Papers by Reginaldo Santos
Anais da II Escola Regional de Alto Desempenho Norte 2 e II Escola Regional de Aprendizado de Máquina e Inteligência Artificial Norte 2 (ERAD-ERAMIA-NO2 2022)
This paper describes the development of a supervised classifier constructed upon knowledge extrac... more This paper describes the development of a supervised classifier constructed upon knowledge extracted from police report public databases, in the years between 2019 and 2021 in the state of Pará, Brazil. The classifier achieved an accuracy of approximately 78% for the prediction of 463 unique labels related to public safety. The resulting model can be used to improve the statistical processes of criminal analysts, both in quantitative and qualitative terms.
In the last decades, the structural health monitoring (SHM) has emerged as a promising approach t... more In the last decades, the structural health monitoring (SHM) has emerged as a promising approach to provide more reliable and quantitative knowledge about structural condition. Posed in the context of a statistical pattern recognition paradigm, the SHM has evolved and assigned, for instance, to the continuous development of machine learning algorithms that model the normal condition of a structure and, automatically, allow to infer early signs of damage. To overcome the unknown effects of operational and environmental variability, new cluster-based algorithms have been required due to their inherent capability to automatically discover the main structural components of a system, allowing a proper learning of the normal condition. Therefore, this paper proposes a novel unsupervised cluster-based technique, the agglomerative concentric hypersphere (ACH), to learn the structural response as a small number of structural states, even when operational an environmental influences produce no...
Anais do XXIX Workshop sobre Educação em Computação (WEI 2021), 2021
Este artigo apresenta o desenvolvimento de uma análise automática com os microdados do ENADE para... more Este artigo apresenta o desenvolvimento de uma análise automática com os microdados do ENADE para o curso de Ciência da Computação. O objetivo é fornecer informações que possam ser úteis para diretores e coordenadores que queiram melhorar a qualidade de seus cursos. Os dados informam quais são as disciplinas deficientes do curso, qual a mudança de desempenho em determinado assunto de um exame ao longo os anos e se os alunos têm baixa participação na prova. O fato da análise de dados ser automática torna possível a geração de resultados para qualquer curso de Ciência da Computação do país sem precisar de esforço adicional.
Journal of Communication and Information Systems, 2019
Frequency response functions have been employed as damage-sensitive features in the vibration-bas... more Frequency response functions have been employed as damage-sensitive features in the vibration-based structural damage detection. However, the need for measuring the excitation forces arises as a remarkable limitation on the application of those features in real-world applications. As an alternative, transmissibility measurements can be explored as features with output-only nature, which implies the need for measuring only the response signals. In this paper, an output-only damage detection method is proposed, combining transmissibilities with kernel principal component analysis (KPCA). This technique is based on the pattern recognition paradigm for structural health monitoring, where feature extraction and feature classification phases are considered. In the first phase, the dimensionality of the transmissibilities is appropriately reduced by applying the KPCA algorithm. In the second phase, an outlier detection strategy is used to determine the condition of the instrumented structure. The possibility of clustering in the high-dimensional space mapped by KPCA is also reported and discussed. The proposed method is experimentally validated with transmissibilities acquired, under distinct structural conditions, from a laboratory steel beam instrumented with several accelerometers. The results demonstrate that the output-only method has high potential to be applied in a wide range of monitoring solutions, where economic issues and life-safety are primary motivations.
Anais de XXXIII Simpósio Brasileiro de Telecomunicações, 2015
This paper proposes a method for the identification of TPs sharing the same binder, based on the ... more This paper proposes a method for the identification of TPs sharing the same binder, based on the analysis of phantom circuit measurements. Herein, phantoming is used to reveal if a 4-wire loop composed by two TPs are close enough in order to be considered in the same binder. K-means and Gaussian Mixture Model are evaluated on S11 parameter features obtained from the phantom-mode measurement of two TPs. Also, an automatic method to labelling the clusters and a method to estimate the length which two TPs share the same binder are briefly presented. Laboratory results confirm the accuracy of the methods.
Revista Brasileira de Computação Aplicada, 2016
Resumo: o Monitoramento de Integridade Estrutural (MIE) é uma importante técnica usada para prese... more Resumo: o Monitoramento de Integridade Estrutural (MIE) é uma importante técnica usada para preservar vários tipos de estruturas a curto e longo prazo, usando redes de sensores para coletar continuamente os dados desejados. No entanto, isso provoca um forte impacto no tamanho dos dados a serem armazenados e processados. Uma solução comum é utilizar algoritmos de compressão, em que o nível de compressão de dados deve ser adequado o suficiente para permitir a correta identificação de danos. Neste trabalho, utilizamos os dados provenientes de uma estrutura de laboratório com três andares para avaliar o desempenho de algoritmos de compressão comuns que, em seguida, são combinados com algoritmos de detecção de danos utilizados em MIE. Analisamos, também, como o uso da Análise Independente de Componentes, técnica comum para reduzir o ruído em dados brutos, pode ajudar o desempenho da detecção. Os resultados mostraram que PWLH combinado com NLPCA têm o melhor custo-benefício entre a compressão e detecção para limiares de compressão pequenos enquanto que APCA com PCA Adaptativo é melhor com valores de limiares mais elevados. Palavras-chave: Framework. Compressão de dados. Detecção de danos. Efeitos ambientais. Efeitos operacionais. Monitoramento de integridade estrutural.
