Sentences with phrase «scale data because»

The BRAIN Initiative is really about developing new technologies to acquire large - scale data because we have new ways to manage those data, analyze them and build models from them.

Not exact matches

Kate Mitchell, managing director at the venture capital firm Scale Venture Partners and a co-chairwoman of a National Venture Capital Association task force on diversity, said her group was working with Project Include because of its tech - centric, start - up approach to sharing data and information with other participants.

The fact that it wasn't suggests that in the beginning, at least, the exploitability of Facebook's API was seen as a feature, not a bug — because no one was thinking that a third - party app might utilize its access to user data at the scale Cambridge Analytica did.

But at the end of the day, scale can only progress so far, because link building, ultimately, isn't a game of who can enter data the fastest, it's a game of who's the best at human interaction.

Because small - scale farmers grow up to 70 percent of all the food consumed throughout the world, WeFarm helps provide data to multinational food and beverage companies that source from these farmers.

Identifying core components of interventions found to be effective and understanding what it takes to implement those components with fidelity to the program model is critical to successful replication and scale - up of effective programs and practices in different community contexts and populations.7 There is growing recognition in the early childhood field of the importance of effective implementation and the need for implementation research that can guide adoption, initial implementation, and ongoing improvement of early childhood interventions.8, 9,10 The promise of implementation research and using data to drive program management is compelling because it offers a potential solution to the problem of persistent gaps in outcomes between at - risk children and their more well - off peers.

Although geologists can use seismic data from large earthquakes to see features deep in the earth, the shallow subsurface geology of the park has remained a mystery, because mapping it out would require capturing everyday miniature ground movement and seismic energy on a much smaller scale.

Until now, such large - scale data storage has been impractical because of the difficulty and cost of reading and writing long sequences of DNA.

The detailed models produced using the MT imaging data of the southwestern U.S. more accurately portrayed surface structures at a scale of less than 100 kilometers, Liu said, which is important because features like volcanoes and faults are localized phenomena that are harder to predict using larger - scale models.

What is more, «we are investigating Semantic Web technologies because traditional approaches for data integration, knowledge management and decision support will not scale to what is needed for personalized medicine,» says John Glaser, chief information officer at Partners HealthCare System in Boston.

General Motors is well placed for crowdsourcing because it has the scale to collect large amounts of data quickly.

The time I spent on the audit team taught me a lot about research design and data management, which was very helpful because my background research experience didn't include the design of large - scale experiments.

But tangled copyright protections make it difficult to access musical data sets on a large scale, because even data mining of musical recordings may not be allowed without permission.

In addition, the data density and geographic extent of this study is far greater than most previous studies because over 16,000 stream temperature sites were used with thousands of biological survey locations to provide precise information at scales relevant to land managers and conservationists.

Alex said: «For years ecologists have struggled to test or extend models of ecosystem - level change because the data were too expensive to collect at the required scales.

Unfortunately, it won't be easy to verify the new method, because fine - scale endemics - species distribution and habitat data are rare.

Because the data don't go beyond 2009, WHO has little or no evidence of progress in 31 other African countries, including big ones like Nigeria and the Democratic Republic of the Congo, where bed nets have only recently been introduced on a large scale.

«The savings increase with scale because we are exploiting the inherent sparsity in big data,» he said.

Few smaller - scale projects release their data, however — possibly because they don't have to.

A number of recent studies indicate that effects of urbanisation and land use change on the land - based temperature record are negligible (0.006 ºC per decade) as far as hemispheric - and continental - scale averages are concerned because the very real but local effects are avoided or accounted for in the data sets used.

The upper tail is particularly long in studies using diagnostics based on large - scale mean data because separation of the greenhouse gas response from that to aerosols or climate variability is more difficult with such diagnostics (Andronova and Schlesinger, 2001; Gregory et al., 2002a; Knutti et al., 2002, 2003).

A lot of available posts on the internet like to serve as romantic stories how we should eat like cavemen «Because that is how our ancestors ate», «it is the right thing to do», «we are not evolved to eat grains, because they did not eat them» we this and that and what not... The thing is, there is actually a substantial amount of direct, clear evidence that supports this eating pattern as one of the healthiest known to people (I dare not say healthiest due to lack of large scale and more long - termBecause that is how our ancestors ate», «it is the right thing to do», «we are not evolved to eat grains, because they did not eat them» we this and that and what not... The thing is, there is actually a substantial amount of direct, clear evidence that supports this eating pattern as one of the healthiest known to people (I dare not say healthiest due to lack of large scale and more long - termbecause they did not eat them» we this and that and what not... The thing is, there is actually a substantial amount of direct, clear evidence that supports this eating pattern as one of the healthiest known to people (I dare not say healthiest due to lack of large scale and more long - term data).

Digital technologies have transformed our lives because: • We can store, process and transmit data in digital form faster, and on a larger scale, than any other technology in human history (speaking, writing, or printing) • We can describe a wide range of problems for the data we can collect or create, solve them by manipulating that data, and (sometimes) actuate change in the physical world

The reporters provide the reader with a host of mostly misleading state - provided test - score data, because the State of New York mis - constructed the proficiency scales on its statewide tests, thereby rendering interpretation of scores over time virtually impossible.

With the push for development of longitudinal data systems during the pit of the Great Recession, many issues surrounding the Common Core State Standards Initiative and its «next generation» tests were not fully vetted in the arena of public opinion partially because it became a «best practice» to «not engage in large scale, open forums.»

