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RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/66212
Set de datos (Dataset). 2022

CODE AND DATA OF THE ARTICLE TARGET INDUCTIVE METHODS FOR ZERO-SHOT REGRESSION

  • Fernández Díaz, Miriam
  • Quevedo Pérez, José Ramón|||0000-0001-7211-4312
  • Montañés Roces, Elena|||0000-0003-0609-8945
Code and data of the article: Target inductive methods for zero-shot regression https://doi.org/10.1016/j.ins.2022.03.075

Proyecto: //
DOI: http://hdl.handle.net/10651/66212, https://dx.doi.org/10.17811/ruo_datasets.66212
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/66212
HANDLE: http://hdl.handle.net/10651/66212, https://dx.doi.org/10.17811/ruo_datasets.66212
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/66212
PMID: http://hdl.handle.net/10651/66212, https://dx.doi.org/10.17811/ruo_datasets.66212
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/66212
Ver en: http://hdl.handle.net/10651/66212, https://dx.doi.org/10.17811/ruo_datasets.66212
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/66212

RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/70832
Set de datos (Dataset). 2019

DATA FROM "HETEROGENEOUS TREE STRUCTURE CLASSIFICATION TO LABEL JAVA PROGRAMMERS ACCORDING TO THEIR EXPERTISE LEVEL"

  • Ortín Soler, Francisco|||0000-0003-1199-8649
  • Rodríguez Prieto, Óscar|||0000-0003-2168-9962
  • Pascual, Nicolás
  • García Rodríguez, Miguel|||0000-0002-3150-2826
Data from the article "F. Ortin, O. Rodriguez-Prieto, N. Pascual, M. Garcia. Heterogeneous tree structure classification to label Java programmers according to their expertise level. Future Generation Computer Systems (105), pp. 380-394, 2020. https://doi.org/10.1016/j.future.2019.12.016", Open-source code repositories are a valuable asset to creating different kinds of tools and services, utilizing machine learning and probabilistic reasoning. Syntactic models process Abstract Syntax Trees (AST) of source code to build systems capable of predicting different software properties. The main difficulty of building such models comes from the heterogeneous and compound structures of ASTs, and that traditional machine learning algorithms require instances to be represented as n-dimensional vectors rather than trees. In this article, we propose a new approach to classify ASTs using traditional supervised-learning algorithms, where a feature learning process selects the most representative syntax patterns for the child subtrees of different syntax constructs. Those syntax patterns are used to enrich the context information of each AST, allowing the classification of compound heterogeneous tree structures. The proposed approach is applied to the problem of labeling the expertise level of Java programmers. The system is able to label expert and novice programs with an average accuracy of 99.6%. Moreover, other code fragments such as types, fields, methods, statements and expressions could also be classified, with average accuracies of 99.5%, 91.4%, 95.2%, 88.3% and 78.1%, respectively., This work has been partially funded by the Spanish Department of Science, Innovation and Universities: project RTI2018-099235-B-I00. The authors have also received funds from the University of Oviedo through its support of official research groups (GR-2011-0040).

Proyecto: //
DOI: https://hdl.handle.net/10651/70832, https://dx.doi.org/10.17811/ruo_datasets.70832
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/70832
HANDLE: https://hdl.handle.net/10651/70832, https://dx.doi.org/10.17811/ruo_datasets.70832
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/70832
PMID: https://hdl.handle.net/10651/70832, https://dx.doi.org/10.17811/ruo_datasets.70832
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/70832
Ver en: https://hdl.handle.net/10651/70832, https://dx.doi.org/10.17811/ruo_datasets.70832
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/70832

RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/79021
Set de datos (Dataset). 2024

DATA DOCUMENTATION FOR: UNPRECEDENTED FORMAL INSERTION OF A METAL CARBENE COMPLEX INTO A Σ-CARBON-CARBON BOND. GOLD-CATALYZED SYNTHESIS OF 3H-INDOLES

  • Allegue González, Dario|||0000-0001-8681-861X
  • Sampedro, Diego
  • Ballesteros Gimeno, Alfredo|||0000-0003-2093-4444
  • Santamaría Victorero, Javier|||0000-0001-6369-4183

