In this dissertation, we consider the clustering problem in data sets with unknown number of clusters having arbitrary shapes, intracluster and intercluster density variations. We introduce a clustering methodology which is composed of three methods that ensures extraction of local density and connectivity properties, data set reduction, and clustering. The first method constructs a unique neighborhood for each data point using the connectivity and density relations among the points based upon the graph theoretical concepts, mainly Gabriel Graphs. Neighborhoods subsequently connected form subclusters (closures) which constitute the skeleton of the clusters. In the second method, the external shape concept in computational geometry is adapted for data set reduction and cluster visualization. This method extracts the external shape of a non-convex n-dimensional data set using Delaunay triangulation. In the third method, we inquire the applicability of Swarm Intelligence to clustering using Ant Colony Optimization (ACO). Ants explore the data set so that the clusters are detected using density break-offs, connectivity and distance information. The proposed ACO-based algorithm uses the outputs of the neighborhood construction (NC) and the external shape formation. In addition, we propose a three-phase clustering algorithm that consists of NC, outlier detection and merging phases. We test the strengths and the weaknesses of the proposed approaches by extensive experimentation with data sets borrowed from literature and generated in a controlled manner. NC is found to be effective for arbitrary shaped clusters, intracluster and intercluster density variations. The external shape formation algorithm achieves significant reductions for convex clusters. The ACO-based and the three-phase clustering algorithms have promising results for the data sets having well-separated clusters.

Functional magnetic resonance imaging (fMRI) based on blood oxygenation level dependent (BOLD) contrast has become a widespread technique in brain research. The central challenge in fMRI is the detection of relatively small activity-induced signal changes in the presence of various other signal fluctuations. Physiological fluctuations due to respiration and cardiac pulsation are dominant sources of confounding variability in BOLD fMRI. This dissertation seeks to characterize and compensate for non-neural physiological fluctuations in fMRI. First, the dissertation presents an improved and generalized technique for correcting T1 effect in cardiac-gated fMRI data incorporating flip angle estimated from fMRI dataset itself. Using an unscented Kalman filter, spatial maps of flip angle and T1 relaxation are estimated simultaneously from the cardiac-gated time series. Accounting for spatial variation in flip angle, the new method is able to remove the T1 effects robustly, in the presence of significant B1 inhomogeneity. The technique is demonstrated with simulations and experimental data. Secondly, this dissertation describes a generalized retrospective technique to precisely model and remove physiological fluctuations from fMRI signal: Physiological Impulse Response Function Estimation and Correction (PIRFECT). It is found that the modeled long-term physiological fluctuations explained significant variance in grey matter, even after removing short-term physiological effects. Finally, application of the proposed technique is observed to substantially increase the intra-session reproducibility of resting-state networks.

Landscape metrics measure the composition and configuration of habitats within landscapes; often the goal is to measure fragmentation. While a variety of existing metrics characterize the connectivity and contiguity of habitat patches, most do not explicitly consider the fragmenting effects of roads in their formulations. This research develops a set of new landscape metrics that explicitly quantify how roads disconnect and break apart habitat patches. This research introduces the following four metrics to consider the fragmenting effects of transportation networks: (1) Number of Connected Patches, a measure of connectivity; (2) Euclidean Nearest Neighbor-Roads, a measure of proximity; (3) Road Density, a measure of dispersion, and (4) Distance to Roads, a measure of division. Each of these formulations explicitly considers the presence of roadways. The metrics are applicable at three spatial scales: patch, class, and landscape. Number of Connected Patches (NCP) provides a new roadway-sensitive measure of patch connectivity by computing the number of patches of identical cover type in a landscape that can be traversed on the shortest straight line distance between them without crossing a road. Euclidean Nearest Neighbor-Roads (ENNR) calculates the distance to the Euclidean nearest neighbor of a patch of the same cover type that is not separated by a roadway. Road Density (RD) leverages the ratio of total roadway network length intersecting a patch, class, or landscape versus respective total unit area. Distance to Roads (DR) provides a new measure of division by taking the shortest Euclidean distance in meters of any patch to the nearest roadway. The performance of the new metrics is evaluated using simulated landscape data with different transportation network structures and habitat patch configurations. This is accomplished by comparing output from the road-based metrics to existing metrics that quantify habitat density, isolation, dispersion, and division. The results of the study demonstrate that the new road-based landscape metrics provide an improved means of quantifying habitat fragmentation caused by transportation networks. This is especially evident as simulated transit network increases for each landscape; response of new metrics to increased road presence is linear and as expected given metric design. These metrics have successfully captured notable patch, class, and landscape level characteristics and their associated responses which are not available with treatment by conventional measures of landscape fragmentation.

