Spatiotemporal analysis of forensic case data: a visualisation approach

Whether for investigative or intelligence aims, crime analysts often face up the necessity to analyse the spatiotemporal distribution of crimes or traces left by suspects. This article presents a visualisation methodology supporting recurrent practical analytical tasks such as the detection of crime series or the analysis of traces left by digital devices like mobile phone or GPS devices. The proposed approach has led to the development of a dedicated tool that has proven its effectiveness in real inquiries and intelligence practices. It supports a more fluent visual analysis of the collected data and may provide critical clues to support police operations as exemplified by the presented case studies.

Analysis, modelling and visualisation of spatiotemporal data for urban studies

The proportion of population living in or around cites is more important than ever. Urban sprawl and car dependence have taken over the pedestrian-friendly compact city. Environmental problems like air pollution, land waste or noise, and health problems are the result of this still continuing process. The urban planners have to find solutions to these complex problems, and at the same time insure the economic performance of the city and its surroundings. At the same time, an increasing quantity of socio-economic and environmental data is acquired. In order to get a better understanding of the processes and phenomena taking place in the complex urban environment, these data should be analysed. Numerous methods for modelling and simulating such a system exist and are still under development and can be exploited by the urban geographers for improving our understanding of the urban metabolism. Modern and innovative visualisation techniques help in communicating the results of such models and simulations. This thesis covers several methods for analysis, modelling, simulation and visualisation of problems related to urban geography. The analysis of high dimensional socio-economic data using artificial neural network techniques, especially self-organising maps, is showed using two examples at different scales. The problem of spatiotemporal modelling and data representation is treated and some possible solutions are shown. The simulation of urban dynamics and more specifically the traffic due to commuting to work is illustrated using multi-agent micro-simulation techniques. A section on visualisation methods presents cartograms for transforming the geographic space into a feature space, and the distance circle map, a centre-based map representation particularly useful for urban agglomerations. Some issues on the importance of scale in urban analysis and clustering of urban phenomena are exposed. A new approach on how to define urban areas at different scales is developed, and the link with percolation theory established. Fractal statistics, especially the lacunarity measure, and scale laws are used for characterising urban clusters. In a last section, the population evolution is modelled using a model close to the well-established gravity model. The work covers quite a wide range of methods useful in urban geography. Methods should still be developed further and at the same time find their way into the daily work and decision process of urban planners. La part de personnes vivant dans une région urbaine est plus élevé que jamais et continue à croître. L'étalement urbain et la dépendance automobile ont supplanté la ville compacte adaptée aux piétons. La pollution de l'air, le gaspillage du sol, le bruit, et des problèmes de santé pour les habitants en sont la conséquence. Les urbanistes doivent trouver, ensemble avec toute la société, des solutions à ces problèmes complexes. En même temps, il faut assurer la performance économique de la ville et de sa région. Actuellement, une quantité grandissante de données socio-économiques et environnementales est récoltée. Pour mieux comprendre les processus et phénomènes du système complexe "ville", ces données doivent être traitées et analysées. Des nombreuses méthodes pour modéliser et simuler un tel système existent et sont continuellement en développement. Elles peuvent être exploitées par le géographe urbain pour améliorer sa connaissance du métabolisme urbain. Des techniques modernes et innovatrices de visualisation aident dans la communication des résultats de tels modèles et simulations. Cette thèse décrit plusieurs méthodes permettant d'analyser, de modéliser, de simuler et de visualiser des phénomènes urbains. L'analyse de données socio-économiques à très haute dimension à l'aide de réseaux de neurones artificiels, notamment des cartes auto-organisatrices, est montré à travers deux exemples aux échelles différentes. Le problème de modélisation spatio-temporelle et de représentation des données est discuté et quelques ébauches de solutions esquissées. La simulation de la dynamique urbaine, et plus spécifiquement du trafic automobile engendré par les pendulaires est illustrée à l'aide d'une simulation multi-agents. Une section sur les méthodes de visualisation montre des cartes en anamorphoses permettant de transformer l'espace géographique en espace fonctionnel. Un autre type de carte, les cartes circulaires, est présenté. Ce type de carte est particulièrement utile pour les agglomérations urbaines. Quelques questions liées à l'importance de l'échelle dans l'analyse urbaine sont également discutées. Une nouvelle approche pour définir des clusters urbains à des échelles différentes est développée, et le lien avec la théorie de la percolation est établi. Des statistiques fractales, notamment la lacunarité, sont utilisées pour caractériser ces clusters urbains. L'évolution de la population est modélisée à l'aide d'un modèle proche du modèle gravitaire bien connu. Le travail couvre une large panoplie de méthodes utiles en géographie urbaine. Toutefois, il est toujours nécessaire de développer plus loin ces méthodes et en même temps, elles doivent trouver leur chemin dans la vie quotidienne des urbanistes et planificateurs.

