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Alterations of the center of pressures in the greater trochanter pain syndrome: evaluation of pelvitrochanteric injuries through dynamic baropodometry
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Estudio e implementación del método EAP-NOOB para autenticación en redes
Full text linkProporcionar una base para comunicaciones seguras en Internet es, claramente, un objetivo importante. Más aún, dada la heterogeneidad de dispositivos y redes con diferentes capacidades, así como los nuevos casos de uso, como son el Internet de las Cosas. Esto promueve el estudio de nuevos métodos de autenticación con capacidad de escalar los despliegues.
Este TFG, propone el estudio y la implementación de un protocolo de autenticación extensible llamado EAP-NOOB, por su interés, su operación de autenticación fuera de banda, y su diseño pensado para el Internet de las Cosas.
Opcionalmente, se estudiará la optimización del protocolo o la aplicación de este en diferentes casos de uso
Energy-scaling behavior of intrinsic transverse-momentum parameters in drell-yan simulation
No full textMatrotrophy and polyandry partially regulate postcopulatory mechanisms and sexual selection in a bimodal viviparous salamander
Full text linkThis work was supported by National Funds through FCT—Foundation for Science and Technology (Portugal) (SALOMICS: PTDC/BIA-EVL/28475/2017 and ANTHROPOPHIBIAN: PTDC/BIA-CBI/2278/2020). G. V.-A. was supported by a Ramón y Cajal research grant (Ref. RYC-2019-026959-I/AEI/https://doi.org/10.13039/501100011033). L. A.-R. was supported by a Margarita Salas contract funded by the European Union-NextGenerationEU, Recuperation, Transformation and Resilience Plan by Spanish Ministry of Universities, on the basis of the University of Oviedo (Spain) call, Ref: MU-21-UP2021-030
Genome-wide patterns of diversity in the european midwife toad complex: phylogeographic and conservation prospects
No full textDual lamellar keratoplasty combined with phacoemulsification and intraocular lens implantation in a case of severe chemical burn
No full textLesión de la rampa meniscal: diagnóstico, clasificación, concordancia inter-observador y correlación quirúrgica
Full text linkTesis doctoral por compendio de publicacione
PLangRec: Deep-learning model to predict the programming language from a single line of code
Full text linkbeen addressed with machine learning and natural language processing. Identifying the language of short code
snippets poses both benefits and challenges across various scenarios, such as embedded code analysis, forums,
Q&A systems, search engines, source code repositories, and text editors. Existing approaches for language
detection typically require multiple lines or even the entire file contents. In this article, we propose a characterlevel deep learning model designed to predict the programming language from a single line of code. To this
aim, we construct a balanced dataset comprising 434.18 million instances across 21 languages, significantly
exceeding the size of existing datasets by three orders of magnitude. Leveraging this dataset, we train a deep
bidirectional recurrent neural network that achieves a 95.07% accuracy and macro-F1
score for a single-line
code. To predict the programming language of multiple lines (e.g., code snippets) and entire files, we build
a stacking ensemble meta-model that leverages our single-line model to efficiently recognize the language
of multiple lines of code. Our system outperforms the state-of-the-art approaches not only for a single line
of code, but also for snippets of 5 and 10 lines and whole files of source code. We also present PLangRec,
an open-source language detection system that includes our trained models. PLangRec is freely available as a
user-friendly web application, a web API, and a Python desktop programThis work has been partially funded by the Spanish Department of Science, Innovation and Universities: project RTI2018-099235-B-I00.
We have also received funds from the University of Oviedo, Spain through its support of official research groups (GR-2011-0040). Project GRU-GIC-24-070 from the Government of the Principality of Asturias,
funded by the European Regional Development Fund (ERDF)
Delegation of Power and Committee Procedure (Chapter XI)
Full text linkAEI, Ministerio de Ciencia, Innovación y Universidades; Cofinanciado por la Unión Europea