Adaptive Fusion Of Particle Filtering And Spatio-Temporal Motion Energy For Human Tracking

Object tracking is an active research area nowadays due to its importance in human computer interface, teleconferencing and video surveillance. However, reliable tracking of objects in the presence of occlusions, pose and illumination changes is still a challenging topic. In this paper, we introduce a novel tracking approach that fuses two cues namely colour and spatio-temporal motion energy within a particle filter based framework. We conduct a measure of coherent motion over two image frames, which reveals the spatio-temporal dynamics of the target. At the same time, the importance of both colour and motion energy cues is determined in the stage of reliability evaluation. This determination helps maintain the performance of the tracking system against abrupt appearance changes. Experimental results demonstrate that the proposed method outperforms the other state of the art techniques in the used test datasets.

Geographical Studies of Underwater Light Dynamics in the Coastal Archipelago of SW Finland, Baltic Sea

The underwater light field is an important environmental variable as it, among other things, enables aquatic primary production. Although the portion of solar radiation that is referred to as visible light penetrates water, it is restricted to a limited surface water layer because of efficient absorption and scattering processes. Based on the varying content of optical constituents in the water, the efficiency of light attenuation changes in many dimensions and over various spatial and temporal scales. This thesis discusses the underwater light dynamics of a transitional coastal archipelago in south-western Finland, in the Baltic Sea. While the area has long been known to have a highly variable underwater light field, quantified knowledge on the phenomenon has been scarce, patchy, or non-existent. This thesis focuses on the variability in the underwater light field through euphotic depths (1% irradiance remaining), which were derived from in situ measurements of vertical profiles of photosynthetically active radiation (PAR). Spot samples were conducted in the archipelago of south-western Finland, mainly during the ice-free growing seasons of 2010 and 2011. In addition to quantifying both the seasonal and geographical patterns of euphotic depth development, the need and usability of underwater light information are also discussed. Light availability was found to fluctuate in multiple dimensions and scales. The euphotic depth was shown to have combined spatio-temporal dynamics rather than separate changes in spatial and temporal dimensions. Such complexity in the underwater light field creates challenges in data collection, as well as in its utilisation. Although local information is needed, in highly variable conditions spot sampled information may only poorly represent its surroundings. Moreover, either temporally or spatially limited sampling may cause biases in understanding underwater light dynamics. Consequently, the application of light availability data, for example in ecological modelling, should be made with great caution.

Modeling the Stream Water Nitrate Dynamics in 60,000-km(2) European Catchment, the Garonne, Southwest France

The spatial and temporal dynamics in the stream water NO3-N concentrations in a major European river-system, the Garonne (62,700 km(2)), are described and related to variations in climate, land management, and effluent point-sources using multivariate statistics. Building on this, the Hydrologiska Byrans Vattenbalansavdelning (HBV) rainfall-runoff model and the Integrated Catchment Model of Nitrogen (INCA-N) are applied to simulate the observed flow and N dynamics. This is done to help us to understand which factors and processes control the flow and N dynamics in different climate zones and to assess the relative inputs from diffuse and point sources across the catchment. This is the first application of the linked HBV and INCA-N models to a major European river system commensurate with the largest basins to be managed tinder the Water Framework Directive. The simulations suggest that in the lowlands, seasonal patterns in the stream water NO3-N concentrations emerge and are dominated by diffuse agricultural inputs, with an estimated 75% of the river load in the lowlands derived from arable farming. The results confirm earlier European catchment studies. Namely, current semi-distrubuted catchment-scale dynamic models, which integrate variations in land cover, climate, and a simple representation of the terrestrial and in-stream N cycle, are able to simulate seasonal NO3-N patterns at large spatial (> 300 km(2)) and temporal (>= monthly) scales using available national datasets.