A Novel Equidistant-Scattering-Based Cluster Index
2018 7th Brazilian Conference on Intelligent Systems (BRACIS), 2018
We propose a new non-parametric internal validity index based on mutual equidistant-scattering am... more We propose a new non-parametric internal validity index based on mutual equidistant-scattering among within-cluster data for fine-tuning the number of clusters, i.e., the hyperparameter K. Most of the validity indexes found in the literature are considered to be dependent on the number of data objects in clusters and often tend to ignore small and low-density groups. Moreover, they select suboptimal clustering solutions when the clusters are in a certain degree of overlapping or low separation. We analysed our index performance with four of the most popular validity indexes. Experiments on both synthetic and real-world data show the effectiveness and reliability of our approach to evaluate the hyperparameter K.
Improving a Genetic Clustering Approach with a CVI-Based Objective Function
Intelligent Systems, 2021
Genetic-based clustering meta-heuristics are important bioinspired algorithms. One such technique... more Genetic-based clustering meta-heuristics are important bioinspired algorithms. One such technique, termed Genetic Algorithm for Decision Boundary Analysis (GADBA), was proposed to support Structural Health Monitoring (SHM) processes in bridges. GADBA is an unsupervised, non-parametric approach that groups data into natural clusters by means of a specialized objective function. Albeit it allows a competent identification of damage indicators of SHM-related data, it achieves lackluster results on more general clustering scenarios. This study improves the objective function of GADBA based on a Cluster Validity Index (CVI) named Mutual Equidistant-scattering Criterion (MEC) to expand its applicability to any real-world problem.
GAVGA: A Genetic Algorithm for Viral Genome Assembly
Bioinformatics has grown considerably since the development of the first sequencing machine, bein... more Bioinformatics has grown considerably since the development of the first sequencing machine, being today intensively used with the next generation DNA sequencers. Viral genomes represent a great challenge to bioinformatics due to its high mutation rate, forming quasispecies in the same infected host. In this paper, we implement and evaluate the performance of a genetic algorithm, named GAVGA, through the quality of a viral genome assembly. The assembly process works by first clustering the reads that share a common substring called seed and for each cluster, checks if there are overlapping reads with a given similarity percentage using a genetic algorithm. The assembled data are then compared to Newbler, SPAdes and ABySS assemblers, and also to a viral assembler such as VICUNA, which confirms the feasibility of our approach. GAVGA was implemented in python 2.7+ and can be downloaded at https://sourceforge.net/projects/gavga-assembler/.
Damage‐sensitive feature extraction with stacked autoencoders for unsupervised damage detection
Structural Control and Health Monitoring, 2021
Empirical study on rotation and information exchange in particle swarm optimization
Swarm and Evolutionary Computation, 2019
Abstract This paper investigates whether rotational variance and information exchange affect the ... more Abstract This paper investigates whether rotational variance and information exchange affect the performance of Particle Swarm Optimization (PSO) algorithms. Four PSO versions which include the presence or absence of rotational variance, and the fast or late information exchange among particles are under evaluation. The goal is to highlight the best approach and principal benefits of each PSO version based on numerical simulations. To accomplish the aforesaid, the algorithms were evaluated on CEC 2017 benchmark optimization problems. Additionally, a method to estimate a reliable number of algorithms executions was also proposed. Statistical measurements based on Clerc's rules were used to strengthen the analyses. The results indicated the rotationally variant PSO as the overall winner, and the fast information exchange was statistically significant better than the late one, according to Friedman's and Wilcoxon's tests.
A semi-autonomous particle swarm optimizer based on gradient information and diversity control for global optimization
Applied Soft Computing, 2018
Abstract The deterministic optimization algorithms far outweigh the non-deterministic ones on uni... more Abstract The deterministic optimization algorithms far outweigh the non-deterministic ones on unimodal functions. However, classical algorithms, such as gradient descent and Newton's method, are strongly dependent on the quality of the initial guess and easily get trapped into local optima of multimodal functions. On the contrary, non-deterministic optimization methods, such as particle swarm optimization and genetic algorithms perform global optimization, however they waste computational time wandering the search space as a result of the random walks influence. This paper presents a semi-autonomous particle swarm optimizer, termed SAPSO, which uses a gradient-based information and diversity control to optimize multimodal functions. The proposed algorithm avoids the drawbacks of deterministic and non-deterministic approaches, by reducing computational efforts of local investigation (fast exploitation with gradient information) and escaping from local optima (exploration with diversity control). The experiments revealed promising results when SAPSO is applied on a suite of test functions based on De Jong's benchmark optimization problems and compared to other PSO-based algorithms.