Much effort of reservoir engineers is devoted to the time-consuming process of history matching in a simulator to understand the reservoir complexity. Its accuracy is debatable because only a few inputs are known. Several analytical tools have been developed to investigate reservoir heterogeneity. The reciprocal productivity index (RPI) is a tool to measure the pressure support observed at a producer. The log (water-oil ratio or WOR) plot can be used to indicate the presence of a channel. A capacitance-resistance model (CRM) is a simple tool to estimate the connectivity between a producer-injector pair from the production/injection and pressure data. Generally field operators implement an improved recovery plan such as water-alternating-gas (WAG) flood to improve displacement efficiency. However, the existence of heterogeneity compromises its performance. The first objective of this study is to improve the assessment of tertiary flood performance by integrating the CRM with other analytical tools. The integrated method was applied to a miscible flood field in West Texas. The results suggest strong interwell connectivity found more frequently in the NE-SW direction and the different preferential flow paths of injected CO2 and water. Overall, the results provide insights into the current flood status. The operating conditions of a producer dynamically change because of well/field constraints. These changes can induce significant interference in other wells, which cannot be captured by CRM. The second objective of this study is to develop a capacitance-resistance model with producer-producer interaction (CRMP-P). The CRMP-P, derived from the continuity and Darcy’s equations, accounts for producer-producer interactions. The CRMP-P was applied to data from three different reservoir models. The results suggest that the CRMP-P could fit the data with higher precision than CRM. Consequently, the CRMP-P estimates of reservoir properties are more accurate. Moreover, the estimated transmissibility between producers is in agreement with the reservoir models. The CRMP-P was also applied to Omani field data. The transmissibility results are consistent with previous study and the drilling information. The more accurate information on producer-producer interactions and reservoir properties can assist in history-matching, locating infill wells, and reservoir management planning. / text

Wireless Sensor Networks (WSNs) continue to evolve as new applications emerge. In the recent past, WSNs were mostly single sink networks with a few number of homogeneous and static sensor nodes. Now, several applications require networks with multiple and moving sinks and targets as well as thousands of heterogeneous devices. However, the same constraints remain: sensor nodes continue to be very limited in resources, posing new challenges in the design of scalable and energy-efficient algorithms and communication protocols to support these new applications. This dissertation first addresses the problem of sink localization in large scale WSNs. A scalable and energy-efficient sink localization mechanism, called the Anchor Location Service (ALS), is introduced to support the use of location-based routing protocols. ALS avoids frequent and costly flooding procedures derived from the mobility of the sinks and targets, and utilizes face routing to guarantee the success of localization. The problem of topology control in heterogeneous environments is addressed next. A new topology control mechanism, the Residual Energy-Aware Dynamic (READ) algorithm, is devised to extend the lifetime of the network while maintaining connectivity. READ extends the lifetime of the network by assigning a more prominent role to more powerful devices. ALS and READ are evaluated and compared with other well-known protocols using analytical means and simulations. Results show that ALS provides a scalable sink location service and reduces the communication overhead in scenarios with multiple and moving sinks and targets. Results also show that READ increases both the network lifetime and the packet delivery rate.

