jealousy
发表于 2025-3-23 09:49:07
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conspicuous
发表于 2025-3-23 14:50:13
to the statutory buy-out of the Lords Proprietors in 1729. In doing so, it adopts the now fashionable “Atlantic” perspective on events and behavior.. But, it does not track the movement of people to a “New World,” the environment of which purportedly compelled social and cultural adaptation on thei
meditation
发表于 2025-3-23 18:25:05
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幻影
发表于 2025-3-24 02:01:04
Thomas Frick,Stefan Glüge,Abbas Rahimi,Luca Benini,Thomas Brunschwilernd statistics.Includes both classic and recent results on co.The purpose of this book is to provide an overview of historical and recent results on concentration inequalities for sums of independent random variables and for martingales..The first chapter is devoted to classical asymptotic results in
向外供接触
发表于 2025-3-24 06:02:22
Conference proceedings 2021nference and 10 full papers from two workshops on medical artificial intelligence and on digital healthcare technologies. The conference papers are organized in topical sections on wearable technologies; health telemetry; mobile sensing and assessment; machine learning in eHealth applications..
HAVOC
发表于 2025-3-24 07:26:04
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喃喃诉苦
发表于 2025-3-24 13:42:18
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Aprope
发表于 2025-3-24 18:26:30
Design of a Mobile-Based Neurological Assessment Tool for Aging Populationsefits of cognitive interference (e.g., the addition of outside stimuli that intrude on task-related activity) on a user’s task performance. Understanding the population’s usability requirements and their performance on configured tasks allows for the formation of usable and objective neurocognitive assessments.
outset
发表于 2025-3-24 20:37:02
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窒息
发表于 2025-3-25 00:58:27
Patient-Independent Schizophrenia Relapse Prediction Using Mobile Sensor Based Daily Behavioral Rhyton time, for example by detecting early behavioral changes in patients, then interventions could be provided to prevent the relapse. In this work, we investigated a machine learning based schizophrenia relapse prediction model using mobile sensing data to characterize behavioral features. A patient-