# Graçaliz Pereira DimuroUniversidade Federal do Rio Grande (FURG) | FURG · Center for Computer Science - C ³

Graçaliz Pereira Dimuro

PhD in Computer Science

## About

334

Publications

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Introduction

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March 2010 - present

## Publications

Publications (334)

In this work, we explore the impact of adaptive fuzzy measures on edge detection, aiming to enhance how computers interpret images by identifying edges more accurately. Traditional methods rely on analysing changes in image brightness to locate edges, but they often use fixed rules that do not account for the unique characteristics of each image. O...

A infraestrutura de redes de computadores é essencial para o acesso rápido e confiável aos recursos digitais, sendo indispensável para negócios e atividades diárias. Com o aumento evidente do fluxo contínuo de dados, as redes são frequentemente alvo de ataques. Este trabalho compara modelos de médias móveis para previsões de tráfego de rede e utili...

The discrete Choquet Integral (CI) and its generalizations have been successfully applied in many different fields, with particularly good results when considered in Fuzzy Rule-Based Classification Systems (FRBCSs). One of those functions is the CC-integral, where the product operations in the expanded form of the CI are generalized by copulas. Rec...

Com a crescente demanda por energia elétrica no Brasil, faz-se necessário estudos que auxiliem no melhor uso deste recurso, evitando perdas e desperdícios. Dentre as metodologias utilizadas, a aprendizagem de máquina vem crescendo, destacando a utilização de controladores por lógica fuzzy. Assim, este trabalho visa realizar uma sondagem bibliográfi...

Os Transformers emergiram como uma poderosa arquitetura em Inteligência Artificial, revolucionando várias tarefas de processamento de linguagem natural e processamento de imagem. Este artigo apresenta uma análise abrangente sobre a evolução dos Transformers historicamente, destacando seu mecanismo de autoatenção e finalizando com o novo modelo de T...

No mercado de ações, investidores interessados em investimentos de longo prazo buscam formas de selecionar ações com potencial de valorização futura para melhorar seus rendimentos. Os métodos de aprendizado de máquina têm um longo histórico de aplicações no mercado financeiro. Este artigo apresenta e avalia uma estratégia simples e eficaz para aloc...

Edge detection is a crucial process in numerous stages of computer vision. This field of study has recently gained momentum due to its importance in various applications. The uncertainty, among other characteristics of images, makes it difficult to accurately determine the edge of objects. Furthermore, even the definition of an edge is vague as an...

Social network analysis is a popular tool to understand the relationships between interacting agents by studying the structural properties of their connections. However, this kind of analysis can miss some of the domain-specific knowledge available in the original information domain and its propagation through the associated network. In this work,...

The interval-valued fuzzy sets and Atanassov intuitionistic fuzzy sets can be extended to a more general framework to simultaneously deal with uncertainty in both membership and non-membership values. This fact leads to the concept of interval-valued Atanassov intuitionistic fuzzy sets (IVAIFS), as given by Atanassov and Gargov (Fuzzy Sets Syst, 31...

There are distinct techniques to generate fuzzy implication functions. Despite most of them using the combination of associative aggregators and fuzzy negations, other connectives such as (general) overlap/grouping functions may be a better strategy. Since these possibly non-associative operators have been successfully used in many applications, su...

Researchers have developed ways to represent uncertainty, but usually, for each new structure, we have to perform a lot of complex analysis from scratch. It is desirable to come up with a general methodology that would automatically produce a natural description of validated uncertainty for all physically interesting situations (or at least for as...

Restricted dissimilarity functions (RDFs) were introduced to overcome problems resulting from the adoption of the standard difference. Based on those RDFs, Bustince
et al.
introduced a generalization of the Choquet integral (CI), called d-Choquet integral, where the authors replaced standard differences with RDFs, providing interesting theoretica...

The main purpose of this book is to describe a class of problem for which interval computations are not sufficient, and to design a physically reasonable extension of interval computations that would enable us to solve these problems. To describe these problems, let us first recall why we need interval computations in the first place.

The main objective of this section is to come up with a general description of validated uncertainty corresponding to a single measuring device. We want to make our description as natural as possible. Because of this, we do not want to simply provide a very general description of a measuring device, with a lot of possible features that may be of us...