Modeling the Stream Water Nitrate Dynamics in 60,000-km(2) European Catchment, the Garonne, Southwest France

The spatial and temporal dynamics in the stream water NO3-N concentrations in a major European river-system, the Garonne (62,700 km(2)), are described and related to variations in climate, land management, and effluent point-sources using multivariate statistics. Building on this, the Hydrologiska Byrans Vattenbalansavdelning (HBV) rainfall-runoff model and the Integrated Catchment Model of Nitrogen (INCA-N) are applied to simulate the observed flow and N dynamics. This is done to help us to understand which factors and processes control the flow and N dynamics in different climate zones and to assess the relative inputs from diffuse and point sources across the catchment. This is the first application of the linked HBV and INCA-N models to a major European river system commensurate with the largest basins to be managed tinder the Water Framework Directive. The simulations suggest that in the lowlands, seasonal patterns in the stream water NO3-N concentrations emerge and are dominated by diffuse agricultural inputs, with an estimated 75% of the river load in the lowlands derived from arable farming. The results confirm earlier European catchment studies. Namely, current semi-distrubuted catchment-scale dynamic models, which integrate variations in land cover, climate, and a simple representation of the terrestrial and in-stream N cycle, are able to simulate seasonal NO3-N patterns at large spatial (> 300 km(2)) and temporal (>= monthly) scales using available national datasets.

Testing for significance of phase synchronisation dynamics in the EEG

A number of tests exist to check for statistical significance of phase synchronisation within the Electroencephalogram (EEG); however, the majority suffer from a lack of generality and applicability. They may also fail to account for temporal dynamics in the phase synchronisation, regarding synchronisation as a constant state instead of a dynamical process. Therefore, a novel test is developed for identifying the statistical significance of phase synchronisation based upon a combination of work characterising temporal dynamics of multivariate time-series and Markov modelling. We show how this method is better able to assess the significance of phase synchronisation than a range of commonly used significance tests. We also show how the method may be applied to identify and classify significantly different phase synchronisation dynamics in both univariate and multivariate datasets.

Dynamics of Dissolved Forms of Carbon and Inorganic Nitrogen in Small Watersheds of the Coastal Atlantic Forest in Southeast Brazil

Based on the fact that streamwater quality reflects landscape conditions, the objectives of this study were: to investigate nitrogen (N), carbon (C), and major ion concentrations in six streams crossing minimally disturbed Atlantic Forest areas, with similar geomorphological characteristics; to determine N and C fluxes in one of these pristine streams (Indaia); and assess the impact of human activity on the biogeochemistry of two other streams in the same region, crossing urbanized areas. The distribution pattern of carbon and inorganic nitrogen dissolved forms, as well as the major ion and biogenic gas concentrations in the streamwater, was similar in pristine streams, indicating that the C and N dynamics were determined by influence of some factors, such as climate, atmospheric deposition, geology, soil type, and land covering, which were analogous in the forested watersheds. The urban streams were significantly different from the pristine streams, showing low dissolved oxygen concentrations, high respiration rates, and high concentrations of carbon dioxide, dissolved inorganic nitrogen, dissolved inorganic carbon, and major ion. These differences were attributed to anthropogenic impact on water quality, especially domestic sewage discharge. Additionally, in the Indaia stream, it was possible to observe the importance of rainfall over temporal dynamics of dissolved carbon forms, and also, the obtained specific flux of dissolved inorganic nitrogen was relatively elevated (approximately 11 kg ha(-1) year(-1)). These results reveal the influence of human activity over the biogeochemistry of coastal streams and also indicate the importance N export of Atlantic Forest to the ocean.

Modeling propagation dynamics of social network worms

Social network worms, such as email worms and facebook worms, pose a critical security threat to the Internet. Modeling their propagation dynamics is essential to predict their potential damages and develop countermeasures. Although several analytical models have been proposed for modeling propagation dynamics of social network worms, there are two critical problems unsolved: temporal dynamics and spatial dependence. First, previous models have not taken into account the different time periods of Internet users checking emails or social messages, namely, temporal dynamics. Second, the problem of spatial dependence results from the improper assumption that the states of neighboring nodes are independent. These two problems seriously affect the accuracy of the previous analytical models. To address these two problems, we propose a novel analytical model. This model implements a spatial-temporal synchronization process, which is able to capture the temporal dynamics. Additionally, we find the essence of spatial dependence is the spreading cycles. By eliminating the effect of these cycles, our model overcomes the computational challenge of spatial dependence and provides a stronger approximation to the propagation dynamics. To evaluate our susceptible-infectious-immunized (SII) model, we conduct both theoretical analysis and extensive simulations. Compared with previous epidemic models and the spatial-temporal model, the experimental results show our SII model achieves a greater accuracy. We also compare our model with the susceptible-infectious-susceptible and susceptible-infectious- recovered models. The results show that our model is more suitable for modeling the propagation of social network worms.

