This is a thesis about the spatial distribution of willow warbler, nightingale, blackbird, robin and grey flycatcher in Svealand and Götaland, that is the southern third of Sweden. It explores the possibilities of using statistics to describe the distribution and variation of birds in a given region.The data was collected by observation of birds on sites called standard routes, with 25 kilometres between them. The standard routes are the points in a grid net placed upon the map of Sweden. The purpose of standard routes is to represent the birds in Sweden both geographic and biotopological.The thesis compare the results from kriging, variogram and four alternative poisson regressions. In the end I come up with the information provided by kriging and variogram and which poisson regression that bests estimates the population sizes of the birds at a given site with information about year, mean temperature from January to May and what kind of environment or habitat the site consist of.

Hydraulic tomography is a cost -effective technique for characterizing the heterogeneity of hydraulic parameters in the subsurface. During hydraulic tomography surveys, a large number of hydraulic heads (i.e., aquifer responses) are collected from a series of pumping or injection tests in an aquifer. These responses are then used to interpret the spatial distribution of hydraulic parameters of the aquifer using inverse modeling. In this study, we developed an efficient sequential successive linear estimator (SSLE) for interpreting data from transient hydraulic tomography to estimate three-dimensional hydraulic conductivity and specific storage fields of aquifers. We first explored this estimator for transient hydraulic tomography in a hypothetical one-dimensional aquifer. Results show that during a pumping test, transient heads are highly correlated with specific storage at early time but with hydraulic conductivity at late time. Therefore, reliable estimates of both hydraulic conductivity and specific storage must exploit the head data at both early and late times. Our study also shows that the transient heads are highly correlated over time, implying only infrequent head measurements are needed during the estimation. Applying this sampling strategy to a well -posed problem, we show that our SSLE can produce accurate estimates of both hydraulic conductivity and specific storage fields. The benefit of hydraulic tomography for ill -posed problems is then demonstrated. Finally, to affirm the robustness of our SSLE approach, we apply the SSLE approach to transient hydraulic tomography in a hypothetical two- dimensional aquifer with nonstationary hydraulic properties, as well as a hypothetical three-dimensional heterogeneous aquifer.

Fine particulate matter (PM2.5) affects the environment in a variety of ways, including of human health, visibility impairment, acid deposition, and climate change. As of March, 2006, 47 counties are designated as non-attainment areas in terms of PM2.5 in the southeastern United States. State agencies with PM2.5 non-attainment counties must develop plans that demonstrate how they will achieve attainment status. State agencies also have to address emission sources of visibility impairment and develop strategies to improve visibility. It is essential to understand PM2.5 composition and sources in order to develop effective control strategies to reduce PM2.5. In this thesis, actual prescribed burning emissions were characterized for better estimation of their impacts on air quality. Chemical mass balance (CMB) modeling, a receptor-oriented source apportionment technique, was applied to understand regional characteristics of PM2.5 source impacts in the Southeast. Uncertainty issues in the CMB source apportionment results due to both poor spatial representativeness and measurement errors was addressed for better understanding and estimation of the uncertainties. Possible future research is recommended based on the findings in this thesis.

Conventional electrocardiography (ECG) is an essential tool for investigating cardiac disorders such as arrhythmias or myocardial infarction. It consists of interpretation of potentials recorded at the body surface that occur due to the electrical activity of the heart. However, electrical signals originated at the heart suffer from attenuation and smoothing within the thorax, therefore ECG signal measured on the body surface lacks some important details. The goal of forward and inverse ECG problems is to recover these lost details by estimating the heart&amp / #8217 / s electrical activity non-invasively from body surface potential measurements. In the forward problem, one calculates the body surface potential distribution (i.e. torso potentials) using an appropriate source model for the equivalent cardiac sources. In the inverse problem of ECG, one estimates cardiac electrical activity based on measured torso potentials and a geometric model of the torso. Due to attenuation and spatial smoothing that occur within the thorax, inverse ECG problem is ill-posed and the forward model matrix is badly conditioned. Thus, small disturbances in the measurements lead to amplified errors in inverse solutions. It is difficult to solve this problem for effective cardiac imaging due to the ill-posed nature and high dimensionality of the problem. Tikhonov regularization, Truncated Singular Value Decomposition (TSVD) and Bayesian MAP estimation are some of the methods proposed in literature to cope with the ill-posedness of the problem. The most common approach in these methods is to ignore temporal relations of epicardial potentials and to solve the inverse problem at every time instant independently (column sequential approach). This is the fastest and the easiest approach / however, it does not include temporal correlations. The goal of this thesis is to include temporal constraints as well as spatial constraints in solving the inverse ECG problem. For this purpose, two methods are used. In the first method, we solved the augmented problem directly. Alternatively, we solve the problem with column sequential approach after applying temporal whitening. The performance of each method is evaluated.

