Placido Pinheiro - Academia.edu (original) (raw)

Papers by Placido Pinheiro

Research paper thumbnail of Multicriteria Methods as Decision Making Aids in the Hydrographic Basin of the Curu River - State of Cear�

2006 International Conference on Service Systems and Service Management, 2006

Decisions on the liberation of dam flows for a basin during a given period, involve great difficu... more Decisions on the liberation of dam flows for a basin during a given period, involve great difficulties with hydrological, social, political and economical aspects. The multicriteria methods frequently support decision making techniques, that help to solve problems that can have several conflicting objectives, multiple possible actions, uncertainties, diverse stages, and many affected individuals. This study combines operational research and multicriteria

Research paper thumbnail of Aligning the Goals Hybrid Model for the Diagnosis of Mental Health Quality

Sustainability

The social distancing imposed by the COVID-19 pandemic has been described as the “greatest psycho... more The social distancing imposed by the COVID-19 pandemic has been described as the “greatest psychological experiment in the world”. It has tested the human capacity to extract meaning from suffering and challenged individuals and society in Brazil and abroad to promote cohesion that cushions the impact of borderline experiences on mental life. In this context, a survey was conducted with teachers, administrative technicians, and outsourced employees at the Federal Institute of Piauí (IFPI). This educational institution offers professional and technological education in Piauí, Brazil. This study proposes a system for the early diagnosis of health quality during social distancing in the years 2020 and 2021, over the COVID-19 pandemic, combining multi-criteria decision support methodology, the Analytic Hierarchy Process (AHP) with machine learning algorithms (Random Forest, logistic regression, and Naïve Bayes). The hybrid approach of the machine learning algorithm with the AHP multi-cr...

Research paper thumbnail of Prioritising Maintenance Work Orders in a Thermal Power Plant: A Multicriteria Model Application

Sustainability

Maintenance is one of the most rapidly expanding activities in the industrial environment, since ... more Maintenance is one of the most rapidly expanding activities in the industrial environment, since its application is no longer limited to simple, regular fixes. In the case of thermal power plants maintenance is essential, since they only operate when the National Electric System Operator wants them to complement the production from renewable sources such as hydro, wind, and solar. To limit the frequency of failures that result in generation unavailability, the operation team performs daily inspections to evaluate the equipment’s condition and the risks to the generating process. If an anomaly is found, the maintenance team will create service notes to address it. This research aims to demonstrate how the method Measuring Attractiveness by a Category-Based Evaluation Technique (Macbeth) can be applied to the development of a multiple-criterion model to support decision making in ordering the criticality of systems in thermal plant operational inspection routes to propose new methodol...

Research paper thumbnail of Assessment of Compressed and Decompressed ECG Databases for Telecardiology Applying a Convolution Neural Network

Electronics

Incalculable numbers of patients in hospitals as a result of COVID-19 made the screening of heart... more Incalculable numbers of patients in hospitals as a result of COVID-19 made the screening of heart patients arduous. Patients who need regular heart monitoring were affected the most. Telecardiology is used for regular remote heart monitoring of such patients. However, the resultant huge electrocardiogram (ECG) data obtained through regular monitoring affects available storage space and transmission bandwidth. These signals can take less space if stored or sent in a compressed form. To recover them at the receiver end, they are decompressed. We have combined telecardiology with automatic ECG arrhythmia classification using CNN and proposed an algorithm named TELecardiology using a Deep Convolution Neural Network (TELDCNN). Discrete cosine transform (DCT), 16-bit quantization, and run length encoding (RLE) were used for compression, and a convolution neural network (CNN) was applied for classification. The database was formed by combining real-time signals (taken from a designed ECG d...

