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Evolution of blended learning in a large enrolment subject: What was blended and why

by Tim Griffin, Rosemary Thomson - In Hello! Where are you in the landscape of educational technology? Proceedings ascilite Melbourne 2008. http://www.ascilite.org.au/conferences/melbourne08/procs/griffin.pdf , 2008
"... was blended and why? ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
was blended and why?

The spread of obesity in a large social network over 32 years

by Nicholas A. Christakis, James H. Fowler - NEW ENGLAND JOURNAL OF MEDICINE , 2007
"... The prevalence of obesity has increased substantially over the past 30 years. We performed a quantitative analysis of the nature and extent of the person-to-person spread of obesity as a possible factor contributing to the obesity epidemic. Methods We evaluated a densely interconnected social networ ..."
Abstract - Cited by 509 (23 self) - Add to MetaCart
network of 12,067 people assessed repeatedly from 1971 to 2003 as part of the Framingham Heart Study. The body-mass index was available for all subjects. We used longitudinal statistical models to examine whether weight gain in one person was associated with weight gain in his or her friends, siblings

For Most Large Underdetermined Systems of Linear Equations the Minimal ℓ1-norm Solution is also the Sparsest Solution

by David L. Donoho - Comm. Pure Appl. Math , 2004
"... We consider linear equations y = Φα where y is a given vector in R n, Φ is a given n by m matrix with n < m ≤ An, and we wish to solve for α ∈ R m. We suppose that the columns of Φ are normalized to unit ℓ 2 norm 1 and we place uniform measure on such Φ. We prove the existence of ρ = ρ(A) so that ..."
Abstract - Cited by 568 (10 self) - Add to MetaCart
that for large n, and for all Φ’s except a negligible fraction, the following property holds: For every y having a representation y = Φα0 by a coefficient vector α0 ∈ R m with fewer than ρ · n nonzeros, the solution α1 of the ℓ 1 minimization problem min �x�1 subject to Φα = y is unique and equal to α0

Estimating Wealth Effects without Expenditure Data— or Tears

by Deon Filmer, Lant Pritchett - Policy Research Working Paper 1980, The World , 1998
"... Abstract: We use the National Family Health Survey (NFHS) data collected in Indian states in 1992 and 1993 to estimate the relationship between household wealth and the probability a child (aged 6 to 14) is enrolled in school. A methodological difficulty to overcome is that the NFHS, modeled closely ..."
Abstract - Cited by 871 (16 self) - Add to MetaCart
reasonable coherence with current consumption expenditures and most importantly, works as well, or better, than traditional expenditure based measures in predicting enrollment status. When the asset index is applied to the Indian data the results show large, and variable, wealth gaps in the enrollment

The PageRank Citation Ranking: Bringing Order to the Web

by Lawrence Page, Sergey Brin, Rajeev Motwani, Terry Winograd - Stanford InfoLab , 1999
"... The importance of a Web page is an inherently subjective matter, which depends on the readers interests, knowledge and attitudes. But there is still much that can be said objectively about the relative importance of Web pages. This paper describes PageRank, a method for rating Web pages objectively ..."
Abstract - Cited by 3269 (1 self) - Add to MetaCart
The importance of a Web page is an inherently subjective matter, which depends on the readers interests, knowledge and attitudes. But there is still much that can be said objectively about the relative importance of Web pages. This paper describes PageRank, a method for rating Web pages objectively

LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares

by Christopher C. Paige, Michael A. Saunders - ACM Trans. Math. Software , 1982
"... An iterative method is given for solving Ax ~ffi b and minU Ax- b 112, where the matrix A is large and sparse. The method is based on the bidiagonalization procedure of Golub and Kahan. It is analytically equivalent to the standard method of conjugate gradients, but possesses more favorable numerica ..."
Abstract - Cited by 653 (21 self) - Add to MetaCart
An iterative method is given for solving Ax ~ffi b and minU Ax- b 112, where the matrix A is large and sparse. The method is based on the bidiagonalization procedure of Golub and Kahan. It is analytically equivalent to the standard method of conjugate gradients, but possesses more favorable

Maté: A Tiny Virtual Machine for Sensor Networks

by Philip Levis, David Culler , 2002
"... Composed of tens of thousands of tiny devices with very limited resources ("motes"), sensor networks are subject to novel systems problems and constraints. The large number of motes in a sensor network means that there will often be some failing nodes; networks must be easy to repopu-late. ..."
Abstract - Cited by 510 (21 self) - Add to MetaCart
Composed of tens of thousands of tiny devices with very limited resources ("motes"), sensor networks are subject to novel systems problems and constraints. The large number of motes in a sensor network means that there will often be some failing nodes; networks must be easy to repopu

Atmospheric Modeling, Data Assimilation and Predictability

by Eugenia Kalnay , 2003
"... Numerical weather prediction (NWP) now provides major guidance in our daily weather forecast. The accuracy of NWP models has improved steadily since the first successful experiment made by Charney, Fj!rtoft and von Neuman (1950). During the past 50 years, a large number of technical papers and repor ..."
Abstract - Cited by 626 (33 self) - Add to MetaCart
Numerical weather prediction (NWP) now provides major guidance in our daily weather forecast. The accuracy of NWP models has improved steadily since the first successful experiment made by Charney, Fj!rtoft and von Neuman (1950). During the past 50 years, a large number of technical papers

Mining the Network Value of Customers

by Pedro Domingos, Matt Richardson - In Proceedings of the Seventh International Conference on Knowledge Discovery and Data Mining , 2002
"... One of the major applications of data mining is in helping companies determine which potential customers to market to. If the expected pro t from a customer is greater than the cost of marketing to her, the marketing action for that customer is executed. So far, work in this area has considered only ..."
Abstract - Cited by 568 (11 self) - Add to MetaCart
|can be extremely eective, but is still a black art. Our work can be viewed as a step towards providing a more solid foundation for it, taking advantage of the availability of large relevant databases. Categories and Subject Descriptors H.2.8 [Database Management]: Database Applications| data mining

Numerical integration of the Cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes

by Jean-paul Ryckaert, Giovanni Ciccotti, Herman J. C. Berendsen - J. Comput. Phys , 1977
"... A numerical algorithm integrating the 3N Cartesian equations of motion of a system of N points subject to holonomic constraints is formulated. The relations of constraint remain perfectly fulfilled at each step of the trajectory despite the approximate character of numerical integration. The method ..."
Abstract - Cited by 704 (6 self) - Add to MetaCart
A numerical algorithm integrating the 3N Cartesian equations of motion of a system of N points subject to holonomic constraints is formulated. The relations of constraint remain perfectly fulfilled at each step of the trajectory despite the approximate character of numerical integration. The method
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