Zobrazeno 1 - 10
of 4 412
pro vyhledávání: '"A. P. Dickens"'
Autor:
S. M. Martins, R. Adams, E. M. Rodrigues, R. Stelmach, P. Adab, C. Chi, K. K. Cheng, B. G. Cooper, J. Correia-de-Sousa, A. P. Dickens, A. Enocson, A. Farley, N. Gale, K. Jolly, R. E. Jordan, S. Jowett, M. Maglakelidze, T. Maghlakelidze, A. Sitch, K. Stavrikj, A. M. Turner, S. Williams, V. B. Nascimento
Publikováno v:
npj Primary Care Respiratory Medicine, Vol 34, Iss 1, Pp 1-10 (2024)
Abstract Physical activity (PA) improves dyspnoea, psychological wellbeing and quality of life (QoL) for people with COPD reducing their risk of exacerbation. However, engagement in PA is low especially amongst those with anxiety and depression, and
Externí odkaz:
https://doaj.org/article/e0f30fdd9a5e4a6592f3a7fcd6f0663f
Autor:
S. M. Martins, A. P. Dickens, W. Salibe-Filho, A. A. Albuquerque Neto, P. Adab, A. Enocson, B. G. Cooper, L. V. A. Sousa, A. J. Sitch, S. Jowett, R. Adams, K. K. Cheng, C. Chi, J. Correia-de-Sousa, A. Farley, N. Gale, K. Jolly, M. Maglakelidze, T. Maghlakelidze, K. Stavrikj, A. M. Turner, S. Williams, R. E. Jordan, R. Stelmach
Publikováno v:
npj Primary Care Respiratory Medicine, Vol 32, Iss 1, Pp 1-10 (2022)
Abstract In Brazil, prevalence of diagnosed COPD among adults aged 40 years and over is 16% although over 70% of cases remain undiagnosed. Hypertension is common and well-recorded in primary care, and frequently co-exists with COPD because of common
Externí odkaz:
https://doaj.org/article/6dc3044aaf554352a6361a674c140693
Given that AI systems are set to play a pivotal role in future decision-making processes, their trustworthiness and reliability are of critical concern. Due to their scale and complexity, modern AI systems resist direct interpretation, and alternativ
Externí odkaz:
http://arxiv.org/abs/2409.13919
A spring in parallel with an effort source (e.g., electric motor or human muscle) can reduce its energy consumption and effort (i.e., torque or force) depending on the spring stiffness, spring preload, and actuation task. However, selecting the sprin
Externí odkaz:
http://arxiv.org/abs/2409.08889
Autor:
Tayal, Anuja, Di Eugenio, Barbara, Salunke, Devika, Boyd, Andrew D., Dickens, Carolyn A, Abril, Eulalia P, Garcia-Bedoya, Olga, Allen-Meares, Paula G
We propose a dialogue system that enables heart failure patients to inquire about salt content in foods and help them monitor and reduce salt intake. Addressing the lack of specific datasets for food-based salt content inquiries, we develop a templat
Externí odkaz:
http://arxiv.org/abs/2404.01182
Cooking recipes are one of the most readily available kinds of procedural text. They consist of natural language instructions that can be challenging to interpret. In this paper, we propose a model to identify relevant information from recipes and ge
Externí odkaz:
http://arxiv.org/abs/2401.12088
Understanding procedural texts, such as cooking recipes, is essential for enabling machines to follow instructions and reason about tasks, a key aspect of intelligent reasoning. In cooking, these instructions can be interpreted as a series of modific
Externí odkaz:
http://arxiv.org/abs/2401.06930
Autor:
Lim, Jue Tao, Bansal, Somya, Chong, Chee Seng, Dickens, Borame, Ng, Youming, Deng, Lu, Lee, Caleb, Tan, Li Yun, Chain, Grace, Ma, Pei, Sim, Shuzhen, Tan, Cheong Huat, Cook, Alex R, Ng, Lee Ching
In a study conducted in Singapore, a country prone to dengue outbreaks due to its climate and urban population, researchers examined the effectiveness of releasing male Aedes aegypti mosquitoes infected with Wolbachia (wAlbB strain) to reduce dengue
Externí odkaz:
http://arxiv.org/abs/2311.09754
Whilst cooking is a very important human activity, there has been little consideration given to how we can formalize recipes for use in a reasoning framework. We address this need by proposing a graphical formalization that captures the comestibles (
Externí odkaz:
http://arxiv.org/abs/2306.09042
Autor:
Zhu, Jiong, Reganti, Aishwarya, Huang, Edward, Dickens, Charles, Rao, Nikhil, Subbian, Karthik, Koutra, Danai
Distributed training of GNNs enables learning on massive graphs (e.g., social and e-commerce networks) that exceed the storage and computational capacity of a single machine. To reach performance comparable to centralized training, distributed framew
Externí odkaz:
http://arxiv.org/abs/2305.09887