18,662 research outputs found
Resolving structural variability in network models and the brain
Large-scale white matter pathways crisscrossing the cortex create a complex
pattern of connectivity that underlies human cognitive function. Generative
mechanisms for this architecture have been difficult to identify in part
because little is known about mechanistic drivers of structured networks. Here
we contrast network properties derived from diffusion spectrum imaging data of
the human brain with 13 synthetic network models chosen to probe the roles of
physical network embedding and temporal network growth. We characterize both
the empirical and synthetic networks using familiar diagnostics presented in
statistical form, as scatter plots and distributions, to reveal the full range
of variability of each measure across scales in the network. We focus on the
degree distribution, degree assortativity, hierarchy, topological Rentian
scaling, and topological fractal scaling---in addition to several summary
statistics, including the mean clustering coefficient, shortest path length,
and network diameter. The models are investigated in a progressive, branching
sequence, aimed at capturing different elements thought to be important in the
brain, and range from simple random and regular networks, to models that
incorporate specific growth rules and constraints. We find that synthetic
models that constrain the network nodes to be embedded in anatomical brain
regions tend to produce distributions that are similar to those extracted from
the brain. We also find that network models hardcoded to display one network
property do not in general also display a second, suggesting that multiple
neurobiological mechanisms might be at play in the development of human brain
network architecture. Together, the network models that we develop and employ
provide a potentially useful starting point for the statistical inference of
brain network structure from neuroimaging data.Comment: 24 pages, 11 figures, 1 table, supplementary material
A semantic web approach for built heritage representation
In a built heritage process, meant as a structured system of activities
aimed at the investigation, preservation, and management of architectural
heritage, any task accomplished by the several actors involved in it is deeply
influenced by the way the knowledge is represented and shared. In the current
heritage practice, knowledge representation and management have shown several
limitations due to the difficulty of dealing with large amount of extremely heterogeneous
data. On this basis, this research aims at extending semantic web
approaches and technologies to architectural heritage knowledge management in
order to provide an integrated and multidisciplinary representation of the artifact
and of the knowledge necessary to support any decision or any intervention and
management activity. To this purpose, an ontology-based system, representing
the knowledge related to the artifact and its contexts, has been developed through
the formalization of domain-specific entities and relationships between them
Synthesis of variable dancing styles based on a compact spatiotemporal representation of dance
Dance as a complex expressive form of motion is able to convey emotion, meaning and social idiosyncrasies that opens channels for non-verbal communication, and promotes rich cross-modal interactions with music and the environment. As such, realistic dancing characters may incorporate crossmodal information and variability of the dance forms through compact representations that may describe the movement structure in terms of its spatial and temporal organization. In this paper, we propose a novel method for synthesizing beatsynchronous dancing motions based on a compact topological model of dance styles, previously captured with a motion capture system. The model was based on the Topological Gesture Analysis (TGA) which conveys a discrete three-dimensional point-cloud representation of the dance, by describing the spatiotemporal variability of its gestural trajectories into uniform spherical distributions, according to classes of the musical meter. The methodology for synthesizing the modeled dance traces back the topological representations, constrained with definable metrical and spatial parameters, into complete dance instances whose variability is controlled by stochastic processes that considers both TGA distributions and the kinematic constraints of the body morphology. In order to assess the relevance and flexibility of each parameter into feasibly reproducing the style of the captured dance, we correlated both captured and synthesized trajectories of samba dancing sequences in relation to the level of compression of the used model, and report on a subjective evaluation over a set of six tests. The achieved results validated our approach, suggesting that a periodic dancing style, and its musical synchrony, can be feasibly reproduced from a suitably parametrized discrete spatiotemporal representation of the gestural motion trajectories, with a notable degree of compression
Study on behavioral impedance for route planning techniques from the pedestrian's perspective: Part I - Theoretical contextualization and taxonomy
The interest of researchers for analyzing of best routes and shortest
paths allows a continuous technological advance in topological analysis
techniques used in the geographic information systems for
transportation. One of the topological analysis techniques is the route
planning, in which the constraint management must be considered. There
have been few studies where the constraint domain for pedestrian in an
urban transportation system was clearly stated. Consequently, more
studies need to be carried out. The aim of this paper is to provide a
theoretical contextualization on identification and management of
constraints to ascertain the behavioral impedance domain from the
pedestrian perspective. In this part of the research the grounded theory
was the research method used to develop the proposed theory. A
meta-model was used to (1) define the behavioral domain structure, (2)
hold the behavioral data collection and (3) verify the design of the
proposed taxonomic tree. The main contribution of this article is the
behavioral domain taxonomy from the pedestrian perspective, which will
be used to implement a module responsible for the constraint management
of an experimental application, named Router. Within this context, the
proposed taxonomy could be used to model cost functions more precisely.Postprint (published version
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