Mapping ice and open water in ocean bodies is important for numerous purposes including environmental analysis and ship navigation. The Canadian Ice Service (CIS) currently has several expert ice analysts manually generate ice maps on a daily basis. The CIS would like to augment their current process with an automated ice-water discrimination algorithm capable of operating on dual-pol synthetic aperture radar (SAR) images produced by RADARSAT-2. Automated methods can provide mappings in larger volumes, with more consistency, and in finer resolutions that are otherwise impractical to generate. We have developed such an automated ice-water discrimination system called MAGIC. The algorithm first classifies the HV scene using the glocal method, a hierarchical region-based classification method. The glocal method incorporates spatial context information into the classification model using a modified watershed segmentation and a previously developed MRF classification algorithm called IRGS. Second, a pixel-based support vector machine (SVM) using a nonlinear RBF kernel classification is performed exploiting SAR grey-level co-occurrence matrix (GLCM) texture and backscatter features. Finally, the IRGS and SVM classification results are combined using the IRGS approach but with a modified energy function to accommodate the SVM pixel-based information. The combined classifier was tested on 61 ground truthed dual-pol RADARSAT-2 scenes of the Beaufort Sea containing a variety of ice types and water patterns across melt, summer, and freeze-up periods. The average leave-one-out classification accuracy with respect to these ground truths is 95.8% and MAGIC attains an accuracy of 90% or above on 88% of the scenes. The MAGIC system is now under consideration by CIS for operational use.

According to previous research, internalizing and externalizing problems tend to be comorbid or co-occur at different ages in development (Angold, Costello, & Erkanli, 1999). The question that this dissertation addresses is how and why internalizing and externalizing problems, two disorders that represent separate forms of psychopathology, co-occur in children. This is an important question for the developmental psychopathology perspective because an appreciation of the concept of co-occurrence is essential for explaining the development and taxonomy of internalizing and externalizing psychopathology, and for understanding the etiology and course of these symptoms (Achenbach, 1990). Attempts to explain co-occurrence have proposed that co-occurring psychopathology might represent distinct, meaningful syndromes (Angold & Costello, 1992; O’Connor et al., 1998), and in support of this idea, evidence of the existence of pure and co-occurring internalizing and externalizing problems has been found (Keiley et al., 2003). However, no previous study has identified heterogeneous developmental patterns of pure or combined internalizing and externalizing problems within a dynamic framework by taking trajectories of change into account. This dissertation uses data from the NICHD study of Early Child Care to explore the co-occurrence between internalizing and externalizing problems from age 2 to 12 with the use of Latent Class Growth Analysis. The sample included 1232 children (52% male). Different groups of children exhibiting low/normative, pure internalizing, pure externalizing, and co-occurring internalizing and externalizing problems across the 10 year period were identified. The higher risk groups deviated from the low/normative group in terms of antecedents, SES risk, medical risk, difficult temperament, and home environment. Moreover, children who exhibited pure moderate externalizing problems, and children who exhibited chronic externalizing problems, with and without co-occurring internalizing problems, engaged in more risky behaviors and were more likely to have friends who also engaged in risky behaviors. Furthermore, the pure chronic externalizing group and the groups scoring high on internalizing problems, with and without co-occurring externalizing problems, were more asocial with peers. Finally, children exhibiting chronic co-occurring externalizing and internalizing problems were more excluded by peers in comparison to the rest of the sample’s population.

