We predict the ellipticity of galaxies from a variety of variables available through data from the Canada-France-Hawaii Lensing Survey. A survey of regression methods, including both nonparametric and tree-based methods, are applied to the prediction problem and results are discussed and compared. We present graphical methods for finding interactions between predictors. Leaveone-out cross-valid...

MARK T. HOLDER1,∗, PAUL O. LEWIS2, AND DAVID L. SWOFFORD3,4 1Department of Ecology and Evolutionary Biology, University of Kansas, 1200 Sunnyside Avenue, Lawrence, KS 66045, USA; 2Department of Ecology and Evolutionary Biology, University of Connecticut, 75 North Eagleville Road, Unit 3043, Storrs, CT 06269-3043, USA; 3Institute for Genome Sciences and Policy Center for Evolutionary Genomics, D...

Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your perso...

Among different candidate parametric detection functions, it is suggested to use Akaike Information Criterion (AIC) to select the most appropriate one of them to fit line transect data. Four different detection functions are considered in this paper. Two of them are taken to satisfy the shoulder condition assumption and the other two estimators do not satisfy this condition. Once the appropriat...

The information of first-arrival time of acoustic emission (AE) signal is important in event location, event identification and source mechanism analysis. Manual picks are time-consuming and sometimes subjective. Several approaches are used in practice. New first arrival automatic determination technique of AE signals in thin metal plates is presented. Based on Akaike information criterion (AIC...

Acoustic emission (AE) method enables real-time monitoring of damage initiation and progression. Recently, AE analysis using machine learning has become widely popular; however, the source location is often located manually to ensure reliability accuracy. Therefore, it desirable that detection fully automated with a high This study proposes novel arrival time identification for can accurately a...

Wireless sensor networks rely on sensor devices deployed in an environment to support sensing and monitoring, including temperature, humidity, motion, and acoustic. Here, we propose a new approach to model physical phenomena and track their evolution by taking advantage of the recent developments of pattern recognition for nonlinear functional learning. These methods are, however, not suitable ...

In this paper, we describe audiovisual automatic speech recognition experiments carried using visual parameters extracted from “natural” images. Unlike many other experiments in the AV ASR field, these visual parameters are obtained without any hand-labeling phase and are naturally noisy, due to the extraction process. We evaluate our models with different strategies among which : use of a shap...

-The isochromatic fringe patterns surrounding an intersonically propagating interface crack are developed and characterized using the recently developed stress field equations. A parametric investigation is conducted to study the influence of various parameters such as the crack-tip velocity and the contact coefficient on the isochromatic fringe patterns. It has been observed that the crack-tip...

This study presents the development of classification and regression tree (CART), artificial neural network (ANN) and linear regression approaches to predict the critical submergence in an open channel flow for different clearance bottoms. To use the models for application purposes and cover the wide range of inputs, the nondimensional parameters are employed to train and test. The testing resu...