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March 2017 - present
February 2010 - present
Publications
Publications (34)
Objetivo: Com aumento da viabilidade da aplicação das neurais convolucionais (CNNs) foi objetivado avaliar o uso de desta tecnologia para a detecção de tumores cerebrais em imagens de ressonância magnética computadorizada Método: Foram desenvolvidos dois modelos distintos de CNNs, uma com o uso de Transfer learning e outra sem, para classificar a o...
Objetivo: Validar se um modelo multi-task (MTL) para classificação e segmentação de tumores cerebrais é superior a um single-task (ST). Método: a arquitetura do modelo é constituída de um encoder, que se bifurca em uma fully connected (classificação) e um decoder (segmentação). Para o ST, apenas a ramificação de classificação foi considerada. Ambos...
A idade biológica, indicador crucial do desenvolvimento humano, reflete as mudanças físicas e mentais associadas ao envelhecimento. A estimativa da idade óssea, um método comum na prática clínica que busca informações sobre idade biológica, pode ser subjetiva e imprecisa. Objetivo: Este estudo propõe métodos baseados em técnicas de aprendizado prof...
A precisão na classificação automática de tumores cerebrais desempenha um papel determinante para a confiabilidade do método para aplicações na saúde. Erros de classificação podem resultar em diagnósticos imprecisos, levando a abordagens inadequadas e potencialmente prejudiciais. Objetivo: Propor uma abordagem visando minimizar erros de classificaç...
Objetivo: Neste estudo é proposto o desenvolvimento de um modelo de detecção de epífises em imagens de raio X, utilizando modelos de aprendizado de máquina. Metodologia: descrevemos o processo de aquisição do dataset e conduzimos testes com modelos como YOLOv5, YOLOv8 e faster R-CNN. Resultados: O modelo YOLOv8 obteve erro de 1% no dataset DHA, enq...
This paper provides a Systematic Literature Review exploring the integration between Game Learning Analytics (GLA) and Recommender Systems (RS), analyzing primary studies located in the main scientific literature databases and national magazines. The methodology used a 6-step framework, starting with the central theme definition until the research...
This study aims to conduct an integrative review of research on computational methods used for mammography quality control while addressing the issue of subjectivity in existing quality control processes. We conducted an integrative search in three electronic databases to achieve our objective. Our search included studies published within the last...
This study aims to conduct an integrative review of research on computational methods used for mammography quality control while addressing the issue of subjectivity in existing quality control processes. We conducted an integrative search in three electronic databases to achieve our objective. Our search included studies published within the last...
Attenuation coefficients are essential physical parameters for many applications, such as the calculation of photon penetration and energy deposition to evaluate biological shielding. Estimating these parameters is complex, making it necessary to apply more sophisticated methodologies. The objective of the present study was to propose a model for e...
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by deficits in communication and social interaction, and presence of repetitive behaviors, and restricted interests. Many structural and functional brain alterations can be observed in individuals with ASD. Therefore, functional magnetic resonance imaging (fMRI) has been...
Objective: AQMI - “Assessment of the quality of mammographic images” was developed to support the quality control (QC) of digital mammographic images. Materials and Methods: The software was implemented in the Python programming language via the Streamlit library, which involved content structuring and environmental planning. The experimental data...
Grabbing students' attention is becoming more challenging in the digital age, distance education, and increasing low literacy. This complex educational phenomenon needs to be mitigated to prevent negative social and economic consequences. This work presents the use of gamification in higher education to engage and motivate students in Calculus, a c...
Many industrial model predictive control applications, called non-square systems, have more variables to be controlled than manipulated variables available. At these cases, the control objectives are related to keep the controlled ones within a range, instead in reference value (setpoint). Assessing the model quality of these controllers is fundame...
The model-plant mismatch (MPM) can be responsible for poor control performance. This can be solved by locating which channels (i.e., pars of MVs-CVs) are suffering the highest MPM, and then, proceed with the model updating using the same historical data used for the assessment and diagnosis steps. This paper proposes a method for updating models ba...
Calculus is of utmost importance because of its huge applicability and form the basis of several science and engineering courses. Historically, this discipline has presented high undergraduate repetition and dropout rates. This paper aims to present an ongoing research of a digital educational game, to be used in the discipline of Calculus I, to he...
