Marcella Scoczynski Ribeiro Martins
YOU?
Author Swipe
View article: HiSAXy: A fast methodology for solar wind structure identification in millions of time series
HiSAXy: A fast methodology for solar wind structure identification in millions of time series Open
We present a hybridized unsupervised clustering algorithm Hisaxy as a novel way to identify frequently occurring magnetic structures embedded in the interplanetary magnetic field (IMF) carried by the solar wind. The Hisaxy algorithm utiliz…
View article: 3D nnU-Net for automated segmentation and quantification of pulmonary nodules in chest CT
3D nnU-Net for automated segmentation and quantification of pulmonary nodules in chest CT Open
View article: Implementation of parcels of land micro-reservoirs as a strategy to reduce water volume in galleries and peak flows in the micro-drainage system of a new subdivision
Implementation of parcels of land micro-reservoirs as a strategy to reduce water volume in galleries and peak flows in the micro-drainage system of a new subdivision Open
Urbanization has caused significant environmental impacts on natural cycles, particularly the hydrological cycle. Soil impermeabilization increases surface runoff, contributing to the higher frequency and intensity of urban flooding. This …
View article: Unsupervised model for structure segmentation applied to brain computed tomography
Unsupervised model for structure segmentation applied to brain computed tomography Open
This article presents an unsupervised method for segmenting brain computed tomography scans. The proposed methodology involves image feature extraction and application of similarity and continuity constraints to generate segmentation maps …
View article: Enhancement of the Performance of Switched Reluctance Generators in Low Wind Speed Conditions Using Advanced Tracking Techniques
Enhancement of the Performance of Switched Reluctance Generators in Low Wind Speed Conditions Using Advanced Tracking Techniques Open
This paper presents a tracking method to improve the performance of switched reluctance generators in areas with low wind speeds. The main contribution of this work is the proposal of an advanced control system that employs dynamic trackin…
View article: Design of a Takagi–Sugeno Fuzzy Exact Modeling of a Buck–Boost Converter
Design of a Takagi–Sugeno Fuzzy Exact Modeling of a Buck–Boost Converter Open
DC–DC converters are used in many power electronics applications, such as switching power supply design, photovoltaic, power management systems, and electric and hybrid vehicles. Traditionally, DC–DC converters are linearly modeled using a…
View article: NASA Science Mission Directorate Knowledge Graph Discovery
NASA Science Mission Directorate Knowledge Graph Discovery Open
The size of the National Aeronautics and Space Administration (NASA) Science Mission Directorate (SMD) is growing exponentially, allowing researchers to make discoveries. However, making discoveries is challenging and time-consuming due to…
View article: Neural Networks And Ensemble Based Architectures To Automatic Musical Harmonization: A Performance Comparison
Neural Networks And Ensemble Based Architectures To Automatic Musical Harmonization: A Performance Comparison Open
Harmony can be defined in a musical way as art that combines several musical notes reproduced simultaneously to create sounds that are coherent to human ears and serve as accompaniment and filling. However, working out harmony is not a sim…
View article: ieee-cis/IEEE-CIS-Open-Access-Book-Volume-1: FirstEdition
ieee-cis/IEEE-CIS-Open-Access-Book-Volume-1: FirstEdition Open
First Edition of the IEEE CIS Open Book on Introduction to Computational Intelligence - Volume 1.
View article: A regression analysis of the impact of routing and packing dependencies on the expected runtime
A regression analysis of the impact of routing and packing dependencies on the expected runtime Open
Problems with multiple interdependent components offer a better representation of the real-world situations where globally optimal solutions are preferred over optimal solutions for the individual components. One such model is the Travelli…
View article: Linear Models Applied to Monthly Seasonal Streamflow Series Prediction
Linear Models Applied to Monthly Seasonal Streamflow Series Prediction Open
Linear models are widely used to perform time series forecasting. The Autoregressive models stand out, due to their simplicity in the parameters adjustment based on close-form solution. The Autoregressive and Moving Average models (ARMA) a…
View article: Bio-Inspired Optimization Algorithms Applied to the GAPID Control of a Buck Converter
Bio-Inspired Optimization Algorithms Applied to the GAPID Control of a Buck Converter Open
Although the proportional integral derivative (PID) is a well-known control technique applied to many applications, it has performance limitations compared to nonlinear controllers. GAPID (Gaussian Adaptive PID) is a non-linear adaptive co…
View article: Deep-SWIM: A few-shot learning approach to classify Solar WInd Magnetic field structures
Deep-SWIM: A few-shot learning approach to classify Solar WInd Magnetic field structures Open
The solar wind consists of charged particles ejected from the Sun into interplanetary space and towards Earth. Understanding the magnetic field of the solar wind is crucial for predicting future space weather and planetary atmospheric loss…
View article: On the Fitness Landscapes of Interdependency Models in the Travelling Thief Problem
On the Fitness Landscapes of Interdependency Models in the Travelling Thief Problem Open