Studien syftar till att testa teorier om effekter av habitatstorlek, konnektivitet, områdesskydd, habitatmängd och fragmentering på enskilda arters förekomstmönster, samt undersöka existensen av fragmenteringströskel och utdöendetröskel. Förekomstdata för revlummer Lycopodium annotinum och mattlummer Lycopodium clavatum har insamlats i 61 skogsfragment utspridda i 10 kartrutor à 2,5×2,5 km i landskapet Södermanland. I vardera skogsfragment undersöktes en yta om 500m2. Revlummer förekom i 13 och mattlummer i 10 av de undersökta skogsfragmenten. I 7 kartrutor förekom revlummer i minst 1 skogsfragment, för mattlummer var motsvarande siffra 8 kartrutor. Resultaten visar att habitatstorlek har en signifikant positiv effekt på förekomst av revlummer och mattlummer samt att konnektivitet har en signifikant positiv effekt på förekomst av mattlummer. Områdesskydd, habitatmängd och fragmentering i landskapet har ingen påvisad effekt på förekomst av dessa arter och ingen fragmenteringströskel eller utdöendetröskel har hittats. Dessa resultat indikerar att ett bevarande av skogsfragment med stor storlek och hög konnektivitet är viktigt för de undersökta arternas fortsatta livskraft. / The aim of this study is to test theories of the effects of habitat size, connectivity, area protection, habitat amount and fragmentation on the occurrence of single species, plus examining the existence of a fragmentation threshold and an extinction threshold. Occurrence of stiff clubmoss Lycopodium annotinum and stag’s-horn clubmoss Lycopodium clavatum was examined in 61 forest fragments scattered over 10 large 2,5×2,5 km plots, located in the county of Stockholm in Sweden. In each forest an area covering 500m2 was searched for the two species. Lycopodium annotinum occured in 13 and L. clavatum in 10 of the investigated fragments. Lycopodium annotinum occurred in at least 1 fragment in 7 large plots, 8 large plots was the corresponding number for L. clavatum. The results showed a significant positive effect of habitat size on the occurrence of both species and a significant positive effect of connectivity on the occurrence of Lycopodium clavatum. Area protection, habitat amount and fragmentation had no observed effect on the occurrence of these species, and no fragmentation threshold or extinction threshold was found. These results indicate the importance of preserving large forest fragments with high connectivity, to assure continued viability of the examined species.

In river ecology the description and understanding of near-natural ecosystem functionality is a difficult task to achieve as the majority of river floodplains have been intensively impacted by human activities. This work addresses ecological functionality of a relatively unimpacted large river system, focussing on the lateral dynamic and connectivity mechanisms driving aquatic vegetation processes. Macrophytes were found to be very patchily distributed at the riverscape scale, being mainly confined to low energy lateral habitats in the floodplain, such as backwaters. Backwaters provided favourable conditions for plants to colonise and recruit and contributed highly to species diversity and productivity at the floodplain scale. Differences between backwaters were attributed to the frequency of connectivity with the main channel during flood events. Nevertheless, the ecological mechanism driving diversity through flooding appears not to be related to flow disturbance. Biomass produced in backwaters was found to remain stable after potentially scouring floods. Therefore the hypothesis that flood disturbances promote species diversity through the removal and destruction of biomass and rejuvenate communities such that species coexistence is increased was rejected. Rather, it appears that diversity in backwaters increases along a temporal gradient as a response to the input of colonists and their accumulation overtime through successive flood inputs. Despite the apparently non-destructive effect of floods on macrophyte biomass, backwaters appear to have a significant role in exporting large amounts of plant propagules from the site of production. Backwaters represented a net source of propagules which highly enriched the main channel pool of potential colonists. However, whereas propagules could be dispersed for long distances in flood flows the probability for them to reach a suitable downstream habitat was extremely low. This work showed that dispersal at baseflow and entry to backwaters through the downstream end after short dispersal drift provided a greater chance of successful colonisation despite the individually much shorter distance moved. Backwaters were demonstrated to be rather isolated aquatic habitats, even though they experience hydrological connectivity, suggesting that primary colonisation of these sites is a limiting step. Instead, colonisation was shown to rely primarily on propagules generated internally by established plants. Whereas colonisation could occur via internal re-organisation of existing plant propagules, the backwater seed bank could also contribute to the macrophytes species established in backwaters. Such contribution was consistently low to medium along a gradient of disturbances and connectivity and showed independence from such river flow processes. Species richness was found to be higher in the established species than in the seed bank, suggesting that asexual reproduction is prioritised by aquatic vegetation in riverine backwaters. The occurrence or persistence of macrophyte species in backwaters depends upon rhizome and plant shoot regeneration. The lack of influence of connectivity revealed that plants may originate from both in situ and externally waterborne vegetative propagules derived from other upstream backwaters. This research demonstrated that the lateral dynamic and associated connectivity are major components of river floodplain ecology which generate a wide spectrum of habitats and have a controlling effect on vegetation processes. Therefore a naturally dynamic ecological state is required to support ecosystem functionality in large river floodplains and especially to maintain a high level of species diversity, productivity and colonisation of backwaters by macrophytes.

