Results 101 to 110 of about 1,355 (166)

Bootstrapped Tests for Epistemic Fuzzy Data

open access: yesInternational Journal of Applied Mathematics and Computer Science
Epistemic bootstrap is a resampling algorithm that generates bootstrap real-valued samples based on some epistemic fuzzy data input. We apply this method as a universal basis for various statistical tests which can be then directly used for fuzzy random ...
Grzegorzewski Przemysław   +1 more
doaj   +1 more source

Asymptotic properties of cross‐classified sampling designs

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract We investigate the family of cross‐classified sampling designs across an arbitrary number of dimensions. We introduce a variance decomposition that enables the derivation of general asymptotic properties for these designs and the development of straightforward and asymptotically unbiased variance estimators.
Jean Rubin, Guillaume Chauvet
wiley   +1 more source

Bridging Theory and Prediction: A Hybrid SEM and Machine Learning Approach to Optimize Lean Construction for Megaproject Sustainability in China

open access: yesCorporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Construction megaprojects, large‐scale, complex, and capital‐intensive, are particularly prone to inefficiencies, cost overruns, delays, and environmental degradation due to fragmented workflows, stakeholder misalignment, and resource intensity.
Abdelazim Ibrahim   +5 more
wiley   +1 more source

Machine Learning‐Assisted Design of BaTiO3‐Based Superparaelectric High‐Entropy Ceramics with Superior Energy Storage

open access: yesENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
This study employed an adaptive iterative strategy combining machine learning algorithms, domain knowledge, experimental design, and experimental feedback to aim to precisely and quickly discover high‐entropy ceramics with excellent energy storage performance.
Haowen Liu   +4 more
wiley   +1 more source

Can epilepsy be predicted after the first febrile seizure? Insights from machine learning of postictal EEG

open access: yesEpileptic Disorders, EarlyView.
Abstract Objective Febrile seizures (FS) are the most common seizures in childhood, yet identifying children at risk of developing epilepsy after the first FS remains challenging. We aimed to evaluate the prognostic potential of machine learning (ML) algorithms applied to post‐febrile seizure electroencephalography (EEG) recordings.
Boran Şekeroğlu   +7 more
wiley   +1 more source

Fully automated three‐dimensional deep learning‐based magnetic resonance imaging segmentation of brain cavities in epilepsy surgery

open access: yesEpilepsia, EarlyView.
Abstract Objective There are several clinical and research applications for determining the amount of brain tissue resected after epilepsy surgery; however, manual segmentation of postoperative magnetic resonance imaging (MRI) is imprecise and time‐consuming.
Raphael Fernandes Casseb   +12 more
wiley   +1 more source

Development and preclinical evaluation of a hybrid stereoelectroencephalographic–laser depth electrode for magnetic resonance imaging‐guided interstitial thermal therapy in drug‐resistant epilepsy

open access: yesEpilepsia, EarlyView.
Abstract Objective This study was undertaken to design and validate a hybrid depth electrode combining stereoelectroencephalographic (sEEG) recording and magnetic resonance‐guided laser interstitial thermal therapy (MRgLITT) under real‐time magnetic resonance thermometry, to streamline the transition from invasive localization to focal ablation in ...
Bertrand Mathon   +3 more
wiley   +1 more source

Smartphone videos for infantile epileptic spasms triaging and assessment (VISTA study): Impact of education and standardized clinical history on diagnostic accuracy

open access: yesEpilepsia Open, EarlyView.
Abstract Objective Diagnostic and treatment delays in infantile epileptic spasms syndrome (IESS) increase the risk of poor neurodevelopmental outcomes. Early clinical recognition of IESS is essential, especially in regions lacking expedited access to electroencephalograms (EEG).
Christine L. Shrock   +11 more
wiley   +1 more source

Decentralized Federated Learning for Wind Turbine Bearing Prognostics Under Data Scarcity and Statistical Heterogeneity

open access: yesEnergy Science &Engineering, EarlyView.
This paper proposes a decentralized peer‐to‐peer federated learning framework for wind turbine bearing remaining useful life prediction, introducing a virtual client paradigm in which statistical health indicators serve as independent feature‐level clients—enabling privacy‐preserving collaborative prognostics from a single physical asset under ...
Jihene Sidhom   +2 more
wiley   +1 more source

Mono‐dimensional, two‐dimensional and Doppler echocardiographic measurements in healthy Standardbred neonatal foals in the first 5 days of life

open access: yesEquine Veterinary Journal, EarlyView.
Abstract Background Bodyweight, age and breed influence the echocardiographic assessment of foals. There are no echocardiographic studies in Standardbred neonatal foals. Objectives To describe echocardiographic values for selected variables, evaluate intra‐ and inter‐observer variability and assess cardiac changes in the first 5 days of life in healthy
Fernanda Timbó D'el Rey Dantas   +8 more
wiley   +1 more source

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