In the above text, we have shown how, based on the information about measuring devices that measure a given quantity with higher and higher accuracy, we can design a natural representation of the measured quantity.

So, we have a set of possible outcomes. On this level, how do we describe uncertainty? Due to measurement uncertainty, when we apply the same measuring device to the same object twice, we may get different measurement results.

In the previous subsection, we have shown that subsets of compatible outcomes often provide more information about a measuring device than pairs of compatible outcomes—and thus provide a more complete description of a measuring device. However, as we will see, this description is still not always fully complete.

Descriptions of a measuring device corresponding to all 5 steps can be summarized in the following table

Measuring devices are either analog or digital. For an analog measuring device, the measurement result is a mark on a scale; examples include old-fashioned thermometers, Voltmeters, manometers, scales that measure weight, etc. For a digital measuring device, the outcome is a sequence of bits (i.e., 0s and 1s); often, for our convenience, this seque...

When we defined a physical quantity, we mentioned that in some cases, we only have a simple sequence of measuring devices, the next one more informative than the previous one \(I\sqsubseteq I'\).

Instead of repeating a measurement twice, we can repeat the same measurement three and more times. As a result, we may get three or more different outcomes for the same object. To describe this situation, we can use the same word “compatible”, and say that the outcomes \(v_1,\ldots ,v_m\) are compatible if for some object, as a result of repeated m...

In the previous subsection, we have shown that the addition of conditional statements sometimes provides more information about a measuring device than the (unconditional) information on which sets of physically possible outcomes are compatible and which are not—and thus provide a more complete description of a measuring device. However, as we will...

How can we describe a general physical quantity? The value of the quantity is obtained from measurements, so it is natural to describe a quantity in terms of measurements.

Fuzzy Rule-Based Classification System (FRBCS) is a well known technique to deal with classification problems. Recent studies have considered the usage of the Choquet integral and its generalizations to enhance the quality of such systems. Precisely, it was applied to the Fuzzy Reasoning Method (FRM) to aggregate the fired fuzzy rules when classify...

An important problem faced when dealing with imperfect information in fusion processes the uncertainty regarding values of the membership degrees to be employed in fuzzy modeling. In this scenario, one can apply interval-valued (iv) fuzzy sets, in which the membership degrees are represented by intervals. A recurrent issue is the situation in which...

Intervals are a popular way to represent the uncertainty related to data, in which we express the vagueness of each observation as the width of the interval. However, when using intervals for this purpose, we need to use the appropriate set of mathematical tools to work with. This can be problematic due to the scarcity and complexity of interval-va...

Fusion functions and their most important subclass, aggregation functions, have been successfully applied in fuzzy modeling. However, there are practical problems, such as classification via Convolutional Neural Networks (CNNs), where the data to be aggregated are not modeling membership degrees in the unit interval. In this scenario, systems could...

Traditionally, Convolutional Neural Networks make use of the maximum or arithmetic mean in order to reduce the features extracted by convolutional layers in a downsampling process known as pooling. However, there is no strong argument to settle upon one of the two functions and, in practice, this selection turns to be problem dependent. Further, bo...

The Choquet integral (CI) is an averaging aggregation function that has been used, e.g., in the fuzzy reasoning method (FRM) of fuzzy rule-based classification systems (FRBCSs) and in multicriteria decision making in order to take into account the interactions among data/criteria. Several generalizations of the CI have been proposed in the literatu...

Recently, several theoretical and applied studies on grouping functions and overlap functions appeared in the literature, mainly because of their flexibility when comparing them with the popular aggregation operators t-conorms and t-norms, respectively. Additionally, they constitute richer classes of disjunction/conjunction operations than t-norms...

Optimized decisions is required by businesses (analysts) if they want to stay open. Even thought some of these are from the know-how of the managers/executives, most of them can be described mathematically and solved (semi)-optimally by computers. The Group Modular Choquet Random Technique for Order of Preference by Similarity to Ideal Solution (GM...

