Sentences with phrase «models of this process predict»

Recent models of this process predict that the orbit of the newly formed Moon should be in, or very near [less than 1 °], the Earth's equatorial plane.

Not exact matches

The rise of the lean process and agile software methodology as major influences on business models helps us adjust to change rather than to predict.

With this in mind, the Materials Genome Initiative is building databases of material properties like strength, density and other things, and also includes computer models to predict what processes will achieve the qualities a manufacturer is looking for.

The project is detailed in the contract as a seven step process — with Kogan's company, GSR, generating an initial seed sample (though it does not specify how large this is here) using «online panels»; analyzing this seed training data using its own «psychometric inventories» to try to determine personality categories; the next step is Kogan's personality quiz app being deployed on Facebook to gather the full dataset from respondents and also to scrape a subset of data from their Facebook friends (here it notes: «upon consent of the respondent, the GS Technology scrapes and retains the respondent's Facebook profile and a quantity of data on that respondent's Facebook friends»); step 4 involves the psychometric data from the seed sample, plus the Facebook profile data and friend data all being run through proprietary modeling algorithms — which the contract specifies are based on using Facebook likes to predict personality scores, with the stated aim of predicting the «psychological, dispositional and / or attitudinal facets of each Facebook record»; this then generates a series of scores per Facebook profile; step 6 is to match these psychometrically scored profiles with voter record data held by SCL — with the goal of matching (and thus scoring) at least 2M voter records for targeting voters across the 11 states; the final step is for matched records to be returned to SCL, which would then be in a position to craft messages to voters based on their modeled psychometric scores.

Our task is not (as it is for positivism) to discover the covering laws that explain and predict observable associations of conditions and events, but to use all available empirical evidence and powers of reason to develop conceptual models that as accurately as possible describe the real capacities and causal processes operating at the deeper, unobservable level of reality.

«Models are used to predict how soil processes change, for example, in response to climate change,» said Steve Allison, coauthor from the University of California, Irvine.

The researchers also were able to use models trained with data from one human subject to predict and decode the brain activity of a different human subject, a process called cross-subject encoding and decoding.

Traditional models predict this process should take tens of millions of years.

I am in the process of creating a model to predict the global spread of HIV subtypes.

They hope to publicly release the new simulation model — based on a direct version of a kinetic Monte Carlo simulation where reaction channels are predicted automatically on the fly as the growth process proceeds — in 2015.

«Our model can help predict if forests are at risk of desertification or other climate change - related processes and identify what can be done to conserve these systems,» he said.

To predict hail storms, or weather in general, scientists have developed mathematically based physics models of the atmosphere and the complex processes within, and computer codes that represent these physical processes on a grid consisting of millions of points.

It will then process all the results of performing the particular action in each model — one may predict that it will cause the robot to tilt left, for instance; another may indicate the machine will tilt right.

To narrow down the number of chemical compounds that could be potential drug candidates, scientists utilize computer models that can predict how a particular chemical compound might interact with a biological target of interest — for example, a key protein that might be involved with a disease process.

Although the Standard Model predicts this decay to occur in more than half of all Higgs boson decays, it is very difficult to distinguish from similar background processes.

Some of these feedback processes are poorly understood — like how climate change affects clouds — and many are difficult to model, therefore the climate's propensity to amplify any small change makes predicting how much and how fast the climate will change inherently difficult.

This machine learning technique builds a model that encodes the information contained in the database, and in turn this model can predict the outcome of the molecular self - assembly process with high accuracy.

Consequently, in the past 20 years his research has evolved from an early focus on prioritizing the effects that humans have on coral reefs and the role that marine protected areas play in conserving biological diversity and ecological processes, to developing theoretical and simulation models of coral reefs that will help predict and suggest alternatives to reduce detrimental effects, to developing practical means to restore degraded reefs through manipulation of the food web and management.

Researchers in the US, China and Taiwan have developed a new systems biology model that mimics the process of wood formation, allowing scientists to predict the effects of switching on and off the 21 (at least) pathway genes involved in producing lignin, a primary component of wood.

