Analysis of Air Mean Temperature Anomalies by Using Horizontal Visibility Graphs.

The last decades have been successively warmer at the Earth's surface. An increasing interest in climate variability is appearing, and many research works have investigated the main effects on different climate variables. Some of them apply complex networks approaches to explore the spatial relation between distinct grid points or stations.

Improving graph-based detection of singular events for photochemical smog agents.

Recently, a set of graph-based tools have been introduced for the identification of singular events of O, NO and temperature time series, as well as description of their dynamics. These are based on the use of the Visibility Graphs (VG). In this work, an improvement of the original approach is proposed, being called Upside-Down Visibility Graph (UDVG).

Digital Image Filtering Optimization Supporting Iberian Ham Quality Prediction.

Digital images of food for later analysis tend to be heterogeneous in terms of color and luminosity. Improving these images by using filters is necessary and crucial before further processing. This paper compares the non-use of filters and the use of high-pass filters in the images of hand-cut Iberian ham that will be used in a multifractal analysis for the study of fat and its infiltration.

A sliding window-based algorithm for faster transformation of time series into complex networks.

A new alternative method to approximate the Visibility Graph (VG) of a time series has been introduced here. It exploits the fact that most of the nodes in the resulting network are not connected to those that are far away from them. This means that the adjacency matrix is almost empty, and its nonzero values are close to the main diagonal.

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 (O, NO concentration and temperature) have been computed. From the resulting complex network, the centrality parameters have been obtained and compared among them.

Can complex networks describe the urban and rural tropospheric O dynamics?

Tropospheric ozone (O) time series have been converted into complex networks through the recent so-called Visibility Graph (VG), using the data from air quality stations located in the western part of Andalusia (Spain). The aim is to apply this novel method to differentiate the behavior between rural and urban regions when it comes to the ozone dynamics. To do so, some centrality parameters of the resulting complex networks have been investigated: the degree, betweenness and shortest path.

Visibility graphs of ground-level ozone time series: A multifractal analysis.

A recent method based on the concurrence of complex networks and multifractal analyses is applied for the first time to explore ground-level ozone behavior. Ozone time series are converted into complex networks for their posterior analysis. The searched purpose is to check the suitability of this transformation and to see whether some features of these complex networks could constitute a preliminary analysis before the more thorough multifractal formalism.

Influence of urban morphology on total noise pollution: multifractal description.

Exposure to ambient noise levels above 65 dB can cause public health problems. The spatial distribution of this kind of pollution is linked to various elements which make up the urban form, such as construction density, the existence of open spaces and the shape and physical position of buildings. Since urban morphology displays multifractal behaviour, the present research studies for the first time the relationship between total noise pollution and urban features, such as street width and building height by means of a joint multifractal spectrum in two neighbourhoods of the city of Cordoba (Andalusia, Spain).

Exploring the relationship between nitrogen dioxide and ground-level ozone by applying the joint multifractal analysis.

High concentrations of ground-level ozone have a negative impact on human health and the environment, especially in urban places. Detailed knowledge on the effects of nitrogen dioxide on the ozone seasonal pattern is convenient to prevent these undesirable effects. Thus, the joint multifractal approach has been used to complete the information provided by descriptive statistics.