Añadido recientemente

Factores determinantes en la toma de decisiones de evacuación : análisis experimental y desarrollo de modelos predictivos

Balboa Marras, Adriana

(2024-05-31)

Laboratory assessment of the infiltration capacity reduction in clogged porous mixture surfaces

Andrés Valeri, Valerio Carlos Alessio

; Marchioni, Mariana; Sañudo Fontaneda, Luis Ángel

; Giustozzi, Filippo; Becciu, Gianfranco (MDPI, 2016)

Multi-criteria analysis of porous asphalt mixtures with aramid fiber under adverse conditions

DeLaFuente-Navarro, Christopher Alfredo; Lastra González, Pedro

; Slebi Acevedo, Carlos José; Indacoechea Vega, Irune

; Castro Fresno, Daniel

(Elsevier Ltd, 2024-05)

D3.2. Multi-criteria decision analysis (MCDA) for selection and location of hybrid solutions

Andrés Valeri, Valerio Carlos Alessio

; Roldán Valcarce, Alejandro

; García Argüelles, Sara; Rodríguez Hernández, Jorge

; Pascual Muñoz, Pablo

; Castro Fresno, Daniel

(2024-02)

Efficient Reuse of Railway Track Waste Materials

Sañudo Ortega, Roberto

; Goswami, Rohit Raj; Ricci, Stefano; Miranda Manzanares, Marina

(MDPI, 2022)

Uncovering non-emergency-related factors in threat responses: logistic regression analysis of online experimental data for behaviour patterns

Balboa Marras, Adriana

; Cuesta Jiménez, Arturo

; González Villa, Javier

; Ortiz Romero, Gemma

; Alvear Portilla, Manuel Daniel

(Elsevier, 2024-02)

End-of-Life approach in permeable pavement systems: a forensic study of the particle-related pollutants retained in porous concrete and porous asphalt surface layers

Andrés Valeri, Valerio Carlos Alessio

; García Argüelles, Sara; Sañudo Fontaneda, Luis Ángel

; Rodríguez Gallego, José Luis; Rodríguez Hernández, Jorge

; Sierra, C. (2023)

Planning policies for the driverless city using backcasting and the participatory Q-Methodology

Nogués Linares, Soledad

; González González, María Esther

; Stead, Dominic; Cordera Piñera, Rubén

(Elsevier, 2023-11)

Logistic regression vs machine learning to predict evacuation decisions in fire alarm situations

Balboa Marras, Adriana

; Cuesta Jiménez, Arturo

; González Villa, Javier

; Ortiz Romero, Gemma

; Alvear Portilla, Manuel Daniel

(Elsevier, 2024-06)

Analysis of manufacturing and material parameters in 3D-printed polylactic acid (PLA) parts filled with glass powder: mechanical, economic, and environmental assessment

Castañón Jano, Laura

; Palomera Obregón, Paula; Blanco Fernández, Elena

; Indacoechea Vega, Irune

(Springer, 2023-09)

Using the point method to estimate failure loads in 3D printed graphene-reinforced PLA notched plates

Cicero González, Sergio

; Arrieta Gómez, Sergio

; Sánchez Matías, Marcos

; Castañón Jano, Laura

(Institute of Physics, 2024)

Assessment of co-contaminated soil amended by graphene oxide: effects on pollutants, microbial communities and soil health

Peña Álvarez, Verónica; Baragaño Coto, Diego

; Prosenkov, Alexander; Rodríguez Gallego, José Luis; Peláez, Ana Isabel (Elsevier, 2024-03-01)

Improving detection of asphalt distresses with deep learning-based diffusion model for intelligent road maintenance

Cano Ortiz, Saúl

; Lloret Iglesias, Lara; Martínez Ruiz del Árbol, Pablo

; Castro Fresno, Daniel

(Elsevier, 2024-03)

An end-to-end computer vision system based on deep learning for pavement distress detection and quantification

