Visibility graphs for image processing.

The family of image visibility graphs (IVG/IHVG) have been recently introduced as simple algorithms by which scalar fields can be mapped into graphs. Here we explore the usefulness of such operator in the scenario of image processing and image classication. We demonstrate that the link architecture of the image visibility graphs encapsulates relevant information on the structure of the images and we explore their potential as image filters. We introduce several graph features, including the novel concept of Visibility Patches, and show through several examples that these features are highly informative, computationally efficient and universally applicable for general pattern recognition and image classication tasks

Visibility graphs for image processing.

The family of image visibility graphs (IVG/IHVG) have been recently introduced as simple algorithms by which scalar fields can be mapped into graphs. Here we explore the usefulness of such operator in the scenario of image processing and image classication. We demonstrate that the link architecture of the image visibility graphs encapsulates relevant information on the structure of the images and we explore their potential as image filters. We introduce several graph features, including the novel concept of Visibility Patches, and show through several examples that these features are highly informative, computationally efficient and universally applicable for general pattern recognition and image classication tasks

Checking complex networks indicators in search of singular episodes of the photochemical smog

A set of indicators derived from the analysis of complex networks have been introduced to identify singularities on a time series. To that end, the Visibility Graphs (VG) from three different signals related to photochemical smog (O3, NO2 concentration and temperature) have been computed. From the resulting complex network, the centrality parameters have been obtained and compared among them. Besides, they have been contrasted to two others that arise from a multifractal point of view, that have been widely used for singularity detection in many fields: the Holder and singularity exponents (specially the first one of them). The outcomes show that the complex network indicators give equivalent results to those already tested, even exhibiting some advantages such as the unambiguity and the more selective results. This suggest a favorable position as supplementary sources of information when detecting singularities in several environmental variables, such as pollutant concentration or temperature.Comment: 32 pages, 7 figure

Checking complex networks indicators in search of singular episodes of the photochemical smog

A set of indicators derived from the analysis of complex networks have been introduced to identify singularities on a time series. To that end, the Visibility Graphs (VG) from three different signals related to photochemical smog (O3, NO2 concentration and temperature) have been computed. From the resulting complex network, the centrality parameters have been obtained and compared among them. Besides, they have been contrasted to two others that arise from a multifractal point of view, that have been widely used for singularity detection in many fields: the Hölder and singularity exponents (specially the first one of them). The outcomes show that the complex network indicators give equivalent results to those already tested, even exhibiting some advantages such as the unambiguity and the more selective results. This suggest a favorable position as supplementary sources of information when detecting singularities in several environmental variables, such as pollutant concentration or temperature

A study of visibility graphs for time series representations

En aquest projecte estudiem i presentem el camp dels grafs de visibilitat (visibility graphs) com una forma de representar i caracteritzar sèries temporals tal com va ser introduït per Lucas Lacasa et al. el 2008. Amb els grafs de visibilitat les sèries temporals es converteixen en grafs que hereten en la seva topologia algunes de les propietats estructurals de les sèries temporals, permetent així el nou anàlisi de sèries temporals a través d'eines pròpies de la teoria de grafs i la teoria de xarxes complexes. Estudiem i analitzem la complexitat computacional d'alguns algoritmes per obtenir grafs de visibilitat i, posteriorment, desenvolupem i presentem el paquet de Python ts2vg que proporciona implementacions eficients i fàcils d'usar per a alguns d'aquests algoritmes. A més, al projecte explorem i discutim algunes de les possibles aplicacions pràctiques d'aquests grafs de visibilitat.In this project we study and present the field of visibility graphs as a way to represent and characterize time series as introduced by Lucas Lacasa et al. in 2008. With visibility graphs, time series are converted into graphs that inherit in their topology some of the structural properties of the time series, allowing the novel analysis of time series via graph theory and complex network theory tools. We study and analyze the computational complexity of a selection of different visibility graph algorithms and subsequently develop and present the ts2vg Python package that provides efficient and easy-to-use implementations for some of these visibility graph algorithms. Additionally, in this project we explore and discuss some of the potential practical applications of these visibility graphs

Network Platform for Tourism Sector: Transformation and Interpretation of Multifaceted Data

Modern network science has become a prominent concept, attracting diverse scientific societies to solve a wide spectrum of theoretical and practical problems. Tourism is a sphere wherein the outlines of the network’s scope are distinct. In the study, the network approach was applied in its dual form for both network-like regional tourism data (NLRTD) and network-unlike regional tourism data (NURTD), to explore the tourism destination of Baikal natural territory, Russia, in regard to the challenges of the general sustainability of regional socio-ecological systems. The aim of the study is to elaborate a comprehensive network platform to harmonize such complex and fragile systems as Baikal natural territory. Saturated with networking ideology, the approach spans a huge set of interacting social, technological and ecological elements of the comprehensive system in order to support its functionality and sustainability in general. Particularly, the paper utilizes data from interviews done in Olkhon island (2017–2018), and publicly available textual, spatial and temporal data. NLRTD with pertinent networkization procedures was utilized in transportation schemes, while the NURTD concept implies the networkalization of landscape and land use maps. The platform provides researchers and stakeholders with concentrated information which might be not only effectively processed, but also intelligible, and correctly compared and implemented in contiguous spheres

Network Platform for Tourism Sector: Transformation and Interpretation of Multifaceted Data

Modern network science has become a prominent concept, attracting diverse scientific societies to solve a wide spectrum of theoretical and practical problems. Tourism is a sphere wherein the outlines of the network’s scope are distinct. In the study, the network approach was applied in its dual form for both network-like regional tourism data (NLRTD) and network-unlike regional tourism data (NURTD), to explore the tourism destination of Baikal natural territory, Russia, in regard to the challenges of the general sustainability of regional socio-ecological systems. The aim of the study is to elaborate a comprehensive network platform to harmonize such complex and fragile systems as Baikal natural territory. Saturated with networking ideology, the approach spans a huge set of interacting social, technological and ecological elements of the comprehensive system in order to support its functionality and sustainability in general. Particularly, the paper utilizes data from interviews done in Olkhon island (2017–2018), and publicly available textual, spatial and temporal data. NLRTD with pertinent networkization procedures was utilized in transportation schemes, while the NURTD concept implies the networkalization of landscape and land use maps. The platform provides researchers and stakeholders with concentrated information which might be not only effectively processed, but also intelligible, and correctly compared and implemented in contiguous spheres