Hartigan’s method for k-means clustering is the following greedy heuristic: select a point, and optimally reassign it. This paper develops two other formulations of the heuristic, one leading to a number of consistency properties, the other showing that the data partition is always quite separated from the induced Voronoi partition. A characterization of the volume of this separation is provide...

T HE THEORY developed in the statistical literature for the method of k-means can be applied to the study of optimal k-level vector quantizers. In this paper, I describe some of this theory, including a consistency theorem (Section II) and a central lim it theorem (Section IV) for k-means cluster centers. These results help to explain the behavior of optimal vector quantizers constructed from l...

The degree to which extrinsic factors influence migration chronology in North American waterfowl has not been quantified, particularly for dabbling ducks. Previous studies have examined waterfowl migration using various methods, however, quantitative approaches to define avian migration chronology over broad spatio-temporal scales are limited, and the implications for using different approaches...

T lymphocyte migration is crucial for adaptive immunity. Manipulation of signaling molecules controlling cell migration combined with in-vitro cell migration analysis provides a powerful research approach. Microfluidic devices, which can precisely configure chemoattractant gradients and allow quantitative single cell analysis, have been increasingly applied to cell migration and chemotaxis stud...

Introduced a new calculation method (K-method) for cognitive maps. K-method consists of two consecutive steps. In the first stage, allocated subgraph composed of all paths from one selected node (concept) to another node (concept) from the cognitive map (directed weighted graph). In the second stage, after the transition to an undirected graph (symmetrization adjacency matrix) the influence of ...

The simulation of turbulent flows is an ongoing challenge. This is especially true for the flows in nuclear reactors. In order to save computational time and resource, accurate numerical schemes are required for such simulations. The encouraging results from the laminar flow simulations using Modified Nodal Integral Method (MNIM), serves as a motivation to use the method for turbulent flow simu...

K-means is a popular clustering method used in data mining area. To work with large datasets, researchers propose PKMeans, which is a parallel k-means on MapReduce [3]. However, the existing k-means parallelization methods including PKMeans have many limitations. It can’t finish all its iterations in one MapReduce job, so it has to repeat cascading MapReduce jobs in a loop until convergence. On...

A capillary electrophoresis system for the simultaneous determination of cations in honey samples has been developed. The complete separation and quantification of K+, Ca2+, Na+, Mg2+, Mn2+, Ni2+ and Li+, which represent more than 99% of the total content of cations in honey, can be achieved in 4 min with only a dilution and filtration of the honey sample. Electrolyte solution was composed by 1...

Kirschner (K) wires can easily migrate, resulting in serious complications. We report a 49-year-old woman who had a rare and late complication related to the migration of K wire. It had been used for left hip replacement 8 years ago. The patient admitted to our hospital with breathing-dependent chest pain and increasing dyspnea for ∼2 h. Chest X-ray and chest computed tomographic scans revealed...

Sparse representation of images has been a recent area of growing interest. It finds applications in many problems in image processing. In this report we study a particular method of achieving sparse representation using the recently proposed K-SVD algorithm by Aharon et al. [1] and how this sparse representation framework has been extended to perform denoising, as illustrated by the authors in...