My broad research interest is in dependable systems, in particular developing fault-tolerant distributed algorithms and applying them to practical problems. Developing dependable systems is an important goal as we increasingly rely upon large-scale wide-area distributed systems to support a wide range of online services. As systems scale in size and extent, efficiently coping with failures is a...

In this paper we propose a Bayesian approach for inference about dependence of high throughput gene expression. Our goals are to use prior knowledge about pathways to anchor inference about dependence among genes; to account for this dependence while making inferences about differences in mean expression across phenotypes; and to explore differences in the dependence itself across phenotypes. U...

In this paper, we present cluster-dependent acoustic modeling for large-vocabulary speech recognition. With large amount of acoustic training data, we build multiple cluster-dependent models (CDM), each focusing on a group of speakers in order to represent speaker-dependent characteristics. It is motivated by the fact that a sufficiently trained speaker-dependent (SD) model is better than the s...

There has been considerable interest in sketch based mesh modeling and editing, from the simple, intuitive interface of Teddy [1], to the more recent techniques to preserve detail in an existing mesh while modifying it with sketched strokes [2]. These approaches apply to editing a single mesh that is consistent in all views, but it is often the case in 2D animation that a character will have a ...

despite the crucial role of introductory sections in argumentative academic writing, the effects of genre- based approaches to writing introductory paragraphs have not been much explored yet. the present study aimed to investigate whether the provision of genre knowledge through modeling and non-modeling could enhance learners’ ability in writing introductory paragraphs of argumentative essays....

The abstract syntax of domain-specific modeling languages (DSMLs) can be defined with meta-models. Meta-models can contain errors. Nevertheless, they are not tested systematically and independently of dependent artifacts like models or tools. Consequently, errors are found late—not before the dependent artifacts have been created. Since all dependent artifacts must be adapted when an error is f...