A uniform approach to fundamental sequences and hierarchies

In this article we give a unifying approach to the theory of fundamental sequences and their related Hardy hierarchies of number-theoretic functions and we show the equivalence of the new approach with the classical one

An empirical evaluation of imbalanced data strategies from a practitioner's point of view

This research tested the following well known strategies to deal with binary imbalanced data on 82 different real life data sets (sampled to imbalance rates of 5%, 3%, 1%, and 0.1%): class weight, SMOTE, Underbagging, and a baseline (just the base classifier). As base classifiers we used SVM with RBF kernel, random forests, and gradient boosting machines and we measured the quality of the resulting classifier using 6 different metrics (Area under the curve, Accuracy, F-measure, G-mean, Matthew's correlation coefficient and Balanced accuracy). The best strategy strongly depends on the metric used to measure the quality of the classifier. For AUC and accuracy class weight and the baseline perform better; for F-measure and MCC, SMOTE performs better; and for G-mean and balanced accuracy, underbagging

Measuring Digital Opportunity for America's Children: Where We Stand and Where We Go From Here

Examines the connection between access to technology and the health, economic opportunity, community involvement, and educational achievement of youth. Makes recommendations for addressing the opportunity gap for low-income and ethnic-minority children

Motivation of R and D enterpreneurs - Determinants of company success

Human performance related to motivations of achievement, power, and company affiliations for determining leadership qualitie