Until now, very few developers have been able to build, deploy, and broadly scale apps with AI capabilities because doing so required access to vast amounts of data, and specialized expertise in machine learning and neural networks.

I know David Gaughran has some fairly accurate estimations that he's used before, but here's a what if for you: What if you could accurately model Amazon's ebook sales using data submitted by selfpub authors (which I remember seeing a blogger on the Writer's Cafe who was already doing this with extreme accuracy) combined with a sliding scale, using the same data, to determine sales at any given time (because being the # 5 bestseller in the Mystery category on Tuesday doesn't mean the same sales on Thursday).

All this talk regarding 4G blackberries... Remember guys — One huge plus with BB is their data management... BB use much less DATA than all other smartphones, which also means the higher speed isn't as necessary because the content is scaled down / processed before it gets to your phone...

This is critical because the normal R ² value for the log linear transformed exponential growth models often underestimates the prediction error in the most recent years of growth because it fails to capture the overestimate of growth in the most current years of data since FCF is still in a log scale.

But to counter Tan a little — because we use a network of people who are focused on data gathering using digital tools tools, scale isn't as great an issue for us.

Given that the answer to this for atmospheric models is a resounding «NO» (particularly because of sub-grid scale processes which need to be effectively pre-ordained through parameterizations), and given that oceanic circulations have much longer adjustment time scales, yet also have much more intense small scale (gyre) circulations than the atmosphere, my instinct is that we are not even close to being able to trust ocean models without long term validation data.

For temperature scales where there are negative values in the data set, root mean square will not produce a meaningful result because negative and positive values of the same magnitude contribute the same positive amount to the average.

Consequently, the inferences and conclusions made by Briske et al. [1,2,3] do not represent the subject adequately because conclusions have been selectively chosen so as to exclude published data showing superior results at commercial ranch scale from adaptively managed multi-paddock grazing.

Because the analysis method and sparse data used in this study will tend to blur out most century - scale changes, we can't use the analysis of Marcott et al. to draw any firm conclusions about how unique the rapid changes of the twentieth century are compared to the previous 10,000 years.

This report is important because it is the first global - scale attempt to systematically translate fragmented data into quantitative environmental impacts of products throughout their life - cycle.»

Data is made up Data is ok but not related Data is related but not on the time scale Data is no good at Tromso but is ok at Honolulu Data is all fine but it correlation is spurious, because some woman found one

I'd expect more variability will be found at any scale you get data for, always revealing a need for yet longer spans of data in order to sort it out, because you can't sort a span out with data short compared to it.

A number of analysis methods have a tendency to lose variance at a range of time scales either because they do not explicitly resolve small scale processes (Kaplan et al. 1997, Smith et al. 2008) or because in the absence of data the method tends towards the climatological average (Ishii et al. 2005).

In fact, recent data indicates that small - scale and community - based wind projects have 3.5 times the economic benefit for local communities because the owners typically reside where the farm has been built.

http://webpages.charter.net/wtelle/Warming/Vostok.jpg These are data from the Vostok ice core, units not implied on the y - axis because the scales have been normalized to track changes.

The team's conclusions were much less definitive for the Southern Hemisphere and on a global scale, which they believe is because data for the south is much more sparsely available.

However, because only large - scale, first - order patterns are reconstructed, similar patterns of spatial / temporal covariance are found in the station data alone (otherwise, there would be very little skill in the reconstruction).

Because of the inclusion of new data and analysis, these new climatologies are an improvement over earlier PRISM climatologies of the region which were available at a scale of 4 kilometres.

However, there are no compelling data to suggest a confluence of climate - change impacts that would affect global production in either direction, particularly because relevant fish population processes take place at regional or smaller scales for which general circulation models (GCMs) are insufficiently reliable.

Because our main goal is to reproduce the centennial solar variability and because magnetograms are unavailable for historical time periods, we scale the faculae and the active network filling factors with the sunspot number instead of using filling factors derived from available magnetograBecause our main goal is to reproduce the centennial solar variability and because magnetograms are unavailable for historical time periods, we scale the faculae and the active network filling factors with the sunspot number instead of using filling factors derived from available magnetograbecause magnetograms are unavailable for historical time periods, we scale the faculae and the active network filling factors with the sunspot number instead of using filling factors derived from available magnetogram data.

Every graph, model, scale, picture, account, projection and forecast CAN NOT be believed because the raw data was deliberately perverted.

Climate models are amalgams of fundamental physics, approximations to well - known equations, and empirical estimates (known as parameterizations) of processes that either can't be resolved (because they happen on too small a physical scale) or that are only poorly constrained from data.

The longer data set of Snyder does not bulwark her climate sensitivity estimate, because her entire curve should be multiplied by the scale factor determined by the best documented glacial - interglacial transition.

I predict that these laws, most of which currently apply primarily to financial institutions, will ultimately incorporate some of the types of client information contained in attorney - client communications, in large part because of rising concerns due to recent large - scale data disclosures.

Clio «s Legal Trends Report aggregates data from paid Clio subscribers in 2015, which is a base of approximately 40,000 Clio users.1 Because people use Clio for timekeeping and billing and Clio keeps track of data like firm location and practice areas, Clio can compile that data and come to some large - scale conclusions about solo and small firms.