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Symone G. Soares Alcalá

Symone G. Soares Alcalá
Federal University of Goiás, Aparecida de Goiânia, Goiás, Brazil · Production Engineering

Professor

About

52
Publications
18,720
Reads
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1,614
Citations
Introduction
Symone G. Soares Alcalá received her Ph.D. degree in Electrical and Computer Engineering from the University of Coimbra, Portugal, in 2015. She is Adjunct Professor at Federal University of Goiás. She has been supervising Master and Undergraduate students in the field of Machine Learning. Her main research interests include Machine Learning, Computational Intelligence Model and Neural Networks. Webpage: https://sites.google.com/site/symonesoares/
Additional affiliations
April 2016 - present
Federal University of Goiás, Aparecida de Goiânia, Goiás, Brazil
Position
  • Professor
Description
  • Adjunct-A Professor at Federal University of Goiás, Faculty of Sciences and Technology, Campus Aparecida de Goiânia, Department of Production Engineering.
February 2010 - March 2015
University of Coimbra
Position
  • Researcher
Description
  • Development of computational learning methodologies for monitoring and controlling industrial processes. Author of 5 journal papers. Main research domains: Machine Learning, Ensemble Learning and Adaptive Learning.
Education
September 2010 - September 2015
University of Coimbra
Field of study
  • Electrical and Computer Engineering
January 2005 - December 2009
Pontifical Catholic University of Goiás (PUC-GO)
Field of study
  • Computer Engineering

