Listar Lenguajes y Ciencias de la Computación - (LCC) por título
Mostrando ítems 140-159 de 675
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C-Mantec: A novel constructive neural network algorithm incorporating competition between neurons.
(Elsevier, 2011-10-18)C-Mantec is a novel neural network constructive algorithm that combines competition between neurons with a stable modified perceptron learning rule. The neuron learning is governed by the thermal perceptron rule that ... -
A Capacity-enhanced local search for the 5G cell switch-off problem
(2020-03-06)Network densification with deployments of many small base stations (SBSs) is a key enabler technology for the fifth generation (5G) cellular networks, and it is also clearly in conflict with one of the target design ... -
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 ... -
The cartography of computational search spaces
(2018-05-04)This talk will present our recent findings and visual (static and animated) maps characterising combinatorial and computer program search spaces. We seek to lay the foundations for a new perspective to understand problem ... -
Caso de uso: Empleo de tecnologías J2EE para el desarrollo de una plataforma para la gestión tecnológica
(2004)En esta presentación se pretende explicar la experiencia que ha supuesto el desarrollo de una plataforma para la gestión de ofertas y demandas tecnológicas, desarrollada para dos organismos dependientes de la Consejería ... -
Checking Business Process Evolution
(2017-06-01)A business process is a collection of structured activities producing a particular product or software. BPMN is a workflow-based graphical notation for specifying business processes. Formally analyzing such processes is ... -
Ciencia, tecnología y biomimética: la innovación está ahí fuera
(2013-12-10)Ponencia oral sobre las aplicaciones de la Biomimética en la innovación industrial. El vídeo de la charla está disponible en http://www.youtube.com/watch?v=gw1_rfSnwag -
Classification of high dimensional data using LASSO ensembles
The estimation of multivariable predictors with good performance in high dimensional settings is a crucial task in biomedical contexts. Usually, solutions based on the application of a single machine ... -
Classifying resilience approaches for protecting smart grids against cyber threats
(Springer, 2022-05-06)Smart grids (SG) draw the attention of cyber attackers due to their vulnerabilities, which are caused by the usage of heterogeneous communication technologies and their distributed nature. While preventing or detecting ... -
Clinical text classification in Cancer Real-World Data in Spanish
(2023-06-29)Healthcare systems currently store a large amount of clinical data, mostly unstructured textual information, such as electronic health records (EHRs). Manually extracting valuable information from these documents is costly ... -
CMSA algorithm for solving the prioritized pairwise test data generation problem in software product lines.
(2020-11-10)In Software Product Lines, it may be difficult or even impossible to test all the products of the family because of the large number of valid feature combinations that may exist (Ferrer et al. in: Squillero, Sim (eds) ... -
CMSA para el problema de la generación de casos de prueba priorizados en líneas de productos software
(2018-09-24)En las líneas de producto software puede ser difícil o incluso imposible probar todos los productos de la familia debido al gran número de combinaciones de características que puede existir. Esto conlleva la necesidad de ... -
Color Space Selection for Self-Organizing Map Based Foreground Detection in Video Sequences
(2014-07-18)The selection of the best color space is a fundamental task in detecting foreground objects on scenes. In many situations, especially on dynamic backgrounds, neither grayscale nor RGB color spaces represent the best solution ... -
Combining multiple granularity variability in a software product line approach for web engineering
(Elsevier, 2022-08)Context: Web engineering involves managing a high diversity of artifacts implemented in different languages and with different levels of granularity. Technological companies usually implement variable artifacts of Software ... -
Combining OCL and Natural Language: a Call for a Community Effort
(ACM, 2022-10)The growing popularity and availability of pretrained natural language models opens the door to many interesting applications combining natural language (NL) with software artefacts. A couple of examples are the generation ... -
Combining user preferences and expert opinions: a criteria synergy-based model for decision making on the Web
(Springer-Verlag, 2019)Customers strongly base their e-commerce decisions on the opinions of others by checking reviews and ratings provided by other users. These assessments are overall opinions about the product or service, and it is not ... -
Comparación de marcos de trabajo de Aprendizaje Profundo para la detección de objetos
(2018-11-08)Muchas aplicaciones en visión por computador necesitan de sistemas de detección precisos y eficientes. Esta demanda coincide con el auge de la aplicación de técnicas de aprendizaje profundo en casi todos las áreas del ... -
Comparative analysis of classical multi-objective evolutionary algorithms and seeding strategies for pairwise testing of Software Product Lines
(2014-10-06)Software Product Lines (SPLs) are families of related software products, each with its own set of feature combinations. Their commonly large number of products poses a unique set of challenges for software testing as it ... -
Comparative structural analysis of the drought responsive dehydrin and aquaporin gene families in Brachypodium and close grasses
(2019-09-10)Dehydrins (DHNs) belong to the group 2 LEA (Late Embryogenesis Abundant) genes and play an important role in the response of plants to abiotic stress, mainly heat, salinity and drought. Under these stresses, DHNs accumulate ... -
Comparing Deep Recurrent Networks Based on the MAE Random Sampling, a First Approach
(2018-11-26)Recurrent neural networks have demonstrated to be good at tackling prediction problems, however due to their high sensitivity to hyper-parameter configuration, finding an appropriate network is a tough task. Automatic ...