P
Paola Caymes Scutari
Researcher at National Technological University (United States)
Publications - 19
Citations - 36
Paola Caymes Scutari is an academic researcher from National Technological University (United States). The author has contributed to research in topics: Evolutionary algorithm & Population. The author has an hindex of 3, co-authored 19 publications receiving 34 citations. Previous affiliations of Paola Caymes Scutari include National Technological University.
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Journal ArticleDOI
Estimation of Volume Rendering Efficiency with GPU in a Parallel Distributed Environment
Cristian Pérez Monte,Cristian Pérez Monte,Fabiana Piccoli,Cristian Luciano,Silvio Rizzi,Germán Bianchini,Paola Caymes Scutari +6 more
TL;DR: A volume rendering algorithm, PD-Render intra for individual networked nodes in a parallel distributed architecture with a single GPU per node is presented, able to achieve photorealistic rendering as well as a high signal-tonoise ratio at interactive frame rates.
Journal Article
Hybrid-Parallel Uncertainty Reduction Method Applied to Forest Fire Spread Prediction
Miguel Méndez Garabetti,Germán Bianchini,María Laura Tardivo,Paola Caymes Scutari,Graciela Verónica Gil Costa +4 more
TL;DR: A hybrid uncertainty reduction method applied to forest fire spread prediction that combines the advantages of two evolutionary population metaheuristics: Evolutionary Algorithms and Differential Evolution.
Evolutionary-statistical system for uncertainty reduction problems in wildfires
TL;DR: This paper shows a method which takes advantage of the computational power provided by High Performance Computing to improve the quality of the output of the model and combines Statistical Analysis with Parallel Evolutionary Algorithms.
Journal ArticleDOI
Método de Reducción de Incertidumbre Basado en Algoritmos Evolutivos y Paralelismo Orientado a la Predicción y Prevención de Desastres Naturales
TL;DR: Two uncertainty reduction methods validated in the forest fire behavior prediction have been developed and these methods use as components Statistical Analysis, Parallel Evolutionary Algorithms, High Performance Computing and Satellite Information.
Predicción del Comportamiento de Incendios Forestales mediante un Métodode Reducción de Incertidumbre basado en HPC y Evolución Diferencial
TL;DR: Mendez-Garabetti et al. as discussed by the authors, Tardivo Maria Laura, Bianchini German, and Caymes-Scutari Paola Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET) Laboratorio de Investigación en Computo Paralelo/Distribuido Departamento de Ingenieria en Sistemas de Informacion Facultad Regional Mendoza/Universidad Tecnologica NACional Rodriguez 273 (M5502AJ