This article presents a statistical theory for texture modeling. This theory combines filtering theory and Markov random field modeling through the maximum entropy principle, and interprets and clarifies many previous concepts and methods for texture analysis and synthesis from a unified point

Purpose: The students will learn, practice, and internalize strategies that are essential life-long learning skills for reading, writing, understanding, and interpreting content specific materials. The strategies will be applied in the content areas of English, mathematics, science, and social

Comprehension Skills during first two years at institute of higher education. They should be able to read, understand and interpret different sources of information connected with their future profession. To achieve this aim it’s important for university teachers to know how to check, control and evaluate

. The experimental results indicate that user eye gaze can provide useful information to establish such mappings, which have important implications in automatically acquiring and interpreting user vocabularies for conversational systems. 1

all to cultural-ist mentalism, textualism and intersubjectivism. The article shows how practice theory and the three other cultural-theoretical vocabularies differ in their localization of the social and in their conceptualization of the body, mind, things, knowledge, discourse, structure

in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Government. Keywords: Speech recognition, hidden Markov models, SPHINX-II 1. INTRODUCTION At Carnegie Mellon, wehave made significant progress in large-vocabulary

of the phonological loop in vocabulary acquisition and for interpreting data from functional neuroimaging.

Three experiments investigated the processes by which 2-year-olds acquire the language to express category hierarchies. The first experiment studied how children use current linguistic knowledge to constrain the potential meanings of new words. This experiment compared interpretations of new words

For over 30 years, the Smart project at Cornell University has been interested in the analysis, search, and retrieval of heterogeneous text databases, where the vocabulary is allowed to vary widely, and the subject matter is unrestricted. Such databases may include newspaper articles, newswire dispatches

associated with patient records, such as those of chronic patients. Providing visualization of the data and of their clinically meaningful interpretations (abstractions), and a capability to explore both, has multiple benefits for clinical care, research, and quality assessment. We describe a system