Fast variance prediction for iteratively reconstructed CT images is useful for the analysis of reconstruction algorithms and potentially for automatic tube current modulation. Prior methods are either computationally intractable or require impractical computation times to produce a map of the reconstructed image variance. In this paper we present the extension of prior work for fast variance pr...

Learning analytics (LA) is a growing research area, which aims at selecting, analyzing and reporting student data (in their interaction with the online learning environment), finding patterns in behaviour, displaying relevant information suggestive formats; end goal prediction of performance, optimization educational platform implementation personalized interventions. According to Society Analy...

introductapplication of neural network of multi layers perceptron (mlp) in site selection of municipal solid ‎waste landfilling with emphasis on hydrogeomorphic characteristics (case study: fereydoonshahr city)‎introduction‏:‏cities are at the nexus of a further threat to the environment, namely the production of an increasing ‎quantity and complexity of wastes. the estimated quantity of munici...

1 Some directions for MAP 2 Orographic Control of Precipitation: What are We Learning from MAP? 3 Alpine Numerical Weather Prediction 2000-2020: A Look Back to the Future 6 SOP 2000 — A better choice? 13 Mesoscale Alpine Climate (MAC) 15 “FACT” — Forecasting in Alpine and Complex Terrain 17 Summary of the final SSC and CIG Meetings 20 MAP Data Centre Status 22 MAP newsletter #15 24 Ongoing Acti...