Lenguajes y Ciencias de la Computación - (LCC)
Estas son las colecciones en las que puede catalogar la producción investigadora del departamento Lenguajes y Ciencias de la Computación. Si considera que ninguna de estas se ajusta a su material pida una nueva colección en la sección de sugerencias.
Colecciones en esta comunidad
Envíos recientes
-
Modelado del proceso de compra del consumidor final en los ecosistemas digitales mediante técnicas de inteligencia computacional.
(UMA Editorial, 2022)La accesibilidad a la información ha provocado un cambio de paradigma en las interacciones entre empresas y consumidores. Esto ha hecho que el conocimiento acerca de los públicos se convierta en una pieza clave para ... -
Walk-IT: An Open-Source Modular Low-Cost Smart Rollator
(IOAP-MPDI, 2022-03-08)Rollators are widely used in clinical rehabilitation for gait assessment, but gait analysis usually requires a great deal of expertise and focus from medical staff. Smart rollators can capture gait parameters autonomously ... -
Multi-objective dynamic programming with limited precision
(Springer, 2021-11-02)This paper addresses the problem of approximating the set of all solutions for Multi-objective Markov Decision Processes. We show that in the vast majority of interesting cases, the number of solutions is exponential or ... -
Capping methods for the automatic configuration of optimization algorithms
(Elsevier, 2022-03)Automatic configuration techniques are widely and successfully used to find good parameter settings for optimization algorithms. Configuration is costly, because it is necessary to evaluate many configurations on different ... -
FIMED: Flexible management of biomedical data
(Elsevier, 2021-11)Background and objectives: In the last decade, clinical trial management systems have become an essential support tool for data management and analysis in clinical research. However, these clinical tools have design ... -
Metaheuristics on quantum computers: Inspiration, simulation and real execution
(ELSEVIER, 22-05)Quantum-inspired metaheuristics are solvers that incorporate principles inspired from quantum mechanics into classical-approximate algorithms using non-quantum machines. Due to the uniqueness of quantum principles, the ... -
Road pollution estimation from vehicle tracking in surveillance videos by deep convolutional neural networks
(ELSEVIER, 2021-12)Air quality and reduction of emissions in the transport sector are determinant factors in achieving a sustainable global climate. The monitoring of emissions in traffic routes can help to improve route planning and to ... -
Semantic modelling of Earth Observation remote sensing
(ELSEVIER, 2022-01)Earth Observation (EO) based on Remote Sensing (RS) is gaining importance nowadays, since it offers a well-grounded technological framework for the development of advanced applications in multiple domains, such as climate ... -
TITAN: A knowledge-based platform for Big Data workflow management
(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. ... -
A takeover time-driven adaptive evolutionary algorithm for mobile user tracking in pre-5G cellular networks
(ELSEVIER, 2022-02)Cellular networks are one of today’s most popular means of communication. This fact has made the mobile phone industry subject to a huge scientific and economic competition, where the quality of service is key. Such a ... -
Using machine learning techniques for architectural design tracking: an experimental study of the design of a shelter
(Elsevier, 2022)In this paper, we present a study aimed at tracking and analysing the design process. More concretely, we intend to explore whether some elements of the conceptual design stage in architecture might have an influence on ... -
Improved detection of small objects in road network sequences using CNN and super resolution
(2021)The detection of small objects is one of the problems present in deep learning due to the context of the scene or the low number of pixels of the objects to be detected. According to these problems, current pre-trained ... -
Adaptive music: Automated music composition and distribution
(UMA Editorial, 2021-12-20)La creatividad, o la habilidad de producir nuevas y útiles ideas, es comúnmente asociada al ser humano; pero hay muchos otros ejemplos en la naturaleza donde se puede observar este fenómeno. Inspirado por esto, en ingeniería ... -
Desarrollo de microservicios basado en la especificación OpenAPI
(2021)En los últimos años, a la hora de desarrollar infraestructuras de altas prestaciones las arquitecturas orientadas a microservicio se están posicionando como el paradigma predominante. En el corazón de estas arquitecturas, ... -
Development of artificial neural network-based object detection algorithms for low-cost hardware devices
(UMA Editorial, 2021-12-01)The human brain is the most complex, powerful and versatile learning machine ever known. Consequently, many scientists of various disciplines are fascinated by its structures and information processing methods. Due to the ... -
Modelos de predicción de crisis financieras internacionales con técnicas de aprendizaje automático: aplicaciones a la reputación país
(UMA Editorial, 2021-11-10)El presente estudio ha escogido tres de los tipos más importantes de crisis tratadas en las finanzas internacionales: la crisis de deuda soberana, la crisis de divisas y la crisis sistémica bancaria. Por tanto, se trata ... -
Energy-efficient Deployment of IoT Applications in Edge-based Infrastructures: A Software Product Line Approach
(2021-09)In order to lower latency and reduce energy consumption, Edge Computing proposes offloading some computation intensive tasks usually performed in the Cloud onto nearby devices in the frontier/Edge of the access networks. ... -
Hierarchical Color Quantization with a Neural Gas Model Based on Bregman Divergences
(Springer, 2021-09)In this paper, a new color quantization method based on a self-organized artificial neural network called the Growing Hierarchical Bregman Neural Gas (GHBNG) is proposed. This neural network is based on Bregman divergences, ... -
Peer assessments in Engineering: A pilot project
(2021)The evaluation methods employed in a course are the most important point for the students, above any other learning aspect. For teachers, this task is arduous when the number of students is high. Traditional evaluation ... -
Longitudinal study of the learning styles evolution in Engineering degrees
(2021)A learning style describes what are the predominant skills for learning tasks. In the context of university education, knowing the learning styles of the students constitutes a great opportunity to improve both teaching ...