Cognitive radio technology provides a solution for the spectrum scarcity issue by allowing the unlicensed users which are the cognitive radio devices to share the licensed band with the licensed (primary) users. The abilities of cognitive radio device help the secondary (unlicensed) nodes to observe the licensed band and to adjust their transmission parameters for maintaining the primary communication since in cognitive radio networks, it is essential that the existence of the unlicensed users must not harm the licensed network. Under these circumstances, we consider vertical cooperative transmission where primary transmission is not severely damaged by the secondary interference since each primary pair (transmitter and receiver) selects a neighbor secondary user as a cooperative relay to assist their transmission. Cooperation provides an increase in the signal-tointerference-ratio (SIR) of the primary network which can be harnessed by the secondary network as an additional bandwidth for their communication. We propose three relay selection rules so the influence of the relay’s position over the temporal and spatial correlations can be evaluated for different network conditions. Additionally, we implement primary exclusive region (PER) for each primary pair in the network which covers primary nodes, and all secondary users locate inside the zone become inactive. According to the outage model proposed in paper [2], temporal and spatial correlations are assumed to be 1 and 0 respectively; however it is estimated that regarding the environmental factors and the relay’s location, these correlation values may vary. This thesis work is based on the validation of the assumptions provided in paper [2] and our results demonstrate that the temporal and spatial correlation values changes under different circumstances and with different relay selection rules. The simulation results also show that PER significantly stimulates the cooperation performance thereby increases the transmission quality of the primary network.

Submitted by Deyse Queiroz (deysequeirozz@hotmail.com) on 2018-06-06T12:40:50Z No. of bitstreams: 1 MARCUS VINÍCIUS DO CARMO LOIOLA - DISSERTAÇÃO PPGSA PROFISSIONAL 2018..pdf: 820964 bytes, checksum: 8762c281ed02351e37733b5465883902 (MD5) / Made available in DSpace on 2018-06-06T12:40:50Z (GMT). No. of bitstreams: 1 MARCUS VINÍCIUS DO CARMO LOIOLA - DISSERTAÇÃO PPGSA PROFISSIONAL 2018..pdf: 820964 bytes, checksum: 8762c281ed02351e37733b5465883902 (MD5) Previous issue date: 2018-03 / A informática está cada vez mais presente na vida escolar, seja via internet, multimídia ou outros. Compreender a espacialidade dos fenômenos estudados, no presente e no passado, e compará-lo por meio de suas sobreposições, é algo que a própria Geografia busca fazer, e compreender e utilizar a linguagem cartográfica, ampliando as possibilidades dos alunos de analisar informações em vários campos do conhecimento, além de contribuir para a estruturação de uma noção espacial. O objetivo desse projeto foi de aplicar as possibilidades de uso de geotecnologias como incentivo para o ensino da geografia na EEEFM Plínio Lemos, do município de Puxinanã – PB, buscando verificar a visão temporal dos educandos a cerca de seu meio ambiente e as modificações ao longo do tempo. Foi aplicado um questionário nas turmas do 3º Ano médio, turno manhã, onde 50% afirmaram saber o que são geotecnologias e que têm acesso a softwares do gênero (Google Earth, Wikimapia e GPS-Sistema de Posicionamento Global), 73,8% disseram não terem sentido dificuldade em responder o questionário, no entanto, o tempo usado para responder o mesmo bem como as vezes em que os aplicadores do questionário foram chamados para tirar dúvidas mostram o contrário. É importante destacar que 85,7% dos alunos afirmaram que nunca tinham ouvido falar esse termo por parte do professor da disciplina. / Information technology is increasingly present in school life, either via the Internet or other multimedia. Understanding the spatiality of the phenomena studied, the present and the past, and compare it with their overlapping, is something that own search geography do, and understand and use the cartographic language, expanding the possibilities of students to analyze information in various fields of knowledge, and contribute to the development of a space notion. The project goal was to apply the geo usage possibilities as an incentive to the teaching of geography in EEEFM Pliny Lemos, the municipality of Puxinanã – PB, seeking to verify the temporal vision of the students about their environment and changes over of time. A questionnaire in class 3rd year average was applied, morning shift, where 50% said they know what they are geotechnology and who have access to the genus software (Google Earth, Wikimapia and Global Positioning System-GPS), 73.8% said they did not have experienced difficulty in answering the questionnaire, however, the time used to answer the same and the times in which the questionnaire applicators were called to answer questions show otherwise. Importantly, 85.7% of students said they had never heard that term by the subject teacher.