Research paper thumbnail of A Neuroevolutionary Model to Estimate the Tensile Strength of Manufactured Parts Made by 3D Printing

Algorithms

Three-dimensional printing has advantages, such as an excellent flexibility in producing parts fr... more Three-dimensional printing has advantages, such as an excellent flexibility in producing parts from the digital model, enabling the fabrication of different geometries that are both simple or complex, using low-cost materials and generating little residue. Many technologies have gained space, highlighting the artificial intelligence (AI), which has several applications in different areas of knowledge and can be defined as any technology that allows a system to demonstrate human intelligence. In this context, machine learning uses artificial intelligence to develop computational techniques, aiming to build knowledge automatically. This system is responsible for making decisions based on experiences accumulated through successful solutions. Thus, this work aims to develop a neuroevolutionary model using artificial intelligence techniques, specifically neural networks and genetic algorithms, to predict the tensile strength in materials manufactured by fused filament fabrication (FFF)-t...

Research paper thumbnail of Using the Multi-Criteria Model for Optimization of Operational Routes of Thermal Power Plants

Energies, 2021

The constant problems evidenced in the Brazilian hydrological scenario, where the source of hydra... more The constant problems evidenced in the Brazilian hydrological scenario, where the source of hydraulic potential corresponds to about 63.9% of the energy matrix, coupled with the exponential growth in the supply of renewable energy, corroborates the importance of thermal power generation as the basis of Brazilian’s energy matrix. With the operation of thermal power plants, which characteristically involve a large number of systems, subsystems, and auxiliary equipment, there is a high demand for the use of methodologies for monitoring and controlling processes, analyzing failures, and implementing improvements and actions that increase the reliability and, consequently, reduce the failure rate. In this context, decision-making about prioritizing criticality for operational monitoring of an asset’s components, from the perspective of operation and maintenance planning and based on reliability-centered maintenance (RCM) concepts, can be considered a complex task. Given this, the researc...

Research paper thumbnail of Analyzing the Multicriteria of the Interaction Design of an Educational Map Application for Digital TV from User Preferences

Research paper thumbnail of Handing a Hybrid Multicriteria Model for Choosing Specialists to Analyze Application Management Service Tickets

Research & Innovation Forum 2019, 2019

Research paper thumbnail of Multicriteria Model for Evaluation of Outsourcing Services by Logistics Operators

Intelligent Algorithms in Software Engineering, 2020

Research paper thumbnail of Strategic Decision Method Structured in SWOT Analysis and Postures Based in the MAGIQ Multicriteria Analysis

Applied Computational Intelligence and Mathematical Methods, 2017

Research paper thumbnail of Applying Bayesian Networks in the Early Diagnosis of Bulimia and Anorexia Nervosa in Adolescents: Applying Bayesian Networks in Early Diagnosis in Adolescents

The diseases and health problems are concerns of managers of the Unified Health System has costs ... more The diseases and health problems are concerns of managers of the Unified Health System has costs in more sophisticated care sector are high. The World Health Organization focused on prevention of chronic diseases to prevent millions of premature deaths in the coming years, bringing substantial gains in economic growth by improving the quality of life. Few countries appear to be aimed at prevention, if not note the available knowledge and control of chronic diseases and may represent an unnecessary risk to future generations. Early diagnosis of these diseases is the first step to successful treatment in any age group. The objective is to build a model, from the establishment of a Bayesian network, for the early diagnosis of nursing to identify eating disorders bulimia and anorexia nervosa in adolescents, from the characteristics of the DSM-IV and Nursing Diagnoses The need for greater investment in technology in public health actions aims to increase the knowledge of health professio...

Research paper thumbnail of A Protocol for the Diagnosis of Autism Spectrum Disorder Structured in Machine Learning and Verbal Decision Analysis

Computational and Mathematical Methods in Medicine, 2021

Autism Spectrum Disorder is a mental disorder that afflicts millions of people worldwide. It is e... more Autism Spectrum Disorder is a mental disorder that afflicts millions of people worldwide. It is estimated that one in 160 children has traces of autism, with five times the higher prevalence in boys. The protocols for detecting symptoms are diverse. However, the following are among the most used: the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5), of the American Psychiatric Association; the Revised Autistic Diagnostic Observation Schedule (ADOS-R); the Autistic Diagnostic Interview (ADI); and the International Classification of Diseases, 10th edition (ICD-10), published by the World Health Organization (WHO) and adopted in Brazil by the Unified Health System (SUS). The application of machine learning models helps make the diagnostic process of Autism Spectrum Disorder more precise, reducing, in many cases, the number of criteria necessary for evaluation, denoting a form of attribute engineering (feature engineering) efficiency. This work proposes a hybri...