Diffusion tensor imaging (DTI) is a noninvasive MRI technique used to assess white matter (WM) integrity, fiber orientation, and structural connectivity (SC) using water diffusion properties. DTI techniques are rapidly evolving and are now having a dramatic effect on depression research. Major depressive disorder (MDD) is highly prevalent and a leading cause of worldwide disability. Despite decades of research, the neurobiology of MDD remains poorly understood. MDD is increasingly viewed as a disorder of neural circuitry in which a network of brain regions involved in mood regulation is dysfunctional. In an effort to better understand the neurobiology of MDD and develop more effective treatments, much research has focused on delineating the structure of this mood regulation network. Although many studies have focused on the structural connectivity of the mood regulation network, findings using DTI are highly variable, likely due to many technical and analytical limitations. Further, structural connectivity pattern analyses have not been adequately utilized in specific clinical contexts where they would likely have high relevance, e.g., the use of white matter deep brain stimulation (DBS) as an investigational treatment for depression. In this dissertation, we performed a comprehensive analysis of structural WM integrity in a large sample of depressed patients and demonstrated that disruption of WM does not play a major role in the neurobiology of MDD. Using graph theory analysis to assess organization of neural network, we elucidated the importance of the WM network in MDD. As an extension of this WM network analysis, we identified the necessary and sufficient WM tracts (circuit) that mediate the response of subcallosal cingulate cortex DBS treatment for depression; this work showed that such analyses may be useful in prospective target selection. Collectively, these findings contribute to better understanding of depression as a neural network disorder and possibly will improve efficacy of SCC DBS.

La douleur est une expérience perceptive comportant de nombreuses dimensions. Ces dimensions de douleur sont inter-reliées et recrutent des réseaux neuronaux qui traitent les informations correspondantes. L’élucidation de l'architecture fonctionnelle qui supporte les différents aspects perceptifs de l'expérience est donc une étape fondamentale pour notre compréhension du rôle fonctionnel des différentes régions de la matrice cérébrale de la douleur dans les circuits corticaux qui sous tendent l'expérience subjective de la douleur. Parmi les diverses régions du cerveau impliquées dans le traitement de l'information nociceptive, le cortex somatosensoriel primaire et secondaire (S1 et S2) sont les principales régions généralement associées au traitement de l'aspect sensori-discriminatif de la douleur. Toutefois, l'organisation fonctionnelle dans ces régions somato-sensorielles n’est pas complètement claire et relativement peu d'études ont examiné directement l'intégration de l'information entre les régions somatiques sensorielles. Ainsi, plusieurs questions demeurent concernant la relation hiérarchique entre S1 et S2, ainsi que le rôle fonctionnel des connexions inter-hémisphériques des régions somatiques sensorielles homologues. De même, le traitement en série ou en parallèle au sein du système somatosensoriel constitue un autre élément de questionnement qui nécessite un examen plus approfondi. Le but de la présente étude était de tester un certain nombre d'hypothèses sur la causalité dans les interactions fonctionnelle entre S1 et S2, alors que les sujets recevaient des chocs électriques douloureux. Nous avons mis en place une méthode de modélisation de la connectivité, qui utilise une description de causalité de la dynamique du système, afin d'étudier les interactions entre les sites d'activation définie par un ensemble de données provenant d'une étude d'imagerie fonctionnelle. Notre paradigme est constitué de 3 session expérimentales en utilisant des chocs électriques à trois différents niveaux d’intensité, soit modérément douloureux (niveau 3), soit légèrement douloureux (niveau 2), soit complètement non douloureux (niveau 1). Par conséquent, notre paradigme nous a permis d'étudier comment l'intensité du stimulus est codé dans notre réseau d'intérêt, et comment la connectivité des différentes régions est modulée dans les conditions de stimulation différentes. Nos résultats sont en faveur du mode sériel de traitement de l’information somatosensorielle nociceptive avec un apport prédominant de la voie thalamocorticale vers S1 controlatérale au site de stimulation. Nos résultats impliquent que l'information se propage de S1 controlatéral à travers notre réseau d'intérêt composé des cortex S1 bilatéraux et S2. Notre analyse indique que la connexion S1→S2 est renforcée par la douleur, ce qui suggère que S2 est plus élevé dans la hiérarchie du traitement de la douleur que S1, conformément aux conclusions précédentes neurophysiologiques et de magnétoencéphalographie. Enfin, notre analyse fournit des preuves de l'entrée de l'information somatosensorielle dans l'hémisphère controlatéral au côté de stimulation, avec des connexions inter-hémisphériques responsable du transfert de l'information à l'hémisphère ipsilatéral. / Pain is a perceptual experience comprising many dimensions. These pain dimensions interrelate with each other and recruit neuronal networks that process the corresponding information. Elucidating the functional architecture that supports different perceptual aspects of the experience is thus, a fundamental step to our understanding of the functional role of different regions in the cerebral pain matrix that are involved in the cortical circuitry underlying the subjective experience of pain. Among various brain regions involved in the processing of nociceptive information, primary and secondary somatosensory cortices (S1 and S2) are the main areas generally associated with the processing of sensory-discriminative aspect of pain. However the functional organization in these somatosensory areas is not completely clear and relatively few studies have directly examined the integration of information among somatic sensory regions. Thus, several questions remain regarding the hierarchical relationship between S1 and S2, as well as the functional role of the inter-hemispheric connections of the homologous somatic sensory areas. Likewise, the question of serial or parallel processing within the somatosensory system is another questionable issue that requires further investigation. The purpose of the present study was to test a number of causal hypotheses regarding the functional interactions between S1 and S2, while subjects were receiving painful electric shocks. We implemented a connectivity modeling approach, which utilizes a causal description of system dynamics, in order to study the interactions among activation sites defined by a data set derived from a functional imaging study. Our paradigm consists of 3 experimental scans using electric shock stimuli, with the stimulus intensity changing from moderately painful (level 3), to slightly painful (level 2), and to completely non-painful (level 1) during the final scan. Therefore our paradigm allowed us to investigate how stimulus intensity is encoded within our network of interest, and how the connectivity of the different regions is modulated across the different stimulus conditions. Our result is in favor of serial mode of somatosensory processing with thalamocortical input to S1 contralateral to stimulation site. Thus our results implicates that pain information is propogated from S1 contralateral through our network of interest comprising of bilateral S1 and S2. Our analysis indicates that S1→S2 connection is modulated by pain, which suggests that S2 is higher on the hierarchy of pain processing than S1, in accordance with previous neurophysiological and MEG findings. Lastly, our analysis provides evidence for the entrance of somatosensory information into the hemisphere contralateral to the stimulation side, with inter-hemispheric connections responsible for the transfer of information to the ipsilateral hemisphere.

