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18 results on '"Matta, Arthur"'

1. A Data Drift Approach to Update Deployed Energy Prediction Machine Learning Models

Author

Teixeira, Hélder, Matta, Arthur, Pilastri, André, Ferreira, Luís, Pereira, Pedro, Gonçalves, Carlos, Cortez, Paulo, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Santos, Manuel Filipe, editor, Machado, José, editor, Novais, Paulo, editor, Cortez, Paulo, editor, and Moreira, Pedro Miguel, editor

Published
2025
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3. Powered Smart Textile-Based Exoskeleton for Human Support Movement

Author

Ferreira, César, Fertuzinhos, Aureliano, Silva, Ricardo, Ramalho, Miguel, Vale, Bruno, Silva, João, Costa, Luani, Oliveira, Cristina, Ramôa, Ana, Aguiar, Fabiana, Pilastri, André, Matta, Arthur, Dias, Paula, Sampaio, Rosane, Machado, Dário, Costa, Marta, Roças, Ana, Madureira, Pedro, Moreira, Juliana, Pereira, João Rui, Pereira, Carla, Pereira, Fernando Bruno, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Salopek Čubrić, Ivana, editor, Čubrić, Goran, editor, Jambrošić, Kristian, editor, Jurčević Lulić, Tanja, editor, and Sumpor, Davor, editor

Published
2023
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4. Machine Learning for Predicting Production Disruptions in the Wood-Based Panels Industry: A Demonstration Case

Author

Afonso, Cláudia, Matta, Arthur, Matos, Luís Miguel, Gomes, Miguel Bastos, Santos, Antonina, Pilastri, André, Cortez, Paulo, Rannenberg, Kai, Editor-in-Chief, Soares Barbosa, Luís, Editorial Board Member, Goedicke, Michael, Editorial Board Member, Tatnall, Arthur, Editorial Board Member, Neuhold, Erich J., Editorial Board Member, Stiller, Burkhard, Editorial Board Member, Stettner, Lukasz, Editorial Board Member, Pries-Heje, Jan, Editorial Board Member, Kreps, David, Editorial Board Member, Rettberg, Achim, Editorial Board Member, Furnell, Steven, Editorial Board Member, Mercier-Laurent, Eunika, Editorial Board Member, Winckler, Marco, Editorial Board Member, Malaka, Rainer, Editorial Board Member, Maglogiannis, Ilias, editor, Iliadis, Lazaros, editor, MacIntyre, John, editor, and Dominguez, Manuel, editor

Published
2023
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5. Powered Smart Textile-Based Exoskeleton for Human Support Movement

Author

Ferreira, César, primary, Fertuzinhos, Aureliano, additional, Silva, Ricardo, additional, Ramalho, Miguel, additional, Vale, Bruno, additional, Silva, João, additional, Costa, Luani, additional, Oliveira, Cristina, additional, Ramôa, Ana, additional, Aguiar, Fabiana, additional, Pilastri, André, additional, Matta, Arthur, additional, Dias, Paula, additional, Sampaio, Rosane, additional, Machado, Dário, additional, Costa, Marta, additional, Roças, Ana, additional, Madureira, Pedro, additional, Moreira, Juliana, additional, Pereira, João Rui, additional, Pereira, Carla, additional, and Pereira, Fernando Bruno, additional

Published
2023
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6. An Intelligent Decision Support System for Road Freight Transport

Author

Carvalho, Hugo Silva, Pilastri, André, Matta, Arthur, Matos, Luís Miguel, Novais, Rui, Cortez, Paulo, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Yin, Hujun, editor, Camacho, David, editor, and Tino, Peter, editor

Published
2022
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7. An Empirical Study on Anomaly Detection Algorithms for Extremely Imbalanced Datasets

Author

Fontes, Gonçalo, Matos, Luís Miguel, Matta, Arthur, Pilastri, André, Cortez, Paulo, Rannenberg, Kai, Editor-in-Chief, Soares Barbosa, Luís, Editorial Board Member, Goedicke, Michael, Editorial Board Member, Tatnall, Arthur, Editorial Board Member, Neuhold, Erich J., Editorial Board Member, Stiller, Burkhard, Editorial Board Member, Tröltzsch, Fredi, Editorial Board Member, Pries-Heje, Jan, Editorial Board Member, Kreps, David, Editorial Board Member, Reis, Ricardo, Editorial Board Member, Furnell, Steven, Editorial Board Member, Mercier-Laurent, Eunika, Editorial Board Member, Winckler, Marco, Editorial Board Member, Malaka, Rainer, Editorial Board Member, Maglogiannis, Ilias, editor, Iliadis, Lazaros, editor, Macintyre, John, editor, and Cortez, Paulo, editor

