We apply spectral biclustering to mortality datasets in order to capture three relevant aspects: the period, the age and the cohort effects, as their knowledge is a key factor in understanding actuarial liabilities of private life insurance companies, pension funds as well as national pension systems. While standard techniques generally fail to capture the cohort effect, on the contrary, biclus...

Quadratic bottom boundary layer drag is a potentially significant source of energy dissipation in the deep ocean. This study presents a new estimate of the energy dissipated by this process, using results from the world’s largest archive of ocean current meter time series and focusing strongly upon the potential uncertainties in this calculation. Two methods are used, one based on a simple divi...

Recent advances in wireless networking technologies introduce several energy aware routing protocols in sensor networks. Such protocols aim to extend the lifetime of network by reducing the energy consumption of nodes. Many researchers are looking for certain challenges that are predominant in the grounds of energy consumption. One such protocol that addresses this energy consumption issue is ‘...

This paper presents a validation methodology in ascending hierarchical clustering. The objects in validation are clustering hierarchies, and simulation is used. Under certain conditions, this methodology allows us to evaluate the quality of hierarchical structures, its robustness and fiability, according to the data structure. The effect of the application of a given criterion on some kind of s...

We investigate the environments of quasars using a semi-analytic model which includes both galaxy and quasar formations based on a hierarchical clustering scenario. We assume that a supermassive black hole is formed and fueled by the accretion of cold gas during a major merger of galaxies. Our model can reproduce not only the general form of the galaxy luminosity functions in the local Universe...

This paper deals with lidar point cloud filtering and classification for modelling the Terrain and more generally for scene segmentation. In this study, we propose to use the well-known K-means clustering algorithm that filters and segments (point cloud) data. The Kmeans clustering is well adapted to lidar data processing, since different feature attributes can be used depending on the desired ...

In the image databases, there is often a need to organize the images automatically by their content. For the content-based organization of the images, clustering operations can be applied. We present a new, efficient method for the clustering of large image databases. The method is based on hierarchical clustering of the image database using grid. In this paper, the grid-based clustering method...

We present the results of exploratory data analysis for a data set that consists of crossposting information for 89,687 newsgroups over a period of 3.4 years. The data set we use is a part of Microsoft Netscan data. Our goal is to investigate the community structure of the newsgroup data set with a specific focus on spectral hierarchical clustering. We present a spectral hierarchical clustering...

This paper presents a new method for solving the following problem: Given a polygonal model of some geometric object generate several more and more approximative representations of this object containing less and less polygons. The idea behind the method is that small detail in the model is represented by many spatially close points. A hierarchical clustering algorithm is used to generate a hie...