55,341 research outputs found
Complex networks in climate dynamics - Comparing linear and nonlinear network construction methods
Complex network theory provides a powerful framework to statistically
investigate the topology of local and non-local statistical interrelationships,
i.e. teleconnections, in the climate system. Climate networks constructed from
the same global climatological data set using the linear Pearson correlation
coefficient or the nonlinear mutual information as a measure of dynamical
similarity between regions, are compared systematically on local, mesoscopic
and global topological scales. A high degree of similarity is observed on the
local and mesoscopic topological scales for surface air temperature fields
taken from AOGCM and reanalysis data sets. We find larger differences on the
global scale, particularly in the betweenness centrality field. The global
scale view on climate networks obtained using mutual information offers
promising new perspectives for detecting network structures based on nonlinear
physical processes in the climate system.Comment: 24 pages, 10 figure
On the Modeling of Musical Solos as Complex Networks
Notes in a musical piece are building blocks employed in non-random ways to
create melodies. It is the "interaction" among a limited amount of notes that
allows constructing the variety of musical compositions that have been written
in centuries and within different cultures. Networks are a modeling tool that
is commonly employed to represent a set of entities interacting in some way.
Thus, notes composing a melody can be seen as nodes of a network that are
connected whenever these are played in sequence. The outcome of such a process
results in a directed graph. By using complex network theory, some main metrics
of musical graphs can be measured, which characterize the related musical
pieces. In this paper, we define a framework to represent melodies as networks.
Then, we provide an analysis on a set of guitar solos performed by main
musicians. Results of this study indicate that the presented model can have an
impact on audio and multimedia applications such as music classification,
identification, e-learning, automatic music generation, multimedia
entertainment.Comment: to appear in Information Science, Elsevier. Please cite the paper
including such information. arXiv admin note: text overlap with
arXiv:1603.0497
Mining and Analyzing the Italian Parliament: Party Structure and Evolution
The roll calls of the Italian Parliament in the XVI legislature are studied
by employing multidimensional scaling, hierarchical clustering, and network
analysis. In order to detect changes in voting behavior, the roll calls have
been divided in seven periods of six months each. All the methods employed
pointed out an increasing fragmentation of the political parties endorsing the
previous government that culminated in its downfall. By using the concept of
modularity at different resolution levels, we identify the community structure
of Parliament and its evolution in each of the considered time periods. The
analysis performed revealed as a valuable tool in detecting trends and drifts
of Parliamentarians. It showed its effectiveness at identifying political
parties and at providing insights on the temporal evolution of groups and their
cohesiveness, without having at disposal any knowledge about political
membership of Representatives.Comment: 27 pages, 14 figure
- …