Proyecto: //
DOI: https://hdl.handle.net/10651/79021, https://dx.doi.org/10.17811/ruo_datasets.79021
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/79021
HANDLE: https://hdl.handle.net/10651/79021, https://dx.doi.org/10.17811/ruo_datasets.79021
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/79021
PMID: https://hdl.handle.net/10651/79021, https://dx.doi.org/10.17811/ruo_datasets.79021
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/79021
Ver en: https://hdl.handle.net/10651/79021, https://dx.doi.org/10.17811/ruo_datasets.79021
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/79021

RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/70831
Set de datos (Dataset). 2018

DATA FROM "RULE-BASED PROGRAM SPECIALIZATION TO OPTIMIZE GRADUALLY TYPED CODE"

  • Ortín Soler, Francisco|||0000-0003-1199-8649
  • García Rodríguez, Miguel|||0000-0002-3150-2826
  • McSweeney, Seán
Data from the article "F. Ortin, M. Garcia, S. McSweeney. Rule-based program specialization to optimize gradually typed code. Knowledge-Based Systems (179), pp. 145-173, 2019. https://doi.org/10.1016/j.knosys.2019.05.013", Both static and dynamic typing provide different benefits to the programmer. Statically typed languages support earlier type error detection and more opportunities for compiler optimizations. Dynamically typed languages facilitate the development of runtime adaptable applications and rapid prototyping. Since both approaches provide benefits, gradually typed languages support both typing approaches in the very same programming language. Gradual typing has been an active research field in the last years, turning out to be a strong influence on commercial languages. However, one important drawback of gradual typing is the runtime performance cost of the additional type checks performed at runtime. In this article, we propose a rule-based program specialization mechanism to provide significant performance optimizations of gradually typed code. Our system gathers dynamic type information of the application by simulating its execution. That type information is used to optimize the generated code, reducing the number of type checks performed at runtime. Moreover, program specialization allows the early detection of compile-time type errors, providing static type safety. To ensure the correctness of the proposed approach, we prove its soundness and efficiency properties. The specialization system has been implemented as part of a full-fledged programming language, measuring the runtime performance gain. The generated code performs significantly better than the state-of-theart techniques to optimize dynamically typed code. Unlike the existing approaches, our system does not consume additional memory resources at runtime, because program specialization is performed statically. Program specialization involves an average compilation time increase from 2% to 11.75%., This work has been partially funded by the Spanish Department of Science, Innovation and Universities: project RTI2018-099235-B-I00. The authors have also received funds from the Banco Santander, Spain through its support of the Campus of International Excellence

Proyecto: //
DOI: https://hdl.handle.net/10651/70831, https://dx.doi.org/10.17811/ruo_datasets.70831
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/70831
HANDLE: https://hdl.handle.net/10651/70831, https://dx.doi.org/10.17811/ruo_datasets.70831
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/70831
PMID: https://hdl.handle.net/10651/70831, https://dx.doi.org/10.17811/ruo_datasets.70831
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/70831
Ver en: https://hdl.handle.net/10651/70831, https://dx.doi.org/10.17811/ruo_datasets.70831
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/70831

RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/80003
Set de datos (Dataset). 2023

DATA FROM "OPTIMAL POSITION OF AIR PURIFIERS IN ELEVATOR CABINS FOR THE IMPROVEMENT OF THEIR VENTILATION EFFECTIVENESS"

  • Santamaría Bertolín, Luis
  • Fernández Oro, Jesús Manuel
  • Argüelles Díaz, Katia
  • Galdo Vega, Mónica
  • Velarde Suárez, Sandra

Proyecto: //
DOI: https://hdl.handle.net/10651/80003, https://dx.doi.org/10.17811/ruo_datasets.80003
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/80003
HANDLE: https://hdl.handle.net/10651/80003, https://dx.doi.org/10.17811/ruo_datasets.80003
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/80003
PMID: https://hdl.handle.net/10651/80003, https://dx.doi.org/10.17811/ruo_datasets.80003
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/80003
Ver en: https://hdl.handle.net/10651/80003, https://dx.doi.org/10.17811/ruo_datasets.80003
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/80003

RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/74584
Set de datos (Dataset). 2024

ALTITUDINAL VARIATION IN REPRODUCTIVE INVESTMENT AMONG GRYLLUS CAMPESTRIS POPULATIONS

  • Martínez Viejo, David
  • Rodríguez-Muñoz, Rolando|||0000-0002-6067-845X
  • Fernández-Ojanguren García-Comas, Alfredo|||0000-0001-6273-1122