What Rhoden's team observed in their study was that during this process, several models predict that Charon's orbit around Pluto could have been highly eccentric, which would have caused severe tides on both celestial bodies, possibly leading to the formation of underground oceans of liquid water, similar to those that probably exist inside Europa.

Computational biology researchers at Pacific Northwest National Laboratory developed a model for predicting what's happening during a stroke, how the process evolves over time, the potential outcomes, and the effects of different treatment options.

We model the evolutionary processes that have produced these novel traits and develop algorithms that compare genomes to predict the functional relevance of specific genetic differences between individuals and species.

Then, we should also ask ourselves what the criteria would be in order to define the success, as at the end of the process we only get the model out of data, that only predicts and not exactly gives us the answer.

The Concerns - Based Adoption Model (CBAM) is a conceptual framework that describes, explains, and predicts probable teacher concerns and behaviors during the process of implementing a school reform.

Stage theory conceptualizes leadership succession as a process with distinct phases and demands, rather than a singular event.212 Patterns in the process have been identified, and the ways in which each phase of the succession process shapes and influences the outcome of subsequent phases have been described.213 Most stage models predict that it takes at least five to seven years to build relationships of trust that can serve as a foundation for movement to later stages of the succession process — «consolidation and refinement,» in Gabarro «s (1987) terms.

Several major automakers are in the process of bringing all - new battery - electric models to market, but a couple of surprising segments that were barely blips on the radar are making a comeback that few had predicted a mere three years ago: two - door and four - door coupes.

Of course, there are some differences — the butterfly effect has a basis in physical reality, so as our understanding of physical processes and the ability to mathematically model them improves, so will our ability to bridge the gap between predicting weather and climatOf course, there are some differences — the butterfly effect has a basis in physical reality, so as our understanding of physical processes and the ability to mathematically model them improves, so will our ability to bridge the gap between predicting weather and climatof physical processes and the ability to mathematically model them improves, so will our ability to bridge the gap between predicting weather and climate.

Anyhow, not the point, the reason for the hand wringing is that what has happened in the last decade was not predicted, not expected and todate can not be explained by the processes and models that were thought to be indicative of this planet's climate.

We derived onset dates from processed NDVI data sets and used growing degree day (GDD) summations from the NCEP re-analysis to calibrate and validate a phenology model to predict the onset of the growing season over Europe.

To present regional multi-decadal climate projections to the impact communities as part of their driving forces and boundary conditions (for their models and process studies), when there is NO skill on this time scale at predicting changes in climate statistics, is a serious misleading application of the scientific method.

A European team of ecologists around Stefan Dullinger from the Department of Conservation Biology, Vegetation and Landscape Ecology of the University of Vienna presents a new modeling tool to predict migration of mountain plants which explicitly takes population dynamic processes into account.

For the first time, these processes are represented in a computer model that predicts the fate of soil carbon as temperatures rise.

We are helping you to understand that there are other plausible explanations for global warming, and the assumption that it is due to CO2 is based only on opinionated papers hand - waved through the peer review process by friendly referees [while skeptical papers rarely see the light of day], and by computer model outputs, which are invariably unable to predict the future climate, or even today's climate with all available past data as the input.

We will discuss the evidence for change, the inability of our climate models to predict these changes, the processes responsible for sea ice reduction and improved representation of these processes in climate models, and the impacts of sea ice change on local and global weather and climate.

Furthermore in contrast to researchers arguing rising atmospheric CO2 will inhibit calcification, increased photosynthesis not only increases calcification, paradoxically the process of calcification produces CO2 and drops pH to levels lower than predicted by climate change models.

Publication (Open access): Aalto, J., Harrison, S., Luoto, M. Statistical modelling predicts almost complete loss of major periglacial processes in Northern Europe by 2100.

The net effect of these processes taken together is a sustained growth of the carbon storage in the Southern Ocean, notwithstanding a weaker global ocean carbon uptake predicted by all models in a warming climate.