Automatic image detection is one of the most important areas in computing due to its potential application in numerous real-world scenarios. One important tool to deal with that is called
overlap indices
. They were introduced as a procedure to provide the maximum lack of knowledge when comparing two fuzzy objects. They have been successfully app...

The core point of the research process are data. They are records from scientific investigation, which support the results published in journals and conferences. Making research data available in open access digital repositories has many advantages, such as increasing the visibility of associated publications, reproducing experiments, and validatin...

An effective way to cope with classification problems, among others, is by using Fuzzy Rule-Based Classification Systems (FRBCSs). These systems are composed by two main components, the Knowledge Base (KB) and the Fuzzy Reasoning Method (FRM). The FRM is responsible for performing the classification of new examples based on the information stored i...

In this paper we propose a new generalization for the notion of homogeneous functions. We show some properties and how it appears in some scenarios. Finally we show how this generalization can be used in order to provide a new paradigm for decision making theory called consistent influenced/disturbed decision making. In order to illustrate the appl...

It is known that the human visual system performs a hierarchical information process in which early vision cues (or primitives) are fused in the visual cortex to compose complex shapes and descriptors. While different aspects of the process have been extensively studied, such as lens adaptation or feature detection, some other aspects, such as feat...

Human sciences have traditionally relied on human reasoning and intelligence to infer knowledge from a wide range of sources, such as oral and written narrations, reports, and traditions. Here we develop an extension of classical social network analysis approaches to incorporate the concept of meaning in each actor, as a mean to quantify and infer...

Overlap functions are a class of aggregation functions that measure the overlapping degree between two values. They have been successfully applied as a fuzzy conjunction operation in several problems in which associativity is not required, such as image processing and classification. Interval-valued overlap functions were defined as an extension to...

Overlap functions are a class of aggregation functions that measure the overlapping degree between two values. Interval-valued overlap functions were defined as an extension to express the overlapping of interval-valued data, and they have been usually applied when there is uncertainty regarding the assignment of membership degrees. The choice of a...

It is known that the human visual system performs a hierarchical information process in which early vision cues (or primitives) are fused in the visual cortex to compose complex shapes and descriptors. While different aspects of the process have been extensively studied, as the lens adaptation or the feature detection, some other,as the feature fus...

Fuzzy implication functions have been widely investigated, both in theoretical and practical fields. The aim of this work is to continue previous works related to fuzzy implications constructed by means of non necessarily associative aggregation functions. In order to obtain a more general and flexible context, we extend the class of implications d...

This work presents a novel point interpolation algorithm that is derived from a simple weighted linear regression model. The resulting expression is similar to Inverse Distance Weighting (IDW), which is a widely adopted interpolation algorithm. The novel approach is compared to other methods on synthetic data and also over study cases related to so...

Overlap functions are a type of aggregation functions that are not required to be associative, generally used to indicate the overlapping degree between two values. They have been successfully used as a conjunction operator in several practical problems, such as fuzzy-rule-based classification systems (FRBCSs) and image processing. Some extensions...

Fuzzy modeling is frequently used to deal with the problems involving approximate reasoning, such as classification problems. However, fuzzy membership functions defined in terms of real functions sometimes can not reflect the uncertainty of the domain specialists. Also, when considering the use of fuzzy quantities, we are executing operations thro...

The impreciseness of numeric input data can be expressed by intervals. On the other hand, the normalization of numeric data is a usual process in many applications. How do we match the normalization with impreciseness on numeric data? A straightforward answer is that it is enough to apply a correct interval arithmetic, since the normalized exact va...

Brazil has the third-largest prison population globally, and it has been growing steadily for more than two decades. Constant growth and low jail investment generated significant problems, such as overcrowding and widespread diseases. This study proposes the construction of a Random Forest classifier to predict the occurrence of deaths in prisons....

An efficient way to deal with classification problems is by using Fuzzy Rule-Based Classification Systems. A key point in this kind of classifier is the Fuzzy Reasoning Method (FRM). This mechanism is responsible for performing the classification of examples into predefined classes. There are different generalizations of the Choquet integral in the...