Proyecto: //
DOI: https://hdl.handle.net/10651/74584, https://dx.doi.org/10.17811/ruo_datasets.74584
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/74584
HANDLE: https://hdl.handle.net/10651/74584, https://dx.doi.org/10.17811/ruo_datasets.74584
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/74584
PMID: https://hdl.handle.net/10651/74584, https://dx.doi.org/10.17811/ruo_datasets.74584
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/74584
Ver en: https://hdl.handle.net/10651/74584, https://dx.doi.org/10.17811/ruo_datasets.74584
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/74584

RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/65292
Set de datos (Dataset). 2022

ANEXOS DEL ARTÍCULO. FORMACIÓN LABORAL DE LOS TRABAJADORES EN ESPAÑA. EVOLUCIÓN DURANTE EL PERÍODO DE CRISIS Y RECUPERACIÓN ECONÓMICA (2007-2016)

  • García Espejo, María Isabel|||0000-0002-7944-3175
  • Ibáñez Pascual, Marta|||0000-0001-5185-7467

Proyecto: //
DOI: http://hdl.handle.net/10651/65292, https://dx.doi.org/10.17811/ruo_datasets.65292
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/65292
HANDLE: http://hdl.handle.net/10651/65292, https://dx.doi.org/10.17811/ruo_datasets.65292
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/65292
PMID: http://hdl.handle.net/10651/65292, https://dx.doi.org/10.17811/ruo_datasets.65292
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/65292
Ver en: http://hdl.handle.net/10651/65292, https://dx.doi.org/10.17811/ruo_datasets.65292
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/65292

RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/81915
Set de datos (Dataset). 2022

DATASET FOR SWEVO 2022: GREEN JOB SHOP SCHEDULING WITH UNCERTAIN TIMES

  • Afsar, Sezin|||0000-0002-3096-4674
  • Palacios Alonso, Juan José|||0000-0002-0479-1490
  • Puente Peinador, Jorge|||0000-0001-6840-3939
  • Rodríguez Vela, María del Camino|||0000-0001-9271-2360
  • González Rodríguez, Inés|||0000-0003-3266-009X
This dataset is directly associated with the article “Multi-objective enhanced memetic algorithm for green job shop scheduling with uncertain times” (Swarm and Evolutionary Computation, 2022) and contains the complete set of benchmark instances and experimental results reported in the publication., This dataset contains benchmark problem instances and detailed experimental results associated with the SWEVO 2022 article on green job shop scheduling with uncertain times. It includes the solved instances used in the experimental evaluation and the corresponding numerical results, provided both in the original spreadsheet format and in interoperable CSV files (one per instance). The dataset has been archived to support transparency, reproducibility and reuse of the experimental evidence reported in the associated publication., This research has been supported by the Spanish Government under research grants TIN2016-79190-R and PID2019-106263RB-I00, and by the Principality of Asturias Government under grant IDI/2018/000176.

Proyecto: //
DOI: https://hdl.handle.net/10651/81915, https://dx.doi.org/10.17811/ruo_datasets.81915
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/81915
HANDLE: https://hdl.handle.net/10651/81915, https://dx.doi.org/10.17811/ruo_datasets.81915
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/81915
PMID: https://hdl.handle.net/10651/81915, https://dx.doi.org/10.17811/ruo_datasets.81915
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/81915
Ver en: https://hdl.handle.net/10651/81915, https://dx.doi.org/10.17811/ruo_datasets.81915
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/81915

RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/79191
Set de datos (Dataset). 2025

V-BAND SCATTERED FIELD MEASUREMENTS IN 8 DIFFERENT PLANES WITH AN L-SHAPED MULTISTATIC CONFIGURATION

  • Hoyo Vijande, Alejandro del|||0009-0003-2399-2428
  • Álvarez López, Yuri
  • Laviada Martínez, Jaime
  • Las Heras Andrés, Fernando Luis
In addition to the files containing the scattered field measurements, a PDF file with the schematic of the measurement setup is included, as well as a sample code written in MATLAB. This code applies SAR processing based on the measurements from one of the planes and aims to demonstrate how to import one of the files and process the data to generate a reflectivity image of the region of interest., This dataset contains samples of the scattered field from a set of flat metallic objects. It includes several files corresponding to eight different measurement planes, where the distances between the plane containing the antennas and the plane containing the targets are 74.3913 cm, 66.4120 cm, 61.4173 cm, 56.4063 cm, 51.4131 cm, 46.3873 cm, 41.4244 cm, and 36.4289 cm. The measurement setup corresponds to a multistatic L-shaped configuration. Two open-ended waveguides were used as antennas, which were moved along the two sides of the L using two high-precision rails to transmit (Tx) and receive (Rx) signals from different positions in the acquisition array. For each Tx-Rx channel, a total of 201 equally spaced measurements of the S21 parameter were taken between 55 GHz and 60 GHz using a PNA-X device. In addition to the measurements with the metallic targets, the dataset includes two measurements with aluminum foil covering the support structure and two background measurements conducted using the same structure but without the targets. These background measurements in planes one and eight can be used to eliminate clutter caused by various environmental reflections.

