General Spatial Pattern and Meta-Pattern Model for Problems That Need Analytical Approach in Complex Spatial Systems

Spatial Pattern (SP) Description, Identification, and Application Methodology (SPDIAM) was developed for describing and detecting spatial economic, social, and environmental phenomena and providing basic information technology (IT) artefacts that can be used for the spatial analysis development using GIS technologies. SPDIAM allows urban planning and design practitioners to describe SP in a computerized manner, identify SP automatically, and apply them in the spatial planning and design domain. In this article, we explain the general SP and spatial meta-pattern model, used in SPDIAM, that is based on the theory of Complex Spatial System (CSS), spatial configuration, and spatial capital concepts and is presented using UML diagrams as standard used for visualization of project models from structure and behavior points of views. The practical experiment of describing and identifying 6 basic spatial meta-pattern values is conducted using the new algorithm that combines Space Syntax method, Visibility Graph Analysis (VGA), and VGA measures to create a computer model of space and to quantify its configuration, which can then be used to handle geographic and geometric data associated with attribute information, to perform spatial, mathematical, and statistical calculations and to visualize SP. The results of the experiment show that the model and the algorithm are appropriate for spatial meta-patterns identification, and the best results can be achieved using VGA measure Isovist Compactness. In the future, general SP and the spatial meta-pattern model can be used to describe and identify complex SP and to solve problems in CSS with the help of the spatial meta-pattern values described in this article.

Decoding the Spatial Configuration of the Ottoman Palace “Khdewedj El Amia” in Algiers (Algeria) through Space Syntax

Palaces of the Ottoman era, the Golden age of Islamic civilization, bear witness to a prestigious know-how, drawing its rules from a way of life governed by the Islamic Sharia, the socio-cultural context of the Berber-Arab population and the climate-physical environment. The palace of Khdewedj El Amia is one of the majestic palaces located at the Casbah of Algiers and constitutes the subject of this article whose objective is to decode its genome in order to understand the social logic of a space inhabited and designed by a princess who lost her sight. Hence the name El Amia, which means blind in Arabic. The decoding of this building used the space syntax approach via a visibility graph analysis (VGA) performed by the Depthmap tool and a quantitative analysis of the graph justified by the Agraph tool. It is about taking into account the way in which vernacular architecture can stimulate the direct perception of space and participate in the construction of the user’s path. It was found that the palace is made up of two entities; one is of public order highlighting the resident/alien interface, and another intended for the private apartments, the harem of the princess, isolated from the outside world.

Visibility Graph Analysis of IOTA and IoTeX Price Series: An Intentional Risk-Based Strategy to Use 5G for IoT

The transformation of time series into complex networks through visibility graphs is an innovative way to study time-based events. In this work, we use visibility graphs to transform IOTA and IoTeX price volatility time series into complex networks. Our aim is twofold: first, to better understand the markets of the two most capitalised Internet of Things (IoT) platforms at the time of writing. IOTA runs on a public directed acyclic graph (DAG) and IoTeX on a blockchain. Second, to suggest how 5G can improve information security in these two key IoT platforms. The analysis of the networks created by the natural and horizontal visibility graphs shows, first, that both IOTA and IoTeX are still at their infancy in their development, with IoTex seemingly developing faster. Second, both IoT tokens form communities in a hierarchical structure, and third, 5G can accelerate their development. We use intentional risk management as a lever to understand the impact of 5G on IOTA and IoTeX. Our results lead us to provide a set of design recommendations that contribute to improving information security in future 5G-based IoT implementations.

Extracting Correlations in Earthquake Time Series Using Visibility Graph Analysis

Recent observation studies have revealed that earthquakes are classified into several different categories. Each category might be characterized by the unique statistical feature in the time series, but the present understanding is still limited due to their non-linear and non-stationary nature. Here we utilize complex network theory to shed new light on the statistical properties of earthquake time series. We investigate two kinds of time series, which are magnitude and inter-event time (IET), for three different categories of earthquakes: regular earthquakes, earthquake swarms, and tectonic tremors. Following the criterion of visibility graph, earthquake time series are mapped into a complex network by considering each seismic event as a node and determining the links. As opposed to the current common belief, it is found that the magnitude time series are not statistically equivalent to random time series. The IET series exhibit correlations similar to fractional Brownian motion for all the categories of earthquakes. Furthermore, we show that the time series of three different categories of earthquakes can be distinguished by the topology of the associated visibility graph. Analysis on the assortativity coefficient also reveals that the swarms are more intermittent than the tremors.

Characterizing cardiorespiratory interaction in preterm infants across sleep states using visibility graph analysis

The interaction between cardiac and respiratory activities is investigated in preterm infant sleep using an advanced nonlinear method (visibility graph) and some important characteristics are shown to be significantly different across sleep states, which has not been studied before.

Sinicisation and ethnicity: spatial characteristics of Shui vernacular architecture in Guizhou, Southwest China

The Shui people are an ethnic minority living in southern mountainous areas of Guizhou Province, China; they have retained many vernacular houses with a history of over a century. Using spatial analysis software depthmapX to perform visibility graph analysis and field-of-view analysis with space syntax, we examined the sequence, organisation, and hierarchy of the living space in Shui residences. We found that those residences were influenced by external cultures, resulting in two types of plan layout: front-middle-back (type A) and left-middle-right (type B). Those two types of spatial combination were evident in two different line-of-sight axes. With type A, the hearth was the core and served as the daily living space of the family. With type B, the ancestral altar was the core and served as the ritual space. The historical coexistence and changing relationship of the two axes reflect cultural exchange between the Shui and Han as well as with other foreign cultures. This study concludes that the diversity of spatial forms that developed in different historical periods is an important attribute of Shui houses and those of other ethnic minorities in Southwest China.

Searching for Supersymmetry at LHC Using the Complex-Network-Based Method of the Three-Dimensional Visibility-Graph

For the last several decades, there has been tremendous interest in search for Supersymmetry (SUSY) in the area of high energy physics. At Large Hadron Collider (LHC), there have been continuous searches for SUSY for prompt and non-prompt, for particle R-parity conserving and R-parity violating generation and decays. The limits obtained from these experiments and analyses for detection of the signatures of supersymmetric particles (LSP), revealed greater possibilities of such experiments in the collider. However, these signatures are usually derived under the assumption of bit optimistic conditions of the decaying process of sparticles to the final states. Moreover, SUSY might have been in a disguised state at lower mass-scales as a result of difficult and challenging mass spectra and mixed modes of decays. In this investigation, a novel method of 3-dimensional (3D) Visibility-Graph Analysis is proposed. This is an extension of Visibility Graph analysis of data series to perform the scaling analysis for 3D space. The experimental data spaces analyzed are made up of the component-space (in the X,Y and Z coordinates) of transverse momentum (pT) values taken out from 4-momenta of the signatures of the final state of the pair of mega-jets extracted from the multiJet primary pp collision data from Run B of 2010 at 7 TeV which was used for the search of SUSY using razor filter. The symmetry scaling and the inherent scaling behavior, scale-freeness of multi-particle production process is studied in terms of 3D Power-of-Scale-freeness-of-Visibility-Graph (3D-PSVG) extracted from the 3D Visibility Graphs constructed out of the experimental data spaces. The signature of SUSY may be identified by analyzing the scaling behavior and long-range correlation inherent in the 3D space made up of signatures of final state of multi-particles produced in the pp collision at 7 TeV, for the analysis of SUSY, which the conventional method of analyzing the spectrum of invariant mass or pT may miss.