Brownian motion of spiral waves driven by spatiotemporal structured noise

Spiral chemical waves subjected to a spatiotemporal random excitability are experimentally and numerically investigated in relation to the light-sensitive Belousov-Zhabotinsky reaction. Brownian motion is identified and characterized by an effective diffusion coefficient which shows a rather complex dependence on the time and length scales of the noise relative to those of the spiral. A kinematically based model is proposed whose results are in good qualitative agreement with experiments and numerics.

Dynamics of turing patterns under spatiotemporal forcing

We study, both theoretically and experimentally, the dynamical response of Turing patterns to a spatiotemporal forcing in the form of a traveling-wave modulation of a control parameter. We show that from strictly spatial resonance, it is possible to induce new, generic dynamical behaviors, including temporally modulated traveling waves and localized traveling solitonlike solutions. The latter make contact with the soliton solutions of Coullet [Phys. Rev. Lett. 56, 724 (1986)] and generalize them. The stability diagram for the different propagating modes in the Lengyel-Epstein model is determined numerically. Direct observations of the predicted solutions in experiments carried out with light modulations in the photosensitive chlorine dioxide-iodine-malonic acid reaction are also reported.

Spatiotemporal order out of noise

Experimental observations of self-organized behavior arising out of noise are also described, and details on the numerical algorithms needed in the computer simulation of these problems are given.

Self-sustained spatiotemporal oscillations induced by membrane-bulk coupling

We propose a novel mechanism leading to spatiotemporal oscillations in extended systems that does not rely on local bulk instabilities. Instead, oscillations arise from the interaction of two subsystems of different spatial dimensionality. Specifically, we show that coupling a passive diffusive bulk of dimension d with an excitable membrane of dimension d-1 produces a self-sustained oscillatory behavior. An analytical explanation of the phenomenon is provided for d=1. Moreover, in-phase and antiphase synchronization of oscillations are found numerically in one and two dimensions. This novel dynamic instability could be used by biological systems such as cells, where the dynamics on the cellular membrane is necessarily different from that of the cytoplasmic bulk.

Excitability transitions and wave dynamics under spatiotemporal structured noise

We present an analytic and numerical study of the effects of external fluctuations in active media. Our analytical methodology transforms the initial stochastic partial differential equations into an effective set of deterministic reaction-diffusion equations. As a result we are able to explain and make quantitative predictions on the systematic and constructive effects of the noise, for example, target patterns created out of noise and traveling or spiral waves sustained by noise. Our study includes the case of realistic noises with temporal and spatial structures.

Urologie."Revisitons la prostate!" [Urology. Trends in prostatic diseases in 2012].

This article discusses the management of prostate disease and new therapeutic approaches as a result from epidemiological and physiopathological links between benign prostatic hyperplasia and erectile dysfunction.

