Listar LCC - Artículos por título
Mostrando ítems 207-226 de 239
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Teaching compilers: automatic question generation and intelligent assessment of grammars' Parsing
Conejo-Muñoz, Ricardo José
; Barros-Blanco, Beatriz; Del-Campo-Ávila, José; Triviño-Rodríguez, José Luis (IEEE, 2024)
Automatic question generation and the assessment of procedural knowledge is still a challenging research topic. This article focuses on the case of it, the techniques of parsing grammars for compiler construction. There ... -
A temporal difference method for multi-objective reinforcement learning
This work describes MPQ-learning, an temporal-difference method that approximates the set of all non-dominated policies in multi-objective Markov decision problems, where rewards are vectors and each component stands for ... -
The Benefits of Blockchain Technology for Medical Tourism
Tyan, Inessa; Guevara-Plaza, Antonio; Yague-Valle, María Inmaculada (MDPI, 2021-11)
The paper discusses the benefits of blockchain technology for medical tourism. The major focus is placed on pre-procedure and post-procedure of medical tourism. The authors argue that blockchain technology can facilitate ... -
The competitive balance of UEFA and CONMEBOL football leagues: on managing the number of teams in league design
Triguero-Ruiz, Francisco Andrés; Ávila-Cano, Antonio Jesús (Wiley, 2024-01-07)
This article augments the literature on the analysis of competitive balance, encompassing its measurement, comparisons across leagues and seasons, and ramifications for league management. Central to our examination is the ... -
The component model for elementary landscapes and partial neighborhoods
Whitley, L. Darrell; Sutton, Andrew M.; Ochoa, Gabriela; Chicano-García, José-Francisco (2014-09-29)
Local search algorithms exploit moves on an adjacency graph of the search space. An “elementary landscape” exists if the objective function f is an eigenfunction of the Laplacian of the graph induced by the neighborhood ... -
The effect of downsampling-upsampling strategy on foreground detection algorithms
Molina-Cabello, Miguel Ángel; García-González, Jorge; Luque-Baena, Rafael Marcos; López-Rubio, Ezequiel (Springer Nature, 2020)
In video surveillance systems which incorporate stationary cameras, the first phase of movement object detection is crucial for the correct modelling of the behavior of these objects, as well as being the most complex in ... -
The forbidden region self-organizing map neural network
Self-organizing maps are aimed to learn a representation of the input distribution which faithfully describes the topological relations among the clusters of the distribution. For some datasets and applications, it is known ... -
The Internet of Cooperative Agents Architecture (X-IoCA) for Robots, Hybrid Sensor Networks, and MEC Centers in Complex Environments: A Search and Rescue Case Study
Bravo-Arrabal, Juan; Toscano-Moreno, Manuel; Fernández-Lozano, Juan Jesús; Mandow, Anthony; Gómez-Ruiz, José Antonio; García-Cerezo, Alfonso José[et al.] (MPDI, 2021)
Cloud robotics exploits the Internet of things (IoT) for the convergence of shared infrastructure and services for robotics, ranging from using computational resources in the cloud (infrastructure as a service, IaaS) to ... -
The orchestration of Machine Learning frameworks with datastreams and GPU acceleration in Kafka-ML: A deep-learning performance comparative
Machine Learning (ML) applications need large volumes of data to train their modelsso that they can make high-quality predictions. Given digital revolution enablers suchas the Internet of Things (IoT) and the Industry 4.0, ... -
The software project scheduling problem: A scalability analysis of multi-objective metaheuristics
Luna, Francisco; González-Álvarez, David L.; Chicano-García, José-Francisco; Vega-Rodríguez, Miguel A. (2014-10-02)
Computer aided techniques for scheduling software projects are a crucial step in the software development process within the highly competitive software industry. The Software Project Scheduling (SPS) problem relates to ... -
