Fernando Buarque de Lima Neto

Fernando Buarque de Lima Neto
Universidade de Pernambuco | UPE · Programa em Engenharia de Computação

BSc/MSc (Computing) DIC/PhD/Hab (Artificial Intelligence) Sabbatical (1-Information Systems/2-Theoretic Learning) Humboldt Fellow / IEEE SM / Academy of Science PE-Brazil

About

222
Publications
33,678
Reads
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1,633
Citations
Citations since 2017
86 Research Items
1121 Citations
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Introduction
As Associate Professor at University of Pernambuco (UPE), his current research interests are natural inspired metaheuristics, computational semiotics and intelligent decision systems. Prof. Buarque is head of Computational Intelligence at the Doctoral Program on Computer Engineering. He is Senior Member of IEEE, Visiting Professor at University of Johannesburg, University of Exeter, University of Texas A&M, and University of Münster.
Additional affiliations
February 2003 - present
Universidade de Pernambuco
Position
  • Professor (Associate)
October 1998 - December 2002
Imperial College London
Position
  • PhD
Description
  • Cumulative with DIC (Diploma of Imperial College)
March 1996 - May 1998
Universidade Federal de Pernambuco (UFPE)
Position
  • Masters
Education
October 1998 - December 2002
Imperial College London
Field of study
  • Intelligent and Interactive Systems
March 1996 - May 1998
Federal University of Pernambuco
Field of study
  • Computer Science

