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We study an intensive math instruction policy that assigned low-skilled ninth graders to an algebra course that doubled instructional time, altered peer composition and emphasized problem solving skil...
Knowledge-intensive firms are a growing and increasingly important part of our economy. They compete by bringing their knowledge resources to bear on their customers’ challenging problems. Such knowle...
Ten international research agencies, including the United State's National Science Foundation (NSF), recently announced the winners of the third Digging into Data Challenge.
The promotion work 'The Estimation of Transport Logistic Processes Models on the Base of Intensive Computer Methods of Statistics' has been worked out by Helen Afanasyeva to obtain the scientific degr...
How much of the income-based gaps in cognitive ability and academic achievement could be closed by a two-year, center-based early childhood education intervention? Data from the Infant Health and Deve...
A new distribution called intensive natural distribution is introduced with the intent of merging statistics and empirical data. Based on the probability derived from the Bernoulli distribution, this ...
ART is labour intensive. Important reductions in doctor-time per patient can be realized during scaling-up. The doctor-based ART delivery model analysed seems adequate for Cambodia. However, for many ...
This paper explores the motivation for information exchange between firms within a knowledge-intensive industry. The qualitative empirical data is gathered from the Finnish games industry which consis...
The knowledge management scan, which has been developed by the Centre of Research in Knowledge Organisations and Knowledge Management of Zuyd University Heerlen, the Netherlands, initiates from two mo...
Nonlinear regression is a useful statistical tool, relating observed data and a nonlinear function of unknown parameters. When the parameter-dependent nonlinear function is computationally intensive...

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