Emotion classification is essential for understanding human interactions and hence is an important module in HumanComputer Interaction (HCI) systems. Well-performed emotion classification systems have potential to integrate into the HCI systems to provide additional user state details. This paper presents an emotion classification system that employs Emotional Dissimilarity (ED) measure. Instea...

We motivate and describe a GMM method of estimating linear dynamic models from a time series of independent cross-sections. This involves subjecting the model to a quasi-di!erencing transformation across pairs of individuals that belong to the same group. Desirable features of the model include the fact that: (i) no aggregation is involved, (ii) dynamic response parameters can vary across group...

s tructural change is defined as a change in the relative weight of the important constituents of the macro-economic indicator such as production, taxes, imports and exports, workforce etc. since the structure change is one of the main reasons for the growth and economic development of countries, the investigation of the trend of changes in economic important constituents is important. tax as a...

Gaussian mixture models (GMM) and support vector machines (SVM) are introduced to classify faults in a population of cylindrical shells. The proposed procedures are tested on a population of 20 cylindrical shells and their performance is compared to the procedure, which uses multi-layer perceptrons (MLP). The modal properties extracted from vibration data are used to train the GMM, SVM and MLP....

This paper considers the classification of radar target using Backscatter Doppler signature of moving object. Classification performance evaluated by the integrated Bispectrum based technique of feature extraction and compared it with Cepstrum based feature extraction technique. Classifier performance is tested by GMM (Gaussian Mixture Model) and ML (Maximal Likelihood) decision making method. ...

Variability in speech due to dialect is a major factor limiting speech system performance for speech recognition, spoken document retrieval, and dialog systems. In this study, we propose a novel discriminative algorithm to improve dialect classification for unsupervised spontaneous speech in Arabic. No transcripts are used for either training or testing, and all data are spontaneous speech. The...

This paper investigates a generalized method of moments (GMM) approach to the estimation of autoregressive roots near unity with panel data and incidental deterministic trends. Such models arise in empirical econometric studies of Þrm size and in dynamic panel data modeling with weak instruments. The two moment conditions in the GMM approach are obtained by constructing bias corrections to the ...

JEL Classification Code(s): J 31, J 71) "Perceptions of Discrimination, Effort to Obtain Psychological Balance, and Relative Wages: Can We Infer a Happiness Gradient?" There is a substantial literature that finds a linkage between happiness and relative economic well being as measured by earnings or wages. There is also a well documented racial gap in wages. One explanation for this is disparat...

This paper describes a line-based classification method, which labels TLS point clouds into vertical object, ground, tree and low objects. A local classifier implements labeling task on individual site independently of its neighborhood, the inference of which often suffers from similar local appearance across different object classes. In this paper, we describe an approach using contextual info...

Prototype classifiers are a type of pattern classifiers, whereby a number of prototypes are designed for each class so as they act as representatives of the patterns of the class. Prototype classifiers are considered among the simplest and best performers in classification problems. However, they need careful positioning of prototypes to capture the distribution of each class region and/or to d...