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SOPRENE: Assessment of the Spanish Armada’s Predictive Maintenance Tool for Naval Assets
(MDPI, 2021)
[Abstract] Predictive maintenance has lately proved to be a useful tool for optimizing costs, performance and systems availability. Furthermore, the greater and more complex the system, the higher the benefit but also the ...
Machine Learning Based Moored Ship Movement Prediction
(MDPI, 2021)
[Abstract] Several port authorities are involved in the R+D+i projects for developing port management decision-making tools. We recorded the movements of 46 ships in the Outer Port of Punta Langosteira (A Coruña, Spain) ...
A decision-making tool for port operations based on downtime risk and met-ocean conditions including infragravity wave forecast
(MDPI, 2023)
[Abstract:] Port downtime leads to economic losses and reductions in safety levels. This problem is generally assessed in terms of uni-variable thresholds, despite its multidimensional nature. The aim of the present study ...
Digital Image Quality Prediction System
(MDPI AG, 2020-08-19)
[Abstract]
“A picture is worth a thousand words.” Based on this well-known adage, we can say that images are important in our society, and increasingly so. Currently, the Internet is the main channel of socialization and ...
Machine Learning Techniques to Predict Different Levels of Hospital Care of CoVid-19
(Springer, 2022)
[Abstract] In this study, we analyze the capability of several state of the art machine learning methods to predict whether patients diagnosed with CoVid-19 (CoronaVirus disease 2019) will need different levels of hospital ...
New machine learning approaches for real-life human activity recognition using smartphone sensor-based data
(Elsevier B.V., 2023)
[Abstract]: In recent years, mainly due to the application of smartphones in this area, research in human activity recognition (HAR) has shown a continuous and steady growth. Thanks to its wide range of sensors, its size, ...
Fast deep autoencoder for federated learning
(Elsevier Ltd, 2023-11)
[Abstract]: This paper presents a novel, fast and privacy preserving implementation of deep autoencoders. DAEF (Deep AutoEncoder for Federated learning), unlike traditional neural networks, trains a deep autoencoder network ...
Machine learning classification models for fetal skeletal development performance prediction using maternal bone metabolic proteins in goats
(PeerJ, 2019-10)
[Abstract]:
Background
In developing countries, maternal undernutrition is the major intrauterine environmental factor contributing to fetal development and adverse pregnancy outcomes. Maternal nutrition restriction ...
MATEO: intermolecular α-amidoalkylation theoretical enantioselectivity optimization. Online tool for selection and design of chiral catalysts and products
(BMC, 2024-01-23)
[Absctract]: The enantioselective Brønsted acid-catalyzed α-amidoalkylation reaction is a useful procedure is for the production of new drugs and natural products. In this context, Chiral Phosphoric Acid (CPA) catalysts ...
Hybrid machine learning techniques in the management of harmful algal blooms impact
(Elsevier, 2023)
[Abstract]: Harmful algal blooms (HABs) are episodes of high concentrations of algae that are potentially toxic for human consumption. Mollusc farming can be affected by HABs because, as filter feeders, they can accumulate ...