Migration acts as a selective force on the ecology and evolutionary trajectory of species, as well as presenting fundamental challenges for conservation. My thesis examines the impact of migration by exploring patterns of differentiation among and within migratory and non-migratory populations of the Loggerhead Shrike (Lanius ludovicianus). First, I use morphological, genotypic, stable isotope and leg band recovery data to quantify migratory connectivity in the species. Comparison across markers reveals a generally concordant pattern of moderate connectivity to the Gulf Coast, but overall mixing among populations on the wintering grounds. Combining data from multiple markers in a Bayesian framework improves the resolution of assignment of wintering birds to a breeding ground origin. Information on the species’ migratory patterns provides an explicit framework for interpreting patterns of genetic and ecological variation. I test two hypotheses regarding the interaction of gene flow and migratory habit: (1) migration facilitates gene flow; and (2) gene flow will occur most often along the axis of migration. Genetic population structure in migratory populations is weaker than in non-migratory populations, with gene flow facilitated by dispersal movements of females and first year breeders. As predicted, gene flow occurs most often along the north-south axis of migration, likely due either to opportunistic settling of dispersers or potentially, pairing on the wintering grounds. I investigate variation in the extent and scheduling of moult in relation to underlying genetic differences among populations, age, sex, body size, food availability and migratory habit. I find a pattern of interrupted moult across migratory populations, which may represent a trade-off between time allocated to breeding versus molt and migration. Loggerhead Shrikes in eastern and more southerly migratory populations undergo a greater extent of their moult on the breeding grounds and non-migratory individuals undergo a more extensive pre-formative moult than migratory individuals. I interpret this as suggesting a trade-off between resources allocated to molt versus those required for reproduction. / Thesis (Ph.D, Biology) -- Queen's University, 2011-01-25 15:54:36.593