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  <title>accedaCRIS</title>
  <link rel="alternate" href="https://accedacris.ulpgc.es:443" />
  <subtitle>The accedaCRIS digital repository system captures, stores, indexes, preserves, and distributes digital research material.</subtitle>
  <id>https://accedacris.ulpgc.es:443</id>
  <updated>2026-03-06T00:22:10Z</updated>
  <dc:date>2026-03-06T00:22:10Z</dc:date>
  <entry>
    <title>Dataset generated in "ANN-based surrogate model for the structural evaluation of jacket support structures for offshore wind turbines"</title>
    <link rel="alternate" href="https://accedacris.ulpgc.es/jspui/handle/10553/159960" />
    <author>
      <name>Quevedo-Reina, Román</name>
    </author>
    <author>
      <name>Álamo, Guillermo</name>
    </author>
    <author>
      <name>Aznárez, Juan José</name>
    </author>
    <id>https://accedacris.ulpgc.es/jspui/handle/10553/159960</id>
    <updated>2026-03-05T20:30:29Z</updated>
    <published>2025-01-01T00:00:00Z</published>
    <summary type="text">Title: Dataset generated in "ANN-based surrogate model for the structural evaluation of jacket support structures for offshore wind turbines"
Authors: Quevedo-Reina, Román; Álamo, Guillermo; Aznárez, Juan José
Description: &amp;lt;p&amp;gt;This repository contains the train and test datasets used in the following scientific articles:&amp;lt;/p&amp;gt;
&amp;lt;ul&amp;gt;
&amp;lt;li&amp;gt;"ANN-based surrogate model for the structural evaluation of jacket support structures for offshore wind turbines" by Rom&amp;aacute;n Quevedo-Reina, Guillermo M. &amp;Aacute;lamo, Juan J. Azn&amp;aacute;rez&amp;lt;br&amp;gt;(https://doi.org/10.1016/j.oceaneng.2024.119984)&amp;lt;/li&amp;gt;
&amp;lt;li&amp;gt;"Feasibility analysis of jacket support structures for offshore wind turbines employing a regression-based artificial neural network model" by Rom&amp;aacute;n Quevedo-Reina, Guillermo M. &amp;Aacute;lamo, Juan J. Azn&amp;aacute;rez &amp;lt;br&amp;gt;(https://doi.org/10.1016/j.compstruc.2025.108004)&amp;lt;/li&amp;gt;
&amp;lt;/ul&amp;gt;
&amp;lt;p&amp;gt;This dataset was used to train the artifficial neural networks described in the papers above and available at:&amp;lt;/p&amp;gt;
&amp;lt;ul&amp;gt;
&amp;lt;li&amp;gt;https://doi.org/10.5281/zenodo.15132439&amp;lt;/li&amp;gt;
&amp;lt;li&amp;gt;https://doi.org/10.5281/zenodo.15166283&amp;lt;/li&amp;gt;
&amp;lt;/ul&amp;gt;; &amp;lt;p&amp;gt;The datasets are available in two formats: ".mat" (MATLAB file) and ".csv" (comma-separated values).&amp;lt;/p&amp;gt;
&amp;lt;p&amp;gt;The table contains the following details:&amp;lt;/p&amp;gt;
&amp;lt;ul&amp;gt;
&amp;lt;li&amp;gt;Each row represents a single sample.&amp;lt;/li&amp;gt;
&amp;lt;li&amp;gt;The matrix has 105 columns, corresponding to the 74 input variables and 31 outputs of the structural model, all of them described in the cited scientific article.&amp;lt;/li&amp;gt;
&amp;lt;/ul&amp;gt;</summary>
    <dc:date>2025-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>La enfermera en su rol de gestión. Aproximación a una Zona Básica de Salud</title>
    <link rel="alternate" href="https://accedacris.ulpgc.es/jspui/handle/10553/159958" />
    <author>
      <name>Suárez-Diaz, Mª Eugenia</name>
    </author>
    <author>
      <name>Pacheco-López, Mª Carmen</name>
    </author>
    <author>
      <name>Montesdeoca-Ramírez, Daniela Celia</name>
    </author>
    <id>https://accedacris.ulpgc.es/jspui/handle/10553/159958</id>
    <updated>2026-03-05T20:30:29Z</updated>
    <published>2022-01-01T00:00:00Z</published>
    <summary type="text">Title: La enfermera en su rol de gestión. Aproximación a una Zona Básica de Salud
Authors: Suárez-Diaz, Mª Eugenia; Pacheco-López, Mª Carmen; Montesdeoca-Ramírez, Daniela Celia
Description: &amp;lt;p&amp;gt;Material docente relacionado con la asignatura 42413- Cuidados Enfermeros en Atenci&amp;oacute;n Primaria de la Salud. Seminario impartido el 24 de octubre de 2022&amp;lt;/p&amp;gt;</summary>
    <dc:date>2022-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Mechanical data of the compression tests conducted in "Novel piezoelectric nanostructured composite scaffolds for bone regeneration by additive manufacturing" (PID2020-117648RB-I00)</title>
    <link rel="alternate" href="https://accedacris.ulpgc.es/jspui/handle/10553/159959" />
    <author>
      <name>Donate, Ricardo</name>
    </author>
    <author>
      <name>Quintana, Álvaro</name>
    </author>
    <author>
      <name>Paz, Rubén</name>
    </author>
    <author>
      <name>Moriche, Rocío</name>
    </author>
    <author>
      <name>Sayagués, María Jesús</name>
    </author>
    <author>
      <name>Monzón, Mario</name>
    </author>
    <id>https://accedacris.ulpgc.es/jspui/handle/10553/159959</id>
    <updated>2026-03-05T20:30:29Z</updated>
    <published>2025-01-01T00:00:00Z</published>
    <summary type="text">Title: Mechanical data of the compression tests conducted in "Novel piezoelectric nanostructured composite scaffolds for bone regeneration by additive manufacturing" (PID2020-117648RB-I00)
Authors: Donate, Ricardo; Quintana, Álvaro; Paz, Rubén; Moriche, Rocío; Sayagués, María Jesús; Monzón, Mario</summary>
    <dc:date>2025-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>IDSEM dataset: Source code – v1.0.0.</title>
    <link rel="alternate" href="https://accedacris.ulpgc.es/jspui/handle/10553/159961" />
    <author>
      <name>Javier Sánchez</name>
    </author>
    <author>
      <name>Agustín Salgado</name>
    </author>
    <author>
      <name>Alejandro García</name>
    </author>
    <id>https://accedacris.ulpgc.es/jspui/handle/10553/159961</id>
    <updated>2026-03-05T20:30:29Z</updated>
    <published>2022-01-01T00:00:00Z</published>
    <summary type="text">Title: IDSEM dataset: Source code – v1.0.0.
Authors: Javier Sánchez; Agustín Salgado; Alejandro García
Description: &amp;lt;p&amp;gt;Code for the IDSEM dataset, first version. IDSEM is an acronym for &amp;quot;an Invoices Database of the Spanish&amp;nbsp;Electricity Market&amp;quot;&amp;lt;/p&amp;gt;