Publications

Publications (52)
Conference Paper
Full-text available
This paper presents a comparative analysis between classifiers and proposes a fault detection architecture in preventive maintenance programs, through machine learning techniques, in the offshore operating environment of an oil and gas industry. Initially, a mining was carried out in the database with the objective of generating characteristics app...
Article
Additive manufacturing (AM) allows the construction of customized objects from the 3D printing of pre-modeled objects. Defects may occur during the printing process that impact user satisfaction. The inspection procedure is usually performed by a human; however, such a task is often characterized by slowness and a high likelihood of errors. Therefo...
Article
Full-text available
Business Intelligence (BI) is a set of techniques that assist organizations in making data-driven decisions, enabling interactive access to information, often in real-time. In this way, its application provides precise business analyses, contributing to goal tracking, results projection, identification of opportunities, and anticipation of risks. T...
Article
A transformação digital é uma tendência nas indústrias decorrente da Quarta Revolução Industrial e da crescente necessidade de as empresas aumentarem a eficiência e a agilidade para se manterem competitivas. Nesse sentido, a digitalização de processos é um importante componente para essa transformação. No entanto, os métodos de desenvolvimento clás...
Article
Full-text available
Previsões de séries temporais auxiliam a tomada de decisão em diversas áreas como marketing, economia e indústria, sendo que a principal finalidade é estimar o comportamento futuro de uma sequência de observações. Nesse sentido, conjuntos de modelos (ensembles) híbridos, que combinam modelos de aprendizado de máquina e estatísticos, têm se mostrado...
Article
In the current industrial revolution, additive manufacturing (AM) embodies a promising technology that can enhance the effectiveness, adaptability, and competitiveness of supply chains (SCs). Moreover, it facilitates the development of distributed SCs, thereby enhancing product availability, inventory levels, and lead time. However, the wide adopti...
Article
Full-text available
Preventive maintenance of offshore units has proven to be crucial in reducing downtime and maintenance costs. In this work, Big Data analytics, applied in the industry to collect, process and analyze data, is used to identify a system abnormal behavior. This knowledge allows the adoption of a proactive maintenance approach instead of the convention...
Preprint
Full-text available
In the current industrial revolution, additive manufacturing (AM) embodies a promising technology that can enhance the effectiveness, adaptability, and competitiveness of supply chains (SCs). Moreover, it facilitates the development of distributed SCs, thereby enhancing product availability, inventory levels, and lead time. However, the wide adopti...
Article
Full-text available
Machine learning (ML) has become an emerging technology able to solve problems in many areas, including education, medicine, robotic and aerospace. ML is a specific field of artificial intelligence which designs computational models able to learn from data. However, to develop a ML model, it is necessary to ensure data quality, since real-world dat...
Article
Full-text available
Vision systems have been widely employed in industries to automate the inspection process in products. Their use provides standardized, reliable and accurate inspections when compared to a human operator. Vision systems pass to machines the ability to view and automatically extract features in order to indicate abnormalities in products. This paper...
Article
Full-text available
Paper aims In this study, effective strategies to combine and select forecasting methods are proposed. In the selection strategy, the best performing forecasting method from a pool of methods is selected based on its accuracy, whereas the combination strategies are based on the mean methods’ outputs and on the methods’ accuracy. Originality Despit...
Article
Distributed manufacturing systems represent a new paradigm in the industrial context, supported by new technologies provided by industry 4.0. In this paper, a model for dynamic allocation of Production Orders (PO) in the context of distributed additive manufacturing systems is proposed. The scheduling model performs a local optimization of PO alloc...
Conference Paper
Full-text available
Novas tecnologias, como sistemas de visão e braços robóticos, têm possibilitado a inspeção e separação automatizada de produtos em indústrias para reduzir custos operacionais e aumentar a qualidade de produtos e processos. Sendo assim, este artigo propõe um sistema de visão para a inspeção de objetos defeituosos numa esteira transportadora por meio...
Article
The amount of data extracted from production processes has increased exponentially due to the proliferation of sensing technologies. When processed and analyzed, data can bring out valuable information and knowledge from manufacturing process, production system and equipment. In industries, equipment maintenance is an important key, and affects the...
Conference Paper
Full-text available
Additive Manufacturing (AM) is one of the most trending production technologies, with a growing number of companies looking forward to implementing it in their processes. Producing through AM not only means that there are no supplier lead times needed to account for, but also enables production closer to the end customer, reducing then the delivery...
Conference Paper
Full-text available
To be competitive, companies must constantly innovate, and having efficient and well-managed supply chains is undoubtedly an important success factor. In the case of spare parts manufacturing, supply chain management is a very complex and arduous task. Quite often, spare parts have to be produced for products that have been on the market for very l...
Conference Paper
Full-text available
The industry faces more and more the challenge of deploying and taking advantage of evidence-based strategic decisions to enhance profit gain. In this research, the possibility of having a fully integrated system composed by a simulator and an IoT platform with the capability of collecting real-time data from the shop floor and returning performanc...
Conference Paper
Full-text available
FCT/UFG Prof.ª Dr.ª Symone G. S. Alcalá, symone@ufg.br, FCT/UFG Resumo: Com o intuito de reduzir os custos operacionais de empresas na inspeção da qualidade de produtos, este artigo propõe um modelo de Rede Neural (RN) para a classificação de objetos, defeituosos e não defeituosos, numa esteira transportadora sob diferentes condições de luminosidad...
Article
Full-text available
The Industry 4.0 movement is driving innovation in manufacturing through the application of digital technologies, leading to solid performance improvements. In this context, this paper introduces a real-time analytical framework based on predictive, simulation and optimization technologies applied to decision support in manufacturing systems, enabl...
Article
Full-text available
Este trabalho apresenta uma síntese dos principais resultados de experiências de extensão universitária na área de arborização do novo campus da Universidade Federal de Goiás (UFG) em Aparecida de Goiânia. A metodologia envolveu a elaboração de um mapeamento temático, a divulgação dos trabalhos e um inquérito, por meio de questionário online sobre...
Conference Paper
Full-text available
Sistemas de visão têm sido amplamente utilizados no setor industrial para automatizar o processo de inspeção. A utilização deles proporciona inspeções padronizadas, confiáveis e menos suscetíveis a erros causados por fadiga ou falta de atenção de um operador humano. Por outro lado, microcontroladores têm possibilitado a criação de aplicações comput...