Understanding the effect of human-induced pollution on the environment is an important precursor to promoting public health and environmental stability. One aspect of understanding pollution is understanding pollution sources. Various methods have been used and developed to understand pollution sources and the amount of pollution those sources emit. Multivariate receptor modeling seeks to estimate pollution source profiles and pollution emissions from concentrations of pollutants such as particulate matter (PM) in the air. Previous approaches to multivariate receptor modeling make the following two key assumptions: (1) PM measurements are independent and (2) source profiles are constant through time. Notwithstanding these assumptions, the existence of temporal correlation among PM measurements and time-varying source profiles is commonly accepted. In this thesis an approach to multivariate receptor modeling is developed in which the temporal structure of PM measurements is accounted for by modeling source profiles as a time-dependent Dirichlet process. The Dirichlet process (DP) pollution model developed herein is evaluated using several simulated data sets. In the presence of time-varying source profiles, the DP model more accurately estimates source profiles and source contributions than other multivariate receptor model approaches. Additionally, when source profiles are constant through time, the DP model outperforms other pollution receptor models by more accurately estimating source profiles and source contributions.

En Guadeloupe, actuellement, 5,92% de la demande en énergie électrique sont couverts par la filière photovoltaïque et 3,14% par la filière éolienne soit 9,06% pour leur production cumulée selon le bilan 2015 de l’OREC (Observatoire Régional de l’Energie et du Climat). Selon le plan énergétique régional de prospection, la production cumulée du photovoltaïque et de l’éolien devrait représenter 14% du mix électrique en 2020 et 18% en 2030. Pour atteindre les 14% du mix électrique d’ici les cinq prochaines années, il va donc falloir entre autres, améliorer la prédictibilité pour un développement à un rythme soutenu de ces énergies. Ces travaux de recherches ont consisté à apporter de nouveaux résultats de performance de prévision de l’ensoleillement global à court terme et à donner une connaissance plus fine de la ressource sur trois stations en Guadeloupe. L’étude est basée sur une analyse et un modèle de prévision de l’ensoleillement, faisant intervenir des paramètres spatiaux et temporels. La littérature montre qu’un important nombre de sites est en général utilisé pour une analyse spatio-temporelle, ce qui impliquerait pour nous, de poser de multiples capteurs sur l’ensemble du territoire. Les coûts d’un tel système seraient considérables. Notre approche ici consistera à effectuer une analyse spatio-temporelle sur trois stations. Avec peu de stations et des distances non uniformes nous avons donc cherché à développer un modèle de prévision de l’ensoleillement à court terme en dépit de ces contraintes qui ne répondent pas à une approche classique. Le modèle est basé sur une méthodologie VAR (Vecteur Autorégressif) incluant des paramètres spatiaux et temporels. Une stratégie de sélection des variables est développée afin de sélectionner les prédicteurs (stations) utiles pour la prévision sur une localisation. Cette stratégie itérative permettra d’une part d’être plus proche de la réalité, d’autre part d’un point de vue algorithmique, la tendance des calculs sera plus rapide. En amont du développement du modèle, une étude de la variabilité spatio-temporelle de l’ensoleillement a permis de quantifier et caractériser de manière fine, les interactions dynamiques entre ces trois stations. Par comparaison avec les modèles de la littérature, notre modèle de prévision montre une bonne performance avec des valeurs de RMSE relative allant de 17,48% à 23,79% pour des horizons de prévisions de 5 min à 1h. Les méthodologies développées pourraient à terme offrir une opportunité d’assurer des garanties au gestionnaire du réseau. Si d'avenir des solutions de prévision performantes se généralisaient, cette opportunité permettrait d’ouvrir le marché au-delà du seuil de 30% imposé actuellement. / Currently in Guadeloupe, there is 5,92 % of the electric power request covered by the photovoltaic sector and 3,14 % by the wind sector which represents 9,06 % for their accumulated production, according to the OREC report (Regional Monitoring center of Energy and Climate). According to the regional energy plan, the accumulated production of the photovoltaic and the wind energy should represent 14 % of the electric mix in 2020 and 18 % in 2030. To reach the 14 % of the electric mix within the next five years, we need, among other things, to improve forecast for a sustained development of these energies. These research works consisted in bringing new performance results of short-term forecast of the global solar radiation and in giving a finer knowledge of the resource onto three stations in Guadeloupe. The study is based on an analysis and a forecast model of global solar radiation, by including spatial and temporal parameters. The literature shows that an important number of sites is generally used for a spatio-temporal analysis, which would imply for us, to put multiple sensors on the whole territory. The costs of such a system would be considerable. Our approach here will consist in making a spatiotemporal analysis on three stations. With few stations and not uniform distances, we, thus, tried to define a short-term forecast model of global solar radiation, in spite of these constraints which do not answer to a classic approach. The model is based on a methodology the VAR ( Autoregressive Vector) including spatial and temporal parameters. A strategy of selection of variables is developed to select useful predictors (stations) for the forecast on localization. This iterative strategy, on one hand will allow being closer to the reality, on the other hand to the point of algorithmic view, the trend of the calculations will be faster. Preliminarily, a study of the spatiotemporal variability of global solar radiation, allowed to quantify and to characterize in a fine way, the dynamic interactions between these three stations. Compared with the models of the literature, our forecast model shows a good performance with relative RMSE values going from 17.48 % to 23.79 % for horizons from 5 min to 1 hour. The developed methodologies could eventually offer an opportunity to assure guarantees to the network manager. If in the future the successful solutions of forecast became widespread, this opportunity would allow the opening of the market beyond the 30 % threshold imposed at present.

