Lenguajes y Ciencias de la Computación - (LCC): Envíos recientes
Mostrando ítems 1-20 de 707
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Ontology-driven automated reasoning about property crimes
Navarrete, Francisco; Garrido, Ángel L.; Bobed, Carlos; Atencia-Arcas, Manuel
; Vallecillo-Moreno, Antonio Jesús (Springer, 2024)
The classification of police reports according to the typification of the criminal act described in them is not an easy task. The reports are written in natural language and often present missing, imprecise, or even ... -
Yekta: A low-code framework for automated test models generation
Karimi, Meysam; Kolahdouz-Rahimi, Shekoufeh; Troya-Castilla, Javier (Elsevier, 2024)
The methodology under the term model-based software engineering (MBSE) gained importance already around 20 years ago, after the publication of the Model-Driven Architecture (MDA) initiative by the Object Management Group ... -
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’ ... -
Enhanced Cellular Detection Using Convolutional Neural Networks and Sliding Window Super-Resolution Inference.
García Aguilar, Iván; Rostyslav, Zavoiko; Fernández-Rodríguez, Jose David; Luque-Baena, Rafael Marcos; López-Rubio, Ezequiel (Springer, 2024)
Histopathology currently serves as the standard for breast cancer diagnosis, but its manual execution demands time and expertise from pathologists. Artificial intelligence, particularly in digital pathology, has made ... -
Prediction of Optimal Locations for 5G Base Stations in Urban Environments Using Neural Networks and Satellite Image Analysis.
García Aguilar, Iván; Galeano-Brajones, Jesús; Luna-Valero, Francisco; Carmona Murillo, Javier; Fernández-Rodríguez, Jose David; Luque-Baena, Rafael Marcos[et al.] (Springer, 2024)
Deploying 5G networks in urban areas is crucial for meeting the increasing demand for high-speed, low-latency wireless communications. However, the complex topography and diverse building structures in urban environments ... -
Multi-objective context-guided consensus of a massive array oftechniques for the inference of Gene Regulatory Networks
Segura Ortiz, Adrián; García-Nieto, José Manuel; Aldana-Montes, José Francisco; Navas-Delgado, Ismael (Elsevier, 2024-07-15)
Background and Objective: Gene Regulatory Network (GRN) inference is a fundamental task in biology and medicine, as it enables a deeper understanding of the intricate mechanisms of gene expression present in organisms. ... -
Aprendizaje automático para la detección de inicio/fin de la marcha mediante dos sensores inerciales y modelado de datos usando aprendizaje profundo.
(UMA Editorial, 2024)Los médicos utilizan extensamente el análisis de la marcha para detectar anormalidades y determinar posibles tratamientos para los pacientes. El análisis de la marcha tiene diversas aplicaciones, que incluyen la identificación ... -
Data mining process to detect suicidal behaviour in out-of-hospital emergency departments
Del-Campo-Ávila, José; Ramos Martín, Javier; Gómez-Sánchez-Lafuente, Carlos; García-Pedrosa, Johanna; García-Martín, Saúl; Martínez-García, Ana I.; Guzmán-Parra, José; Morales-Bueno, Rafael; Moreno-Kustner, Berta[et al.] (Elsevier, 2024-07-13)
Out-of-hospital emergency departments receive multiple types of requests daily. Their management requires a balance to be found between available resources and the actual needs of the requesting party. Those regarding ... -
Intelligent Testing of Traffic Light Programs: Validation in Smart Mobility Scenarios.
Ferrer-Urbano, Francisco Javier; García-Nieto, José Manuel; Alba-Torres, Enrique; Chicano-García, José-Francisco (Wiley, 2016-02-08)
In smart cities, the use of intelligent automatic techniques to find efficient cycle programs of traffic lights is becoming an innovative front for traffic flow management. However, this automatic programming of traffic ... -
Exploiting medical-expert knowledge via a novel memetic algorithm for the inference of gene regulatory networks.