Genetic-based EM algorithm to improve the robustness of Gaussian mixture models for damage detection in bridges
Structural Control and Health Monitoring, 2016
Summary During the service life of bridges, the bridge management systems (BMSs) seek to handle a... more Summary During the service life of bridges, the bridge management systems (BMSs) seek to handle all performed assessment activities by controlling regular inspections, evaluations, and maintenance of these structures. However, the BMSs still rely heavily on qualitative and visual bridge inspections, which compromise the structural evaluation and, consequently, the maintenance decisions as well as the avoidance of bridge collapses. The structural health monitoring appears as a natural field to aid the bridge management, providing more reliable and quantitative information. Herein, the machine learning algorithms have been used to unveil structural anomalies from monitoring data. In particular, the Gaussian mixture models (GMMs), supported by the expectation-maximization (EM) on the parameter estimation, have been proposed to model the main clusters that correspond to the normal and stable state conditions of a bridge, even when it is affected by unknown sources of operational and environmental variations. Unfortunately, the performance of the EM algorithm is strongly dependent on the choice of the initial parameters. This paper proposes a hybrid approach based on a standard genetic algorithm (GA) to improve the stability of the EM algorithm on the searching of the optimal number of clusters and their parameters, strengthening the damage classification performance. The superiority of the GA-EM-GMM approach, over the classic EM-GMM one, is tested on a damage detection strategy implemented through the Mahalanobis-squared distance, which permits one to track the outlier formation in relation to the chosen main group of states, using real-world data sets from the Z-24 Bridge, in Switzerland. Copyright © 2016 John Wiley & Sons, Ltd.
A global expectation-maximization based on memetic swarm optimization for structural damage detection
Structural Health Monitoring, 2016
During the service life of engineering structures, structural management systems attempt to manag... more During the service life of engineering structures, structural management systems attempt to manage all the information derived from regular inspections, evaluations and maintenance activities. However, the structural management systems still rely deeply on qualitative and visual inspections, which may impact the structural evaluation and, consequently, the maintenance decisions as well as the avoidance of collapses. Meanwhile, structural health monitoring arises as an effective discipline to aid the structural management, providing more reliable and quantitative information; herein, the machine learning algorithms have been implemented to expose structural anomalies from monitoring data. In particular, the Gaussian mixture models, supported by the expectation-maximization (EM) algorithm for parameter estimation, have been proposed to model the main clusters that correspond to the normal and stable state conditions of a structure when influenced by several sources of operational and ...
International Journal of Information and Education Technology, 2014
The digital image processing is widely studied in the scientific literature. Techniques for image... more The digital image processing is widely studied in the scientific literature. Techniques for image treatment derived from satellites are continuously developed and improved. Although most of these techniques are readily available to the researchers, it is known that a minimum knowledge in programming should be purchased by those who wish to use these techniques. In this context, this paper proposes an open source graphical application which refers to preprocessing of images coming from satellites. The main focus is to become simple the use of preprocessing techniques without requiring the user to have knowledge about programming. To achieve this goal, technologies such as Qt framework (used for the development of graphical interface) and TerraLib (used for the development of preprocessing techniques) were used together and Faç ade design pattern was chosen to perform the communication between the technologies. This design pattern consists of developing a single interface to access resources developed and available in TerraLib library. The communication between the technologies is explained in detail and this work concludes with expectations about the proposal graphical application.
International Journal of Information and Education Technology, 2014
A rotationally invariant semi-autonomous particle swarm optimizer with directional diversity
Swarm and Evolutionary Computation, 2020
Abstract The semi-autonomous particle swarm optimizer (SAPSO) [ 1 ] is a relatively recent algori... more Abstract The semi-autonomous particle swarm optimizer (SAPSO) [ 1 ] is a relatively recent algorithm for global continuous optimization based on gradient direction and diversity controlling approach, providing autonomy for the particles and the swarm for exploiting regions in the search space, and preserving exploration during the whole search process. In the first study, although SAPSO algorithm holds the property rotational invariance in which it normally brings a lack of directional diversity in PSO context, the algorithm has shown very good performance in comparison to other PSO-like algorithms. In this paper, an improved version of SAPSO, named rotationally invariant SAPSO (RI-SAPSO), is proposed, which still holds the same property, but now it incorporates a rotation matrix generated by an exponential map to maintain directional diversity. A mathematical proof to prove that the RI-SAPSO algorithm is rotationally invariant is given. RI-SAPSO was evaluated on test functions extracted from CEC 2017 benchmark problems with six other PSO-like algorithms, along with its previous version. The comparative study was strengthened with a non-parametric Friedman's hypothesis test for 1 × k comparisons and p-values were adjusted in the post-hoc procedure. Simulation results showed that the proposed RI-SAPSO, in most problems, was able to find much better solutions and statistical significances were also observed.
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Papers by Reginaldo Santos