The use of observations of soft X-rays and protons in the UMASEP scheme for making real-time predictions of the SEP events that took place in july and september 2017
Núñez-Paz, Marlon (IOAP-MDPI, 2022-01-07)
The prediction of solar energetic particle (SEP) events may help to improve the mitigation of adverse effects on humans and technology in space. UMASEP (University of Málaga Solar particle Event Predictor) is an empirical ... -
Time series features and fuzzy memberships combination for time series classification
(Elsevier, 2024)Time series classification is an increasingly attractive field with the appearance of new problems in an expanding digitalized world. Most of the proposals in the state-of-the-art have focused just on improving the results’ ... -
TITAN: A knowledge-based platform for Big Data workflow management
Benítez-Hidalgo, Antonio; Barba-González, Cristóbal; Gutiérrez-Moncayo, Pedro; Paneque, Manuel; Nebro-Urbaneja, Antonio Jesús; Roldán-García, María del Mar; Aldana-Montes, José Francisco; Navas-Delgado, Ismael[et al.] (ELSEVIER, 2021-11-28)
Modern applications of Big Data are transcending from being scalable solutions of data processing and analysis, to now provide advanced functionalities with the ability to exploit and understand the underpinning knowledge. ... -
Toward a Framework for Cost-Effective and Publicly Verifiable Confidential Computations in Blockchain
Morales, Daniel; Agudo-Ruiz, Isaac; López-Muñoz, Francisco Javier (IEEE Xplore, 2024)
Blockchain technologies have introduced a compelling paradigm for a new understanding of security through decentralized networks and consensus mechanisms. However, they need all data to be public, which may be unacceptable ... -
Towards an ontology-driven clinical experience sharing ecosystem: demonstration with liver cases
Roldán-García, María del Mar; Uskudarli, Suzan; Marvasti, Neda B.; Acar, Burak; Aldana-Montes, José Francisco (ELSEVIER, 2018)
Past medical cases, hence clinical experience, are invaluable resources in supporting clinical practice, research, and education. Medical professionals need to be able to exchange information about patient cases and explore ... -
Towards standarized benchmarks of LLMs in software modeling tasks: a conceptual framework
Cámara-Moreno, Javier; Burgueño-Caballero, Lola; Troya-Castilla, Javier (Springer, 2024-09-03)
The integration of Large Language Models (LLMs) in software modeling tasks presents both opportunities and challenges. This Expert Voice addresses a significant gap in the evaluation of these models, advocating for the ... -
Transforming numerical feature models into propositional formulas and the universal variability language
Muñoz-Guerra, Daniel Jesús; Pinto-Alarcón, Mónica; Fuentes-Fernández, Lidia; Batory, Don (Elsevier, 2023)
Real-world Software Product Lines (SPLs) need Numerical Feature Models (NFMs) whose features have not only boolean values that satisfy boolean constraints but also have numeric attributes that satisfy arithmetic constraints. ... -
Trust interoperability in the Internet of Things
Fernández-Gago, María del Carmen; Ferraris, Davide; Román-Castro, Rodrigo; López-Muñoz, Francisco Javier (Elsevier, 2024)
The Internet of Things (IoT) is a paradigm where entities or things are interconnected, often in heterogeneous contexts. As the interconnection happens, things establish collaborations with others, sometimes under uncertainty. ... -
TrUStAPIS: a trust requirements elicitation method for IoT
Ferraris, Davide; Fernández-Gago, María del Carmen (Springer Link, 2020-02-01)
The internet of things (IoT) is an environment of interconnected entities, which are identifiable, usable and controllable via the Internet. Trust is useful for a system such as the IoT as the entities involved would like ... -
URSUS_UHI: URban SUStainability software for detection of unfavourable areas due to the Urban Heat Island effect
Rodríguez-Gómez, Francisco; Del-Campo-Ávila, José; López-Rodríguez, Domingo; Pérez-Urrestarazu, Luis (Elsevier, 2025)
Identifying the most unfavourable areas of cities, in terms of high temperatures and lack of vegetation, can help to improve urban sustainability and combat climate change. URSUS_UHI is a software that could help make ...