Titlebook: Hybrid Artificial Intelligent Systems; 17th International C Pablo García Bringas,Hilde Pérez García,Emilio Cor Conference proceedings 2022

FLIT

Smartwatch Sleep-Tracking Services Precision Evaluation Using Supervised Domain Adaptation accuracy of the sleep stages labels were obtained with the study smartwatch SleepApp. The proposed method is based on the supervised domain adaptation paradigm, where the source domain is the sleep dataset (SrcDataset) obtained with the smartwatch used in the pilot (SrcWatch), and the target domain

Original

Frailty Related Survival Risks at?Short and?Middle Term of?Older Adults Admitted to?Hospitalonally, we compute Cox regression for these censoring times over patient variables selected by independent sample t-test and logistic regression. We confirm that frailty predicts greater mortality at all censoring times. Significant hazard risks (HRs) identified in frail cohort were sex, age, weight

jumble

On the?Analysis of?a?Real Dataset of?COVID-19 Patients in?Alavaof the principal component analysis (PCA) and Logistic Regression (LR) techniques to find out which variables are the most relevant and their respective weight. The results show that there are two very relevant variables for the detection of the most severe cases, yielding promissing results. One of

蟄伏

alabaster

Measuring the?Quality Information of?Sources of?Cybersecurity by?Multi-Criteria Decision Making Techrces through the usual records received in a cybersecurity incident response team. The study was carried out over a real dataset containing . cybersecurity event records, 27 sources, and 55 types of cybersecurity events. From the results, we have performed the diagnosis identifying those data aspect

set598

https://doi.org/10.1007/978-3-031-15471-3hybrid intelligent systems; artificial intelligence; machine learning; computer vision; algorithims; data

推崇

978-3-031-15470-6Springer Nature Switzerland AG 2022

Ambiguous

Hybrid Artificial Intelligent Systems978-3-031-15471-3Series ISSN 0302-9743 Series E-ISSN 1611-3349

元音

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