Research paper thumbnail of Metaheuristics for the Minimum Time Cut Path Problem with Different Cutting and Sliding Speeds

Algorithms, 2021

The problem of efficiently cutting smaller two-dimensional pieces from a larger surface is recurr... more The problem of efficiently cutting smaller two-dimensional pieces from a larger surface is recurrent in several manufacturing settings. This problem belongs to the domain of cutting and packing (C&P) problems. This study approached a category of C&P problems called the minimum time cut path (MTCP) problem, which aims to identify a sequence of cutting and sliding movements for the head device to minimize manufacturing time. Both cutting and slide speeds (just moving the head) vary according to equipment, despite their relevance in real-world scenarios. This study applied the MTCP problem on the practical scope and presents two metaheuristics for tackling more significant instances that resemble real-world requirements. The experiments presented in this study utilized parameter values from typical laser cutting machines to assess the feasibility of the proposed methods compared to existing commercial software. The results show that metaheuristic-based solutions are competitive when ad...

Research paper thumbnail of A Novel Model Structured on Predictive Churn Methods in a Banking Organization

Journal of Risk and Financial Management, 2021

A constant in the business world is the frequent movement of customers joining or abandoning comp... more A constant in the business world is the frequent movement of customers joining or abandoning companies’ services and products. The customer is one of the company’s most important assets. Reducing the customer abandonment rate has become a matter of survival and, at the same time, the most efficient way to maintain the customer base, since the replacement of dropouts by new customers costs, on average, 40% more. Aiming to mitigate the churn (customer evasion) phenomenon, this study compared predictive models to discover the most efficient method to identify customers who tend to drop out in the context of a banking organization. A literature review of related works on the subject found the neural network, decision tree, random forest and logistic regression models were the most cited, and thus the models were chosen for this work. Quantitative analyses were carried out on a sample of 200,000 credit operations, with 497 explanatory variables. The statistical treatment of the data and ...

Research paper thumbnail of Next-Generation Smart Electric Vehicles Cyber Physical System for Charging Slots Booking in Charging Stations

Research paper thumbnail of Um modelo de otimização multi-objetivo de demand response para programação de carga residencial

Learning and Nonlinear Models, Apr 2, 2019

Research paper thumbnail of A Hybrid Model for Optimizing the Municipal Public Budget

Management of Information Systems, Oct 24, 2018

Research paper thumbnail of Automatic Detection and Diagnosis of Neurologic Diseases

Research paper thumbnail of An educational game to teach numbers in Brazilian Sign Language while having fun

Computers in Human Behavior, 2018

Research paper thumbnail of Towards the Verbal Decision Analysis Paradigm for Prioritization of Software Requirements Implementable

The activity of prioritizing software requirements should be done as efficiently as possible. Sel... more The activity of prioritizing software requirements should be done as efficiently as possible. Selecting the most stable requirements for the most important customers for the development company can be a positive factor when we consider that the available resource does not always encompass the implementation of all requirements. Quantitative methods for reaching software prioritization in releases are many in the field of Search-Based Software Engineering (SBSE). However, we show that it is possible to use qualitative Verbal Decision Analysis (VDA) methods to solve this same type of problem. Moreover, we will use the ZAPROS III-i methods to prioritize requirements considering the opinion of the decision-maker, who will participate in this process. Finally, the results obtained in the VDA structured methods were quite satisfactory when compared to the methods using SBSE. A comparison of results between quantitative and qualitative methods will be made and discussed later.

