Clustering is automated identification of groups of objects based on similarity. In clustering two major research issues are scalability and the requirement of domain knowledge to determine input parameters. Most approaches suggest the use of sampling to address the issue of scalability. However, sampling does not guarantee the best solution and can cause significant loss in accuracy. Most appr...

one of recent developments in modern societies is the evolution in the structure of power division in the family and changes in reciprocal actions between wife and husband. this research aims to study the factors affecting distribution of power in the family by using the theories of: social capital, valuable resources, and sociability of gender. the data has been collected through survey method...

Cluster sampling has recently been used to estimate the mortality in various conflicts around the world. The Burnham et al. (2006) study on Iraq employs a new variant of this cluster sampling methodology. The stated methodology of Burnham et al. (2006) is to (1) select a random main street, (2) choose a random cross street to this main street, and (3) select a random household on the cross stre...

A multi-stage cluster sampling is proposed for quantifying and monitoring plant species richness at multiple spatial grains over large spatial extents. An unbiased estimator of average species richness at different grains and a conservative estimator of its sampling variance are obtained in a complete design-based framework, i.e., avoiding any assumption about the ecological community under stu...

Scott and Smith (1969) develop estimators for linear functions from a two stage cluster sample, with their discussion repeated in many places. This discussion was reviewed in c01ed13.doc. It is note-worthy that Scott and Smith allow expressions for the variance to depend on the cluster. A similar development is given by Vallient et al.. We repeated the derivation of Vallient et al using the fin...

A technique is presented that permits fast view-reconstruction of individual objects. This method improves a previous approach to solve the problem of approximated view reconstruction by combining clustering of polygons with visibility bitfields to determine visibility for novel viewpoints. The technique consists of three steps: patch creation, spherical sampling, and rendering. In the first st...

in this paper an application of the cluster analysis technique in educational planning is demonstrated by means of a developed computer software with some characteristics of an expert system. the main idea is based on the knowledge-based systems which have been applied in group technology. the software is applied to weekly schedules of the courses and professors of the industrial engineering de...

BACKGROUND Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate t...