The elicitation of power priors, based on the availability historical data, is realized by raising likelihood function data to a fractional δ, which quantifies degree discounting information in making inference with current data. When δ not pre-specified and treated as random, it can be estimated from using Bayesian updating paradigm. However, original form joint prior approach, certain positiv...

with rapid economic development and industrialization, the construction industry continues to rank among the most hazardous industries in the world. therefore, construction safety is always a significant concern for both practitioners and researchers. the objective of this study was to create a structural modeling of components that influence the safety performance in construction projects.we f...

We propose novel speaker independent (SI) modeling and speaker adaptation based on a linear transformation. An SI model and speaker dependent (SD) models are usually generated using the same preprocessing of acoustic data. This straightforward preprocessing causes a serious problem. Probability distributions of the SI models become broad and the SI models do not give good initial estimates for ...

Online learning has witnessed an increasing interest over the recent past due to its low computational requirements and relevance a broad range of streaming applications. In this brief, we focus on online regularized regression. We propose novel efficient regression algorithm, called normalized least-squares (ONLS). perform theoretical analysis by comparing total loss ONLS against gradient desc...

BACKGROUND AND OBJECTIVE In many clinical situations, measurement of the total drug concentration does not provide the needed information concerning the fraction of unbound drug in plasma, which is available for pharmacodynamic action. To address this, a 'normalized concentration' can be calculated on the basis of the observed total drug concentration and the serum protein level. Up to now, thi...

We propose a novel approach for solving the perceptual grouping problem in vision. Rather than fo-cusing on local features and their consistencies in the image data, our approach aims at extracting the global impression of an image. We treat image segmenta-tion as a graph partitioning problem and propose a novel global criterion, the normalized cut, for segmenting the graph. The normalized cut ...