BUSCADOR RECOLECTA

[ES] Base de datos con información mensual y anual de pescado comercializado en las diferentes lonjas de Catalunya, Comunitat Valenciana, Murcia, Baleares y Andalucía. Datos mensuales de cantidad, precio medio y valor total por especie ., Este base de datos se ha realizado a través del proyecto Digitalización y valorización de la pesca en el Mediterráneo español (DIGIPESCA,) financiado por el Ministerio de Agricultura, Pesca y Alimentación a través de los fondos NextGeneration UE.

This dataset includes the raw data used to carry out a long-term study on press releases from Eurekalert! The file includes python scripts used to capture web-based data, supplementary material, and raw data from Twitter and the web-at-large.

Base de datos con información mensual y anual de pescado comercializado en las diferentes lonjas de Catalunya, Comunitat Valenciana, Murcia, Baleares y Andalucía. Datos mensuales de cantidad, precio medio y valor total por especie ., Esta base de datos se ha realizado a través del proyecto Digitalización y valorización de la pesca en el Mediterráneo español (DIGIPESCA,) financiado por el Ministerio de Agricultura, Pesca y Alimentación a través de los fondos NextGeneration UE.

[EN] The data set contains the input/output data that was entered into the mathematical model to develop the case study. The data is synthetically generated and developed with an algorithm encoded in Python 3.7, the parameters for programming the algorithm are based on real data from a company in the automotive sector and the values have been structured according to the indices defined in the model. Input/output data details have been added to make the model replicable., This work was supported by the Conselleria de Educación, Investigación, Cultura y Deporte - Generalitat Valenciana for hiring predoctoral research staff with Grant (ACIF/2018/170) and European Social Fund with Grant Operational Program of FSE 2014-2020, the Valencian Community, and the authors would like to acknowledge the support of the researchers participating in the collaborative projects ‘Cloud Collaborative Manufacturing Networks’ (C2NET) (http://c2net-project.eu/), which has received funding from the EU Horizon 2020 Research and Innovation Programme with grant agreement No. 636909. “Zero Defects Manufacturing Platform” (ZDMP) (www.zdmp.eu) which has received funding from the EU Horizon 2020 Research and Innovation Programme with grant agreement No. 825631

Datasets of English and Spanish tweets used in the project "ALLEGRO: Smart multi-modal crowdsensing-based system as a service oriented to the prediction of social problems". Tweets in each dataset were manually tagged according to a specific social problem: Black Economy, Institutional Elder Abuse, Student Dropout, and Violence Against Women., Este database es parte del proyecto de I+D+i PID2020-112827GB-I00 financiado por MICIU/AEI/10.13039/501100011033.

The data were used to analyze the thrust produced by a propeller, whose operating principles are based on the conservation of linear momentum. The study was carried out on an air track to avoid frictional forces. Several system characteristics were established, such as the angle of attack and different magnitudes were determined, including the dynamic thrust. 3D CAD software was used to design the propellers for the experiments. As propulsive systems are challenging for undergraduates to understand, it is essential to design experiments that can help their visualization and testing. The development of digital technology (high-speed cameras, digital tracking software, or 3D printers) facilitates the implementation of such designs., We would like to thank the Instituto de Ciencias de la Educación (ICE) in the Universitat Politècnica de València for their help, through the Innovation and Educational Quality Program and for supporting the team Innovación en Metodologías Activas para el Aprendizaje de la Física (e-MACAFI). This work has been supported by the UPV through the Project of Innovation and Educational Improvement Program (Projects PIME/18-19/76 and PIME/22-23/309 Convocatoria de Proyectos de Innovación y Convergencia de la UPV).

Base de datos con información mensual y anual de pescado comercializado en las diferentes lonjas de Catalunya, Comunitat Valenciana, Murcia, Baleares y Andalucía. Datos mensuales de cantidad, precio medio y valor total por especie ., Esta base de datos se ha realizado a través del proyecto Digitalización y valorización de la pesca en el Mediterráneo español (DIGIPESCA,) financiado por el Ministerio de Agricultura, Pesca y Alimentación a través de los fondos NextGeneration UE.

[ES] Los datos representan los valores numéricos para la representación de la onda QRS3 de un electrocardiograma

Recopilación de datos sobre proyectos medioambientales financiados por el Fondo Europeo Marítimo y de Pesca (FEMP) y recogidos de la Red Española de Grupos de Pesca (REGP)., This work was supported by the National Plan for Scientific and Technological Research and Innovation (Spanish Economy and Competitiveness Ministry), the Research Project PID2019-105497 GB-I00, the European Fisheries Funds, opportunities for the fisheries sector through diversification, and the FLAGs management (DivPesc).

Here you will find a model of the cooling system of a PEMFC-based micro-CHP system. This model is implemented in Matlab/Simulink, version 9.3.0.713579 (R2017b). The model and the tests conducted for its development are described in detail in the following paper: Title: Control-Oriented Modeling of the Cooling Process of a PEMFC-Based micro-CHP System Authors: SANTIAGO NAVARRO GIMÉNEZ, JUAN MANUEL HERRERO DURÁ, FRANCESC XAVIER BLASCO FERRAGUD and RAÚL SIMARRO FERNÁNDEZ. Instituto Universitario de Automática e Informática Industrial Universidad Politécnica de Valencia In this folder (uCHP_Cooling_System), you will find the following files: Complete_Model_M.slx Complete_Model_V.slx Filter.m Modeling_Test.mat Parameters.mat S_Complete_Model_M.m S_Complete_Model_V.m Validation_Test.mat In both Complete_Model_M.slx and Complete_Model_V.slx you will find the implementation of the complete model in Simulink. The only difference between them is that the former is prepared for the data set from the modeling test (Modeling_Test.mat) and the latter for the data set from the modeling test (Validation_Test.mat). In order to launch the simulations, you have to run the scripts S_Complete_Model_M.m and S_Complete_Model_V.m, respectively. The file Parameters.mat contain the values of the parameters of the model. The file Filter.m is just a filter, which is used in both scripts. Please, read the comments in the scripts mentioned for more information. Thanks.