This is a survey on wearable computers consists of a comprehensive introduction and an overview of research activities in I/O interface, searching, communication, and power.

We propose a new kind of finite-state automata, suitable for structured input characters corresponding to unranked trees of small depth. As a motivating application, we regard executing morphosyntactic queries on a richly annotated text corpus.

Such differences may also be responsible for the cause of hereditary disease. Genetic Association Hypothesis testing then is the study to find which SNP’s are causal (or associated) vis-a-vis a hereditary disease. Going site to site we try and associate the genotype with a phenotype. Usually these genetic association mappings are very sparse, (1 in 1000) and may represent basic differences in b...

in the present study, an application of multilevel modeling approach to the input- output analysis are presented first, the regional input-output table of all provinces in iran was extracted based on the adjusted flegg location quotient method (aflq). second differentiation in the leontief technical coefficients and the backward and forward linkages among various activities and sectors of all p...

This paper presents an environment for collecting clinical data using structured speech input. The system uses nomenclature terms and data consistency rules to limit speech input to a discrete set of phrases which can be configured to support a wide range of studies. This information is stored in an eventoriented data model as strongly typed observations for subsequent distribution and data ana...

We employ a recently introduced structured input-output analysis (SIOA) approach to analyze streamwise and spanwise wavelengths of flow structures in stably stratified plane Couette flow. In the low-Reynolds number ($Re$) low-bulk Richardson ($Ri_b$) spatially intermittent regime, we demonstrate that SIOA predicts high amplification associated with corresponding characteristic oblique turbulent...

Abstract Artificial neural networks are referred to as universal approximators due their inherent ability reconstruct complex linear and nonlinear output maps conceived input-output relationships from data sets. This can be done by reducing large via regularization in order establish compact models containing fewer parameters aimed at describing vital dependencies In situations where the sets c...