Details
Name
Maria Clara VazCluster
Industrial and Systems EngineeringRole
External Research CollaboratorSince
01st March 2014
Nationality
PortugalCentre
Industrial Engineering and ManagementContacts
+351 22 209 4190
maria.c.vaz@inesctec.pt
2022
Authors
Gruetzmacher, SB; Vaz, CB; Ferreira, AP;
Publication
REVISTA FACULTAD DE INGENIERIA-UNIVERSIDAD DE ANTIOQUIA
Abstract
2022
Authors
Vaz, CB; Ferreira, ÂP;
Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Abstract
2022
Authors
Silva, FG; Sena, I; Lima, LA; Fernandes, FP; Pacheco, MF; Vaz, CB; Lima, J; Pereira, AI;
Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Abstract
2022
Authors
Lima, L; Pereira, AI; Vaz, C; Ferreira, O;
Publication
2022 17TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI)
Abstract
Predicting the performance of a mixture is crucial to designing experiences in product development and formulation research. In this work, an application, MDesign, is proposed to construct models in a mixture design with a practical, educational, and intuitive approach. Developed in MATLAB software, the standalone application aims to contribute to the study of mixtures through the definition of multivariate models of different orders, enabling their statistical analysis to verify the robustness of each of those models. Compared to the obtained results from other applications using data experiments published in the literature, the proposed application presents accurate results and good execution. MDesign can be considered an automatic, robust, and valuable tool to support the mixture design in an industrial context.
2021
Authors
Gruetzmacher, SB; Vaz, CB; Ferreira, ÂP;
Publication
Communications in Computer and Information Science
Abstract
Based in the current growth rate of metropolitan areas, providing infrastructures and services to allow the safe, quick and sustainable mobility of people and goods, is increasingly challenging. The European Union has been promoting diverse initiatives towards sustainable transport development and environment protection by setting targets for changes in the sector, as those proposed in the 2011 White Paper on transport. Under this context, this study aims at evaluating the environmental performance of the transport sector in the 28 European Union countries, from 2015 to 2017, towards the policy agenda established in strategic documents. The assessment of the transport environmental performance was made through the aggregation of seven sub-indicators into a composite indicator using a Data Envelopment Analysis approach. The model used to determine the weights to aggregate the sub-indicators is based on a variant of the Benefit of the Doubt model with virtual proportional weights restrictions. The results indicate that, overall, the European Union countries had almost no variation on its transport environmental performance during the time span under analysis. The inefficient countries can improve the transport sustainability mainly by drastically reducing the greenhouse gas emissions from fossil fuels combustion, increasing the share of freight transport that uses rail and waterways and also the share of transport energy from renewable sources. © 2021, Springer Nature Switzerland AG.
Supervised Thesis
2018
Author
João Filipe Magalhães Moreira
Institution
UP-FEUP
2018
Author
João Gabriel Marques Costa
Institution
UP-FEUP
2018
Author
João Manuel Estrada Pereira Gouveia
Institution
UP-FEUP
2018
Author
João Miguel Fidalgo Esteves Nogueira
Institution
UP-FEUP
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