An effective way to deal with classification problems, among other approaches, is using Fuzzy Rule-Based Classification Systems (FRBCSs). These classification systems are mainly composed of two modules, the Knowledge Base (KB) and the Fuzzy Reasoning Method (FRM). The KB is responsible for storing information related to the problem, while the FRM p...

In this chapter we make a review of the notion of overlap function. Although originally developed in order to determine up to what extent a given element belongs to two sets, overlap functions have widely developed in the last years for very different problems. We recall here the motivation that led to the introduction of this new notion and we dis...

Inverse Distance Weighting (IDW) is a widely adopted interpolation algorithm. This work presents a novel formulation for IDW which is derived from a weighted linear regression. The novel method is evaluated over study cases related to elevation data, climate and also on synthetic data. Relevant aspects of IDW are preserved while the novel algorithm...

In this paper, in order to generalize the Choquet integral, we replace the difference between inputs in its definition by a restricted dissimilarity function and refer to the obtained function as d-Choquet integral. For some particular restricted dissimilarity function the corresponding d-Choquet integral with respect to a fuzzy measure is just the...

Some aggregation functions that are not necessarily associative, namely overlap and grouping functions, have called the attention of many researchers in the recent past. This is probably due to the fact that they are a richer class of operators whenever one compares with other classes of aggregation functions, such as t-norms and t-conorms, respect...

This paper introduces a generalization of migrative functions by extending the conditions of the product operation applied in the variables. More specifically, instead of requiring to multiply the variable x by a real number x3B1; in this work we operate this x3B1; number with the variables according to a t-norm. We call such generalization as a t-...

The paper introduces a new class of functions from [0,1]n to [0,n] called d-Choquet integrals. These functions are a generalization of the “standard” Choquet integral obtained by replacing the difference in the definition of the usual Choquet integral by a dissimilarity function. In particular, the class of all d-Choquet integrals encompasses the c...

Overlap functions are aggregation functions that express the overlapping degree between two values. They have been used both as a conjunction in several practical problems (e.g., image processing and decision making), and to generate overlap indices between two fuzzy sets, which can be used to construct fuzzy confidence values to be applied in fuzz...

Academic genealogy investigates the relationships between student researchers and advisors and has been used as a resource to analyze the spread of scientific knowledge. This work presents the development of a system that creates academic genealogy trees of researchers from the Brazilian library of theses and dissertations. The proposed system allo...

In 2013, Barrenechea et al. used the Choquet integral as an aggregation function in the fuzzy reasoning method (FRM) of fuzzy rule-based classification systems. After that, starting from 2016, new aggregation-like functions generalizing the Choquet integral have appeared in the literature, in particular in the works by Lucca et al. Those generaliza...

The data volume expansion has generated the need to develop efficient knowledge extraction techniques. Most problems that are processed by these techniques have complex information to be identified and use different machine learning methods, such as Convolutional and Deep Learning Network. These networks may use a variety of aggregation functions t...

In this work we introduce a definition of interval-valued similarity measures taking into account the width of the input intervals. We discuss a construction method based on the aggregation of interval-valued restricted equivalence functions.

O crescente aumento do volume de dados, juntamente com a alta complexidade destes, tem gerado a necessidade de se desenvolver técnicas de extração de conhecimento cada vez mais eficientes, tanto em custo computacional quanto em precisão. A maioria dos problemas que são tratados por esses técnicas tem informações complexas a serem identificadas. Par...

Brain-computer interface technologies, such as steady-state visually evoked potential, P300, and motor imagery are methods of communication between the human brain and the external devices. Motor imagery-based brain-computer interfaces are popular because they avoid unnecessary external stimuli. Although feature extraction methods have been illustr...

In this work we consider some classes of functions with relaxed monotonicity conditions generalizing some other given classes of fusion functions. In particular, directionally increasing aggregation functions (called also pre-aggregation functions), directionally increasing conjunctors, or directionally increasing implications, etc., generalize the...

This paper introduces the theoretical framework for a generalization of CF1F2-integrals, a family of Choquet-like integrals used successfully in the aggregation process of the fuzzy reasoning mechanisms of fuzzy rule based classification systems. The proposed generalization, called by gCF1F2-integrals, is based on the so-called pseudo pre-aggregati...