Cano Ortiz, Saúl

; Lloret Iglesias, Lara; Martínez Ruiz del Árbol, Pablo

; Lastra González, Pedro

; Castro Fresno, Daniel

(Elsevier Ltd, 2024-02-16)

Desarrollo de herramientas de modelización espacial de riesgos ambientales urbanos para facilitar su mitigación mediante soluciones basadas en la naturaleza

Roldán Valcarce, Alejandro

(2024-01-18)

Hg and As pollution in the soil-plant system evaluated by combining multispectral UAV-RS, geochemical survey and machine learning

Salgado, Lorena; López Sánchez, Carlos A.; Colina Vuelta, Arturo; Baragaño Coto, Diego

; Forján Castro, Rubén; Rodríguez Gallego, José Luis (Elsevier, 2023-09-15)

Modelling parking choice behaviour considering alternative availability and systematic and random variations in user tastes

Rodríguez Gutiérrez, Andrés

; Dell´Olio, Luigi

; Moura Berodia, José Luis

; Alonso Oreña, Borja

; Cordera Piñera, Rubén

(MDPI, 2023-06-01)

Low-noise and pollutant-reducing asphalt mixtures

Miera Domínguez, Helena

; Indacoechea Vega, Irune

; Lastra González, Pedro

; Van Loon, Ronald; Van Blokland, Gijsjan; Castro Fresno, Daniel

(Elsevier, 2023)

Development of improved porous asphalt mixtures with high porosity levels

Slebi Acevedo, Carlos José; Lastra González, Pedro

; Indacoechea Vega, Irune

; Castro Fresno, Daniel

(Elsevier, 2023-12)

Rheological and mechanical consequences of reducing the curing time of cold asphalt mixtures by means of magnetic induction

DeLaFuente-Navarro, Christopher Alfredo; Lastra González, Pedro

; Calzada Pérez, Miguel Ángel

; Castro Fresno, Daniel

(Elsevier, 2023-12)

D09 Proyectos de investigación: Envíos recientes

Factores determinantes en la toma de decisiones de evacuación : análisis experimental y desarrollo de modelos predictivos

Laboratory assessment of the infiltration capacity reduction in clogged porous mixture surfaces

Multi-criteria analysis of porous asphalt mixtures with aramid fiber under adverse conditions

D3.2. Multi-criteria decision analysis (MCDA) for selection and location of hybrid solutions

Efficient Reuse of Railway Track Waste Materials

Uncovering non-emergency-related factors in threat responses: logistic regression analysis of online experimental data for behaviour patterns

End-of-Life approach in permeable pavement systems: a forensic study of the particle-related pollutants retained in porous concrete and porous asphalt surface layers

Planning policies for the driverless city using backcasting and the participatory Q-Methodology

Logistic regression vs machine learning to predict evacuation decisions in fire alarm situations

Analysis of manufacturing and material parameters in 3D-printed polylactic acid (PLA) parts filled with glass powder: mechanical, economic, and environmental assessment

Using the point method to estimate failure loads in 3D printed graphene-reinforced PLA notched plates

Assessment of co-contaminated soil amended by graphene oxide: effects on pollutants, microbial communities and soil health

Improving detection of asphalt distresses with deep learning-based diffusion model for intelligent road maintenance

An end-to-end computer vision system based on deep learning for pavement distress detection and quantification

Desarrollo de herramientas de modelización espacial de riesgos ambientales urbanos para facilitar su mitigación mediante soluciones basadas en la naturaleza

Hg and As pollution in the soil-plant system evaluated by combining multispectral UAV-RS, geochemical survey and machine learning

Modelling parking choice behaviour considering alternative availability and systematic and random variations in user tastes

Low-noise and pollutant-reducing asphalt mixtures

Development of improved porous asphalt mixtures with high porosity levels

Rheological and mechanical consequences of reducing the curing time of cold asphalt mixtures by means of magnetic induction

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D09 Proyectos de investigación: Envíos recientes