Research paper thumbnail of Multicriteria Methods as Decision Making Aids in the Hydrographic Basin of the Curu River - State of Cear�

2006 International Conference on Service Systems and Service Management, 2006

Decisions on the liberation of dam flows for a basin during a given period, involve great difficu... more Decisions on the liberation of dam flows for a basin during a given period, involve great difficulties with hydrological, social, political and economical aspects. The multicriteria methods frequently support decision making techniques, that help to solve problems that can have several conflicting objectives, multiple possible actions, uncertainties, diverse stages, and many affected individuals. This study combines operational research and multicriteria

Research paper thumbnail of Aligning the Goals Hybrid Model for the Diagnosis of Mental Health Quality

Sustainability

The social distancing imposed by the COVID-19 pandemic has been described as the “greatest psycho... more The social distancing imposed by the COVID-19 pandemic has been described as the “greatest psychological experiment in the world”. It has tested the human capacity to extract meaning from suffering and challenged individuals and society in Brazil and abroad to promote cohesion that cushions the impact of borderline experiences on mental life. In this context, a survey was conducted with teachers, administrative technicians, and outsourced employees at the Federal Institute of Piauí (IFPI). This educational institution offers professional and technological education in Piauí, Brazil. This study proposes a system for the early diagnosis of health quality during social distancing in the years 2020 and 2021, over the COVID-19 pandemic, combining multi-criteria decision support methodology, the Analytic Hierarchy Process (AHP) with machine learning algorithms (Random Forest, logistic regression, and Naïve Bayes). The hybrid approach of the machine learning algorithm with the AHP multi-cr...

Research paper thumbnail of Prioritising Maintenance Work Orders in a Thermal Power Plant: A Multicriteria Model Application

Sustainability

Maintenance is one of the most rapidly expanding activities in the industrial environment, since ... more Maintenance is one of the most rapidly expanding activities in the industrial environment, since its application is no longer limited to simple, regular fixes. In the case of thermal power plants maintenance is essential, since they only operate when the National Electric System Operator wants them to complement the production from renewable sources such as hydro, wind, and solar. To limit the frequency of failures that result in generation unavailability, the operation team performs daily inspections to evaluate the equipment’s condition and the risks to the generating process. If an anomaly is found, the maintenance team will create service notes to address it. This research aims to demonstrate how the method Measuring Attractiveness by a Category-Based Evaluation Technique (Macbeth) can be applied to the development of a multiple-criterion model to support decision making in ordering the criticality of systems in thermal plant operational inspection routes to propose new methodol...

Research paper thumbnail of Assessment of Compressed and Decompressed ECG Databases for Telecardiology Applying a Convolution Neural Network

Electronics

Incalculable numbers of patients in hospitals as a result of COVID-19 made the screening of heart... more Incalculable numbers of patients in hospitals as a result of COVID-19 made the screening of heart patients arduous. Patients who need regular heart monitoring were affected the most. Telecardiology is used for regular remote heart monitoring of such patients. However, the resultant huge electrocardiogram (ECG) data obtained through regular monitoring affects available storage space and transmission bandwidth. These signals can take less space if stored or sent in a compressed form. To recover them at the receiver end, they are decompressed. We have combined telecardiology with automatic ECG arrhythmia classification using CNN and proposed an algorithm named TELecardiology using a Deep Convolution Neural Network (TELDCNN). Discrete cosine transform (DCT), 16-bit quantization, and run length encoding (RLE) were used for compression, and a convolution neural network (CNN) was applied for classification. The database was formed by combining real-time signals (taken from a designed ECG d...