In this thesis, the relationship between several high-latitude phenomena and the ionospheric conductance in both hemispheres is studied theoretically and experimentally. </p>Theoretically, the high-latitude electrodynamics is studied by considering currents in the magnetosphere-ionosphere system resulting from the ionospheric sheet current redistribution between the conjugate ionospheres. It is shown that strong flow between the conjugate ionospheres, the interhemispheric currents (IHC), can be set up if the conductance distribution is asymmetric in the conjugate ionospheric regions. Such conditions are typical for solstices owing to the differences in the solar illumination. Analytical and numerical modeling shows that IHCs can appear in the regions of strong conductance gradient, more specifically around the solar terminator line, and that the intensity of the IHCs can be comparable to the intensity of the well known Region 1/Region 2 currents. The effect of IHC excitation on observable magnetic perturbations on the ground is investigated. It is shown that in the vicinity of the solar terminator line, the pattern of magnetic perturbation can be such that an apparent equivalent current vortex can be detected. In addition, strong conductance gradients are shown to affect significantly the quality of the ionospheric plasma flow estimates from the ground-based magnetometer data. </p>Experimentally, the effect of the nightside ionospheric conductance on occurrence of substorms, global storm sudden commencement and radar auroras is investigated. To characterize substorm occurrence, new parameters, the derivatives of the classical AE and AO indices, are introduced. It is shown that the seasonal and diurnal variations of these parameters are controlled by the total nightside ionospheric conductance in the conjugate regions. The substorm onsets preferentially occur at low levels of the total conductance, which is consistent with the idea of the substorm triggering through the magnetosphere-ionosphere feedback instability. It is hypothesized that the total conductance affects the global storm onsets as well. To check this idea, the 33-year sudden storm commencement (SSC) data are considered. The semiannual, annual, semidiurnal, and diurnal variations in the SSC occurrence rate are found to be significant and these components exhibit a strong relationship with the total conductance of the high-latitude ionospheres. Finally, the SuperDARN midnight echo occurrence is shown to correlate, for some radars, with the total conductance minima and presumably with electric field maxima, which is consistent with general expectation that the F-region irregularities occur preferentially during times of enhanced electric fields. The gradients of the high-latitude conductance can also lead to significant errors in the plasma convection estimates from the ground-based magnetometers, and to investigate this effect a statistical assessment of the difference between the true plasma convection (SuperDARN) and the magnetometer-inferred equivalent convection direction is performed. The largest differences are found for the transition region between the dark and sunlit ionospheres and in the midnight sector where strong conductance gradients are expected due to particle precipitation. Consideration of regular conductance gradients due to solar illumination improves the agreement between the radar and magnetometer data. Finally, an attempt is made to demonstrate the effects of conductance upon the properties of traveling convection vortices (TCVs). Joint SuperDARN and magnetometer data reveal that there is resemblance between the magnetometer and radar inferred TCV images on a scale of thousands of kilometers. However, on a smaller scale of hundreds of kilometers, significant differences are observed.

BAsCET est un système multi-agents à « blackboard », fondé sur l'émergence de concepts dans un modèle dynamique et inspiré de COPYCAT. Pour éviter un raisonnement déterministe unique limitant sa<br />créativité il adapte son comportement en fonction de la solution courante. Nous l'avons appliqué à la reconnaissance automatique de la structure logique (des champs) de références bibliographiques dans les articles scientifiques (en format uniquement physique, c'est-à-dire en PostScript). Le modèle, appelé Réseau de Concepts, s'apparentant à la fois aux réseaux sémantiques et aux réseaux de neurones, est construit automatiquement à partir d'une base de références BIBTeX. Le système utilise les co-occurrences entre les termes des références pour rapprocher dans le modèle ceux qui sont conceptuellement voisins. Le principe de l'analogie est utilisé sur les références de la base : quand le système rencontre une référence inconnue, il fait l'analogie avec la partie physique de la base et essaye de proposer une solution correspondante. Les résultats obtenus, bien que modérés (65,5% de reconnaissance), laissent augurer des résultats encore meilleurs, après optimisation du système.

