DSpace Communidade:https://repositorio.uema.br/jspui/handle/123456789/19072026-07-14T20:24:24Z2026-07-14T20:24:24ZEstudo teórico das propriedades eletrônicas, termodinâmicas e ópticas na estrutura de zeólita (rub-11) com as dopagens de metais de transiçãohttps://repositorio.uema.br/jspui/handle/123456789/62832026-07-09T15:38:14Z2026-03-13T00:00:00ZTítulo: Estudo teórico das propriedades eletrônicas, termodinâmicas e ópticas na estrutura de zeólita (rub-11) com as dopagens de metais de transição
Abstact: The molecular selectivity of zeolites gives these materials the function of molecular sieves,
a central property in research focused on the space sector. The ability to őlter molecules
based on nanometric dimensions is what drives the development of new structural and chemical
applications in this őeld. Furthermore, zeolitic material possesses speciőc requirements for
environments in this segment, since the material has a certain resistance to extreme environments,
thermal stability, and eiciency in adsorption and air puriőcation processes in enclosed
environments, such as aircraft cabins or space stations, serving to control contaminants such
as ��3, �2�, and ��4, given its already consolidated use. Therefore, this work aims to
investigate possible enhancements of the properties of RUB-11 zeolite through metallic doping
by silicon atom substitution and branching at points previously calculated by population analysis,
using the DFT computational method with PBE-GGA functional. Initially, the structure
of RUB-11 zeolite exhibited characteristics of an insulating material; however, the results of
doping with transition metals show considerable alterations in the characteristics of the original
structure, making the zeolitic material more reactive. Furthermore, the viability is conőrmed
by the thermodynamic properties (Enthalpy, Heat Capacity at Constant Pressure, Entropy, and
Gibbs Free Energy) and the reactivity through the band gap energy, agreeing with the optical
results, with only an expected variation due to the methods used. Adsorption studies resulted in
adsorption for all gases proposed in this research; however, ammonia and sulfur dioxide obtained
the best results. Finally, the stability analysis of the materials demonstrated that the nature of the
transition elements with oxygen atoms are determining factors for the stability of the variations
in the doping process2026-03-13T00:00:00ZEstimativas de arrecadação do ICMS do Estado do Maranhão usando algoritmos de machine learninghttps://repositorio.uema.br/jspui/handle/123456789/62792026-07-08T14:14:01Z2025-01-01T00:00:00ZTítulo: Estimativas de arrecadação do ICMS do Estado do Maranhão usando algoritmos de machine learning
Abstact: Tax collection forecasting is a cornerstone of fiscal planning and efficient public
management. The Tax on Circulation of Goods and Services (ICMS) constitutes the
main source of revenue for Brazilian states, and its accurate projection is crucial
for allocating resources to strategic areas. However, the complexity of its dynamics,
influenced by non-linear macroeconomic variables, and the lack of studies applied
to the reality of the state of Maranhão pose a challenge for public administrators.
This work aims to address this gap by investigating how machine learning
techniques can improve the accuracy of forecasting monthly ICMS revenue in
Maranhão. The overall objective is to develop and validate advanced computational
models using a historical series of economic and social data from January 1997
to April 2024. This quantitative and applied research adopted the CRISP-DM
framework. Data were collected from public sources such as SEFAZ-MA, IBGE,
and the Central Bank. Initially, nineteen independent variables were considered,
and a Multiple Linear Regression model was used to select the most relevant ones,
such as GDP, diesel consumption, and electricity consumption indicators. Four
machine learning algorithms were implemented, compared, and validated:
Random Forest, Decision Tree, Linear Regression, and XGBoost. Performance
evaluation was performed using the RMSE, MAE, MAPE, SMAPE, and R² metrics,
using the k-fold cross-validation technique (with k=10) and a data split of 80% for
training and 20% for testing. This study contributes a practical and validated
model that can be integrated into the state's budget planning process, promoting
more transparent, efficient, and data-driven fiscal management2025-01-01T00:00:00ZMétodo computacional para auxiliar o diagnóstico precoce da Granulomatose de Wegenerhttps://repositorio.uema.br/jspui/handle/123456789/62732026-07-07T19:41:20Z2016-07-22T00:00:00ZTítulo: Método computacional para auxiliar o diagnóstico precoce da Granulomatose de Wegener
Abstact: This paper presents a proteomic pattern recognition system aimed at assisting in the early diagnosis of Wegener's Granulomatosis (WG), a rare idiopathic vasculitis that is difficult to detect and carries a high mortality rate for untreated individuals. The proposed method involves extracting features from proteomic signals and classifying them as belonging to individuals with or without WG. To achieve this, Independent Component Analysis is used for feature extraction, the Minimum Redundancy Maximum Relevance algorithm is employed to reduce the number of features and computational costs, and a Support Vector Machine is used for classification. The method's performance was evaluated using a dataset of 335 proteomic signals, comprising 75 active cases, 101 negative cases, and 159 cases in remission. The best result was obtained using a twenty-feature vector, yielding accuracy, specificity, and sensitivity of 98.24%, 99.73%, and 99.50%, respectively. These results demonstrate that the proposed system is efficient for diagnosing WG and outperforms the current methodology, which is based on clinical, serological, and radiological examinations proposed by the American College of Rheumatology.2016-07-22T00:00:00ZSistemas de gerenciamento e monitoramento de rack’s outdoors de telecomunicações, baseado em internet of thingshttps://repositorio.uema.br/jspui/handle/123456789/62472026-07-06T18:33:27Z2022-10-31T00:00:00ZTítulo: Sistemas de gerenciamento e monitoramento de rack’s outdoors de telecomunicações, baseado em internet of things
Abstact: The present work aims to correlate concepts, technologies and application of a solution
based on embedded systems, Internet Of Things and 5G, to monitor and ensure data
persistence in telecommunications companies. First, a survey of the current scenario of the
Telecommunications industry is carried out. In addition, they present intrinsic problems, in
which consumers are the most affected, such as the lack of reliability and interactivity of the
product offered by energy concessionaires. The bibliographic research was through a literary
review based on articles, books and works by several authors from the period 2019 to 2022.
The collection of information on the topic took place through the databases: Google Scholar
and IEEE. In this way, conceptual information was presented on technologies such as ESP32,
5G, sensing and especially the MQTT protocol, for long-distance solutions, which belong to
the concept of Internet of Things (IoT). Therefore, we propose the development of a device
capable of monitoring and assisting telecommunications companies in the management to
maintain their external assets.2022-10-31T00:00:00Z