Proyecto: //
DOI: https://hdl.handle.net/10651/79191, https://dx.doi.org/10.17811/ruo_datasets.79191
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/79191
HANDLE: https://hdl.handle.net/10651/79191, https://dx.doi.org/10.17811/ruo_datasets.79191
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/79191
PMID: https://hdl.handle.net/10651/79191, https://dx.doi.org/10.17811/ruo_datasets.79191
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/79191
Ver en: https://hdl.handle.net/10651/79191, https://dx.doi.org/10.17811/ruo_datasets.79191
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/79191

RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/80843
Set de datos (Dataset). 2025

DATA FOR "THICKNESS DEPENDENT RARE EARTH SEGREGATION IN MAGNETRON DEPOSITED NDCO

_{4.6}

  • Díaz Fernández, Javier Ignacio
  • Rodríguez Fernández, Jonathan|||0000-0001-9448-6328
  • Rubio Zuazo, Juan
Data contains readme file with an explanation to localize specific data. Three sets of data: Xray Photoemission data Magnetic Hysteresis loops data Xray Reflectivity data, The magnetic anisotropy of amorphous NdCo$_{4.6}$ compounds deposited by magnetron sputtering change with film thickness from in plane to out of plane anisotropy at thickness above 40 nm. Xray reflectivity measurements shows the progressive formation of an additional layer in between the 3 nm thick Si capping layer and the NdCo compound film. Hard Xray Photoemission spectroscoy (HAXPES) was used to analyze the composition and distribution of cobalt and neodymium at the top layers region of NdCo$_{4.6}$ films of thickness ranging from 5 nm to 65 nm using 7 keV, 10 keV and 13 keV incident photon energies, with inelastic electron mean free paths ranging from 7.2 nm to 12.3 nm in cobalt. The atomic cobalt concentration of the alloy deduced from HAXPES measurements at the Nd 3d and Co 2p excitations results to be below the nominal value, changing with thickness and incident photon energy. This proves a segregation of the rare earth at the surface of the NdCo$_{4.6}$ thin film which increases with thickness. The analysis of the background of the Co 2p and Nd 3d peaks was consistent with this conclusion. This demonstrates that neodymium incorporation in the cobalt lattice have a cost in energy which can be associated to strain due to the difference in volume between the two elements. The lowering of this strain energy will favor atomic anisotropic environments for neodymium that explains the perpendicular anisotropy and its thickness dependence of these NdCo compound films., European Synchrotron ESRF, the Spanish Ministerio de Ciencia, Innovacion y Universidades, and the Consejo Superior de Investigaciones Científicas for provision of synchrotron radiation at BM25 and for financial support through the projects PIE 2010-6-0E-013, 2021-60-E-030 and CEX2024-001445-S. J. D. and J. R-F. acknowledges Spanish Minister of Science and Innovation support under grants 104604RB/AEI/10.13039/501100011033 and PID2022-136784NB and by Agencia SEKUENS (Asturias) under grant UONANO IDE/2024/000678 with the support of FEDER funds

Proyecto: //
DOI: https://hdl.handle.net/10651/80843, https://dx.doi.org/10.17811/ruo_datasets.80843
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/80843
HANDLE: https://hdl.handle.net/10651/80843, https://dx.doi.org/10.17811/ruo_datasets.80843
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/80843
PMID: https://hdl.handle.net/10651/80843, https://dx.doi.org/10.17811/ruo_datasets.80843
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/80843
Ver en: https://hdl.handle.net/10651/80843, https://dx.doi.org/10.17811/ruo_datasets.80843
RUO. Repositorio Institucional de la Universidad de Oviedo
oai:digibuo.uniovi.es:10651/80843

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