Modeling the spatial and temporal heterogeneity of deforestation-driven carbon emissions: the INPE-EM framework applied to the Brazilian Amazon

We present a generic spatially explicit modeling framework to estimate carbon emissions from deforestation (INPE-EM). The framework incorporates the temporal dynamics related to the deforestation process and accounts for the biophysical and socioeconomic heterogeneity of the region under study. We build an emission model for the Brazilian Amazon combining annual maps of new clearings, four maps of biomass, and a set of alternative parameters based on the recent literature. The most important results are as follows: (a) Using different biomass maps leads to large differences in estimates of emission; for the entire region of the Brazilian Amazon in the last decade, emission estimates of primary forest deforestation range from 0.21 to 0.26 similar to Pg similar to C similar to yr-1. (b) Secondary vegetation growth presents a small impact on emission balance because of the short duration of secondary vegetation. In average, the balance is only 5% smaller than the primary forest deforestation emissions. (c) Deforestation rates decreased significantly in the Brazilian Amazon in recent years, from 27 similar to Mkm2 in 2004 to 7 similar to Mkm2 in 2010. INPE-EM process-based estimates reflect this decrease even though the agricultural frontier is moving to areas of higher biomass. The decrease is slower than a non-process instantaneous model would estimate as it considers residual emissions (slash, wood products, and secondary vegetation). The average balance, considering all biomass, decreases from 0.28 in 2004 to 0.15 similar to Pg similar to C similar to yr-1 in 2009; the non-process model estimates a decrease from 0.33 to 0.10 similar to Pg similar to C similar to yr-1. We conclude that the INPE-EM is a powerful tool for representing deforestation-driven carbon emissions. Biomass estimates are still the largest source of uncertainty in the effective use of this type of model for informing mechanisms such as REDD+. The results also indicate that efforts to reduce emissions should focus not only on controlling primary forest deforestation but also on creating incentives for the restoration of secondary forests.

Avaliação quantitativa da dinâmica espaço-temporal da precipitação na região hidrográfica Tocantins-Araguaia

A análise do comportamento da precipitação em uma bacia hidrográfica é fundamental para a engenharia e gerenciamento dos recursos hídricos. A Região Hidrográfica Tocantins-Araguaia (RHTA) pela sua ocupação recente e potencialidades econômicas, ganha destaque no cenário nacional. Este trabalho avalia quantitativamente a dinâmica espaço-temporal da precipitação anual nesta região durante um período de 30 anos de dados. A dinâmica da precipitação pode ser analisada pelo cálculo da precipitação média em uma dada área, compondo assim mapas de isoietas de precipitação anual. No entanto, a confecção destes mapas requer um método de interpolação que melhor represente as características pluviométricas em locais não amostrados para posterior análise quantitativa do comportamento da precipitação. Para tanto, foram realizados análises exploratórias descritivas amostral e espacial como requisito de estacionaridade do método de interpolação geoestatístico, ajuste e validação do modelo teórico que se adéque ao variograma de precipitação anual. Após a confecção do mapa de isoietas pelo método de Krigagem Ordinária (sem tendência) e Krigagem Universal (com tendência) foi realizado o cálculo do volume precipitado na região hidrográfica pelo método dos contornos. A dinâmica espacial da precipitação foi realizada com base na análise da estatística descritiva, mapa de isoietas, mapa hipsométrico, Índice de Irregularidade Meteorológica (IMM) e Coeficiente de Variação. A dinâmica temporal foi analisada pela distribuição dos totais anuais de precipitação volumétrica para cada sub-bacia da RHTA, pelo Índice de Anomalia Padronizada, na variação interanual de precipitação e teste de tendência e magnitude representados respectivamente pelo Teste de Mann Kendall e Sen’s. Os resultados correlacionados com as anomalias meteorológicas do Oceano Atlântico (Dipolo) e Pacífico (ENOS) indicam o comportamento da precipitação bastante heterogêneo e com grande variabilidade temporal principalmente na sub-bacia Tocantins-Alto (TOA) (14%). Diminuição da amplitude pluviométrica, em anos de anomalia meteorológica intensa ocasionando um incremento de precipitação ao sul das sub-bacias TOA e ARA e diminuição da precipitação na sub-bacia TOB, em eventos de El Niño. Não se pode comprovar pelo teste de Mann Kendall que há uma tendência estatisticamente significativa no volume precipitado na RHTA, mas o estimador Sen’s dá indícios de queda na precipitação na sub-bacia TOA (-1,24 Km^³/ano) e Araguaia (ARA) (-1,13 Km^³/ano) e aumento da precipitação na sub-bacia do Tocantins Baixo (TOB) (0,53 Km^³/ano) e para a RHTA (-1,5 Km^³/ano). Assim a variabilidade espacial e temporal nas sub-bacias está intimamente relacionada aos eventos de anomalia meteorológica, na qual, a sua ação ocorre de maneira irregular ao longo da área de estudo e pode influenciar as diversas atividades sócio-econômicas na RHTA de acordo com sua magnitude e área de ocorrência.

