This thesis addresses the design of multiple description lattice vector quantizer (MDLVQ) with a general number L of descriptions, L >= 3. In the previous work on MDLVQ with L>= 3, once the central and side lattice codebooks are fixed, the decoding quality is determined for all numbers k of received descriptions. Therefore, it is not possible to achieve tradeoffs between the quality of reconstruction for different values of k, 1<= k <= L-1. In order to overcome the above drawback, we propose two flexible MDLVQ schemes for L >= 3. Our first design employs a different reconstruction method than in prior work and a heuristic index assignment algorithm, which uses L-2 parameters to control the distortions for 2 <= k <= L-1. Experimental results for the cases L=3 and L=4 show that significant tradeoffs are achieved by controlling the parameters mentioned above. Our second design is based on a structured index assignment. We start with the case L=3 and then generalize the index assignment to any L >= 3. The structured index assignment is able to control the tradeoff by adjusting the sizes of some L-1 subsets of side lattice points. Another important contribution of the thesis is the derivation of analytical expressions of the distortions for the structured index assignment, under the high resolution assumption. These expressions show that a wide range of distortion values can be achieved. / Thesis / Master of Applied Science (MASc)

In this thesis we propose two lattice-based robust distributed source coding systems, one for two correlated sources and the other for three correlated sources. We provide a detailed performance analysis under the high resolution assumption. It is shown that, in a certain asymptotic regime, our scheme for two correlated sources achieves the information-theoretic limit of quadratic multiple description coding (MDC) when the lattice dimension goes to infinity, whereas a variant of the random coding scheme by Chen and Berger with Gaussian codes is 0.5 bits away from this limit. Our analysis also shows that, under the same asymptotic regime, when the lattice dimension goes to infinity, the proposed scheme for three correlated sources is very close to the theoretical bound for the symmetric quadratic Gaussian MDC problem with single description and all three descriptions decoders. / Thesis / Doctor of Philosophy (PhD)

The quantification of sediment budget in a well-defined ancient source-to-sink (S2S) system is vital to understand Earth history and basin evolution. Fulcrum analysis is an effective approach to estimate sediment volumes of depositional systems, given total mass balance throughout source areas to basins. The key to this approach is to quantify sediment in a closed S2S system with time controls. We analyzed Allomember E of the Cretaceous Dunvegan Alloformation in the Western Canadian Sedimentary Basin to test this sediment estimation approach. The results indicate that the sediment transported by the trunk-river generically matches the sediment estimated to be deposited in the basin. The upper-range estimate may suggest mud dispersal southward by geostrophic currents. Deciphering the relationships between traditional lithostratigraphy and sequence stratigraphy is the key to correctly understanding time-stratigraphic relationships. High-resolution sequence stratigraphic analysis of the Cretaceous Gallup system documents the high-frequency depositional cyclicity using detailed facies analysis in extensively exposed outcrops in northwestern New Mexico, US. We identified thirteen stratigraphic sequences, consisting of twenty-six parasequence and sixty-one parasequences. Shoreline trajectories are evaluated based on the geometry of the parasequences. The results show the previously identified sandstone tongues are equivalent to high-frequency sequence sets. The depositional duration estimates of respective sequence stratigraphic units, associated with the estimated changes in relative sea level, imply that Milankovitch-cycle-dominated glacio-eustasy may be the predominant control on the high-frequency sequence stratigraphy. Shoreline processes are more dynamic and complicated with mixed-energy dominance. The re-evaluation of the depositional environments of the Gallup system and the reconstructions of the paleogeography with temporal controls help to examine the depositional evolution in space and time. Paleogeographic reconstructions at parasequence scales allow for the documentation of the process-based lateral facies variations and the depositional evolution. The distinction between different wave-dominated facies associations is proposed based on this process-based facies analysis. / Dissertation / Doctor of Philosophy (PhD)

Heterogeneous geospatial big data, from multi-modal Earth Observation (EO) data to geo-social media data, has become more and more accessible in recent years. This provides a potential data source for automatically extracting and mapping key geographical characteristics, hence mitigating the global mapping problem using current data mining methods. These automated geographic feature mapping techniques, especially for man-made infrastructure, are crucial to a lot of our socio-economic existence. Machine learning techniques, among many other data mining methodologies, have demonstrated better performance across a wide range of academic domains, most notably natural language processing and computer vision. In recent times, there has been a growing interest in research on ML-based Geospatial Artificial Intelligence (GeoAI), particularly in its ability to support autonomous mapping with heterogeneous geographical data. Though the potential is high and obvious, it remains a major challenge to handle inherent heterogeneity and empower data synergy when building robust and scalable GeoAI models for large-scale automated mapping purposes. For geospatial analysis, citizen science initiative is seen to be the most effective. This is a result of the fast development of Web 2.0 and crowdsourcing/Volunteered Geographic Information (VGI) technologies. These technologies enable even regular users or volunteer mappers to develop, gather, and distribute geospatial data using a variety of digital devices (such as desktop computers, mobile tablets, and smartphones). The technological obstacles to digital mapping have been significantly reduced by ongoing crowdsourcing and VGI efforts. In the real world, though, problems with global mapping have persisted for a considerable amount of time even in higher-income nations. Intelligent automated mapping techniques for geospatial analysis are desperately needed in this situation since they may effectively and efficiently close significant data gaps across nations. The research effort reported in this dissertation explores the possibilities of using citizen science or VGI to conduct geospatial analysis of different man-made infrastructures using ML from diverse geospatial data sources (e.g., multi-modal EO data, OSM, and GIS data). Three main research questions (RQs), derived from data-driven, method-driven, and application-driven research perspectives, are established to better address the issue of geospatial analysis with remote sensing and citizen science. The thesis especially goes in this direction by i) investigating the data-driven issue that combines ML for segmentation tasks; ii) creating strategies to deal with VGI data noises; and iii) using the created strategies in various mapping tasks. This creates even more intriguing possibilities for related works in the future.

