943 resultados para spatio-temporal models


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One of the greatest concerns related to the popularity of GPS-enabled devices and applications is the increasing availability of the personal location information generated by them and shared with application and service providers. Moreover, people tend to have regular routines and be characterized by a set of “significant places”, thus making it possible to identify a user from his/her mobility data. In this paper we present a series of techniques for identifying individuals from their GPS movements. More specifically, we study the uniqueness of GPS information for three popular datasets, and we provide a detailed analysis of the discriminatory power of speed, direction and distance of travel. Most importantly, we present a simple yet effective technique for the identification of users from location information that are not included in the original dataset used for training, thus raising important privacy concerns for the management of location datasets.

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We present experimental measurements of intensity spatiotemporal dynamics in quasi-CW Raman fiber laser. Depending on the power, the laser operates in different spatio-temporal regimes varying from partial mode-locking near the generation threshold to almost stochastic radiation and a generation of short-lived pulses at high power. The transitions between the generation regimes are evident in intensity spatio-temporal dynamics. Two-dimensional auto-correlation functions provide an additional insight into temporal and spatial properties of the observed regimes.

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Fibre lasers are light sources that are synonymous with stability. They can give rise to highly coherent continuous-wave radiation, or a stable train of mode locked pulses with well-defined characteristics. However, they can also exhibit an exceedingly diverse range of nonlinear operational regimes spanning a multi-dimensional parameter space. The complex nature of the dynamics poses significant challenges in the theoretical and experimental studies of such systems. Here, we demonstrate how the real-time experimental methodology of spatio-temporal dynamics can be used to unambiguously identify and discern between such highly complex lasing regimes. This two-dimensional representation of laser intensity allows the identification and tracking of individual features embedded in the radiation as they make round-trip circulations inside the cavity. The salient features of this methodology are highlighted by its application to the case of Raman fibre lasers and a partially mode locked ring fibre laser operating in the normal dispersion regime.

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We present here experimental observation of different spatio-temporal generation regimes in quasi-CW Raman fiber laser in the most simple experimental configuration. The generation regimes depend on pump power and range from partial mode-locking to turbulent, and a generation of short-lived pulses. While in temporal domain transitions could be described in quantitative way, in spatio-temporal domain they represent qualitative change in observed dynamics.

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Temporal dynamics of Raman fibre lasers tend to have very complex nature, owing to great cavity lengths and high nonlinearity, being stochastic on short time scales and quasi-continuous on longer time scales. Generally fibre laser intensity dynamics is represented by one-dimensional time-series, which in case of quasi-continuous wave generation in Raman fibre lasers gives little insight into the processes underlying the operation of a laser. New methods of analysis and data representation could help to uncover the underlying physical processes, understand the dynamics or improve the performance of the system. Using intrinsic periodicity of laser radiation, one dimensional intensity time series of a Raman fibre laser was analysed over fast and slow variation time. This allowed to experimentally observe various spatio-temporal regimes of generation, such as laminar, turbulent, partial mode-lock, as well as transitions between them and identify the mechanisms responsible for the transitions. Great cavity length and high nonlinearity also make it difficult to achieve stable high repetition rate mode-locking in Raman fibre lasers. Using Faraday parametric instability in extremely simple linear cavity experimental configuration, a very high order harmonic mode-locking was achieved in ò.ò kmlong Raman fibre laser. The maximum achieved pulse repetition rate was 12 GHz, with 7.3 ps long Gaussian shaped pulses. There is a new type of random lasers – random distributed feedback Raman fibre laser, which temporal properties cannot be controlled by conventionalmode-locking or Q-switch techniques and mechanisms. By adjusting the pump configuration, a very stable pulsed operation of random distributed feedback Raman fibre laser was achieved. Pulse duration varied in the range from 50 to 200 μs depending on the pump power and the cavity length. Pulse repetition rate scaling on the parameters of the system was experimentally identified.

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The Ráckeve-Soroksár Danube has a great importance as it is the second largest side arm in the Hungarian section of the river Danube and many demands of exploitation are expected. The aim of this study is to analyse the spatial and temporal changes of the zooplankton (Copepoda, Cladocera) community in this river arm, moreover the similarity patterns of zooplankton communities in different Hungarian water bodies are presented in special consideration of the Ráckeve-Soroksár Danube. Basically this study is based on data from literature, however our data are also used for compiling the database for the spatio-temporal changes of the Ráckeve-Soroksár Danube. We put emphasis on the three typical sections of the side arm, as these are stressed due to hydromorphological aspects, but creating artificial borders are objectionable as well. The results show that both spatial and temporal changes are evident, what is more, the stagnant water character of the side arm should be underlined.