Research paper thumbnail of A Neuroevolutionary Model to Estimate the Tensile Strength of Manufactured Parts Made by 3D Printing

Algorithms

Three-dimensional printing has advantages, such as an excellent flexibility in producing parts fr... more Three-dimensional printing has advantages, such as an excellent flexibility in producing parts from the digital model, enabling the fabrication of different geometries that are both simple or complex, using low-cost materials and generating little residue. Many technologies have gained space, highlighting the artificial intelligence (AI), which has several applications in different areas of knowledge and can be defined as any technology that allows a system to demonstrate human intelligence. In this context, machine learning uses artificial intelligence to develop computational techniques, aiming to build knowledge automatically. This system is responsible for making decisions based on experiences accumulated through successful solutions. Thus, this work aims to develop a neuroevolutionary model using artificial intelligence techniques, specifically neural networks and genetic algorithms, to predict the tensile strength in materials manufactured by fused filament fabrication (FFF)-t...

Research paper thumbnail of Using the Multi-Criteria Model for Optimization of Operational Routes of Thermal Power Plants

Energies, 2021

The constant problems evidenced in the Brazilian hydrological scenario, where the source of hydra... more The constant problems evidenced in the Brazilian hydrological scenario, where the source of hydraulic potential corresponds to about 63.9% of the energy matrix, coupled with the exponential growth in the supply of renewable energy, corroborates the importance of thermal power generation as the basis of Brazilian’s energy matrix. With the operation of thermal power plants, which characteristically involve a large number of systems, subsystems, and auxiliary equipment, there is a high demand for the use of methodologies for monitoring and controlling processes, analyzing failures, and implementing improvements and actions that increase the reliability and, consequently, reduce the failure rate. In this context, decision-making about prioritizing criticality for operational monitoring of an asset’s components, from the perspective of operation and maintenance planning and based on reliability-centered maintenance (RCM) concepts, can be considered a complex task. Given this, the researc...

Research paper thumbnail of Analyzing the Multicriteria of the Interaction Design of an Educational Map Application for Digital TV from User Preferences

Research paper thumbnail of Handing a Hybrid Multicriteria Model for Choosing Specialists to Analyze Application Management Service Tickets

Research & Innovation Forum 2019, 2019

Research paper thumbnail of Multicriteria Model for Evaluation of Outsourcing Services by Logistics Operators

Intelligent Algorithms in Software Engineering, 2020

Research paper thumbnail of Strategic Decision Method Structured in SWOT Analysis and Postures Based in the MAGIQ Multicriteria Analysis

Applied Computational Intelligence and Mathematical Methods, 2017

Research paper thumbnail of Applying Bayesian Networks in the Early Diagnosis of Bulimia and Anorexia Nervosa in Adolescents: Applying Bayesian Networks in Early Diagnosis in Adolescents

The diseases and health problems are concerns of managers of the Unified Health System has costs ... more The diseases and health problems are concerns of managers of the Unified Health System has costs in more sophisticated care sector are high. The World Health Organization focused on prevention of chronic diseases to prevent millions of premature deaths in the coming years, bringing substantial gains in economic growth by improving the quality of life. Few countries appear to be aimed at prevention, if not note the available knowledge and control of chronic diseases and may represent an unnecessary risk to future generations. Early diagnosis of these diseases is the first step to successful treatment in any age group. The objective is to build a model, from the establishment of a Bayesian network, for the early diagnosis of nursing to identify eating disorders bulimia and anorexia nervosa in adolescents, from the characteristics of the DSM-IV and Nursing Diagnoses The need for greater investment in technology in public health actions aims to increase the knowledge of health professio...

Research paper thumbnail of A Protocol for the Diagnosis of Autism Spectrum Disorder Structured in Machine Learning and Verbal Decision Analysis

Computational and Mathematical Methods in Medicine, 2021

Autism Spectrum Disorder is a mental disorder that afflicts millions of people worldwide. It is e... more Autism Spectrum Disorder is a mental disorder that afflicts millions of people worldwide. It is estimated that one in 160 children has traces of autism, with five times the higher prevalence in boys. The protocols for detecting symptoms are diverse. However, the following are among the most used: the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5), of the American Psychiatric Association; the Revised Autistic Diagnostic Observation Schedule (ADOS-R); the Autistic Diagnostic Interview (ADI); and the International Classification of Diseases, 10th edition (ICD-10), published by the World Health Organization (WHO) and adopted in Brazil by the Unified Health System (SUS). The application of machine learning models helps make the diagnostic process of Autism Spectrum Disorder more precise, reducing, in many cases, the number of criteria necessary for evaluation, denoting a form of attribute engineering (feature engineering) efficiency. This work proposes a hybri...

