Listar LCC - Artículos por título
Mostrando ítems 75-94 de 161
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Fault localization in DSLTrans model transformations by combining symbolic execution and spectrum-based analysis
(Springer Nature, 2023-09-29)The verification of model transformations is important for realizing robust model-driven engineering technologies and quality-assured automation. Many approaches for checking properties of model transformations have been ... -
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 ... -
Fitness function distributions over generalized search neighborhoods in the q-ary hypercube
(2014-10-03)The frequency distribution of a fitness function over regions of its domain is an important quantity for understanding the behavior of algorithms that employ randomized sampling to search the function. In general, exactly ... -
Foreground detection by competitive learning for varying input distributions
(World Scientific Publishing, 2018)One of the most important challenges in computer vision applications is the background modeling, especially when the background is dynamic and the input distribution might not be stationary, i.e. the distribution of the ... -
Foreground detection by probabilistic modeling of the features discovered by stacked denoising autoencoders in noisy video sequences
(2019-06-07)A robust foreground detection system is presented, which is resilient to noise in video sequences. The proposed model divides each video frame in patches that are fed to a stacked denoising autoencoder, which is responsible ... -
Fotogrametría y modelado 3D: un caso práctico para la difusión del patrimonio y su promoción turística
(Facultad de Turismo, 2012) -
Fractal structure of the soliton scattering for the graphene superlattice equation
(Elsevier, 2021-10)The graphene superlattice equation, a modified sine-Gordon equation, governs the propagation of solitary electromagnetic waves in a graphene superlattice. This equation has kink solutions without explicit analytical ... -
Functions as a service for distributed deep neural network inference over the cloud-to-things continuum
(Wiley, 2024-02-11)The use of serverless computing has been gaining popularity in recent years as an alternative to traditional Cloud computing. We explore the usability and potential development benefits of three popular open-source serverless ... -
GENECI: A novel evolutionary machine learning consensus-based approach for the inference of gene regulatory networks
(Elsevier, 2023)Gene regulatory networks define the interactions between DNA products and other substances in cells. Increasing knowledge of these networks improves the level of detail with which the processes that trigger different ... -
Graph grammars with string-regulated rewriting
(Elsevier, 2011)Multicellular organisms undergo a complex developmental process, orchestrated by the genetic information in their cells, in order to form a newborn individual from a fertilized egg. This complex process, not completely ... -
How do preschoolers interact with peers? Characterising child and group behaviour in games with tangible interfaces in school
(Elsevier, 2022-09)Learning social skills is an important part of the socialisation process of children, which should occur at school, at home and in any place where children live. There are very few studies on social interaction and ... -
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 ... -
Injecting domain knowledge in multi-objective optimization problems: A semantic approach.
(Elsevier, 2021-05-15)In the field of complex problem optimization with me-taheuristics, semantics has been used for modeling different aspects, such as: problem characterization, parameters, decision-maker's preferences, or algorithms. However, ... -
Integrating Blockchain in safety-critical systems: an application to the nuclear industry
(IEEE, 2020-10)Safety-Critical Systems (SCSs) often manage sensible data that must be trustworthy, especially in many cases in which different actors participate whose interests may not coincide. Blockchain is a disruptive technology ... -
Integrating FMI and ML/AI models on the open-sourcedigital twin framework OpenTwins
(Wiley, 2024-03-24)The realm of digital twins is experiencing rapid growth and presents a wealth ofopportunities for Industry 4.0. In conjunction with traditional simulation meth-ods, digital twins offer a diverse range of possibilities. ... -
Introducing passive strategies in the initial stage of the design to reduce the energy demand in single-family dwellings.
(Elsevier, 2021-06-15)This article analyses the influence of various variables defined in the initial stage of the design of a single-family dwelling on its energy efficiency. It also studies the possible contribution of a computer tool in ... -
Kafka-ML: Connecting the data stream with ML/AI frameworks
(Elsevier, 2022-01-01)Machine Learning (ML) and Artificial Intelligence (AI) depend on data sources to train, improve, and make predictions through their algorithms. With the digital revolution and current paradigms like the Internet of Things, ... -
KNIT: Ontology reusability through knowledge graph exploration
(Elsevier, 2023)Ontologies have become a standard for knowledge representation across several domains. In Life Sciences, numerous ontologies have been introduced to represent human knowledge, often providing overlapping or conflicting ... -
Learning Multi-Party Adversarial Encryption and Its Application to Secret Sharing
(2022-11)Neural networks based cryptography has seen a significant growth since the introduction of adversarial cryptography which makes use of Generative Adversarial Networks (GANs) to build neural networks that can learn encryption. ... -
Low Disruption Transformations on Cyclic Automata
(IOS Press, 2010)We extend the edit operators of substitution, deletion, and insertion of a symbol over a word by introducing two new operators (partial copy and partial elimination) inspired by biological gene duplication. We define a ...