Återskapade våtmarker är av stor vikt för den biologiska mångfalden och särskilt viktiga för hotade simfåglar. För att öka kunskapen kring hur faktorer som våtmarkers area, ålder och fiskförekomst påverkar simfåglar i återskapade våtmarker studerades fyra våtmarker i Tinnerö naturreservat, Linköpings kommun. Av speciellt intresse var svarthakedoppingen (Podiceps auritus). Antalet svarthakedoppingar i de studerade våtmarkerna hade en positiv utveckling under våtmarkernas första år. Dock minskade antalet svarthakedoppingar i området mellan år 2009 och 2011. År 2011, efter anläggandet av Ekängsdalsgångens våtmarker, stabiliserades antalet igen. Slutsatsen är att nyskapade, fiskfria våtmarker ger goda förutsättningar för hotade arter såsom svarthakedoppingen. Utöver detta undersöktes även de didaktiska möjligheter, utifrån Skolverkets ämnes- och kursplaner för biologi, som exkursioner erbjuder. / Restored wetlands are of great importance for biodiversity, and especially important for endangered waterfowl. In order to increase knowledge about how factors such as wetlands area, age, and fish occurrence affect waterfowl in restored wetlands four wetlands in Tinnerö nature reserve, Linköping municipality, were studied. Of special interest was the horned grebe (Podiceps auritus). The number of horned grebes in the studied wetlands had seen a positive development during the wetlands first years. Between 2009 and 2011, the number of horned grebes in the area declined. The numbers were stabilized in 2011, after the establishment of Ekängsdalsgångens wetlands. The conclusion is that newly created, fish-free wetlands provide good conditions for endangered species such as the horned grebe. In addition to this the study also examined the didactic opportunities, based on the curriculum for biology, which excursions offers.

Η χρήση των δεδομένων Ραντάρ Συνθετικού Ανοίγματος (SAR) σε εφαρμογές απομακρυσμένης παρακολούθησης της Γης έχει ήδη αρχίσει να πρωταγωνιστεί τις τελευταίες δεκαετίες. Τα συστήματα SAR με δυνατότητες μεταξύ άλλων συνεχούς λειτουργίας παντός καιρού, ημέρα και νύχτα, προσφέροντας μεγάλη κάλυψη εδάφους και με δυνατότητα λήψης απεικονίσεων πολλαπλών πολώσεων, έχουν αποτελέσει πηγή πολύτιμων πληροφοριών τηλεπισκόπησης. Έτσι, η χρήση των SAR δεδομένων για την ταξινόμηση κάλυψης γης προσελκύει όλο και περισσότερο την προσοχή των ερευνητών και φαίνεται να είναι πολλά υποσχόμενη. Η παρούσα ειδική επιστημονική εργασία έχει στόχο τη μελέτη και ερμηνεία των δεδομένων SAR μέσω επιβλεπόμενης ταξινόμησης, με τη χρήση νευρωνικών δικτύων (Neural Networks). Αφού πρώτα γίνεται εκτενής αναφορά στη τεχνολογία και τα συστήματα SAR, παρουσιάζεται αναλυτικά η πειραματική διαδικασία ταξινόμησης τριών βασικών δομών κάλυψης γης. Τα δεδομένα προέρχονται από το Προηγμένο Ραντάρ Συνθετικού Ανοίγματος (ASAR) του δορυφόρου ENVISAT από τον Ευρωπαϊκό Οργανισμό Διαστήματος και αφορούν στην ευρύτερη περιοχή του Άμστερνταμ. Πριν την διεξαγωγή της ταξινόμησης, τα δεδομένα δέχθηκαν τις απαραίτητες διαδικασίες προ-επεξεργασίας (ραδιομετρική βαθμονόμηση, γεωαναφορά, φιλτράρισμα θορύβου, συμπροσαρμογή). Όσον αφορά τη διαδικασία της ταξινόμησης, εξετάζεται η συμπεριφορά του ταξινομητή του νευρωνικού δικτύου για μεταβολές ποικίλων παραμέτρων, όπως η επιλογή δεδομένων διαφόρων πολώσεων, το πλήθος των νευρώνων κ.α. και ήδη από τα πρώτα πειράματα λαμβάνονται ικανοποιητικά αποτελέσματα. Στη συνέχεια εφαρμόζονται τεχνικές σύνθεσης πληροφορίας (average rule, majority rule) βελτιώνοντας τις επιδόσεις ταξινόμησης. Τέλος, ένα σημαντικό βήμα που εφαρμόζεται στη διαδικασία ταξινόμησης αποτελεί η εξαγωγή χαρακτηριστικών υφής από τις μήτρες συνεμφάνισης φωτεινοτήτων (Gray Level Co-occurrence Matrix-GLCM) και μήκους διαδρομής φωτεινότητας (Gray Level Run Length Matrix-GLRLM). Η χρήση των χαρακτηριστικών αυτών βελτιστοποιεί το σύστημα ταξινόμησης, δίνοντας εξαιρετικά αποτελέσματα. / The use of Synthetic Aperture Radar (SAR) data in remote sensing applications has become a cutting edge technology during the past few decades. The SAR systems have several capabilities, like day & night and all weather operation and they offer large ground coverage with the ability of multi-polarized imagery; therefore, they have proved to be a valuable source of remote sensing data. As a result, the use of SAR data for land cover classification increasingly attracts the attention of researchers and seems to be highly promising. Goal of this master thesis is the study and interpretation of SAR data through supervised classification, with the use of Neural Networks method. First, there is an extensive presentation of SAR systems and technology and then follows the detailed presentation of the experimental classification process for three basic land cover structures. The available data are from the Advanced SAR (ASAR) radar of the ESA ENVISAT satellite and correspond to the Amsterdam city and suburbs. Prior to the classification process, the data have been appropriately pre-processed (radiometric calibration, geocoding, speckle filtering, co-registration). Regarding the classification process, the response of the neural network classifier with the variation of several parameters (e.g. data polarization and number of neurons) is studied and from the initial test already the results were quite satisfactory. Further on, ensemble classifying methods (average rule, majority rule) are applied to improve the classification performance. Finally, as an essential step applied in the classification process is the textural feature extraction from Gray Level Co-occurrence Matrix (GLCM) and Gray Level Run Length Matrix (GLRLM). The use of these texture features optimizes the classification system, resulting to an exceptional performance.