Wireless sensor networks (WSN) are event based systems that rely on the collective effort of densely deployed sensor nodes continuously observing a physical phenomenon. The spatio-temporal correlation between the sensor observations and the cross-layer design advantages are significant and unique to the design of WSN. Due to the high density in the network topology, sensor observations are highly correlated in the space domain. Furthermore, the nature of the energy-radiating physical phenomenon constitutes the temporal correlation between each consecutive observation of a sensor node. This unique characteristic of WSN can be exploited through a cross-layer design of communication functionalities to improve energy efficiency of the network. In this thesis, several key elements are investigated to capture and exploit the correlation in the WSN for the realization of advanced efficient communication protocols. A theoretical framework is developed to capture the spatial and temporal correlations in WSN and to enable the development of efficient communication protocols. Based on this framework, spatial Correlation-based Collaborative Medium Access Control (CC-MAC) protocol is described, which exploits the spatial correlation in the WSN in order to achieve efficient medium access. Furthermore, the cross-layer module (XLM), which melts common protocol layer functionalities into a cross-layer module for resource-constrained sensor nodes, is developed. The cross-layer analysis of error control in WSN is then presented to enable a comprehensive comparison of error control schemes for WSN. Finally, the cross-layer packet size optimization framework is described.

Dans cette thèse, nous proposons des techniques de gestion de données pour économiser l’énergie dans les réseaux de capteurs périodiques basés sur l’architecture de clustering. Premièrement, nous proposons d’adapter le taux d’échantillonnage du capteur à la dynamique de la condition surveillée en utilisant le modèle de one-way ANOVA et des tests statistiques (Fisher, Tukey et Bartlett), tout en prenant en compte l’énergie résiduelle du capteur. Le deuxième objectif est d’éliminer les données redondantes générées dans chaque cluster. Au niveau du capteur, chaque capteur cherche la similarité entre les données collectées à chaque période et entre des périodes successives, en utilisant des fonctions de similarité. Au niveau du CH, nous utilisons des fonctions de distance pour permettre CH d’éliminer les ensembles de données redondantes générées par les nœuds voisins. Enfin, nous proposons deux stratégies actif/inactif pour ordonnancer les capteurs dans chaque cluster, après avoir cherché la corrélation spatio-temporelle entre les capteurs. La première stratégie est basée sur le problème de couverture des ensembles tandis que la seconde prend avantages du degré de corrélation et les énergies résiduelles de capteurs pour ordonnancer les nœuds dans chaque cluster. Pour évaluer la performance des techniques proposées, des simulations sur des données de capteurs réelles ont été menées. La performance a été analysée selon la consommation d’énergie, la latence et l’exactitude des données, et la couverture, tout en montrant comment nos techniques peuvent améliorer considérablement les performances des réseaux de capteurs. / In this thesis, we propose energy-efficient data management techniques dedicated to periodic sensor networks based on clustering architecture. First, we propose to adapt sensor sampling rate to the changing dynamics of the monitored condition using one-way ANOVA model and statistical tests (Fisher, Tukey and Bartlett), while taking into account the residual energy of sensor. The second objective is to eliminate redundant data generated in each cluster. At the sensor level, each sensor searches the similarity between readings collected at each period and among successive periods, based on the sets similarity functions. At the CH level, we use distance functions to allow CH to eliminate redundant data sets generated by neighboring nodes. Finally, we propose two sleep/active strategies for scheduling sensors in each cluster, after searching the spatio-temporal correlation between sensor nodes. The first strategy uses the set covering problem while the second one takes advantages from the correlation degree and the sensors residual energies for scheduling nodes in the cluster. To evaluate the performance of the proposed techniques, simulations on real sensor data have been conducted. We have analyzed their performances according to energy consumption, data latency and accuracy, and area coverage, and we show how our techniques can significantly improve the performance of sensor networks.