Modeling consumer heterogeneity helps practitioners understand market structures and devise effective marketing strategies. In this research the authors study finite mixture specifications for modeling consumer heterogeneity when each regression coefficient has its own finite mixture, that is, an attribute finite mixture model. An important challenge of such an approach to modeling heterogeneit...

Although there have been some promising results in computer lipreading, there has been a paucity of data on which to train automatic systems. However the recent emergence of the TCDTIMIT corpus, with around 6000 words, 59 speakers and seven hours of recorded audio-visual speech, allows the deployment of more recent techniques in audio-speech such as Deep Neural Networks (DNNs) and sequence disc...

Multi-band speech recognition is powerful in band-limited noise, when the recognizer of the noisy band, which is less reliable, can be given less weight in the recombination process. An accurate decision on which bands can be considered as reliable and which bands are less reliable due to corruption by noise is usually hard to take. In this article, we investigate a maximum-likelihood (ML) appr...

This paper describes a flexible, cost-effective, wireless in-home activity monitoring system for assisting patients with cognitive impairments due to traumatic brain injury (TBI). The system locates the subject with fixed home sensors and classifies early morning bathroom activities of daily living with a wearable wireless accelerometer. The system extracts timeand frequencydomain features from...

A pasallcl partitioned for partitioning unstructured finite element meshes on distributed memory architectures is developed. The, element based partitioned can handle mixtures of different element types. All algoritlnns adopted in the partitioned are scalable, including a communication template for ullpredictable incoming messages, as shown in actual timing measurements.

We introduce and analyze a mixture model for supervised learning of probabilistic transducers. We devise an online learning algorithm that efficiently infers the structure and estimates the parameters of each model in the mixture. Theoretical analysis and comparative simulations indicate that the learning algorithm tracks the best model from an arbitrarily large (possibly infinite) pool of mode...

A finite mixture model is used to describe the diameter distributions of mixed-species forest stands. A three-parameter Weibull function is assumed as the component probability density function in the finite mixture model. Four example plots, each with two species, are selected to demonstrate model fitting and comparison. It appears that the finite mixture model is flexible enough to fit irregu...