Cluster analysis is a useful technique in multivariate statistical analysis. Different types of hierarchical cluster analysis and K-means have been used for data analysis in previous studies. However, the K-means algorithm can be improved using some metaheuristics algorithms. In this study, we propose simulated annealing based algorithm for K-means in the clustering analysis which we refer it a...

OBJECTIVE We introduce a structural-lexical approach for auditing SNOMED CT using a combination of non-lattice subgraphs of the underlying hierarchical relations and enriched lexical attributes of fully specified concept names. Our goal is to develop a scalable and effective approach that automatically identifies missing hierarchical IS-A relations. METHODS Our approach involves 3 stages. In ...

BACKGROUND Estimating the disease prevalence and test accuracy (sensitivity and specificity) for two dependent screening tests when the status of individuals who are negative on both tests is unverified represents a considerable challenge, as the disease rates for individuals negative on both tests are not identifiable without additional assumptions. METHODS This article presents a unified fr...

the hierarchical hub location problem is encountered three-level network that is applied in production-distribution system, education system, emergency medical services, telecommunication network, etc. this paper addresses the hierarchical hub covering problem with single assignment accounting for mandatory dispersion of central hubs restriction as a special case. this formulation with incorpor...

Bayesian hierarchical models typically involve specifying prior distributions for one or more variance components. This is rather removed from the observed data, so specification based on expert knowledge can be difficult. While there are suggestions for ‘default’ priors in the literature, often a conditionally conjugate inverse-gamma specification is used, despite documented drawbacks with thi...

In system design, allocation of circuit resources like power and noise budget is a difficult problem. It is difficult to know the optimal distribution of resources because the performance space of each component is not fully characterized. This uncertainty results in an iterative approach with frequent re-design of circuit blocks for different distribution schemes. Equation-based optimization h...

This paper addresses the task of producing candidate regions for detecting objects (e.g., car, cat) and background regions (e.g., sky, water). We describe a simple and rapid algorithm which generates a set of candidate regions CR by combining up to three ”selected-segments”. These are obtained by a hierarchical merging algorithm which seeks to identify segments corresponding to roughly homogene...