satelital usando o algoritmo On+BARROS, José Flávio Gomeshttps://tedebc.ufma.br/jspui/handle/tede/71612026-08-13T13:14:39Z2026-07-11T00:00:00ZTítulo: Compressão sem perdas de dados de telemetria satelital usando o algoritmo On+
Autor: BARROS, José Flávio Gomes
Primeiro orientador: BARROS FILHO, Allan Kardec Duailibe
Abstract: Satellite data telemetry comprises the set of information required to monitor, control, and
ensure the safe and efficient operation of space missions. The reduction in the volume of
this data, transmitted from the satellite to ground stations, is called telemetry stream
compression. Lossless compression applied to this data is essential to guarantee the integrity
of the original data. This approach primarily exploits the statistical redundancy present
in the data to reduce the volume of information transmitted or stored. In this context,
lossless compression becomes even more relevant, given the severe bandwidth constraints
on communication links and the limited on-board storage capacity of satellites. This study
proposes On+, a new lossless compression algorithm for satellite telemetry data. Using real
telemetry data captured by the Aldebaran-1 CubeSat satellite and the TinyGS Ground
Station platform, a dataset consisting of 2500 binary files was created. The performance
of the proposed algorithm was evaluated in comparison with classical methods (Huffman
coding and Arithmetic coding) and various commercial compressors (.rar, .zip, .7z, .xz, and
.gz). The On+ algorithm achieved an average compression ratio of 29.19% on Aldebaran-1
satellite data, with a standard deviation of 1.26% and a median of 29.09%, outperforming
the evaluated methods in terms of compression ratio. For satellites on the TinyGS platform,
On+ also delivered significant results, achieving a median compression ratio close to 50% in
specific satellite classes, with Starlink standing out in particular. This result demonstrates
the method’s ability to efficiently exploit the statistical characteristics of certain telemetry
datasets, obtaining substantial compression gains.
Instituição: Universidade Federal do Maranhão
Tipo do documento: Tese2026-07-11T00:00:00ZMapeamento de sedimentos da margem equatorial brasileira usando algoritmos de aprendizado de máquinaDANTAS, Diego de Oliveirahttps://tedebc.ufma.br/jspui/handle/tede/71602026-08-13T13:03:29Z2026-07-10T00:00:00ZTítulo: Mapeamento de sedimentos da margem equatorial brasileira usando algoritmos de aprendizado de máquina
Autor: DANTAS, Diego de Oliveira
Primeiro orientador: BARROS FILHO, Allan Kardec Duailibe
Abstract: Large-scale mapping of seafloor sediments is essential for environmental management,
offshore engineering, and the sustainable exploitation of resources, especially in optically
complex coastal regions such as the Brazilian Equatorial Margin (BEM). Although tradi-
tional acoustic surveys provide high accuracy, their application is limited by operational
costs and low acquisition frequency. This thesis presents a reproducible machine learning
pipeline for regional sediment classification using Sentinel-2 imagery, systematically cover-
ing the shallow shelf between 0 and 30 m depth. The methodology integrates Principal
Component Analysis (PCA), Multilayer Perceptron (MLP), and Synthetic Minority Over-
sampling Technique (SMOTE), combined with a conservative curation protocol based on
historical granulometric consistency, local spatial agreement, and independence between
image patches. The final predictive scope was defined as the binary Sand vs Mud scenario,
using 2,199 spatially independent samples under 25 km block-based spatial validation with
five folds. Among the evaluated model families, including convolutional neural networks,
MLPs, SVMs, and EfficientNet models, the MLP+PCA+SMOTE pipeline was selected as
the recommended configuration because it combined competitive performance, stability,
and low computational cost. The optimized configuration achieved an accuracy of 92.64%
± 1.95, macro F1 of 89.04% ± 2.40, and computational cost 6.6 times lower than that of
CNN-Base. Although no statistically significant differences were observed in relation to
the evaluated convolutional architectures, the cartographic agreement of 84.9% with an
independent sedimentological map indicates regional cartographic consistency, without
constituting contemporary in situ validation. The results demonstrate that lightweight
spectral models represent a viable and scalable alternative for regional sediment mapping
in complex coastal environments, provided that they are accompanied by rigorous curation,
adequate spatial validation, and cautious interpretation of the temporal limitations of the
data.
Instituição: Universidade Federal do Maranhão
Tipo do documento: Tese2026-07-10T00:00:00ZMetodologia 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: Dissertação2026-03-16T00:00:00Z