This study introduces an innovative memetic algorithm for optimizing the consensus of well-adapted techniques for the inference of gene regulation networks. Building on the methodology of a previous proposal (GENECI), this ... -
Using energy consumption for self-adaptation in FaaS.
Serrano Gutiérrez, Pablo; Ayala-Viñas, Inmaculada (Springer Nature, 2024)
One of the programming models that has been developing the most in recent years is Function as a Service (FaaS). The growing concern over data centre energy footprints has driven sustainable software development. In ... -
Polyglot software development: wait, what?
Mussbacher, Gunter; Combemale, Benoit; Kienzle, Jörg; Burgueño-Caballero, Lola; Garcia-Dominguez, Antonio; Jézéquel, Jean-Marc; Jouneaux, Gwendal; Khelladi, Djamel-Eddine; Mosser, Sébastien; Pulgar, Corinne; Sahraoui, Houari; Schiedermeier, Maximilian; Storm, Tijs van der[et al.] (IEEE, 2024)
We propose a concise and unambiguous definition of polyglot software development with a conceptual model and characterize the techniques used for the specification and operationalization of polyglot software development ... -
Análisis y evaluación de procesos de desarrollo en empresas como actividad docente y evaluativa.
Álvarez-Palomo, José María (2024)
El estudiantado de grados de Ingeniería Informática y relacionados no suele tener experiencia en el desarrollo de sistemas medianos o grandes, lo que provoca que no sea consciente de los problemas a los que se enfrentarán ... -
Mitigating Carlini & Wagner attacks with Encoding Generative Adversarial Network.
Tell-Gónzalez, Guillermo; Fernández-Rodríguez, Jose David; Molina-Cabello, Miguel Ángel; Benítez-Rochel, Rafaela; López-Rubio, Ezequiel (2024)
Deep Learning models are experiencing a significant surge in popularity, expanding into various domains, including critical applications like object recognition in autonomous vehicles, where any failure could have fatal ... -
Online learning and continuous model upgrading with data streams through the Kafka-ML framework
Carnero Hijano, Alejandro; Martín-Fernández, Cristian; Jeon, Gwanggil; Díaz-Rodríguez, Manuel (Elsevier, 2024)
A pipeline of constant data streams is being built by the Internet of Things (IoT) to monitor information about the physical environment. In parallel, Artificial Intelligence (AI) is constantly developing and enhancing ... -
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 ... -
Deep Learning-Based Attack Detection and Classification in Android Devices.
Gómez Alfonso, Bernardo; Muñoz-Gallego, Antonio Jesús (MDPI, 2023-07-28)
The increasing proliferation of Androidbased devices, which currently dominate the market with a staggering 72% global market share, has made them a prime target for attackers. Consequently, the detection of Android ... -
Evolutionary Algorithms for Optimizing Emergency Exit Placement in Indoor Environments.
Cotta-Porras, Carlos; Gallardo-Ruiz, José Enrique (Springer Nature, 2024)
The problem of finding the optimal placement of emergency exits in an indoor environment to facilitate the rapid and orderly evacuation of crowds is addressed in this work. A cellular-automaton model is used to simulate ... -
Regression of the Rician Noise Level in 3D Magnetic Resonance Images from the Distribution of the First Significant Digit.
Maza-Quiroga, Rosa; Thurnhofer-Hemsi, Karl; López-Rodríguez, Domingo; López-Rubio, Ezequiel (MDPI, 2023-12-13)
This paper investigates the distribution characteristics of Fourier, discrete cosine, and discrete sine transform coefficients in T1 MRI images. The study reveals their adherence to Benford’s law, characterized by a ... -
Rician noise estimation for 3D Magnetic Resonance Images based on Benford's Law.
Maza Quiroga, Rosa María; Thurnhofer-Hemsi, Karl; López-Rodríguez, Domingo; López-Rubio, Ezequiel (Springer Nature, 2021)
In this paper, a novel method to estimate the level of Rician noise in magnetic resonance images is presented. We hypothesize that noiseless images follow Benford's law, that is, the probability distribution of the first ...