Mapping ice and open water in ocean bodies is important for numerous purposes including environmental analysis and ship navigation. The Canadian Ice Service (CIS) currently has several expert ice analysts manually generate ice maps on a daily basis. The CIS would like to augment their current process with an automated ice-water discrimination algorithm capable of operating on dual-pol synthetic aperture radar (SAR) images produced by RADARSAT-2. Automated methods can provide mappings in larger volumes, with more consistency, and in finer resolutions that are otherwise impractical to generate. We have developed such an automated ice-water discrimination system called MAGIC. The algorithm first classifies the HV scene using the glocal method, a hierarchical region-based classification method. The glocal method incorporates spatial context information into the classification model using a modified watershed segmentation and a previously developed MRF classification algorithm called IRGS. Second, a pixel-based support vector machine (SVM) using a nonlinear RBF kernel classification is performed exploiting SAR grey-level co-occurrence matrix (GLCM) texture and backscatter features. Finally, the IRGS and SVM classification results are combined using the IRGS approach but with a modified energy function to accommodate the SVM pixel-based information. The combined classifier was tested on 61 ground truthed dual-pol RADARSAT-2 scenes of the Beaufort Sea containing a variety of ice types and water patterns across melt, summer, and freeze-up periods. The average leave-one-out classification accuracy with respect to these ground truths is 95.8% and MAGIC attains an accuracy of 90% or above on 88% of the scenes. The MAGIC system is now under consideration by CIS for operational use.

