Daily physical activity assessment with accelerometers: new insights and validation studies
The field of application of accelerometry is diverse and ever expanding. Because by
definition all physical activities lead to energy expenditure, the doubly labelled water (DLW) …
definition all physical activities lead to energy expenditure, the doubly labelled water (DLW) …
Predicting compressive strength of lightweight foamed concrete using extreme learning machine model
In this research, a machine learning model namely extreme learning machine (ELM) is
proposed to predict the compressive strength of foamed concrete. The potential of the ELM …
proposed to predict the compressive strength of foamed concrete. The potential of the ELM …
A youth compendium of physical activities: activity codes and metabolic intensities
NF Butte, KB Watson, K Ridley, IF Zakeri… - … and science in …, 2017 - pmc.ncbi.nlm.nih.gov
ABSTRACT Purpose A Youth Compendium of Physical Activities (Youth Compendium) was
developed to estimate the energy costs of physical activities using data on youth only …
developed to estimate the energy costs of physical activities using data on youth only …
Universally deployable extreme learning machines integrated with remotely sensed MODIS satellite predictors over Australia to forecast global solar radiation: A new …
Global advocacy to mitigate climate change impacts on pristine environments, wildlife,
ecology, and health has led scientists to design technologies that harness solar energy with …
ecology, and health has led scientists to design technologies that harness solar energy with …
Drought forecasting in eastern Australia using multivariate adaptive regression spline, least square support vector machine and M5Tree model
Drought forecasting using standardized metrics of rainfall is a core task in hydrology and
water resources management. Standardized Precipitation Index (SPI) is a rainfall-based …
water resources management. Standardized Precipitation Index (SPI) is a rainfall-based …
Estimation of monthly evaporative loss using relevance vector machine, extreme learning machine and multivariate adaptive regression spline models
The forecasting of evaporative loss (E) is vital for water resource management and
understanding of hydrological process for farming practices, ecosystem management and …
understanding of hydrological process for farming practices, ecosystem management and …
Development of ensemble machine learning approaches for designing fiber-reinforced polymer composite strain prediction model
Over the past few decades, it has been observed a remarkable progression in the
development of computer aid models in the field of civil engineering. Machine learning …
development of computer aid models in the field of civil engineering. Machine learning …
A practical and time-efficient high-intensity interval training program modifies cardio-metabolic risk factors in adults with risk factors for type II diabetes
BE Phillips, BM Kelly, M Lilja… - Frontiers in …, 2017 - frontiersin.org
Introduction Regular physical activity (PA) can reduce the risk of developing type 2 diabetes,
but adherence to time-orientated (150 min week− 1 or more) PA guidelines is very poor. A …
but adherence to time-orientated (150 min week− 1 or more) PA guidelines is very poor. A …
An efficient neuro-evolutionary hybrid modelling mechanism for the estimation of daily global solar radiation in the Sunshine State of Australia
This research paper aims to develop a hybrid neuro-evolutionary wrapper-based model for
daily global solar radiation estimation in the solar-rich Sunshine State of Queensland …
daily global solar radiation estimation in the solar-rich Sunshine State of Queensland …
Evaluation of artificial neural network algorithms for predicting METs and activity type from accelerometer data: validation on an independent sample
PS Freedson, K Lyden… - Journal of Applied …, 2011 - journals.physiology.org
Previous work from our laboratory provided a “proof of concept” for use of artificial neural
networks (nnets) to estimate metabolic equivalents (METs) and identify activity type from …
networks (nnets) to estimate metabolic equivalents (METs) and identify activity type from …