Publications

Publications (222)
Article
Full-text available
This article presents the domain engineering process carried out to obtain the requirements for the implementation of an Artificial Intelligence (AI) compliance framework aimed at the public sector. Owing to the current competitive and fast economy, which generates huge demand for increasingly efficient, reliable, and transparent intelligent system...
Article
Full-text available
Problem: Currently, many public organizations have adopted applications for process automation to avoid repetitive work and produce more efficient results; however, the development of intelligent mechanisms to support complex decision-making is not often observed. In public services, in particular, difficulties may be related to the abundance of da...
Chapter
In this work we investigate the effectiveness of the application of a niching metaheuristic of the Fish School Search family in solving constrained optimization problems. Sub-swarms are used to allow the achievement of many feasible regions to be exploited in terms of fitness function. The niching approach employed was wFSS, a version of the Fish S...
Preprint
Full-text available
Autonomous control for unmanned aerial vehicles (UAVs) has rapidly raised research interest in the last decade. Widely used in civilian, military, and private areas, UAVs have been implemented in surveillance, search and rescue, and delivery tasks, solving problems where a significant space must be covered and traveled. However, using UAVs for navi...
Article
Full-text available
Parameter control methods for metaheuristics with reinforcement learning put forward so far usually present the following shortcomings: (1) Their training processes are usually highly time-consuming and they are not able to benefit from parallel or distributed platforms; (2) they are usually sensitive to their hyperparameters, which means that the...
Article
Full-text available
Problem: The development of intelligent routines to support complex decision-making is not always straight-forward. In the public service the difficulties may be related to the abundance of available data sources and the number of legal standards to be met, in addition to the need for the incorporation of transparency, auditability, standardization...
Article
Full-text available
The integration of Artificial Intelligence techniques into Decision Support Systems yields effective solutions to decision problems, especially when complex scenarios are at hand. However, the use of intelligent black-box models can hinder the decision support system’s potential to be fully adopted because opaque processes raise suspicions and doub...
Article
Full-text available
Swarm Intelligence (SI) algorithms are frequently applied to tackle complex optimization problems. SI is especially used when good solutions are requested for NP hard problems within a reasonable response time. And when such problems possess a very high dimensionality, a dynamic nature, or present intrinsic complex intertwined independent variables...
Conference Paper
This study proposes a new strategy to improve the performance of the algorithms of the Fish School Search (FSS) family via the individualization of the step-size of each fish. We propose to be calculated in two different manners: using individual weight or using individual fitness, depending on the chosen variation of the proposed technique. Our me...
Conference Paper
Full-text available
This work consists of applying supervised Machine Learning techniques to identify which types of active debts are appropriate for the collection method called protest, one of the means of collection used by the Attorney General of the State of Pernambuco. For research, the following techniques were applied, Neural Network (NN), Logistic Regression...
Article
We present an innovative step towards a parameterless out-of-the-box population size control for evolutionary and swarm-based algorithms for single objective bound constrained real-parameter numerical optimization. To the best of our knowledge, our approach is the first parameterless out-of-the-box parameter control for such a kind of technique. It...
Article
Full-text available
Activities of daily living require efficient management between motor and cognitive tasks, known as dual tasks. The ability to properly perform such activities progressively decreases with aging. Hence, there is much effort in developing methods to identify relevant features and attenuate this functional loss. This study aimed at testing the abilit...
Article
Full-text available
Parallel implementations of swarm intelligence algorithms such as the ant colony optimization (ACO) have been widely used to shorten the execution time when solving complex optimization problems. When aiming for a GPU environment, developing efficient parallel versions of such algorithms using CUDA can be a difficult and error-prone task even for e...
Article
Full-text available
Background The implementation of a population-based screening programme for diabetic retinopathy involves several challenges, often leading to postponements and setbacks at high human and material costs. Thus, it is of the utmost importance to promote the sharing of experiences, successes, and difficulties. However, factors such as the existence of...
Conference Paper
This paper proposes a semantic Natural Language Processing (NLP) approach used to assist in the automated characterization of information relevant to compliance activities. In this context, the Latent Semantic Analysis (LSA) technique was used to assist in the dimensionality reduction process. The evaluated results were achieved through the submiss...
Conference Paper
A calibração de braços robóticos é uma atividade crucial para utilização efetiva desses equipamentos na indústria. No entanto, as técnicas tradicionais envolvem equipamentos de alto custo, muitas horas de engenharia e profissionais altamente qualificados. Sendo assim, o presente trabalho propõe um dispositivo e uma metodologia para autocalibração d...
Article
We present PALLAS, a practical method for gene regulatory network (GRN) inference from time series data, which employs penalized maximum likelihood and particle swarms for optimization. PALLAS is based on the Partially-Observable Boolean Dynamical System (POBDS) model and thus does not require ad-hoc binarization of the data. The penalty in the lik...
Preprint
Full-text available
Background: The implementation of a population-based screening programme for diabetic retinopathy involves several challenges, often leading to postponements and setbacks at high human and material costs. Thus, it is of the utmost importance to promote the sharing of experiences, successes and difficulties. However, factors such as the existence of...
Preprint
Full-text available
Background: The implementation of a population-based screening programme for diabetic retinopathy involves several challenges, often leading to postponements and setbacks at high human and material costs. Thus, it is of the utmost importance to promote the sharing of experiences, successes and difficulties. However, factors such as the existence of...
Preprint
Full-text available
Background: The implementation of a population-based screening programme for diabetic retinopathy involves several challenges, often leading to postponements and setbacks at high human and material costs. Thus, it is of the utmost importance to promote the sharing of experiences, successes and difficulties. However, factors such as the existence of...
Article
This paper presents a systematic literature review on general parameter control for evolutionary and swarm-based algorithms. General methods can be applied to any algorithm, parameter or problem, in contrast to methods that are tailored to specific applications. In this literature review, a total of 4449 studies were retrieved by the search engines...
Conference Paper
Full-text available
Abstract. Process mining has emerged as a new scientific research topic on the interface between process modeling and event data gathering. In the search for process models that best fit to reality, the process discovery approach of creating referential processes from observed behavior. However, despite these methods showing relevant results, when...
Chapter
Full-text available
Graphics Processing Units (GPUs) have been widely used to speed up the execution of various meta-heuristics for solving hard optimization problems. In the case of Ant Colony Optimization (ACO), many implementations with very distinct parallelization strategies and speedups have been already proposed and evaluated on the Traveling Salesman Problem (...
Article
Full-text available
Age-associated changes in walking parameters are relevant to recognize functional capacity and physical performance. However, the sensible nuances of slightly different gait patterns are hardly noticeable by inexperienced observers. Due to the complexity of this evaluation, we aimed at verifying the efficiency of applied hybrid-adaptive algorithms...
