Resultados de investigación

Base de datos en el programa Excel sobre las publicaciones relacionadas con el bronceado y la fotoprevención solar que fueron descargados de la red social Twitter -ahora X-.

Número y valor de las primeras propiedades registradas con títulos posesorios y absolutos (1863-1944)

The FireCCI project is part of the European Space Agency's (ESA) Climate Change Initiative (CCI) programme. The project focuses on the Fire Disturbance Essential Climate Variable(ECV) and specifically on 'Burned Area' (BA) products. The main objective of the FireCCI project is the development and improvement of the burned area detection algorithms, including the product validation protocols. The FireCCI project has developed several global BA products: FireCCI31 and FireCCI41 based on MERIS data, FireCCI50 and the last version FireCCI51 based on MODIS data at 250 m spatial resolution (Chuvieco, et al., 2018; Lizundia-Loiola, et al., 2020). In addition, high resolution BA products have been produced for regional or continental scale (e.g. FireCCISFD11 (Roteta, et al., 2019) based on Sentinel-2 data, for Sub-Saharan Africa at 20 m spatial resolution, and FireCCIS1SA10 (Belenguer-Plomer, et al., 2019) derived from Sentinel-1 for 2017 for the Amazon basin in South America). Moreover, the FireCCI project has promoted the research on BA validation methodologies generating statistically rigorous protocols to implement the accuracy assessment of BA product according the CEOS LPVS stage 3 validation requeriments (Padilla, et al., 2014; 2015; 2017). As a result of this research and the BA product validation activities, several global and regional burned area reference datasets were generated and compiled to create a Burned Area Reference Database (BARD) for validation. Contributions from other international projects and researches as CONUS Landsat Burned Area, and NOFFI, have significantly increased the BARD database.

3. Descripción del proyecto

CoMetaS establishes a network of interdisciplinary research groups to solve, through collaborative research and training, a new scientific and technological challenge of high practical interest for industry. The scientific and technological overall objective is to develop an integrated, reliable and efficient multiscale methodology for Concurrent Metamaterial-Structure Design employing functionally graded mechanical metamaterials (MMs).

4. Descripción del dataset

This folder contains the results asociated with the WP1 of the project Marie Sklodowska-Curie Grant Agreement No. 101007815.

METODOLOGÍA

1. Metolodogía (empleada para la recogida o generación de los datos)

Struts of Ti6Al4V were additively manufactured using selective laser melting. Then some lattice structures were printed with different unit cells and strut diameters. The defects produced in the lattice structures during the AM process were studied by optical microscope and SEM. Finally static test of this lattice structures were done in a universal testing machine.

Este dataset se enmarca dentro del trabajo "Creación de un Modelo de Descripciones de Imágenes Especializado en Arqueología Griega". Un modelo de descripción de imágenes especializado en arqueología griega, que combina técnicas avanzadas de Computer Vision y Natural Language Processing para generar descripciones más precisas y contextualizadas en un ámbito altamente especializado. El proyecto abre la puerta a nuevas aplicaciones de la IA en el estudio, documentación y divulgación del patrimonio cultural.

This dataset was collected during a quasi-experimental study involving 161 secondary school students (aged 14) from Madrid, Spain. The objective was to evaluate the impact of three programming environments—Scratch (2D), Scratch with Kibotics (3D robotics simulation), and Python with Kibotics—on the development of Computational Thinking (CT) skills. The data includes pre-test and post-test scores based on a validated CT assessment instrument, as well as programming exam scores and item-level data related to CT subskills (loops, conditionals, functions, etc.). Gender, platform, and programming language are also included as independent variables for analysis. The study also explores the effect of these tools on reducing gender gaps in CT education. The dataset is anonymized and includes both raw scores and normalized results (0–10 scale). It can be used to reproduce the statistical analysis of the study, to conduct further research in STEM education, or to test machine learning models for educational data mining.

Assessment of the food (pulses) self-sufficiency supply capacity in the Comunidad de Madrid (Spain) with different dietary and distribution scenarios. The dataset is detailed at the municipal level, providing the number of people in each municipality that could meet their food (pulses) needs considering a) the average legume intake and b) the dietary recommendation and with two different distribution models: a) Centralizaed in the capital city, b) descentralized

This dataset contains six files and a descriptive readme.txt. For this study data was gathered from secondary school students, teachers and families in four European countries (Spain, Italy, Romania, and Lithuania). The study aimed to compare these bilingual education stakeholders’ attitudes towards bilingual education across these regions. This contrast was meant to contribute to the ultimate goal of learning about bilingual education from different countries and sociolinguistic contexts. Three Excel files contain the data gathered. The other three contain the variables.

This dataset contains the data related to the article "Adoption and Impact of ChatGPT in Computer Science Education: A Case Study on a Database Administration Course" available at https://arxiv.org/abs/2407.12145. This dataset contains data of 37 computer science students. The file contains the grades of the students and the results of questionnaire. All data was anonymized so that the identity of the participants cannot be ascertained. The aforementioned article can be openly accessed at https://arxiv.org/abs/2407.12145

Este dataset se enmarca dentro del proyecto: "Análisis de aplicaciones móviles desde la perspectiva de la protección de datos: Ciberprotección y Ciber-riesgos de la información de la ciudadanía" Los objetivos son la creación de un Dataset que detalla las características esenciales para poder construir modelos predictivos para la detección de exposición de privacidad de datos. Cada elemento del Dataset desglosa las actividades posibles en cada una de las redes sociales sujetas al análisis en los experimentos por cada sujeto. La generación del dataset toma como elemento de partida el corpus de licencias de uso y términos de servicio en inglés y castellano disponible en doi:10.21950/YSG7FQ.