Zobrazeno 1 - 10
of 530
pro vyhledávání: '"Chris D, Nugent"'
Publikováno v:
Intelligent Systems with Applications, Vol 18, Iss , Pp 200215- (2023)
Computer networks form much of the infrastructure supporting day-to-day life in this digital age. Computer networks, however, are prone to attack and therefore require intrusion detection systems. Intrusion detection systems provide a mechanism to de
Externí odkaz:
https://doaj.org/article/2799e704fd174102a385d9244ad5243d
Autor:
Aoife Stephenson, Matias Garcia-Constantino, Marie H. Murphy, Suzanne M. McDonough, Chris D. Nugent, Jacqueline L. Mair
Publikováno v:
BMC Public Health, Vol 21, Iss 1, Pp 1-15 (2021)
Abstract Background Office work generally consists of high amounts of sedentary behaviour (SB) which has been associated with negative health consequences. We developed the “WorktivIty” mobile app to help office workers reduce their SB through se
Externí odkaz:
https://doaj.org/article/cb7f2220e0884cd38d9318a73e57b59f
Autor:
Federico Cruciani, Chris D. Nugent, Javier Medina Quero, Ian Cleland, Paul Mccullagh, Kare Synnes, Josef Hallberg
Publikováno v:
IEEE Access, Vol 8, Pp 207794-207804 (2020)
Smartphone-based approaches for Human Activity Recognition have become prevalent in recent years. Despite the amount of research undertaken in the field, issues such as cross-subject variability are still posing an obstacle to the deployment of solut
Externí odkaz:
https://doaj.org/article/20310b0d40894a13b6ce08180680df46
Publikováno v:
IEEE Access, Vol 8, Pp 228804-228817 (2020)
Activity Recognition is an active research topic focused on detecting human actions and behaviours in smart environments. In most cases, the use of data-driven models aim to relate data from sensors to an activity through a model developed by a super
Externí odkaz:
https://doaj.org/article/474dc7b68522462d802c86a8ef42c0a7
Publikováno v:
Information Fusion. 95:275-292
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1f961d09fbca7463683583d9f0401657
https://doi.org/10.1016/j.inffus.2023.02.025
https://doi.org/10.1016/j.inffus.2023.02.025
Autor:
Aoife Stephenson, Matias Garcia-Constantino, Suzanne M McDonough, Marie H Murphy, Chris D Nugent, Jacqueline L Mair
Publikováno v:
Digital Health, Vol 6 (2020)
Introduction As high amounts of occupational sitting have been associated with negative health consequences, designing workplace interventions to reduce sedentary behaviour (SB) is of public health interest. Digital technology may serve as a cost-eff
Externí odkaz:
https://doaj.org/article/43dcbcc54e5f4963b58f8f27b4c75ea5
Autor:
Joseph Rafferty, Jonathan Synnott, Chris D. Nugent, Andrew Ennis, Philip A. Catherwood, Ian Mcchesney, Ian Cleland, Sally Mcclean
Publikováno v:
IEEE Access, Vol 6, Pp 45473-45484 (2018)
Research interests spanning numerous domains increasingly rely upon computational systems which can store and process a large volume of variable data that is stored at high velocity-representing a big data problem. This is particularly notable within
Externí odkaz:
https://doaj.org/article/50a31f1b76c0443cb8b55a7db8624073
Publikováno v:
International Journal of Behavioral Nutrition and Physical Activity, Vol 14, Iss 1, Pp 1-17 (2017)
Abstract Background High levels of sedentary behaviour (SB) are associated with negative health consequences. Technology enhanced solutions such as mobile applications, activity monitors, prompting software, texts, emails and websites are being harne
Externí odkaz:
https://doaj.org/article/d901e72f081246f1aac1cfb3013a1eb6
Publikováno v:
IEEE Transactions on Circuits and Systems for Video Technology. 32:210-223
Traditional clustering algorithms are widely used for building bag-of-words (BOW) models to aggregate spatio-temporal feature points extracted from a video for human activity recognition problems. Their performances are restricted by the computationa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b1dc52c011b34ba9346fdd55854ec42e
https://doi.org/10.1109/tcsvt.2021.3057469
https://doi.org/10.1109/tcsvt.2021.3057469
Leveraging Wearable Sensors for Human Daily Activity Recognition with Stacked Denoising Autoencoders
Publikováno v:
Sensors, Vol 20, Iss 18, p 5114 (2020)
Activity recognition has received considerable attention in many research fields, such as industrial and healthcare fields. However, many researches about activity recognition have focused on static activities and dynamic activities in current litera
Externí odkaz:
https://doaj.org/article/deea7ebae4864e109ff880cd00eb8ac6