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The coastal bays of South Florida are located downstream of the Florida Everglades, where a comprehensive restoration plan will strongly impact the hydrology of the region. Submerged aquatic vegetation communities are common components of benthic habitats of Biscayne Bay, and will be directly affected by changes in water quality. This study explores community structure, spatio-temporal dynamics, and tissue nutrient content of macroalgae to detect and describe relationships with water quality. The macroalgal community responded to strong variability in salinity; three distinctive macroalgal assemblages were correlated with salinity as follows: (1) low-salinity, dominated by Chara hornemannii and a mix of filamentous algae; (2) brackish, dominated by Penicillus capitatus, Batophora oerstedii, and Acetabularia schenckii; and (3) marine, dominated by Halimeda incrassata and Anadyomene stellata. Tissue-nutrient content was variable in space and time but tissues at all sites had high nitrogen and N:P values, demonstrating high nitrogen availability and phosphorus limitation in this region. This study clearly shows that distinct macroalgal assemblages are related to specific water quality conditions, and that macroalgal assemblages can be used as community-level indicators within an adaptive management framework to evaluate performance and restoration impacts in Biscayne Bay and other regions where both freshwater and nutrient inputs are modified by water management decisions.

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We present recent results on measurements of intensity spatio-temporal dynamics in passively mode-locked fibre laser. We experimentally uncover distinct, dynamic and stable spatio-temporal generation regimes of various stochasticity and periodicity properties in though-to-be unstable laser. We present a method to distinguish various types of generated coherent structures, including rogue and shock waves, within the radiation by means of introducing of intensity ACF evolution map. We also discuss how the spectral dynamics could be measured in fiber lasers generating irregular train of pulses of quasi-CW generation via combination of heterodyning and intensity spatio-temporal measurement concept.

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Les réseaux de capteurs sont formés d’un ensemble de dispositifs capables de prendre individuellement des mesures d’un environnement particulier et d’échanger de l’information afin d’obtenir une représentation de haut niveau sur les activités en cours dans la zone d’intérêt. Une telle détection distribuée, avec de nombreux appareils situés à proximité des phénomènes d’intérêt, est pertinente dans des domaines tels que la surveillance, l’agriculture, l’observation environnementale, la surveillance industrielle, etc. Nous proposons dans cette thèse plusieurs approches pour effectuer l’optimisation des opérations spatio-temporelles de ces dispositifs, en déterminant où les placer dans l’environnement et comment les contrôler au fil du temps afin de détecter les cibles mobiles d’intérêt. La première nouveauté consiste en un modèle de détection réaliste représentant la couverture d’un réseau de capteurs dans son environnement. Nous proposons pour cela un modèle 3D probabiliste de la capacité de détection d’un capteur sur ses abords. Ce modèle inègre également de l’information sur l’environnement grâce à l’évaluation de la visibilité selon le champ de vision. À partir de ce modèle de détection, l’optimisation spatiale est effectuée par la recherche du meilleur emplacement et l’orientation de chaque capteur du réseau. Pour ce faire, nous proposons un nouvel algorithme basé sur la descente du gradient qui a été favorablement comparée avec d’autres méthodes génériques d’optimisation «boites noires» sous l’aspect de la couverture du terrain, tout en étant plus efficace en terme de calculs. Une fois que les capteurs placés dans l’environnement, l’optimisation temporelle consiste à bien couvrir un groupe de cibles mobiles dans l’environnement. D’abord, on effectue la prédiction de la position future des cibles mobiles détectées par les capteurs. La prédiction se fait soit à l’aide de l’historique des autres cibles qui ont traversé le même environnement (prédiction à long terme), ou seulement en utilisant les déplacements précédents de la même cible (prédiction à court terme). Nous proposons de nouveaux algorithmes dans chaque catégorie qui performent mieux ou produits des résultats comparables par rapport aux méthodes existantes. Une fois que les futurs emplacements de cibles sont prédits, les paramètres des capteurs sont optimisés afin que les cibles soient correctement couvertes pendant un certain temps, selon les prédictions. À cet effet, nous proposons une méthode heuristique pour faire un contrôle de capteurs, qui se base sur les prévisions probabilistes de trajectoire des cibles et également sur la couverture probabiliste des capteurs des cibles. Et pour terminer, les méthodes d’optimisation spatiales et temporelles proposées ont été intégrées et appliquées avec succès, ce qui démontre une approche complète et efficace pour l’optimisation spatio-temporelle des réseaux de capteurs.

