This study presents a system for classifying echolocation clicks of six species of odontocetes in the Southern California Bight: Visually confirmed bottlenose dolphins, short- and long-beaked common dolphins, Pacific white-sided dolphins, Risso's dolphins, and presumed Cuvier's beaked whales. Echolocation clicks are represented by cepstral feature vectors that are classified by Gaussian mixture...

The geometric opinion pool (GOP) ensemble method uses a multiplicative combination of predictors, and it is tailored to probability estimation in multi-class problems. This enables a decomposition of the KullbackLeibler entropy error function into an ambiguity term and an average error term. This can be used to estimate generalization error with a combination of cross-validation and estimation ...

Total body water (TBW) measured by isotope dilution techniques can be used to assess body composition safely and accurately in children. Unfortunately, this method is not readily available for most research projects, particularly when working with large groups of people, because the equipment is complicated and highly specialized. Bioelectrical impedance (BI) method is a simple, quick, and inex...

a reliable quantitative structure retention relationship (qsrr) study has been evaluated to predict the retention indices (ris) of a broad spectrum of compounds, namely 118 non-linear, cyclic and heterocyclic terpenoids (both saturated and unsaturated), on an hp-5ms fused silica column. a principal component analysis showed that seven compounds lay outside of the main cluster. after elimination...

Biopartitioning micellar chromatography (BMC) is a mode of micellar liquid chromatography that uses micellar mobile phases of Brij35 under adequate experimental conditions and can simulate biopartioning process of many kinds of drugs and describe their biological behavior. The capability of BMC to describe and estimate pharmacokinetic and pharmacodynamic parameters of angiotensin-converting enz...

This article describes a new unsupervised methodology to learn F0 classes using HMM on a syllable basis. A F0 class is represented by a HMM with three emitting states. The unsupervised clustering algorithm relies on an iterative gaussian splitting and EM retraining process. First, a single class is learnt on a training corpus (8000 syllables) and it is then divided by perturbing gaussian means ...

This article describes a new unsupervised methodology to learn F0 classes using HMM models on a syllable basis. A F0 class is represented by a HMM with three emitting states. The clustering algorithm relies on an iterative gaussian splitting and EM retraining process. First, a single class is learnt on a training corpus (8000 syllables) and it is then divided by perturbing gaussian means of suc...

Model selection and validation are critical in predicting the performance of manufacturing processes. The correct selection of variables minimizes the model mismatch error whereas the selection of suitable models reduces the model estimation error. Models are validated to minimize the model prediction error. In this paper, the relevant literature is reviewed and a procedure is proposed for the ...

Often, in a regression situation with many variables, a sequence of submodels is generated containing fewer variables using such methods as stepwise addition as deletion of variables, or "best subsets". The question is which of this sequence of submodels is "best", and how can submodel perfornance be evaluated. This was explored in Breiman [1988] for a fixed X-design. This is a sequel exploring...