HIGHLIGHTS:
-- Capable of isolating the channels that are most related to the model discrepancies;
-- Suitable to linear MPC with variables controlled within ranges or setpoint tracking;
-- Results showed that the method can detect both gain and dynamics discrepancies;
-- Captures external variables’ influence in performance problems from distu...
Calculus is a part of many undergraduate programs yet students have a high failure rate in the subject, according to data collected in several studies. This paper aims to analyze students' opinions about the use of Gamification and Digital Game-Based Learning to teach calculus using an RPG Game and to test a prototype with a group of users. The dev...
Poor model quality is one of the most frequent causes of performance deterioration in Model Predictive Controllers. As such, frequent model evaluation and correction is fundamental. Some assessment methods are reported in the literature, but most cannot deal with Model Predictive Controllers (MPCs) without fixed setpoints for controlled variables....
Many processes show limit cycles, meaning that the system presents oscillatory behavior. The parameter estimation of such kind of systems is not a simple task, due to the non-convexity of the optimization problem. This paper proposes the inclusion of a driving term based on the damping factor in the classical objective function formulation, reducin...
This paper presents the results of the model assessment performed on an industrial predictive controller applied to a propylene/propane separation system at Braskem, in Brazil, using the methodology proposed by Botelho et al. (2015a, b, c). Besides identifying the controlled variables with modelling uncertainties that were degrading the controller...
Systems with strong interactions among the variables are frequent in the chemical industry, and the use of Model Predictive Control (MPC) is a standard tool in these scenarios. However, model assessment in this case is more complex when compared with fairly coupled systems, since the interactions make the system more sensitive to the model uncertai...
Poor model quality in model predictive controller (MPC) is often an important source of performance degradation. A key issue in MPC model assessment is to identify whether the bad performance comes from model-plant mismatches (MPM) or unmeasured disturbances (UD). This paper proposes a method for distinguishing between such degradation sources, whe...
The longevity of each MPC application is strongly related to its performance maintenance. This work provides an overview of the methodologies available to fulfill this task, including a discussion about some special requirements of performance assessment methodologies for typical industrial MPC applications. The available methodologies were compare...
Model Predictive Control (MPC) is a class of control systems which use a dynamic process model to predict the best future control actions based on past information. Thus, a representative process model is a key factor for its correct performance. Therefore, the investigation of model-plant-mismatch effect is very important issue for MPC performance...
The model quality for a model predictive control (MPC) is critical for the control loop performance. Thus, assessing the effect of model-plant mismatch (MPM) is fundamental for performance assessment and monitoring the MPC. This paper proposes a method for evaluating model quality based on the investigation of closed-loop data and the nominal outpu...
A baixa qualidade dos modelos é uma das causas mais frequentes da degradação de desempenho de controladores preditivos, por isso a avaliação desses em tempo real é fundamental. Este trabalho apresenta aplicação da metodologia proposta por Botelho et al. (2015 a e b) para avaliação de modelos de controladores preditivos na Unidade de Coqueamento Ret...
Identifiability analysis is an essential tool for parameter estimation of dynamic models. The objective of this technique is to verify which parameters of this model should be identified. This paper proposes a new methodology, based in control system theory applied to the local sensitivity analysis of the model. First, the sensitivity matrix is sca...
This paper presents the comparison of some method related with the most important steps in the parameter estimation procedure to fit kinetic parameters of an HDPE polymerization reactor using real data from an industrial plant. An identifiability analysis was performed prior to the parameters estimation. For this analysis, two methods for scaling t...
Resumo. O presente trabalho apresenta a estruturação e solução do problema de engenharia envolvido na produção de combustíveis sintéticos a partir do gás natural e dióxido de carbono (CO 2). Relata-se uma breve discussão a respeito da matéria-prima-o gás natural, principais produtos e possíveis processos que podem ser aplicados na produção de combu...
This paper presents the comparison of some method related with the most important steps in the parameter estimation procedure to fit kinetic parameters of an HDPE polymerization reactor using real data from an industrial plant. An identifiability analysis was performed prior to the parameters estimation. For this analysis, two methods for scaling t...