Dinâmica espaço-temporal de danos do cancro basal em Eucalyptus grandis

Pós-graduação em Agronomia (Proteção de Plantas) - FCA

Padrões de distribuição espacial e temporal em comunidades de ácaros em seringueira (Hevea SPP.) no Brasil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Feeding and reproductive dynamics of the damselfish, Stegastes fuscus in the coastal reefs of northeastern Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Integration of spatial and temporal models to predict extreme water table depths

The objective of this work was to evaluate extreme water table depths in a watershed, using methods for geographical spatial data analysis. Groundwater spatio-temporal dynamics was evaluated in an outcrop of the Guarani Aquifer System. Water table depths were estimated from monitoring of water levels in 23 piezometers and time series modeling available from April 2004 to April 2011. For generation of spatial scenarios, geostatistical techniques were used, which incorporated into the prediction ancillary information related to the geomorphological patterns of the watershed, using a digital elevation model. This procedure improved estimates, due to the high correlation between water levels and elevation, and aggregated physical sense to predictions. The scenarios showed differences regarding the extreme levels - too deep or too shallow ones - and can subsidize water planning, efficient water use, and sustainable water management in the watershed.

Self-organised transients in a neural mass model of epileptogenic tissue dynamics

Stimulation of human epileptic tissue can induce rhythmic, self-terminating responses on the EEG or ECoG. These responses play a potentially important role in localising tissue involved in the generation of seizure activity, yet the underlying mechanisms are unknown. However, in vitro evidence suggests that self-terminating oscillations in nervous tissue are underpinned by non-trivial spatio-temporal dynamics in an excitable medium. In this study, we investigate this hypothesis in spatial extensions to a neural mass model for epileptiform dynamics. We demonstrate that spatial extensions to this model in one and two dimensions display propagating travelling waves but also more complex transient dynamics in response to local perturbations. The neural mass formulation with local excitatory and inhibitory circuits, allows the direct incorporation of spatially distributed, functional heterogeneities into the model. We show that such heterogeneities can lead to prolonged reverberating responses to a single pulse perturbation, depending upon the location at which the stimulus is delivered. This leads to the hypothesis that prolonged rhythmic responses to local stimulation in epileptogenic tissue result from repeated self-excitation of regions of tissue with diminished inhibitory capabilities. Combined with previous models of the dynamics of focal seizures this macroscopic framework is a first step towards an explicit spatial formulation of the concept of the epileptogenic zone. Ultimately, an improved understanding of the pathophysiologic mechanisms of the epileptogenic zone will help to improve diagnostic and therapeutic measures for treating epilepsy.

Temporal sequence of hard and soft tissue healing around titanium dental implants.

The objective of the present review was to summarize the evidence available on the temporal sequence of hard and soft tissue healing around titanium dental implants in animal models and in humans. A search was undertaken to find animal and human studies reporting on the temporal dynamics of hard and soft tissue integration of titanium dental implants. Moreover, the influence of implant surface roughness and chemistry on the molecular mechanisms associated with osseointegration was also investigated. The findings indicated that the integration of titanium dental implants into hard and soft tissue represents the result of a complex cascade of biological events initiated by the surgical intervention. Implant placement into alveolar bone induces a cascade of healing events starting with clot formation and continuing with the maturation of bone in contact with the implant surface. From a genetic point of view, osseointegration is associated with a decrease in inflammation and an increase in osteogenesis-, angiogenesis- and neurogenesis-associated gene expression during the early stages of wound healing. The attachment and maturation of the soft tissue complex (i.e. epithelium and connective tissue) to implants becomes established 6-8 weeks following surgery. Based on the findings of the present review it can be concluded that improved understanding of the mechanisms associated with osseointegration will provide leads and targets for strategies aimed at enhancing the clinical performance of titanium dental implants.