Published
2022
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8. An Intelligent Decision Support System for Production Planning in Garments Industry

Author

Ribeiro, Rui, Pilastri, André, Carvalho, Hugo, Matta, Arthur, Pereira, Pedro José, Rocha, Pedro, Alves, Marcelo, Cortez, Paulo, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Yin, Hujun, editor, Camacho, David, editor, Tino, Peter, editor, Allmendinger, Richard, editor, Tallón-Ballesteros, Antonio J., editor, Tang, Ke, editor, Cho, Sung-Bae, editor, Novais, Paulo, editor, and Nascimento, Susana, editor

Published
2021
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9. Mixture-Based Open World Face Recognition

Author

Matta, Arthur, Pinto, João Ribeiro, Cardoso, Jaime S., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Rocha, Álvaro, editor, Adeli, Hojjat, editor, Dzemyda, Gintautas, editor, Moreira, Fernando, editor, and Ramalho Correia, Ana Maria, editor

Published
2021
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12. Ahead of Time Prediction of Decorated Particleboard Production Disruptions and Defects Using Single and Multi-Target AutoML.

Author

Matta, Arthur, Matos, Luís Miguel, Pilastri, André, Silva, Jorge Miguel, Gomes, Miguel Bastos, and Cortez, Paulo

Subjects
PRODUCTION planning, MANUFACTURING processes, ARTIFICIAL intelligence, PARTICLE board, MACHINE learning, DEEP learning
Abstract

This paper proposes a Machine Learning (ML) approach to perform an Ahead-of-Time (AoT) prediction of decorated particle-board production disruptions and defects. We worked with a Portuguese company that is adopting the Industry 4.0 concept aiming to improve their decorated particleboard production planning (e.g., reducing production time and waste of materials). This company's business needs are addressed in terms of two nontrivial binary Classification tasks (production disruptions and defects). The AoT prediction is achieved by using only input attributes available before the execution of the production process. To reduce the modeling effort, we focus on Automated ML (AutoML) methods, under two main approaches: Single-Target Classification (STC) and Multi-Target Classification (MTC). The former is achieved by adopting the popular H2O AutoML tool, while the latter adopts a deep learning neural network automatically tuned by using a Bayesian search. The computational experiments adopted a realistic rolling window evaluation over recently collected industrial data (comprising 14 months). Overall, interesting predictive results were achieved by both AutoML approaches, outperforming a baseline Decision Tree method. In addition, an eXplainable Artificial Intelligence (XAI) method based on a Sensitivity Analysis (SA) was adopted, allowing the identification of the most relevant inputs, which is valuable knowledge to support the decorated particleboard production planning. [ABSTRACT FROM AUTHOR]

Published
2024
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14. Categorical Attribute traNsformation Environment (CANE): A python module for categorical to numeric data preprocessing[Formula presented]

Author

Matos, Luís Miguel, Azevedo, João, Matta, Arthur, Pilastri, André, Cortez, Paulo, Mendes, Rui, and Universidade do Minho

Subjects
Science & Technology, Python programming language, Machine learning, Data preprocessing, CANE
Abstract

Categorical Attribute traNsformation Environment (CANE) is a simpler but powerful data categorical preprocessing Python package. The package is valuable since there is currently a large range of Machine Learning (ML) algorithms that can only be trained using numerical data (e.g., Deep Learning, Support Vector Machines) and several real-world ML applications are associated with categorical data attributes. Currently, CANE offers three categorical to numeric transformation methods, namely: Percentage Categorical Pruned (PCP), Inverse Document Frequency (IDF) and a simpler One-Hot-Encoding method. Additionally, the CANE module is well documented with several code examples that can help in its adoption by non expert users., The authors are grateful for project NORTE-01-0247-FEDER-017497, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). This work was also supported by FCT Fundação para a Ciência e Tecnologia, Portugal within the Project Scope: UID/CEC/00319/2019. The authors are also grateful for all the contributors that assisted in making CANE more intuitive.

Published
2022

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