Deakin University

About: Deakin University is a education organization based out in Burwood, Victoria, Australia. It is known for research contribution in the topics: Population & Context (language use). The organization has 12118 authors who have published 46470 publications receiving 1188841 citations. The organization is also known as: Deakin.

Correlates of sedentary behaviours in preschool children: a review

Abstract: Background Sedentary behaviour has been linked with a number of health outcomes. Preschool-aged children spend significant proportions of their day engaged in sedentary behaviours. Research into the correlates of sedentary behaviours in the preschool population is an emerging field, with most research being published since 2002. Reviews on correlates of sedentary behaviours which include preschool children have previously been published; however, none have reported results specific to the preschool population. This paper reviews articles reporting on correlates of sedentary behaviour in preschool children published between 1993 and 2009.

Effectiveness and feasibility of virtual reality and gaming system use at home by older adults for enabling physical activity to improve health-related domains: a systematic review

Abstract: Background: use of virtual reality and commercial gaming systems (VR/gaming) at home by older adults is receiving attention as a means of enabling physical activity. Objective: to summarise evidence for the effectiveness and feasibility of VR/gaming system utilisation by older adults at home for enabling physical activity to improve impairments, activity limitations or participation. Methods: a systematic review searching 12 electronic databases from 1 January 2000–10 July 2012 using key search terms. Two independent reviewers screened yield articles using pre-determined selection criteria, extracted data using customised forms and applied the Cochrane Collaboration Risk of Bias Tool and the Downs and Black Checklist to rate study quality. Results: fourteen studies investigating the effects of VR/gaming system use by healthy older adults and people with neurological conditions on activity limitations, body functions and physical impairments and cognitive and emotional well-being met the selection criteria. Study quality ratings were low and, therefore, evidence was not strong enough to conclude that interventions were effective. Feasibility was inconsistently reported in studies. Where feasibility was discussed, strong retention (≥70%) and adherence (≥64%) was reported. Initial assistance to use the technologies, and the need for monitoring exertion, aggravation of musculoskeletal symptoms and falls risk were reported. Conclusions: existing evidence to support the feasibility and effectiveness VR/gaming systems use by older adults at home to enable physical activity to address impairments, activity limitations and participation is weak with a high risk of bias. The findings of this review may inform future, more rigorous research.

Federated Learning for Internet of Things: A Comprehensive Survey

Abstract: The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation of intelligent services and applications empowered by artificial intelligence (AI). Traditionally, AI techniques require centralized data collection and processing that may not be feasible in realistic application scenarios due to the high scalability of modern IoT networks and growing data privacy concerns. Federated Learning (FL) has emerged as a distributed collaborative AI approach that can enable many intelligent IoT applications, by allowing for AI training at distributed IoT devices without the need for data sharing. In this article, we provide a comprehensive survey of the emerging applications of FL in IoT networks, beginning from an introduction to the recent advances in FL and IoT to a discussion of their integration. Particularly, we explore and analyze the potential of FL for enabling a wide range of IoT services, including IoT data sharing, data offloading and caching, attack detection, localization, mobile crowdsensing, and IoT privacy and security. We then provide an extensive survey of the use of FL in various key IoT applications such as smart healthcare, smart transportation, Unmanned Aerial Vehicles (UAVs), smart cities, and smart industry. The important lessons learned from this review of the FL-IoT services and applications are also highlighted. We complete this survey by highlighting the current challenges and possible directions for future research in this booming area.