420 resultados para Big data, Spark, Hadoop


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The objective of this chapter is to provide an overview of traffic data collection that can and should be used for the calibration and validation of traffic simulation models. There are big differences in availability of data from different sources. Some types of data such as loop detector data are widely available and used. Some can be measured with additional effort, for example, travel time data from GPS probe vehicles. Some types such as trajectory data are available only in rare situations such as research projects.

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Reality television, alongside shows such as Q&A – which may be Reality TV in all but name – frequently drives social media conversations about the Australian television industry. Big Brother, currently screening on Channel 9, is consistently among the shows with the highest levels of chatter in that regard. The precise Facebook data is hard to quantify but the Official Big Brother page boasts 805,400 likes and more than 59,000 comments since the start of the series, suggesting it has established a firm presence on that platform too...

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Magnetic behavior of soils can seriously hamper the performance of geophysical sensors. Currently, we have little understanding of the types of minerals responsible for the magnetic behavior, as well as their distribution in space and evolution through time. This study investigated the magnetic characteristics and mineralogy of Fe-rich soils developed on basaltic substrate in Hawaii. We measured the spatial distribution of magnetic susceptibility (χlf) and frequency dependence (χfd%) across three test areas in a well-developed eroded soil on Kaho'olawe and in two young soils on the Big Island of Hawaii. X-ray diffraction spectroscopy, x-ray fluorescence spectroscopy (XFCF), chemical dissolution, thermal analysis, and temperature-dependent magnetic studies were used to characterize soil development and mineralogy for samples from soil pits on Kaho'olawe, surface samples from all three test areas, and unweathered basalt from the Big Island of Hawaii. The measurements show a general increase in magnetic properties with increasing soil development. The XRF Fe data ranged from 13% for fresh basalt and young soils on the Big Island to 58% for material from the B horizon of Kaho'olawe soils. Dithionite-extractable and oxalate-extractable Fe percentages increase with soil development and correlate with χlf-and χfd%, respectively. Results from the temperature-dependent susceptibility measurements show that the high soil magnetic properties observed in geophysical surveys in Kaho'olawe are entirely due to neoformed minerals. The results of our studies have implications for the existing soil survey of Kaho'olawe and help identify methods to characterize magnetic minerals in tropical soils.

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Large volumes of heterogeneous health data silos pose a big challenge when exploring for information to allow for evidence based decision making and ensuring quality outcomes. In this paper, we present a proof of concept for adopting data warehousing technology to aggregate and analyse disparate health data in order to understand the impact various lifestyle factors on obesity. We present a practical model for data warehousing with detailed explanation which can be adopted similarly for studying various other health issues.

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Recent data indicate that levels of overweight and obesity are increasing at an alarming rate throughout the world. At a population level (and commonly to assess individual health risk), the prevalence of overweight and obesity is calculated using cut-offs of the Body Mass Index (BMI) derived from height and weight. Similarly, the BMI is also used to classify individuals and to provide a notional indication of potential health risk. It is likely that epidemiologic surveys that are reliant on BMI as a measure of adiposity will overestimate the number of individuals in the overweight (and slightly obese) categories. This tendency to misclassify individuals may be more pronounced in athletic populations or groups in which the proportion of more active individuals is higher. This differential is most pronounced in sports where it is advantageous to have a high BMI (but not necessarily high fatness). To illustrate this point we calculated the BMIs of international professional rugby players from the four teams involved in the semi-finals of the 2003 Rugby Union World Cup. According to the World Health Organisation (WHO) cut-offs for BMI, approximately 65% of the players were classified as overweight and approximately 25% as obese. These findings demonstrate that a high BMI is commonplace (and a potentially desirable attribute for sport performance) in professional rugby players. An unanswered question is what proportion of the wider population, classified as overweight (or obese) according to the BMI, is misclassified according to both fatness and health risk? It is evident that being overweight should not be an obstacle to a physically active lifestyle. Similarly, a reliance on BMI alone may misclassify a number of individuals who might otherwise have been automatically considered fat and/or unfit.

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In this paper, a singularly perturbed ordinary differential equation with non-smooth data is considered. The numerical method is generated by means of a Petrov-Galerkin finite element method with the piecewise-exponential test function and the piecewise-linear trial function. At the discontinuous point of the coefficient, a special technique is used. The method is shown to be first-order accurate and singular perturbation parameter uniform convergence. Finally, numerical results are presented, which are in agreement with theoretical results.