&amp;lt;p&amp;gt;This database contains electricity bills related to energy consumption in Spanish households. &amp;nbsp;The contents of bills are automatically generated using this code. The main purpose of the dataset is for training machine learning algorithms, especially for designing new methods for extracting information from invoices. There are 86 different labels, which are related to several topics, such as the customer and marketer, the contract, energy consumption, or billing.&amp;lt;/p&amp;gt;

&amp;lt;p&amp;gt;The code relies on a set of dictionaries and template documents for generating many&amp;nbsp;training and test samples. The file format of invoices is&amp;nbsp;PDF and the labels are stored in JSON files.&amp;lt;/p&amp;gt;

&amp;lt;p&amp;gt;More information can be found at https://idsem.ulpgc.es/ and in the following article:&amp;lt;/p&amp;gt;

&amp;lt;p&amp;gt;[1] Javier S&amp;aacute;nchez, Agust&amp;iacute;n Salgado, Alejandro Garc&amp;iacute;a, and Nelson Monz&amp;oacute;n, &amp;quot;IDSEM, an invoices database of the Spanish electricity market&amp;quot;, Sci. Data, (2022).&amp;lt;/p&amp;gt;

&amp;lt;p&amp;gt;&amp;lt;strong&amp;gt;Full Changelog&amp;lt;/strong&amp;gt;: &amp;lt;a href="https://github.com/jsanchezperez/idsem/commits/v1.0.0"&amp;gt;https://github.com/jsanchezperez/idsem/commits/v1.0.0&amp;lt;/a&amp;gt;&amp;lt;/p&amp;gt;</summary>
    <dc:date>2022-01-01T00:00:00Z</dc:date>
  </entry>
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