51 a 60 de 604 Resultados
5 nov 2024
Diez-Pascual, Ana María; Champa-Bujaico, Elisabeth; Garcia Díaz, Pilar; Sesini, Valentina; G. Mosquera, Marta E., 2024, "Machine learning algorithms to optimize the properties of bio-based poly(butylene succinate-co- butylene adipate) nanocomposites with carbon nanotubes", https://doi.org/10.21950/AN5SP2, e-cienciaDatos, V1
In this project, a simple, cost-effective and scalable solution to improve the mechanical properties of poly(butylene succinate-co- butylene adipate) (PBSA) is reported by using functionalized single-walled carbon nanotubes (SWCNTs). Different SWCNT percentages w/w (0.15, 0.25, 0... |
5 nov 2024
Diez-Pascual, Ana María; Champa-Bujaico, Elisabeth; Garcia Díaz, Pilar; Lomas Redondo, Alba, 2024, "Optimization of mechanical properties of multiscale hybrid polymer nanocomposites: A combination of experimental and machine learning techniques", https://doi.org/10.21950/2ZUDRR, e-cienciaDatos, V1
Machine learning (ML) algorithms offer quick and accurate predictions of material properties at a low computational cost. In this project, the mechanical properties of multiscale poly(3-hydroxybutyrate) (P3HB)-based nanocomposites reinforced with different concentrations of multi... |
24 oct 2024
Domínguez-Rodrigo, Manuel, 2025, "Replication Data for: Computer vision enables taxon-specific identification of African carnivore tooth marks on bone", https://doi.org/10.7910/DVN/MLDCIC
Image data set of tooth marks of lions, leopards, spotted hyenas and crocodiles used to create models for computer vision classification of African carnivore taphonomic agency | Please do not use until manuscript is published. Also, please remove duplicated images when used. The...Dataset recolectado desde DataCite con autores de la UAH. El enlace le llevará directamente a los datos originales en dicho archivo. |
24 oct 2024
Sureda Riera, Tomás; Bermejo Higuera, Juan Ramón; Bermejo Higuera, Javier; Sicilia Montalvo, Juan Antonio; Martínez Herráiz, José Javier, 2025, "SR-BH 2020 multi-label dataset", https://doi.org/10.7910/DVN/OGOIXX
The dataset is composed of web requests collected during 12 days of July 2020 by a web server (Wordpress) installed on a virtual machine and exposed to Internet. On this server, Modsecurity version 2.9.2 for Apache, with Core Rule Set (CRS) version 3.3.0 was installed in ”Detecti...Dataset recolectado desde DataCite con autores de la UAH. El enlace le llevará directamente a los datos originales en dicho archivo. |
24 oct 2024
Domínguez-Rodrigo, Manuel, 2025, "Replication Data for: African bovid tribe classification using transfer learning and computer vision", https://doi.org/10.7910/DVN/TMLXGW
Image data set of African bovid teeth used for classification of tribe through computer vision. | The original image data set was published in: Brophy, J.K., Matthews, G.J. Reference database of teeth images from the Family Bovidae. Sci Data 9, 396 (2022). https://doi.org/10.1038...Dataset recolectado desde DataCite con autores de la UAH. El enlace le llevará directamente a los datos originales en dicho archivo. |
24 oct 2024
Alarcon Robledo, Sergio; Morales, Antonio J., 2025, "Survey Markers in Luxor West Bank - Data", https://doi.org/10.7910/DVN/WKELGD
This dataset includes raw data of two spatial reference networks that the Middle Kingdom Theban Project set on the Theban necropoleis, on the West Bank of Luxor, Egypt. It contains two CSV charts and four PDF files with the spatial data (Coordinates in WGS 84, UTM 36N projection;...Dataset recolectado desde DataCite con autores de la UAH. El enlace le llevará directamente a los datos originales en dicho archivo. |
24 oct 2024
Domínguez-Rodrigo, Manuel, 2025, "Replication Data for: TESTING THE RELIABILITY OF GEOMETRIC MORPHOMETRIC AND COMPUTER VISION METHODS TO IDENTIFY CARNIVORE AGENCY USING BI-DIMENSIONAL INFORMATION.", https://doi.org/10.7910/DVN/77MZDL
A comparison of geometric morphometric methods and computer vision methods to identify carnivore agency in bone surface modifications | submitted to Quaternary Science AdvancesDataset recolectado desde DataCite con autores de la UAH. El enlace le llevará directamente a los datos originales en dicho archivo. |
24 oct 2024
Domínguez-Rodrigo, Manuel, 2025, "Replication Data for: High accuracy in the classification of butchery cut marks and crocodile tooth marks using machine learning methods and computer vision algorithms", https://doi.org/10.7910/DVN/9NOD8W
Image dataset for the binary comparison of experimental crocodile tooth marks and cut marks made with stone tool flakes. An extended discussion of the advantages of the method is found in the original paper's supplementary files. Given the extensive resources that are involved in...Dataset recolectado desde DataCite con autores de la UAH. El enlace le llevará directamente a los datos originales en dicho archivo. |
22 oct 2024
González-Molina, Irene; Jiménez-García, Blanca; Maíllo-Fernández, José-Manuel; Baquedano, Enrique; Domínguez-Rodrigo, Manuel, 2025, "Replication Data for: Distinguishing Discoid and Centripetal Levallois methods through machine learning", https://doi.org/10.7910/DVN/T8SEC2
Database and R code used in the Research Article "Distinguishing Discoid and Centripetal Levallois methods through machine learning". We applied Machine Learning (ML) algorithms to study the differences between Discoid and Centripetal Levallois methods. For this purpose, we have...Dataset recolectado desde DataCite con autores de la UAH. El enlace le llevará directamente a los datos originales en dicho archivo. |
22 oct 2024
Domínguez-Rodrigo, Manuel, 2025, "Replication data for "Artificial intelligence provides greater accuracy in the classification of modern and ancient bone surface modifications"", https://doi.org/10.7910/DVN/62BRBP
Image data set for the paper: https://doi.org/10.1038/s41598-020-75994-7 Key: SF= cut marks; LS= tooth marks; tmp= trampling marks. Total images= 488 cut marks, 106 tooth marks and 63 trampling marksDataset recolectado desde DataCite con autores de la UAH. El enlace le llevará directamente a los datos originales en dicho archivo. |