Conference Paper
Full-text available
Com a evolução das tecnologias, sistemas de visão têm possibilitado a realização de inspeções automatizadas. Eles repassam para máquinas a capacidade da visão, podendo extrair automaticamente características e indicar anormalidades em produtos. Atualmente, a maioria dos sistemas de visão reconhecem padrões de cores e poucos são capazes de reconhece...
Conference Paper
Full-text available
The advent of the Industry 4.0 is posing several challenges for industries - for instance the pace of change, technologies to adopt, and user integration into the development process. In this context, digital technologies such as cloud infrastructures, big data and artificial intelligence, along with physical advancements in smart materials, nanote...
Conference Paper
Full-text available
O processo de inspeção e classificação de produtos por meio da detecção visual humana nem sempre se mostra eficiente, tendo em vista que fatores como o cansaço podem influenciar negativamente nesse processo, fazendo com que o operador não consiga inspecionar e classificar produtos. Sistemas de visão têm sido importantes no setor industrial, porque...
Conference Paper
Full-text available
A inspeção de produtos permite detectar anormalidades nos produtos produzidos, com o intuito de atender às normas e às expectativas dos consumidores. Geralmente, ela é feita manualmente, acarretando em altos custos, falhas e dificuldades na padronização. Com a evolução das tecnologias, sistemas de visão têm possibilitado a realização de inspeções a...
Conference Paper
Full-text available
Este trabalho analisa a percepção das comunidades sobre vegetações em áreas urbanas, no âmbito do projeto de extensão de arborização do novo campus UFG de Aparecida de Goiânia. Para a pesquisa estruturou-se e aplicou-se um questionário com sete questões sobre a vegetação urbana. Um total de 98,7% dos inquiridos considerou importante a presença de á...
Conference Paper
Full-text available
Soft Sensors (SSs) have been widely investigated and employed as inferential sensing systems for providing on-line estimations of industrial processes' variables. However, industrial processes suffer from different complex characteristics (e.g. time-variance and non-linearity), being very difficult for the SS models to perform well over time. This...
Conference Paper
Full-text available
Automatic recognition of sign languages to help hearing impaired people is an area that has been explored for quite some time. However, this is still a practical problem due to the complexity involved making it a big challenge. The use of devices, such as the Kinect sensor, has been shown to be promising in gesture recognition. Therefore, is propos...
Thesis
Full-text available
Increasing demands for on-line monitoring and control of industrial processes and their associated variables, and difficulties related to measuring systems have led to the development of predictive models called Soft Sensors (SSs). SSs use computational intelligence methods to estimate difficult-to-measure variables based on some easy-to-measure va...
Article
A demand for predictive models for on-line estimation of variables is increasing in industry. As industrial processes are time-varying, on-line learning algorithms should be adaptive to capture process changes. On-line ensemble methods have been shown to provide better generalization performance than single models in changing environments. However,...
Article
On-line learning in environments and applications with time-varying behavior pose serious challenges. Changes may lead the learning model designed with old data, to become inconsistent with the new data, so that adaptation strategies are necessary. Unfortunately, most adaptation strategies are performed only on a batch basis, i.e. after accumulatin...
Article
Full-text available
Many estimation, prediction, and learning applications have a dynamic nature. One of the most important challenges in machine learning is dealing with concept changes. Underlying changes may make the model designed on old data, inconsistent with new data. Also, algorithms usually specialize in one type of change. Other challenge is reusing previous...
Article
Full-text available
The success of mobile robots relies on the ability to extract from the environment additional information beyond simple spatial relations. In particular, mobile robots need to have semantic information about the entities in the environment such as the type or the name of places or objects. This work addresses the problem of classifying places (room...
Article
In the last decades ensemble learning has established itself as a valuable strategy within the computational intelligence modeling and machine learning community. Ensemble learning is a paradigm where multiple models combine in some way their decisions, or their learning algorithms, or different data to improve the prediction performance. Ensemble...
Conference Paper
Ensemble Methods (EMs) are sets of models that combine their decisions, or their learning algorithms, or different data to obtain good predictions. The motivations are the possibility of improving the generalization capability and the overall system performance. However, several issues are at stake in EM development, such as the design of models th...
Article
Ensemble Methods (EMs) are sets of models that combine their decisions, or their learning algorithms, or different data to obtain good predictions. The motivations are the possibility of improving the generalization capability and the overall system performance. However, several issues are at stake in EM development, such as the design of models th...
Article
Full-text available
Advances in digital electronics have enable the development of low-cost, low-power, multifunctional sensor nodes that are small in size and communicate in short distances. These tiny sensor nodes consist of sensing, data processing, and communication components, leverage the idea of Wireless Sensor Networks (WSN) based on collaborative effort of a...
Conference Paper
Industries are faced with the choice of suitable process control policies to improve costs, quality and raw material consumption. In the paper pulp industry, it is important to estimate quickly the Chemical Oxygen Demand (COD), a parameter that is highly correlated to product quality. Soft Sensors (SSs) have been established as alternative to hardw...
Article
Full-text available
Industries are faced with the choice of suitable process control policies to improve costs, quality and raw material consumption. In the paper pulp industry, it is important to estimate quickly the Chemical Oxygen Demand (COD), a parameter that is highly correlated to product quality. Soft Sensors (SSs) have been established as alternative to hardw...
Conference Paper
This paper cover a new method for variable selection in Soft Sensors design for industrial applications. We propose the use of Mutual Information for variable selection and to exclude redundant variables. As evaluation of quality model, we use a new criterion of tracking precision called relative variance tracking precision in parallel with the roo...
Conference Paper
Full-text available
Wireless Sensor Networks (WSN) is an emerging technology that is developed with a large number of useful applications. On the other hand, Artificial Neural Networks (ANN) have found many successful applications in nonlinear system and control, digital communication, pattern recognition, pattern classification, etc. There are many similarities betwe...
Thesis
Este trabalho propõe um estudo de Redes de Sensores para aplicações em Domótica. Para isso, são apresentadas tecnologias para suporte à Redes de Sensores, além do Perceptron, um modelo de Rede Neural para reconhecimento de padrões. Como estudo de caso, foi desenvolvida uma aplicação de Domótica – uma mesa inteligente, utilizando tecnologias de redu...

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