The «pause», should it continue, will discredit every model that did not predict it, including every model that included a strong functional relationship with CO2 without strong residual («natural») processes of hypothesized influences (the gravitational thingies of Scafetta, for example), or processes of unknown causation.

Understanding and modeling the fundamental processes that govern the large precipitation variability and extremes in the western U.S. is a critical test for the ability of climate models to predict the regional water cycle, including floods and droughts.

And if this process of water changing state, which is pretty much just a process of physics and a bit of chemistry, is so very easy to get wrong — specifically, is so easy to model too conservatively so the models predict wrongly that it will be a very slow process when in fact it seems to be a much faster process — how confident can we be that other models and estimates of processes that involve multiple feedbacks that include chemical and biological interactions as well as physical ones aren't even more wildly inaccurate on the «conservative» side?

These models will have the capability to predict the ancient hydrologic history of a sedimentary basin together with the related processes of organic maturation, hydrocarbon migration, rock alteration, and mineralization.

We conclude that the ice sheet surface is efficiently drained under optimal conditions, that digital elevation models alone can not fully describe supraglacial drainage and its connection to subglacial systems, and that predicting outflow from climate models alone, without recognition of subglacial processes, may overestimate true meltwater release from the ice sheet.

Our ability to understand and predict changes in the forest carbon cycle — particularly net primary productivity and carbon storage — increasingly relies on models that represent biological processes across several scales of biological organization, from tree leaves to forest stands2, 3.

Even if Earth truly were a flat disk without terrain, and even if the energy transfer processes were linear, and even if the system were in steady - state, the models would not be accurate enough to make a long - term forecast of the effects of doubling CO2 because the models can not even predict changes in cloud cover.

Some of the above examples of access to justice are those that are commonly predicted by advocates of alternative structures: business models that facilitate reduced and fixed price legal services and / or unbundling, technology that enables standardization and improved processes to handle large volumes of cases or contracts, branding that reduces the client's search costs and increases their level of trust, multidisciplinary services that significantly ease the client experience notably because they do not need to assemble or coordinate different streams of work.

Innovation processes also rely heavily on creativity, ideation, problem definition and prototyping, all of which sit uncomfortably within more traditional planning models that ask project leaders to predict in advance what both the problem and the solution are.

The project is detailed in the contract as a seven step process — with Kogan's company, GSR, generating an initial seed sample (though it does not specify how large this is here) using «online panels»; analyzing this seed training data using its own «psychometric inventories» to try to determine personality categories; the next step is Kogan's personality quiz app being deployed on Facebook to gather the full dataset from respondents and also to scrape a subset of data from their Facebook friends (here it notes: «upon consent of the respondent, the GS Technology scrapes and retains the respondent's Facebook profile and a quantity of data on that respondent's Facebook friends»); step 4 involves the psychometric data from the seed sample, plus the Facebook profile data and friend data all being run through proprietary modeling algorithms — which the contract specifies are based on using Facebook likes to predict personality scores, with the stated aim of predicting the «psychological, dispositional and / or attitudinal facets of each Facebook record»; this then generates a series of scores per Facebook profile; step 6 is to match these psychometrically scored profiles with voter record data held by SCL — with the goal of matching (and thus scoring) at least 2M voter records for targeting voters across the 11 states; the final step is for matched records to be returned to SCL, which would then be in a position to craft messages to voters based on their modeled psychometric scores.

The Mate 10 uses on - device processing to build a model of how you use the phone and allocates resources accordingly with machine learning predicting user behavior.

The target selection process is favorable by many employers who opt for the concept that past performance / behavior predicts future performance - the targeted selection model of interviewing is a well known method these days and used by many recruiters.

The aims of the project are to (1) develop a culturally specific parent training intervention for Latino families with youngsters at risk for substance use and related problems, (2) evaluate implementation feasibility and initial efficacy of the intervention in a pilot study, (3) develop and refine measurement methods for assessing Latino individual family processes, and (4) test an integrative theoretical model that hypothesizes how social and acculturation contexts, family stress processes, and parenting practices are linked to predict Latino youngster adjustment.