Framing: Toward Clarification of a Fractured Paradigm
Journal Article Framing: Toward Clarification of a Fractured Paradigm Get access Robert M. Entman Robert M. Entman 1Robert M. Entman is an associate professor of communication s...
Explore 3,575 academic publications
Journal Article Framing: Toward Clarification of a Fractured Paradigm Get access Robert M. Entman Robert M. Entman 1Robert M. Entman is an associate professor of communication s...
Neural machine translation is a recently proposed approach to machine translation. Unlike the traditional statistical machine translation, the neural machine translation aims at...
This third edition of Braun and Murdoch's bestselling textbook now includes discussion of the use and design principles of the tidyverse packages in R, including expanded covera...
influenced particles characteristics in Northern Territory Australia based on airborne measurements. Atmospheric Research, 96(1). pp. 103-109.
Abstract We present here a framework for the study of molecular variation within a single species. Information on DNA haplotype divergence is incorporated into an analysis of va...
Abstract The relationship between the two estimates of genetic variation at the DNA level, namely the number of segregating sites and the average number of nucleotide difference...
Abstract IQ-TREE (http://www.iqtree.org, last accessed February 6, 2020) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood....
Journal Article Markets and Hierarchies: Analysis and Antitrust Implications Get access Markets and Hierarchies: Analysis and Antitrust Implications. By O. E. WILLIAMSON. (Londo...
Data Analysis Using Regression and Multilevel/Hierarchical Models, first published in 2007, is a comprehensive manual for the applied researcher who wants to perform data analys...
This book presents the econometric analysis of single-equation and simultaneous-equation models in which the jointly dependent variables can be continuous, categorical, or trunc...
Deep Neural Networks (DNNs) are powerful models that have achieved excellent performance on difficult learning tasks. Although DNNs work well whenever large labeled training set...