Preprint
Full-text available
The inference of gene regulatory networks (GRN) from gene expression time series data is key to understanding the development and functioning of organisms in health and disease. Boolean models for GRN can effectively describe temporal patterns of gene activation and inactivation. However, all existing practical inference methods for Boolean GRNs as...
Conference Paper
Dengue has become one of the most important worldwide arthropodborne diseases around the world. Here, one hundred and two Brazilian dengue virus (DENV) III patients and controls were genotyped for 322 innate immunity gene loci. All biological data (including age, sex and genome background) were analyzed using Machine Learning techniques to discrimi...
Book
Full-text available
Artificial Intelligence and Learning is a teaser in a series of books and pioneering book for kids on Artificial Intelligence (A.I.) which focuses on its chief concept: LEARNING. The My First A.I. Books Series introduces kids of all ages to the foundational concepts for Artificial Intelligence and the 4th Industrial/Human Revolution, AKA I4.0 or 4I...
Article
Dengue has become one of the most important worldwide arthropod-borne diseases. Dengue phenotypes are based on laboratorial and clinical exams, which are known to be inaccurate. Objective: We present a machine learning approach for the prediction of dengue fever severity based solely on human genome data. Methods: One hundred and two Brazilian...
Article
Full-text available
Gait analysis is relevant for the functional diagnostic of several musculoskeletal disorders. Walking patterns can be analyzed using techniques such as video processing and inertial measurement units (IMU). In this work, a Self-Organizing Maps (SOM) algorithm is applied to reduce the complexity of kinematic features obtained by IMU sensors of a sam...
Article
Over the recent years, computational trust and reputation models have become an invaluable method to improve computer-computer and human-computer interaction. As a result, a considerable amount of research has been published trying to solve open problems and improving existing models. This survey will bring additional structure into the already con...
Preprint
Formulating database queries in terms of SQL is often a challenge for journalists, business administrators, and the growing number of non-database experts that are required to access and explore data. To alleviate this problem, we proposed a Query By Example (QBE) approach powered by intelligent algorithms that discovers database queries from a few...
Poster
Dengue has become one of the most important worldwide arthropod-borne diseases around the world. Here, one hundred and two Brazilian dengue virus (DENV) III patients and controls were genotyped for 322 innate immunity gene loci. All biological data (including age, sex and genome background) were analyzed using Machine Learning techniques to discrim...
Article
The accumulation of secretions in the airways of ventilator-dependent patients is a common problem, and if not detected and treated in due time, it greatly increases the risk of infections and asynchrony. Unfortunately, cardiogenic oscillation modifies the flow signal shape that can confuse clinical staff and modern lung ventilators. In this articl...
Article
Swarm intelligence (SI) algorithms are handy tools for solving complex optimization problems. When problems grow in size and complexity, an increase in population or number of iterations might be required in order to achieve a good solution. These adjustments also impact the execution time. This article investigates the trade-off involving populati...
Article
The need for appropriate decisions to tackle complex problems increases every day. Selecting destinations for vacation, comparing and optimizing resources to create valuable products, or purchasing a suitable car are just a few examples of puzzling situations in which there is no standard form to find an appropriate solution. Such scenarios become...
Conference Paper
Full-text available
This paper proposes a mechanism of dynamic adjustment of the population size of population based metaheuristics in order to balance its efficacy and efficiency. In this approach, an external trajectory based metaheuristic (MH) is used to dynamically adjust the population size of an inner population based metaheuristic. A Particle Swarm Optmization...
Chapter
The intermittency of wind remains the greatest challenge to its large scale adoption and sustainability of wind farms. Accurate wind power predictions therefore play a critical role for grid efficiency where wind energy is integrated. In this paper, we investigate two hybrid approaches based on the genetic algorithm (GA) and particle swarm optimisa...
Article
Full-text available
There is a direct relationship between the prevalence of musculoskeletal disorders of the temporomandibular joint (TMJ) and orofacial disorders. A well-elaborated analysis of the jaw movements provides relevant information for healthcare professionals to conclude their diagnosis. Different approaches have been explored to track jaw movements such t...
Conference Paper
Trust is considered an essential factor to develop and maintain business and supply chain relationships. However, it is hard to investigate its mechanisms due to the lack of supply chain trust-related datasets. This lack forces researchers to use artificially and often self-generated datasets which limit the validity of results and comparability wi...
Conference Paper
Full-text available
Electricity consumption has increased all around the world in the last decades. This has caused a rise in the use of fossil fuels and in the harming of the environment. In the past years the use of renewable energies and reduction of consumption has growth in order to deal with that problem. The change in the production paradigm led to an increasin...
Article
Human decision-making involves cognitive processes of selection, evaluation, and interpretation among candidate solutions in order to solve decision problems. Nonintelligent decision support systems (DSS) lack automatic interpretations, at least in a low level scale, which can lead to undesired solutions. To tackle this limitation, hence producing...
Conference Paper
The Big Data era is affording a paradigm change on decision-making approaches. More and more, companies as well as individuals are relying on data rather than on the so called "gut feeling" to make decisions. However, searching the Web for carrying out purchases is not completely satisfactory yet, given the arduousness of finding suitable quality d...
Article
Optimization problems with more than one objective consist in a very attractive topic for researchers due to its applicability in real-world situations. Over the years, the research effort in Computational Intelligence area resulted in algorithms able to achieve good results by solving problems with more than one conflicting objective. However, the...
Conference Paper
Full-text available
Online social networks (e.g., Twitter) offer an open platform for people to interact and connect without restrictions of language usage or geographic borders. Because of their pervasiveness, online social networks provide data and become real-time sensors of society. This work looks at Twitter to reveal the hidden relationship of languages that ste...
Article
Full-text available
Balancing assembly lines, a family of optimization problems commonly known as Assembly Line Balancing Problem, is notoriously NP-Hard. They comprise a set of problems of enormous practical interest to manufacturing industry due to the relevant frequency of this type of production paradigm. For this reason, many researchers on Computational Intellig...
Article
Full-text available
Many assembly lines related optimization problems have been tackled by researchers in the last decades due to its relevance for the decision makers within manufacturing industry. Many of theses problems, more specifically Assembly Lines Balancing and Sequencing problems, are known to be NP-Hard. Therefore, Computational Intelligence solution approa...
Article
Full-text available
In this work we investigate the effectiveness of the application of niching able swarm metaheuristic approaches in order to solve constrained optimization problems. Sub-swarms are used in order to allow the achievement of many feasible regions to be exploited in terms of fitness function. The niching approach employed was wFSS, a version of the Fis...
Article
The conventional methods to assess human gait are either expensive or complex to be applied regularly in clinical practice. To reduce the cost and simplify the evaluation, inertial sensors and adaptive algorithms have been utilized, respectively. This paper aims to summarize studies that applied adaptive also called artificial intelligence (AI) alg...