963 resultados para INDOOR SWIMMING POOLS
Resumo:
This pilot project aimed to try something different - rekindle positive memories of swimming in people with dementia who enjoyed swimming throughout their lives, and involve them in active swimming again using a swimming club intervention. Club members were recruited from two residential aged care facilities in Queensland, Australia (n=25 recruited, n=18 commenced, n=11 (median age=88.4, IQR=12.3; 1 male) completed the intervention). The 12 week program consisted of two, 45 minute sessions per week held at a municipal pool, using a trained instructor and assistants. Measures, taken at baseline, Week 6, Week 9 and post intervention included psychosocial and physical assessments such as the Revised Memory and Behavior Problems Checklist, Psychological Well-Being in Cognitively Impaired Persons, Seniors Physical Performance Battery and bioelectric impedance analysis. Stakeholder focus groups determined the barriers and facilitators for the club. Three outcomes have been achieved: 1) the development of a dementia specific, evidence-based, aquatic exercise program. This valuable resource will ensure that the benefits will be maximized with tailored exercises for strength, agility, flexibility, balance, relaxation and stress reduction, 2) improved quality of life for members, with statistically significant improvements in psychological wellbeing (χ2 =8.66, p<0.05), BPSD expression (χ2=16.91, p=0.001) and staff distress (χ2=16.86, p=0.001) and 3) an informative website with instructional video clips and a manual to assist others in implementing and maintaining a Watermemories Swimming Club. This pilot project has provided strong evidence that aquatic exercise can produce positive physical, psychosocial and behavioral outcomes for people with dementia.
Resumo:
Polybrominated diphenyl ethers (PBDEs) are compounds that are used as flame retardants. Human exposure is suggested to be via food, dust and air. An assessment of PBDE exposure via indoor environments using samples of air, dust and surface wipes from eight sites in South East Queensland, Australia was conducted. For indoor air, ΣPBDEs ranged from 0.5 -179 pg/m3 for homes and 15 - 487 pg/m3 for offices. In dust, ΣPBDEs ranged from 87 - 733 ng/g dust and 583 - 3070 ng/g dust in homes and offices, respectively. PBDEs were detected on 9 out of 10 surfaces sampled and ranged from non-detectable to 5985 pg/cm2. Overall, the congener profiles for air and dust were dominated by BDE-209. This study demonstrated that PBDEs are ubiquitous in the indoor environments of selected buildings in South East Queensland and suggest the need for detailed assessment of PBDE concentrations using more sites to further investigate the factors influencing PBDE exposure in Australia.
Resumo:
This work investigated the impact of the HVAC filtration system and indoor particle sources on the relationship between indoor and outdoor airborne particle size and concentrations in an operating room. Filters with efficiency between 65% and 99.97% were used in the investigation and indoor and outdoor particle size and concentrations were measured. A balance mass model was used for the simulation of the impact of the surgical team, deposition rate, HVAC exhaust and air change rates on indoor particle concentration. The experimental results showed that high efficiency filters would not be expected to decrease the risk associated with indoor particles larger than approximately 1 µm in size because normal filters are relatively efficient for these large particles. A good fraction of outdoor particles were removed by deposition on the HVAC system surfaces and this deposition increased with particle size. For particles of 0.3-0.5 µm in diameter, particle reduction was about 23%, while for particles >10 µm the loss was about 78%. The modelling results showed that depending on the type of filter used, the surgical team generated between 93-99% of total particles, while the outdoor air contributed only 1-6%.
Resumo:
We introduce the MiniOrb platform, a combined sensor and interaction platform built to understand and encourage the gathering of data around personal indoor climate preferences in office environments. The platform consists of a sensor device, gathering localised environmental data and an attached tangible interaction and ambient display device. This device allows users to understand their local environment and record preferences with regards to their preferred level of office comfort. In addition to the tangible device we built a web-based mobile application that allowed users to record comfort preferences through a different interface. This paper describes the design goals and technical setup of the MiniOrb platform.
Resumo:
In this paper we describe the preliminary results of a field study which evaluated the use of MiniOrb, a system that employs ambient and tangible interaction mechanisms to allow inhabitants of office environments to report on subjectively perceived office comfort levels. The purpose of this study was to explore the role of ubiquitous computing in the individual control of indoor climate and specifically answer the question to what extent ambient and tangible interaction mechanisms are suited for the task of capturing individual comfort preferences in a non-obtrusive manner. We outline the preliminary results of an in-situ trial of the system.
Resumo:
In elite sports, nearly all performances are captured on video. Despite the massive amounts of video that has been captured in this domain over the last 10-15 years, most of it remains in an 'unstructured' or 'raw' form, meaning it can only be viewed or manually annotated/tagged with higher-level event labels which is time consuming and subjective. As such, depending on the detail or depth of annotation, the value of the collected repositories of archived data is minimal as it does not lend itself to large-scale analysis and retrieval. One such example is swimming, where each race of a swimmer is captured on a camcorder and in-addition to the split-times (i.e., the time it takes for each lap), stroke rate and stroke-lengths are manually annotated. In this paper, we propose a vision-based system which effectively 'digitizes' a large collection of archived swimming races by estimating the location of the swimmer in each frame, as well as detecting the stroke rate. As the videos are captured from moving hand-held cameras which are located at different positions and angles, we show our hierarchical-based approach to tracking the swimmer and their different parts is robust to these issues and allows us to accurately estimate the swimmer location and stroke rates.
