Fernando Buarque de Lima Neto

University of Pernambuco | UPE · Programa em Engenharia de Computação

Diabetic retinopathy screenings are a vital strategy to avoid the severe consequences of this disease. However, their success depends on the adherence of the target population. The present work aims to review the adherence to diabetic retinopathy screening, more specifically the influence of the persons with diabetes’ social network (contacts betwe...

Diabetic retinopathy screenings are a vital strategy to avoid the severe consequences of this disease. However, their success depends on the adherence of the target population. The present work aims to analyse the influence of the diabetics’ social network (contacts between diabetics) on their screening behaviour. The used data set comprises inform...

A wide range of outcomes makes identifying clinical and functional features distinguishing older persons who fall from non-fallers challenging, especially for professionals with less clinical experience. Thus, this study aimed to map a high-dimensional and complex clinical and functional dataset and determine which outcomes better discriminate olde...

Research interest in autonomous control of unmanned aerial vehicles (UAVs) has increased rapidly over the past decade. They are now widely used in civilian, military, and private areas. Applications include surveillance, search and rescue, and delivery tasks. More broadly, they excel at solving problems where a significant amount of space must be c...

The success of screening programs depends to a large extent on the adherence of the target population, so it is therefore of fundamental importance to develop computer simulation models that make it possible to understand the factors that correlate with this adherence, as well as to identify population groups with low adherence to define public hea...

Nowadays, device monitoring is an activity present in various different environments. Ranging from monitoring workers in their workplaces, city traffic, surveillance in shops, to elderly at home, all that rely on effective anomaly detection in video scenes. In the context of residences, although there are many kinds of monitoring cameras and sensor...

This paper presents a proposed three-step methodology designed to enhance the performance and efficiency of industrial systems by integrating Digital Twins with particle swarm optimization (PSO) algorithms while prioritizing interpretability. Digital Twins are becoming increasingly prevalent due to their capability to offer a comprehensive virtual...

The success of screening programs depends to a large extent on the adherence of the target population, so it is therefore of fundamental importance to develop computer simulation models that make it possible to understand the factors that correlate with this adherence, as well as to identify population groups with low adherence to define public hea...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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 (...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...