Factores determinantes en la toma de decisiones de evacuación : análisis experimental y desarrollo de modelos predictivos ﻿

Laboratory assessment of the infiltration capacity reduction in clogged porous mixture surfaces ﻿

Multi-criteria analysis of porous asphalt mixtures with aramid fiber under adverse conditions ﻿

D3.2. Multi-criteria decision analysis (MCDA) for selection and location of hybrid solutions ﻿

Efficient Reuse of Railway Track Waste Materials ﻿

Uncovering non-emergency-related factors in threat responses: logistic regression analysis of online experimental data for behaviour patterns ﻿

End-of-Life approach in permeable pavement systems: a forensic study of the particle-related pollutants retained in porous concrete and porous asphalt surface layers ﻿

Planning policies for the driverless city using backcasting and the participatory Q-Methodology ﻿

Logistic regression vs machine learning to predict evacuation decisions in fire alarm situations ﻿

Analysis of manufacturing and material parameters in 3D-printed polylactic acid (PLA) parts filled with glass powder: mechanical, economic, and environmental assessment ﻿

Using the point method to estimate failure loads in 3D printed graphene-reinforced PLA notched plates ﻿

Assessment of co-contaminated soil amended by graphene oxide: effects on pollutants, microbial communities and soil health ﻿

Improving detection of asphalt distresses with deep learning-based diffusion model for intelligent road maintenance ﻿

An end-to-end computer vision system based on deep learning for pavement distress detection and quantification ﻿

Desarrollo de herramientas de modelización espacial de riesgos ambientales urbanos para facilitar su mitigación mediante soluciones basadas en la naturaleza ﻿

Hg and As pollution in the soil-plant system evaluated by combining multispectral UAV-RS, geochemical survey and machine learning ﻿

Modelling parking choice behaviour considering alternative availability and systematic and random variations in user tastes ﻿

Low-noise and pollutant-reducing asphalt mixtures ﻿

Development of improved porous asphalt mixtures with high porosity levels ﻿

Rheological and mechanical consequences of reducing the curing time of cold asphalt mixtures by means of magnetic induction ﻿

Factores determinantes en la toma de decisiones de evacuación : análisis experimental y desarrollo de modelos predictivos

Laboratory assessment of the infiltration capacity reduction in clogged porous mixture surfaces

Multi-criteria analysis of porous asphalt mixtures with aramid fiber under adverse conditions

D3.2. Multi-criteria decision analysis (MCDA) for selection and location of hybrid solutions

Efficient Reuse of Railway Track Waste Materials

Uncovering non-emergency-related factors in threat responses: logistic regression analysis of online experimental data for behaviour patterns

End-of-Life approach in permeable pavement systems: a forensic study of the particle-related pollutants retained in porous concrete and porous asphalt surface layers

Planning policies for the driverless city using backcasting and the participatory Q-Methodology

Logistic regression vs machine learning to predict evacuation decisions in fire alarm situations

Analysis of manufacturing and material parameters in 3D-printed polylactic acid (PLA) parts filled with glass powder: mechanical, economic, and environmental assessment

Using the point method to estimate failure loads in 3D printed graphene-reinforced PLA notched plates

Assessment of co-contaminated soil amended by graphene oxide: effects on pollutants, microbial communities and soil health

Improving detection of asphalt distresses with deep learning-based diffusion model for intelligent road maintenance

An end-to-end computer vision system based on deep learning for pavement distress detection and quantification

Desarrollo de herramientas de modelización espacial de riesgos ambientales urbanos para facilitar su mitigación mediante soluciones basadas en la naturaleza

Hg and As pollution in the soil-plant system evaluated by combining multispectral UAV-RS, geochemical survey and machine learning

Modelling parking choice behaviour considering alternative availability and systematic and random variations in user tastes

Low-noise and pollutant-reducing asphalt mixtures

Development of improved porous asphalt mixtures with high porosity levels

Rheological and mechanical consequences of reducing the curing time of cold asphalt mixtures by means of magnetic induction