Generation of spatiotemporal colored noise

We develop an algorithm to simulate a Gaussian stochastic process that is non-¿-correlated in both space and time coordinates. The colored noise obeys a linear reaction-diffusion Langevin equation with Gaussian white noise. This equation is exactly simulated in a discrete Fourier space.

Cancer mortality in Europe, 2005-2009, and an overview of trends since 1980.

BACKGROUND: After a peak in the late 1980s, cancer mortality in Europe has declined by ∼10% in both sexes up to the early 2000s. We provide an up-to-date picture of patterns and trends in mortality from major cancers in Europe. METHODS: We analyzed cancer mortality data from the World Health Organization for 25 cancer sites and 34 European countries (plus the European Union, EU) in 2005-2009. We computed age-standardized rates (per 100 000 person-years) using the world standard population and provided an overview of trends since 1980 for major European countries, using joinpoint regression. RESULTS: Cancer mortality in the EU steadily declined since the late 1980s, with reductions by 1.6% per year in 2002-2009 in men and 1% per year in 1993-2009 in women. In western Europe, rates steadily declined over the last two decades for stomach and colorectal cancer, Hodgkin lymphoma, and leukemias in both sexes, breast and (cervix) uterine cancer in women, and testicular cancer in men. In central/eastern Europe, mortality from major cancer sites has been increasing up to the late 1990s/early 2000s. In most Europe, rates have been increasing for lung cancer in women and for pancreatic cancer and soft tissue sarcomas in both sexes, while they have started to decline over recent years for multiple myeloma. In 2005-2009, there was still an over twofold difference between the highest male cancer mortality in Hungary (235.2/100 000) and the lowest one in Sweden (112.9/100 000), and a 1.7-fold one in women (from 124.4 in Denmark to 71.0/100 000 in Spain). CONCLUSIONS: With the major exceptions of female lung cancer and pancreatic cancer in both sexes, in the last quinquennium, cancer mortality has moderately but steadily declined across Europe. However, substantial differences across countries persist, requiring targeted interventions on risk factor control, early diagnosis, and improved management and pharmacological treatment for selected cancer sites.

Conviction Statistics as an Indicator of Crime Trends in Europe from 1990 to 2006

Convictions statistics were the first criminal statistics available in Europe during the nineteenth century. Their main weaknesses as crime measures and for comparative purposes were identified by Alphonse de Candolle in the 1830s. Currently, they are seldom used by comparative criminologists, although they provide a less valid but more reliable measure of crime and formal social control than police statistics. This article uses conviction statistics, compiled from the four editions of the European Sourcebook of Crime and Criminal Justice Statistics, to study the evolution of persons convicted in European countries from 1990 to 2006. Trends in persons convicted for six offences -intentional homicide, assault, rape, robbery, theft, and drug offences- and up to 26 European countries are analysed. These trends are established for the whole of Europe as well as for a cluster of Western European countries and a cluster of Central and Eastern European countries. The analyses show similarities between both regions of Europe at the beginning and at the end of the period under study. After a general increase of the rate of persons convicted in the early 1990s in the whole of Europe, trends followed different directions in Western and in Central and Eastern Europe. However, during the 2000s, it can be observed, throughout Europe, a certain stability of the rates of persons convicted for intentional homicides, accompanied by a general decrease of the rate of persons convicted for property offences, and an increase of the rate of those convicted for drug offences. The latter goes together with an increase of the rate of persons convicted for non lethal violent offences, which only reached some stability at the end of the time series. These trends show that there is no general crime drop in Europe. After a discussion of possible theoretical explanations, a multifactor model, inspired by opportunity-based theories, is proposed to explain the trends observed.

Spatiotemporal stochastic resonance in the Swift-Hohenberg equation

We show the appearance of spatiotemporal stochastic resonance in the Swift-Hohenberg equation. This phenomenon emerges when a control parameter varies periodically in time around the bifurcation point. By using general scaling arguments and by taking into account the common features occurring in a bifurcation, we outline possible manifestations of the phenomenon in other pattern-forming systems.