Some recent developments for the validation of nonlinear models built from data are reviewed. Besides giving an overall view of the field, a procedure is proposed and investigated based on the concept of dissipative synchronization between the data and the model, which is very useful in validating models that should reproduce dominant dynamical features, like bifurcations, of the original syste...

The research presented in this article is aimed at the development of an automated imaging system for classification of tissues in medical images obtained from Computed Tomography (CT) scans. The article focuses on using ridgelet-based multi-resolution texture analysis. The approach consists of two steps: automatic extraction of the most discriminative texture features of regions of interest an...

We present a novel Discriminant Locality Preserving Projections (DLPP) algorithm named Collaborative Discriminant Locality Preserving Projection (CDLPP). In our algorithm, the discriminating power of DLPP are further exploited from two aspects. On the one hand, the global optimum of class scattering is guaranteed via using the between-class scatter matrix to replace the original denominator of ...

Model-based attempts to rigorously study the broad and imprecise concept of 'discriminating power' are scarce, and generally limited to nonlinear models for binary responses. This paper proposes a comprehensive framework for assessing the discriminating power of item and test scores which are analyzed or obtained using Spearman’s factor-analytic model. The proposed framework is organized on the...

We describe an opinion analysis system developed for Multilingual Opinion Analysis Task at NTCIR7. Given a topic and relevant newspaper articles, our system determines whether a sentence in the articles carries an opinion, if so, then extract the polarity and holder of the opinion. Our system uses subjectivity lexicons to score the sentiment weight of a word, in addition with a weight that refl...

Two crucial problems arise from a microarray experiment in which the primary objective is to locate differentially expressed genes for the diagnosis of diseases such as cancer and Alzheimer's. The first problem is the detection of a subset of genes which provides an optimum discriminatory power between diseased and normal subjects, and the second problem is the statistical estimation of discrim...

This paper presents the results of applying a Genetic Programming (GP) based feature selection algorithm to find a small set of highly discriminating features for the detection of clinical depression from a patient’s speech. While the performance of the GP-based classifiers was not as good as hoped for, several Bayesian classifiers were trained using the features found via GP and it was determi...

In the context of the application of WFD, a scientific debate is growing about the applicability of biotic indices in coastal and transitional waters. In the present work, the question about the discriminating power of different biotic indices and the relationships with the structure and functioning of the macrobenthic community in a transitional environment is discussed. A time series of sampl...

Existing gait recognition approaches do not give their theoretical or experimental performance predictions. Therefore, the discriminating power of gait as a feature for human recognition cannot be evaluated. In this paper, we first propose a kinematic-based approach to recognize human by gait. The proposed approach estimates 3D human walking parameters by performing a least squares fit of the 3...

Optimized jet substructure observables for identifying boosted topologies will play an essential role in maximizing the physics reach of the Large Hadron Collider. Ideally, the design of discriminating variables would be informed by analytic calculations in perturbative QCD. Unfortunately, explicit calculations are often not feasible due to the complexity of the observables used for discriminat...