Dipartimento di Fisica

Abstract. Clustering of real-world datasets is a complex problem. Op-timization models seeking to maximize a fitness function assume that the solution corresponding to the global optimum is the best clustering solution. Unfortunately, this is not always the case, mainly because ...

Clustering of real-world data is often ill-posed. Because of noise and intrinsic ambiguity in data, optimization models attempting to maximize a fitness function can be misled by the assumption of uniqueness of the solution. In this work we present a methodology including classic ...

Abstract. Clustering is one of the most important unsupervised learn-ing problems and it deals with finding a structure in a collection of unla-beled data; however, different clustering algorithms applied to the same data-set produce different solutions. In many applications the ...

In this work we propose a scientific data exploration methodology and software environment that permits to obtain both data meta-clustering and interactive visualizations. Our approach is based on an elaboration pipeline, including data reading, multiple clustering solution ...

1 Executive Summary Executive Summary The aim of this report is to present a series of case studies illustrating the work of the 14 pilot projects, whereupon comparisons of common features or experiences may be made. This in turn leads to a set of generalised ...

ABSTRACT Stick-Slip motion is the basis for the description of a great variety of phenomena characterized by the presence of sliding friction between bodies with elastic features. In this article a simple experimental equipment for the analysis of this kind of dynamics is described. A wide set of possible experimental observations and measures are presented. This equipment has been tested at the university of Napoli Federico 11 in courses for undergraduate students and in the teacher training school for secondary education.