Cette monographie propose une description des noms discrets collectifs et tente d'en dresser une typologie, à partir d'une définition de la notion sémantique de collectif. Les exemples examinés sont tous tirés de corpus. Les noms discrets collectifs peuvent alors être interprétés comme des touts intégrés formant une unité de rang supérieur qui rassemble des unités de rang inférieur, elles aussi tout intégrés et parties de l'unité collective. Ils sont analysés en fonction de divers paramètres tels que, outre leurscaractéristiques ontologiques et méronymiques, la discernabilité des occurrences et le degré de connexité du tout collectif, ainsi que, par exemple et dans certains cas, le mouvement de l'unité collective, le nombre de dimensions spatiales pris en compte, la variété des occurrences... Dans une deuxième partie, est évalué le rôle du modèle du tout intégré dans la linguistique des noms collectifs et, plus particulièrement, des noms discrets collectifs, dont le prototype est donné par le nom body. La dimension cognitive du tout intégré est double et concerne les constructions linguistiques référentielles et les constructions métalinguistiques. Les noms discrets collectifs sont analysés comme des noms discrets collectifs non prototypiques, ce qui rend compte du fait qu'un certain nombre d'entre eux, tels que line, readership, list, range ou network, ne soient pratiquement jamais mentionnés comme tels dans les ouvrages de linguistique ou de grammaire.

Competition between species is believed to lead to patterns of either competitive exclusion or limiting similarity within ecological communities; however, to date the amount of support for either as an outcome has been relatively weak. The two classes of null model commonly used to assess co-occurrence and limiting similarity have both been well studied for statistical performance; however, the methods used to evaluate their performance, particularly in terms of type II statistical errors, may have resulted in the underreporting of both patterns in the communities tested. The overall purpose of this study was to evaluate the efficacy of the negative co-occurrence and limiting similarity null models to detect patterns believed to result from competition between species and to develop an improved method for detecting said patterns. The null models were tested using synthetic but biologically realistic presence-absence matrices for both type I and type II error rate estimations. The effectiveness of the null models was evaluated with respect to community dimension (number of species × number of plots), and amount of pattern within the community. A novel method of subsetting species was developed to assess communities for patterns of co-occurrence and limiting similarity and four methods were assessed for their ability to isolate the species contributing signal to the pattern. Both classes of null model provided acceptable type I and type II error rates when matrices of more than 5 species and more than 5 plots were tested. When patterns of negative co-occurrence or limiting similarity were add to all species both null models were able to detect significant pattern (β > 0.95); however, when pattern was added to only a proportion of species the ability of the null models to detect pattern deteriorated rapidly with proportions of 80% or less. The use of species subsetting was able to detect significant pattern of both co-occurrence and limiting similarity when fewer than 80% of species were contributing signal but was dependent on the metric used for the limiting similarity null model. The ability of frequent pattern mining to isolate the species contributing signal shows promise; however, a more thorough evaluation is required in order to confirm or deny its utility.

Tsunamis are characterized as shallow water waves, with long periods and wavelengths. They occur by a sudden water volume displacement. Earthquake is one of the main reasons of a tsunami development. Historical data for an observation period of 3500 years starting from 1500 B.C. indicates that approximately 100 tsunamis occurred in the seas neighboring Turkey. Historical earthquake and tsunami data were collected and used to develop two artificial neural network models to forecast tsunami characteristics for future occurrences and to estimate the tsunami return period. Artificial Neural Network (ANN) is a system simulating the human brain learning and thinking behavior by experiencing measured or observed data. A set of artificial neural network is used to estimate the future earthquakes that may create a tsunami and their magnitudes. A second set is designed for the estimation of tsunami inundation with relation with the tsunami intensity, the earthquake depth and the earthquake magnitude that are predicted by the first set of neural networks. In the case study, Marmara and Aegean regions are taken into consideration for the estimation process. Return periods including the last occurred earthquake in the Turkish seas, which was the izmit (Kocaeli) Earthquake in 1999, were utilized together with the average earthquake depths calculated for Marmara and Aegean regions for the prediction of the earthquake magnitude that may create a tsunami in the stated regions for various return periods of 1-100 years starting from the year of 2004. The obtained earthquake magnitudes were used together with tsunami intensities and earthquake depth to forecast tsunami wave height at the coast. It is concluded that, Neural Networks predictions were a satisfactory first step to implement earthquake parameters such as depth and magnitude, for the average tsunami height on the shore calculations.