28 resultados para GPS


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Background Average annual fertility rates in industrialised countries have been below two children per woman for the past 3 decades. The reasons behind women’s childbearing behaviour are complex. However, a lack of awareness regarding the consequences of delayed childbearing and the inability of reproductive technologies to overcome the ‘biological clock’ may be contributory factors.

Objective A narrative review guided by the research question: What do women need to know about the consequences of delayed childbearing in order to make informed decisions about their fertility?

Discussion There are three facts that women need to know in order to make informed decisions around their fertility: Some women want to have more children than they are able to have because they postpone childbearing; there can be medical consequences to delaying childbearing and; some women’s ideas about their fertility don’t match the ‘the scientific facts’. General practitioners are well placed to play a strategic role in the provision of timely, relevant information to help women make informed decisions about their fertility. Further research is needed to identify the most appropriate ways for GPs to communicate this information.

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Over recent years, a major breakthrough in marine animal tracking has occurred with the advent of Fastloc-GPS that provides highly accurate location data even for animals that only surface briefly such as sea turtles, marine mammals and penguins. We assessed the accuracy of Fastloc-GPS locations using fixed trials of tags in which >45 000 locations were obtained. Procedures for determining the speed of travel and heading were developed by simulating tracks and then adding Fastloc-GPS location errors. The levels of detail achievable for speed and heading estimates were illustrated by using empirical Fastloc-GPS data for a green turtle (Chelonia mydas, Linnaeus, 1758) travelling over 3000 km across the Indian Ocean. The accuracy of Fastloc-GPS locations varied as a function of the number of GPS satellites used in the location calculation. For example, when Fastloc-GPS locations were calculated using 4 GPS satellites, 50% of locations were within 36 m and 95% within 724 m of the true position. These values improved to 18 and 70 m, respectively, when 6 satellites were used. Simulations indicated that for animals travelling around 2·5 km h-1 (e.g. turtles, penguins and seals) and depending on the number of satellites used in the location calculation, robust speed and heading estimates would usually be obtained for locations only 1-6 h apart. Fastloc-GPS accuracy is several orders of magnitude better that conventional Argos tracking or light-based geolocation and consequently will allow new insights into small-scale movement patterns of marine animals.

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Determining suitable bus-stop locations is critical in improving the quality of bus services. Previous studies on selecting bus stop locations mainly consider environmental factors such as population density and traffic conditions, seldom of them consider the travel patterns of people, which is a key factor for determining bus-stop locations. In order to draw people’s travel patterns, this paper improves the density-based spatial clustering of applications with noise (DBSCAN) algorithm to find hot pick-up and drop-off locations based on taxi GPS data. The discovered density-based hot locations could be regarded as the candidate for bus-stop locations. This paper further utilizes the improved DBSCAN algorithm, namely as C-DBSCAN in this paper, to discover candidate bus-stop locations to Capital International Airport in Beijing based on taxi GPS data in November 2012. Finally, this paper discusses the effects of key parameters in C-DBSCAN algorithm on the clustering results. Keywords Bus-stop locations, Public transport service, Taxi GPS data, Centralize density-based spatial clustering of applications with noise.

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Determining the foraging behaviour of free-ranging marine animals is fundamental for assessing their habitat use and how they may respond to changes in the environment. However, despite recent advances in bio-logging technology, collecting information on both at-sea movement patterns and activity budgets still remains difficult in small pelagic seabird species due to the constraints of instrument size. The short-tailed shearwater, the most abundant seabird species in Australia (ca 23 million individuals), is a highly pelagic procellariiform. Despite its ecological importance to the region, almost nothing is known about its at-sea behaviour, in particular, its foraging activity. Using a combination of GPS and tri-axial accelerometer data-loggers, the fine scale three-dimensional foraging behaviour of 10 breeding individuals from two colonies was investigated. Five at-sea behaviours were identified: (1) resting on water, (2) flapping flight, (3) gliding flight, (4) foraging (i.e., surface foraging and diving events), and (5) taking-off. There were substantial intra- and inter- individual variations in activity patterns, with individuals spending on average 45.8% (range: 17.1-70.0%) of time at sea resting on water and 18.2% (range: 2.3-49.6%) foraging. Individuals made 76.4 ± 65.3 dives (range: 8-237) per foraging trip (mean duration 9.0 ± 1.9 s), with dives also recorded during night-time. With the continued miniaturisation of recording devices, the use of combined data-loggers could provide us with further insights into the foraging behaviour of small procellariiforms, helping to better understand interactions with their prey.

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The purpose of this study was to assess the validity of a GPS tracking system to estimate energy expenditure (EE) during exercise and field sport locomotor movements. Twenty-seven participants each completed one 90 minute exercise session on an outdoor synthetic futsal pitch. During the exercise session participants wore a 5 Hz GPS unit interpolated to 15 Hz (SPI HPU, GPSports Pty Ltd, Australia) and a portable gas analyser (Metamax® 3B, Cortex Pty Ltd, Germany) which acted as the criterion measure of EE. The exercise session was comprised of alternating five minute exercise bouts of randomised walking, jogging, running or a field sport circuit (x3) followed by 10 minutes of recovery. One-way ANOVA showed significant (p<0.01) and very large underestimations between GPS metabolic power derived EE and VO2 derived EE for all field sport circuits (% difference ≈ -44%). No differences in EE were observed for the jog (7.8%) and run (4.8%) while very large overestimations were found for the walk (43.0%). The GPS metabolic power EE over the entire 90 minute session was significantly lower (p<0.01) than the VO2 EE, resulting in a moderate underestimation overall (-19%). The results of this study suggest that a GPS tracking system using the metabolic power model of EE does not accurately estimate EE in field sport movements or over an exercise session consisting of mixed locomotor activities interspersed with recovery periods; however is able to provide a reasonably accurate estimation of EE during continuous jogging and running.

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Use of the Global Positioning System (GPS) for quantifying athletic performance is common in many team sports. The effect of running velocity on measurement validity is well established, but the influence of rapid directional change is not well understood in team sport applications. This effect was systematically evaluated using multidirectional and curvilinear adaptations of a validated soccer simulation protocol that maintained identical velocity profiles. Team sport athletes completed 90 min trials of the Loughborough Intermittent Shuttle-running Test movement pattern on curvilinear, and multidirectional shuttle running tracks while wearing a 5 Hz (with interpolated 15 Hz output) GPS device. Reference total distance (13 200 m) was systematically over- and underestimated during curvilinear (2.61±0.80%) and shuttle (-3.17±2.46%) trials, respectively. Within-epoch measurement uncertainty dispersion was widest during the shuttle trial, particularly during the jog and run phases. Relative measurement reliability was excellent during both trials (Curvilinear r = 1.00, slope = 1.03, ICC = 1.00; Shuttle r = 0.99, slope = 0.97, ICC = 0.99). Absolute measurement reliability was superior during the curvilinear trial (Curvilinear SEM = 0 m, CV = 2.16%, LOA ± 223 m; Shuttle SEM = 119 m, CV = 2.44%, LOA ± 453 m). Rapid directional change degrades the accuracy and absolute reliability of GPS distance measurement, and caution is recommended when using GPS to quantify rapid multidirectional movement patterns.