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The spike-diffuse-spike (SDS) model describes a passive dendritic tree with active dendritic spines. Spine-head dynamics is modeled with a simple integrate-and-fire process, whilst communication between spines is mediated by the cable equation. In this paper we develop a computational framework that allows the study of multiple spiking events in a network of such spines embedded on a simple one-dimensional cable. In the first instance this system is shown to support saltatory waves with the same qualitative features as those observed in a model with Hodgkin-Huxley kinetics in the spine-head. Moreover, there is excellent agreement with the analytically calculated speed for a solitary saltatory pulse. Upon driving the system with time varying external input we find that the distribution of spines can play a crucial role in determining spatio-temporal filtering properties. In particular, the SDS model in response to periodic pulse train shows a positive correlation between spine density and low-pass temporal filtering that is consistent with the experimental results of Rose and Fortune [1999, Mechanisms for generating temporal filters in the electrosensory system. The Journal of Experimental Biology 202, 1281-1289]. Further, we demonstrate the robustness of observed wave properties to natural sources of noise that arise both in the cable and the spine-head, and highlight the possibility of purely noise induced waves and coherent oscillations.

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Due to increasing population and the recent implementation of policies to intensify the use of land and water resources, the transhumant pastoral systems in the Chinese-Mongolian Altay-Dzungarian region are rapidly changing, leading to modifications of herd size, herd composition and spatial distribution of livestock grazing. This may have major consequences for the supply and quality of rangeland biomass. Despite similar topographic settings, the socio-political framework for Chinese and Mongolian pastoralists differs significantly, leading to differences in rangeland utilization. To substantiate these claims, the long-distance transhumance routes, frequency of pasture changes, daily grazing itineraries and size of pastures were recorded by means of GPS tracking of cattle and goats on 1,535 (China) and 1,396 (Mongolia) observation days. The status quo of the main seasonal pastures was captured by measuring the herbage offer and its nutritive value in 869 sampling spots. In the Altay-Dzungarian region, small ruminant herds covered up to 412 km (Mongolia) and grazed on up to nine pastures per year (China). In Mongolia, the herds’ average duration of stay at an individual pasture was longer than in China, particularly in spring and autumn. Herbage allowance at the onset of a grazing period (kg dry matter per sheep unit and day) ranged from 34/17 to 91/95 (China/Mongolia). Comparing crude protein and phosphorous concentrations of herbage, in China, the highest concentrations were measured for spring and summer pastures, whereas in Mongolia, the highest concentrations were determined for autumn and winter pastures. Based on our data, we conclude that regulation of animal numbers and access to pastures seemingly maintained pasture productivity in China, especially at high altitudes. However, this policy may prohibit flexible adaptation to sudden environmental constraints. In contrast, high stocking densities and grazing of pastures before flowering of herbaceous plants negatively affected rangeland productivity in Mongolia, especially for spring and summer pastures.

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This thesis analyzes the impact of heat extremes in urban and rural environments, considering processes related to severely high temperatures and unusual dryness. The first part deals with the influence of large-scale heatwave events on the local-scale urban heat island (UHI) effect. The temperatures recorded over a 20-year summer period by meteorological stations in 37 European cities are examined to evaluate the variations of UHI during heatwaves with respect to non-heatwave days. A statistical analysis reveals a negligible impact of large-scale extreme temperatures on the local daytime urban climate, while a notable exacerbation of UHI effect at night. A comparison with the UrbClim model outputs confirms the UHI strengthening during heatwave episodes, with an intensity independent of the climate zone. The investigation of the relationship between large-scale temperature anomalies and UHI highlights a smooth and continuous dependence, but with a strong variability. The lack of a threshold behavior in this relationship suggests that large-scale temperature variability can affect the local-scale UHI even in different conditions than during extreme events. The second part examines the transition from meteorological to agricultural drought, being the first stage of the drought propagation process. A multi-year reanalysis dataset involving numerous drought events over the Iberian Peninsula is considered. The behavior of different non-parametric standardized drought indices in drought detection is evaluated. A statistical approach based on run theory is employed, analyzing the main characteristics of drought propagation. The propagation from meteorological to agricultural drought events is found to develop in about 1-2 months. The duration of agricultural drought appears shorter than that of meteorological drought, but the onset is delayed. The propagation probability increases with the severity of the originating meteorological drought. A new combined agricultural drought index is developed to be a useful tool for balancing the characteristics of other adopted indices.

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This paper applies Hierarchical Bayesian Models to price farm-level yield insurance contracts. This methodology considers the temporal effect, the spatial dependence and spatio-temporal models. One of the major advantages of this framework is that an estimate of the premium rate is obtained directly from the posterior distribution. These methods were applied to a farm-level data set of soybean in the State of the Parana (Brazil), for the period between 1994 and 2003. The model selection was based on a posterior predictive criterion. This study improves considerably the estimation of the fair premium rates considering the small number of observations.