Výsledky vyhledávání - "Hopkinson Andrew"

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KIDS: kinematics-based (in)activity detection and segmentation in a sleep case study

Autor: Elnaggar, Omar, Arelhi, Roselina, Coenen, Frans, Hopkinson, Andrew, Mason, Lyndon, Paoletti, Paolo

Sleep behaviour and in-bed movements contain rich information on the neurophysiological health of people, and have a direct link to the general well-being and quality of life. Standard clinical practices rely on polysomnography for sleep assessment;

Externí odkaz: http://arxiv.org/abs/2301.03469

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Sleep Posture One-Shot Learning Framework Using Kinematic Data Augmentation: In-Silico and In-Vivo Case Studies

Autor: Elnaggar, Omar, Coenen, Frans, Hopkinson, Andrew, Mason, Lyndon, Paoletti, Paolo

Sleep posture is linked to several health conditions such as nocturnal cramps and more serious musculoskeletal issues. However, in-clinic sleep assessments are often limited to vital signs (e.g. brain waves). Wearable sensors with embedded inertial m

Externí odkaz: http://arxiv.org/abs/2205.10778

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Akademický článek

Comparative transcriptional profiling of the limbal epithelial crypt demonstrates its putative stem cell niche characteristics

Autor: Shanmuganathan Vijay A, Hopkinson Andrew, Powe Desmond G, Yeung Aaron M, Mohammed Imran, Tighe Patrick J, Kulkarni Bina B, Dua Harminder S

Publikováno v: BMC Genomics, Vol 11, Iss 1, p 526 (2010)

Abstract Background The Limbal epithelial crypt (LEC) is a solid cord of cells, approximately 120 microns long. It arises from the undersurface of interpalisade rete ridges of the limbal palisades of Vogt and extends deeper into the limbal stroma par

Externí odkaz: https://doaj.org/article/bfe04cc2e13e4f5484cfd11a751667b8

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Akademický článek

Sleep posture one-shot learning framework based on extremity joint kinematics: In-silico and in-vivo case studies

Autor: Elnaggar, Omar, Coenen, Frans, Hopkinson, Andrew, Mason, Lyndon, Paoletti, Paolo

Publikováno v: In Information Fusion July 2023 95:215-236

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Demand-Weighted Completeness Prediction for a Knowledge Base

Autor: Hopkinson, Andrew, Gurdasani, Amit, Palfrey, Dave, Mittal, Arpit

In this paper we introduce the notion of Demand-Weighted Completeness, allowing estimation of the completeness of a knowledge base with respect to how it is used. Defining an entity by its classes, we employ usage data to predict the distribution ove

Externí odkaz: http://arxiv.org/abs/1804.11109

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