Resumo:
Due to the popularity of security cameras in public places, it is of interest to design an intelligent system that can efficiently detect events automatically. This paper proposes a novel algorithm for multi-person event detection. To ensure greater than real-time performance, features are extracted directly from compressed MPEG video. A novel histogram-based feature descriptor that captures the angles between extracted particle trajectories is proposed, which allows us to capture motion patterns of multi-person events in the video. To alleviate the need for fine-grained annotation, we propose the use of Labelled Latent Dirichlet Allocation, a “weakly supervised” method that allows the use of coarse temporal annotations which are much simpler to obtain. This novel system is able to run at approximately ten times real-time, while preserving state-of-theart detection performance for multi-person events on a 100-hour real-world surveillance dataset (TRECVid SED).
Resumo:
This paper evaluates the performance of different text recognition techniques for a mobile robot in an indoor (university campus) environment. We compared four different methods: our own approach using existing text detection methods (Minimally Stable Extremal Regions detector and Stroke Width Transform) combined with a convolutional neural network, two modes of the open source program Tesseract, and the experimental mobile app Google Goggles. The results show that a convolutional neural network combined with the Stroke Width Transform gives the best performance in correctly matched text on images with single characters whereas Google Goggles gives the best performance on images with multiple words. The dataset used for this work is released as well.
Co-optimisation of indoor environmental quality and energy consumption within urban office buildings
Resumo:
This study aimed to develop a multi-component model that can be used to maximise indoor environmental quality inside mechanically ventilated office buildings, while minimising energy usage. The integrated model, which was developed and validated from fieldwork data, was employed to assess the potential improvement of indoor air quality and energy saving under different ventilation conditions in typical air-conditioned office buildings in the subtropical city of Brisbane, Australia. When operating the ventilation system under predicted optimal conditions of indoor environmental quality and energy conservation and using outdoor air filtration, average indoor particle number (PN) concentration decreased by as much as 77%, while indoor CO2 concentration and energy consumption were not significantly different compared to the normal summer time operating conditions. Benefits of operating the system with this algorithm were most pronounced during the Brisbane’s mild winter. In terms of indoor air quality, average indoor PN and CO2 concentrations decreased by 48% and 24%, respectively, while potential energy savings due to free cooling went as high as 108% of the normal winter time operating conditions. The application of such a model to the operation of ventilation systems can help to significantly improve indoor air quality and energy conservation in air-conditioned office buildings.
Resumo:
The control of environmental factors in open-office environments, such as lighting and temperature is becoming increasingly automated. This development means that office inhabitants are losing the ability to manually adjust environmental conditions according to their needs. In this paper we describe the design, use and evaluation of MiniOrb, a system that employs ambient and tangible interaction mechanisms to allow inhabitants of office environments to maintain awareness of environmental factors, report on their own subjectively perceived office comfort levels and see how these compare to group average preferences. The system is complemented by a mobile application, which enables users to see and set the same sensor values and preferences, but using a screen-based interface. We give an account of the system’s design and outline the results of an in-situ trial and user study. Our results show that devices that combine ambient and tangible interaction approaches are well suited to the task of recording indoor climate preferences and afford a rich set of possible interactions that can complement those enabled by more conventional screen-based interfaces.
Resumo:
Recent 'Global Burden of Disease' studies have provided quantitative evidence of the significant role air pollution plays as a human health risk factor (Lim et al., The Lancet, 380: 2224–2260, 2012). Tobacco smoke, including second hand smoke, household air pollution from solid fuels and ambient particulate matter are among the top risks, leading to lower life expectancy around the world. Indoor air constitutes an environment particularly rich in different types of pollutants, originating from indoor sources, as well as penetrating from outdoors, mixing, interacting or growing (when considering microbes) under the protective enclosure of the building envelope. Therefore, it is not a simple task to follow the dynamics of the processes occurring there, or to quantify the outcomes of the processes in terms of pollutant concentrations and other characteristics. This is further complicated by limitations such as building access for the purpose of air quality monitoring, or the instrumentation which can be used indoors, because of their possible interference with the occupants comfort (due to their large size, noise generated or amount of air drawn). European studies apportioned contributions of indoor versus outdoor sources of indoor air contaminants in 26 European countries and quantified IAQ associated DALYs (Disability-Adjusted Life Years) in those countries (Jantunen et al., Promoting actions for healthy indoor air (IAIAQ), European Commission Directorate General for Health and Consumers, Luxembourg, 2011). At the same time, there has been an increase in research efforts around the world to better understand the sources, composition, dynamics and impacts of indoor air pollution. Particular focus has been directed towards the contemporary sources, novel pollutants and new detection methods. The importance of exposure assessment and personal exposure, the majority of which occurs in various indoor micro¬environments, has also been realized. Overall, this emerging knowledge has been providing input for global assessments of indoor environments, the impact of indoor pollutants and their science based management and control. It was a major outcome of recent international conferences that interdisciplinarity and especially a better colla¬boration between exposure and indoor sciences would be of high benefit for the health related evaluation of environmental stress factors and pollutants. A very good example is the combination of biomonitoring and indoor air, particle and dust analysis to study the exposure routes of semi volatile organic compounds (SVOCs). We have adopted the idea of combining the forces of exposure and indoor sciences for this Special Issue, identified new and challenging topics and have attracted colleagues who are top researchers in their field to provide their inputs. The Special Issue includes papers, which collectively present advances in current research topics and in our view, build the bridge between indoor and exposure sciences.