Sentences with phrase «scale measurement data»

Not exact matches

Apple's HealthKit works by gathering data from sources such as glucose measurement tools, food and exercise - tracking apps and Wi - fi connected scales.

Those data are proprietary, however, and the measurements can not be scaled up to the level of an entire oil and gas field.

Using different calibration and filtering processes, the two researchers succeeded in combining a wide variety of available data from temperature measurements and climate archives in such a way that they were able to compare the reconstructed sea surface temperature variations at different locations around the globe on different time scales over a period of 7,000 years.

Better predictions would require improved climate - measurement tools, more sophisticated climate models that work on regional scales, and a better organized system to integrate all the data, the report concludes.

However, experimental measurements have, to date, not been able to provide data with enough depth to identify all the fundamental mechanisms and to explain weaknesses of currently used design tools, due to the difficulties of performing engine - scale experiments and acquiring spatially and temporally resolved data.

Witten analyzes «high - dimensional data,» or large - scale data sets coming out of biology that has tens of thousands of measurements — for instance genome screening projects.

Magnets and magnetic phenomena underpin the vast majority of modern data storage, and the measurement scales for research focused on magnetic behaviors continue to shrink with the rest of digital technology.

This relatively new and still emerging way of seeing depends on taking MRI measurements with conventional millimeter - scale resolution, and developing theoretical models to interpret the resulting data in terms of changes occurring at the scale of microns.

We aim to push its limits on all fronts to establish a technique which combines nanometre 3D resolution with maximum labelling efficiencies, absolute measurements of protein copy numbers, precise multi-colour measurements, high - throughput for large scale statistics and novel data analysis approaches, to address the vast array of exciting biological questions at the nanoscale, which are becoming accessible only now.

The ARM Aerosol Measurement Science Group (AMSG) coordinates ARM Climate Research Facility observations of aerosols and atmospheric trace gases with user needs to ensure advanced, well - characterized observational measurements and data products — at the spatial and temporal scales necessary — for improving climate science and model forecasts.

They used two measurements to gauge a drug's effectiveness and tolerability: the percentage of patients who showed at least a 50 % improvement in their symptoms as measured by one of two scales, or who scored «much improved or very much improved» after eight weeks of treatment (or from 6 to 12 weeks if eight - week data wasn't available) and the percentage of patients who dropped out of the study before eight weeks for any reason.

As noted in a 1986 article in the Journal of Educational Measurement by Wendy Yen, formerly the chief research psychologist with CBT / McGraw - Hill and now with the Educational Testing Service (ETS), there are infinitely many nonlinear transformations of the ability scale that will fit the data equally well, yielding the same probabilities.

There are several data measurement concepts, however, that teachers can use to get more comfortable interpreting and communicating the data and evidence that larger scale assessments produce.

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Combining longitudinal data, multilevel modeling and state - of - the - art measurement scales from The Lexile ® Framework for Reading and The Quantile ® Framework for Mathematics, Williamson (2016) premiered incremental velocity norms for average reading growth and average mathematics growth.

This data is not noisy on an annual scale, and in fact is decelerating over the last decade from a previous nearly linear 3 mm / year since the measurements began.

In the spring of 2014 we were part of a program that performed some ground - truth measurements to validate aircraft sensors and thus moving up the scale to satellite data.

The first simulates the true temperatures, the second treats the measurement errors that would arise from this series from three different sources of uncertainty: i) usual auto - regressive (AR)- type short range errors, ii) missing data, iii) the «scale reduction factor».

Other needs: make cloud and radiation measurements; perform experiments at appropriately short physical and temporal scales; and amass relevant data any climate researcher could use.

[1] Reconstructing solar activity variability beyond the time scale of actual measurements provides invaluable data for modeling of past and future climate change.

«Routine measurements from space can provide quasi-synoptic, reproducible data for investigating processes on global scales; they may also be the most efficient way to monitor the ocean surface,» the researchers wrote.

This requires collecting more data at high resolution in time and space, and the use of isotopes to bridge top - down and bottom - up observations to identify methane sources across these measurement scales.

Various methods collect data at different scales: Chamber measurements collect data over square - meter areas, tall towers and aircraft observe larger areas, and satellites (e.g., Greenhouse Gases Observing Satellite, or GOSAT) observe areas larger than a square kilometer.

Evidence of warming from ocean heat content measurements comes from a data set that is not mature and interpretation of this warming is confounded by the long time scales of circulation and heat transfer in the ocean.

GaryM, «initially collected data with wide ranges of uncertainty can be processed using statistics to provide a more accurate measurement on a much larger scale.»

You claim that initially collected data with wide ranges of uncertainty can be processed using statistics to provide a more accurate measurement on a much larger scale.

If we really want to know who's cherry picking data — land - based measurements vs geological time scales vs models, the answer is to create a betting market for climate prediction and get the people who think they know put their money where their mouths are.

Scaling these measurements to the entire Amazon basin with rainfall data, we estimate that drought suppressed Amazon - wide photosynthesis in 2010 by 0.38 petagrams of carbon (0.23 — 0.53 petagrams of carbon).

In 2004 - 5, D'Arrigo and others carried the contemplated update to the Thelon River (Hornby Cabin) and Coppermine River measurement data on a much expanded scale, this time obtaining over 350 cores from each location, as compared to ~ 30 cores in the earlier collection.

The study also uses so - called «proxy» measurements, including data gleaned from coral reefs and tree rings, to extend large - scale surface climate conditions back to 900 AD.

Given the data limitations it is concluded that using radiosondes to validate multidecadal - scale trends in MSU data, or vice versa, or trying to use such metrics alone to pick a «winner» is an ill - conditioned approach and has limited utility without one or more of additional independent measurements, or methodological, or physical analysis.»

These surface networks have had so many changes over time that the number of stations that have been moved, had their time of observation changed, had equipment changes, maintenance issues, or have been encroached upon by micro site biases and / or UHI using the raw data for all stations on a national scale or even a global scale gives you a result that is no longer representative of the actual measurements, there is simply too much polluted data.

Parts of the data may have some elements of the errors that are Gaussian — the example of measurement error in terms of scale may be Gaussian — after get through the problems of variances in the thermometers themselves, which is also a well - known problem for mercury thermometers vis a vis their manufacturing — but their measured variance from the true temperature is not demonstrably Gaussian, and gets worse the further back you go.

PEARL was the only research station taking measurements during that cold dark time — data which, as Drummond points out, would be vital to operating large - scale oil drilling operations year - round in the region.

«Scaling (our) measurements to the entire Amazon basin with rainfall data, we estimate that drought suppressed Amazon - wide photosynthesis in 2010 by 0.38 petagrams of carbon (equivalent to 380 million tonnes carbon, or 1.4 billion tonnes of CO2).»

Using only the wind data (radiosondes and commercia jet measurements), the short term large scale forecast error over the US was just as small as with all additional sources of data combined.

To obtain the required data, three questionnaires were utilized: Allport and Ross's (1967) Intrinsic - Extrinsic Religious Orientation Scale (IEROS) to measure extrinsic and intrinsic religious orientations, Short Measurement of Psychological Well - Being by Clarke, Marshall, Ryff, and Wheaton (2001) to measure psychological well - being, and finally, The Rosenberg Self - Esteem Scale by Rosenberg (1965) to assess self - esteem.

It is an item response theory model which helps to describe the required scaling properties of linear interval measurement and the response pattern observed in the data corresponds to the theoretical pattern expected by the model (Embretson & Reise, 2000; Tennant & Conaghan, 2007).