Research paper thumbnail of Metaheuristics for the Minimum Time Cut Path Problem with Different Cutting and Sliding Speeds

Algorithms, 2021

The problem of efficiently cutting smaller two-dimensional pieces from a larger surface is recurr... more The problem of efficiently cutting smaller two-dimensional pieces from a larger surface is recurrent in several manufacturing settings. This problem belongs to the domain of cutting and packing (C&P) problems. This study approached a category of C&P problems called the minimum time cut path (MTCP) problem, which aims to identify a sequence of cutting and sliding movements for the head device to minimize manufacturing time. Both cutting and slide speeds (just moving the head) vary according to equipment, despite their relevance in real-world scenarios. This study applied the MTCP problem on the practical scope and presents two metaheuristics for tackling more significant instances that resemble real-world requirements. The experiments presented in this study utilized parameter values from typical laser cutting machines to assess the feasibility of the proposed methods compared to existing commercial software. The results show that metaheuristic-based solutions are competitive when ad...

Research paper thumbnail of A Novel Model Structured on Predictive Churn Methods in a Banking Organization

Journal of Risk and Financial Management, 2021

A constant in the business world is the frequent movement of customers joining or abandoning comp... more A constant in the business world is the frequent movement of customers joining or abandoning companies’ services and products. The customer is one of the company’s most important assets. Reducing the customer abandonment rate has become a matter of survival and, at the same time, the most efficient way to maintain the customer base, since the replacement of dropouts by new customers costs, on average, 40% more. Aiming to mitigate the churn (customer evasion) phenomenon, this study compared predictive models to discover the most efficient method to identify customers who tend to drop out in the context of a banking organization. A literature review of related works on the subject found the neural network, decision tree, random forest and logistic regression models were the most cited, and thus the models were chosen for this work. Quantitative analyses were carried out on a sample of 200,000 credit operations, with 497 explanatory variables. The statistical treatment of the data and ...

Research paper thumbnail of Next-Generation Smart Electric Vehicles Cyber Physical System for Charging Slots Booking in Charging Stations

Research paper thumbnail of Um modelo de otimização multi-objetivo de demand response para programação de carga residencial

Learning and Nonlinear Models, Apr 2, 2019

Research paper thumbnail of A Hybrid Model for Optimizing the Municipal Public Budget

Management of Information Systems, Oct 24, 2018

Research paper thumbnail of Automatic Detection and Diagnosis of Neurologic Diseases

Research paper thumbnail of An educational game to teach numbers in Brazilian Sign Language while having fun

Computers in Human Behavior, 2018

Research paper thumbnail of Towards the Verbal Decision Analysis Paradigm for Prioritization of Software Requirements Implementable

The activity of prioritizing software requirements should be done as efficiently as possible. Sel... more The activity of prioritizing software requirements should be done as efficiently as possible. Selecting the most stable requirements for the most important customers for the development company can be a positive factor when we consider that the available resource does not always encompass the implementation of all requirements. Quantitative methods for reaching software prioritization in releases are many in the field of Search-Based Software Engineering (SBSE). However, we show that it is possible to use qualitative Verbal Decision Analysis (VDA) methods to solve this same type of problem. Moreover, we will use the ZAPROS III-i methods to prioritize requirements considering the opinion of the decision-maker, who will participate in this process. Finally, the results obtained in the VDA structured methods were quite satisfactory when compared to the methods using SBSE. A comparison of results between quantitative and qualitative methods will be made and discussed later.