A multistage clustering and data processing method, SWIFT (detailed in a companion
manuscript), has been developed to detect rare subpopulations in large, high‐dimensional …

In this paper we are introducing a framework towards the inclusion of Green IT metrics as
part of service level agreements for future Grids and Clouds. As part of this effort we need to …

Flow cytometry is a mainstay technology used by biologists and immunologists for counting,
sorting, and analyzing cells suspended in a fluid. Like many modern scientific applications …

The Partition Around Medoids (PAM) is a variation of well known k-Means clustering
algorithm where center of each cluster should be chosen as an object of clustered set of …

The paper touches upon the problem of implementation Partition Around Medoids (PAM)
clustering algorithm for the Intel Many Integrated Core architecture. PAM is a form of well …

В работе описана параллельная версия алгоритма кластеризации Partitioning Around
Medoids для сопроцессора Intel Xeon Phi. Распараллеливание выполнено на основе …

Veri demetleme algoritmaları, arama; spam, saldırı tespiti; hücre, gen, doküman analizi;
moleküler dinamik simülasyonlarının biçimlerinin analizi gibi uygulamalar için oldukça …

Change detection is now routinely applied in many application domains, such as damage
assessment, environmental monitoring and agricultural surveys. As the number of remote …

Despite the benefits of the Gustafson-Kessel (GK) clustering algorithm, it becomes
computationally inefficient when applied to high-dimensional data. In this letter, a parallel …

The PAM (Partitioning Around Medoids) is a partitioning clustering algorithm where each
cluster is represented by an object from the input dataset (called a medoid). The medoid …