Since its inception in 2013, the Travelling Thief Problem (TTP) has been widely studied as an example of problems with multiple interconnected sub-problems. The dependency in this model arises when tying the travelling time of the "thief" …
View article: A methodology for coffee price forecasting based on extreme learning machines
A methodology for coffee price forecasting based on extreme learning machines Open
View article: MATE: A Model-based Algorithm Tuning Engine - A proof of concept towards transparent feature-dependent parameter tuning using symbolic regression
MATE: A Model-based Algorithm Tuning Engine - A proof of concept towards transparent feature-dependent parameter tuning using symbolic regression Open
In this paper, we introduce a Model-based Algorithm Tuning Engine, namely MATE, where the parameters of an algorithm are represented as expressions of the features of a target optimisation problem. In contrast to most static (feature-indep…
View article: MATE: A Model-Based Algorithm Tuning Engine
MATE: A Model-Based Algorithm Tuning Engine Open
View article: Person Re-Identification Using Convolutional Neural Network and Autoencoder Embedded on Frameworks Based on Siamese and Triplet Networks
Person Re-Identification Using Convolutional Neural Network and Autoencoder Embedded on Frameworks Based on Siamese and Triplet Networks Open
The person re-identification problem addresses the task of identify if a person being watched by security cameras in surveillance environments has ever been in the scene. This problem is considered challenging, since the images obtained by…
View article: Multi-layer local optima networks for the analysis of advanced local search-based algorithms
Multi-layer local optima networks for the analysis of advanced local search-based algorithms Open
A Local Optima Network (LON) is a graph model that compresses the fitness landscape of a particular combinatorial optimization problem based on a specific neighborhood operator and a local search algorithm. Determining which and how landsc…
View article: Fitness Landscape Analysis of Dimensionally-Aware Genetic Programming Featuring Feynman Equations
Fitness Landscape Analysis of Dimensionally-Aware Genetic Programming Featuring Feynman Equations Open
View article: Fitness Landscape Analysis of Dimensionally-Aware Genetic Programming\n Featuring Feynman Equations
Fitness Landscape Analysis of Dimensionally-Aware Genetic Programming\n Featuring Feynman Equations Open
Genetic programming is an often-used technique for symbolic regression:\nfinding symbolic expressions that match data from an unknown function. To make\nthe symbolic regression more efficient, one can also use dimensionally-aware\ngenetic …
View article: Fitness Landscape Analysis of Dimensionally-Aware Genetic Programming Featuring Feynman Equations
Fitness Landscape Analysis of Dimensionally-Aware Genetic Programming Featuring Feynman Equations Open
View article: A characterisation of S-box fitness landscapes in cryptography
A characterisation of S-box fitness landscapes in cryptography Open
Substitution Boxes (S-boxes) are nonlinear objects often used in the design of cryptographic algorithms. The design of high quality S-boxes is an interesting problem that attracts a lot of attention. Many attempts have been made in recent …
View article: On resampling vs. adjusting probabilistic graphical models in estimation of distribution algorithms
On resampling vs. adjusting probabilistic graphical models in estimation of distribution algorithms Open
The Bayesian Optimisation Algorithm (BOA) is an Estimation of Distribution Algorithm (EDA) that uses a Bayesian network as probabilistic graphical model (PGM). Determining the optimal Bayesian network structure given a solution sample is a…
View article: COMPARAÇÃO DO DESEMPENHO ENTRE MODELOS LINEARES E REDES NEURAIS PARA PREVISÃO DO PREÇO DO CAFÉ
COMPARAÇÃO DO DESEMPENHO ENTRE MODELOS LINEARES E REDES NEURAIS PARA PREVISÃO DO PREÇO DO CAFÉ Open
Coffee is a delicacy that for centuries delight the human palate, Brazil being the main producer and exporter of this delicacy in the world.The commercialization of grains affects the country's economy, generating jobs and increasing natio…
View article: METAHEURÍSTICAS BIO-INSPIRADAS DE CLUSTERIZAÇÃO PARA ESCOLHA DE COMPONENTES NA INDÚSTRIA AUTOMOBILÍSTICA
METAHEURÍSTICAS BIO-INSPIRADAS DE CLUSTERIZAÇÃO PARA ESCOLHA DE COMPONENTES NA INDÚSTRIA AUTOMOBILÍSTICA Open
O objetivo desse trabalho foi comparar o desempenho de algoritmos de clusterização na análise de custos relativos a componentes similares em montadoras da indústria automobilística, através de métodos bio-inspirados
View article: On the Performance of Multi-Objective Estimation of Distribution Algorithms for Combinatorial Problems
On the Performance of Multi-Objective Estimation of Distribution Algorithms for Combinatorial Problems Open
Fitness landscape analysis investigates features with a high influence on the performance of optimization algorithms, aiming to take advantage of the addressed problem characteristics. In this work, a fitness landscape analysis using probl…
View article: On the performance of multi-objective estimation of distribution\n algorithms for combinatorial problems
On the performance of multi-objective estimation of distribution\n algorithms for combinatorial problems Open
Fitness landscape analysis investigates features with a high influence on the\nperformance of optimization algorithms, aiming to take advantage of the\naddressed problem characteristics. In this work, a fitness landscape analysis\nusing pr…