This paper describes the design and simulation of a microwave band, high resolution imaging ground penetrating radar. A conceptual explanation is given on the mechanics of wave-based imaging, followed by the governing radar equations. The performance specifications for the imaging system are given as inputs to the radar equations, which output the full system specifications. Those specifications are entered into a MATLAB simulation, and the simulation results are discussed with respect to both the mechanics and the desired performance. Finally, this paper discusses limitations of the design, both with the simulations and anticipated issues if the device is fully realized. / Master of Science

The intricate task of segmenting and quantifying cell nuclear pores in high-resolution 3D microscopy data is critical for cellular biology and disease research. This thesis introduces a deep learning pipeline crafted to automate the segmentation and quantification of nuclear pores from high-resolution 3D cell organelle images. Our aim is to refine computational methods capable of handling the data's complexity and size, thus improving accuracy and reducing manual labor in biological image analysis. The developed pipeline incorporates data preprocessing, augmentation strategies, random block sampling, and a three-stage post-processing algorithm. It utilizes a 3D U-Net with a VGG-16 backbone, optimized through cyclical data augmentation and random block sampling to tackle the challenges posed by limited labeled data and the processing of large-scale 3D images. The pipeline has demonstrated its capability to effectively learn and predict nuclear pore structures, achieving improvements in validation metrics compared to baseline models. Our experiments suggest that cyclical augmentation helps prevent overfitting, and random block sampling contributes to managing data imbalance. The post-processing phase successfully automates the quantification of nuclear pores without the need for manual intervention. The proposed pipeline offers an efficient and scalable approach to segmenting and quantifying nuclear pores in 3D microscopy images. Despite the ongoing challenges of computational intensity and data volume, the techniques developed in this study provide insights into the automation of complex biological image analysis tasks, with potential applications extending beyond the detection of nuclear pores. / Master of Science / This thesis outlines a computer program developed to automatically segment and count nuclear pores in 3D cell images, aiding cell and disease research. This program aims to handle large, complex image data more effectively, boost accuracy, and cut down the need for manual labor. We created a system that prepares data, applies a technique called augmentation to enrich it, selects specific image sections, and carries out a three-step final analysis. At the core of our program is a 3D U-Net model, a type of deep learning network, that has been enhanced to address the challenges of scarce labeled data and the processing of very large images. The system developed is capable of learning and identifying the structure of nuclear pores in cell images. Our experiments indicate that using augmentation in a cyclical manner during training can prevent overfitting, which is when a model learns the training data too well, and cannot suitably generalize. Selecting certain parts of the images for processing proves helpful with imbalanced data. Additionally, the program can automatically count nuclear pores in the final step. The proposed program is effective for analyzing and counting nuclear pores in 3D cell images and has the potential for broader applications in cell analysis. Despite the challenges of managing large datasets and the significant computational power required, our methods open new possibilities for automating cell studies, with uses extending beyond just nuclear pores.

Two primary types of multiplayer gaming have emerged over the years. The first type involves co-located players on a shared display, and typically caps at four players. The second type of gaming provides a single display for each player. This type scales well beyond four players, but places no requirement on co-location. This paper will attempt to combine the best of both worlds via high-resolution, highly-multiplayer gaming. Over the past few years, there has been a rise in the number of extremely high-resolution, tiled displays. These displays provide an enormous amount of screen space to work with. This space was used to allow twelve co-located players to play a game together. This study accomplishes three things: we designed and built PyBomber, a high-resolution and highly multiplayer game for up to twelve players; secondly, user trials were conducted to see whether this type of gaming is enjoyable as well as to learn what sorts of social interactions take place amongst so many players; lastly, the lessons learned were generalized into design criteria for future high-resolution games. Results show that with more people, much more of the time during a game was filled with vocal interactions between players. There were also more physical movements in the larger games. Over the course of this study, we learned that good high-resolution games will: decide between a singular gameplay area and split views, use the physical space in front of the display, provide feedback that is localized to each player, and utilize input devices appropriately. / Master of Science

In der vorliegenden Arbeit wird erstmals das QQDS-Magnetspektrometer für die höchstauflösende Ionenstrahlanalytik leichter Elemente am Helmholtz-Zentrum Dresden-Rossendorf umfassend vorgestellt. Zusätzlich werden sowohl alle auf die Analytik Einfluss nehmenden Parameter untersucht als auch Methoden und Modelle vorgestellt, wie deren Einfluss vermieden oder rechnerisch kompensiert werden kann. Die Schwerpunkte dieser Arbeit gliedern sich in fünf Bereiche. Der Erste ist der Aufbau und die Inbetriebnahme des QQDS-Magnetspektrometers, der zugehörige Streukammer mit allen Peripheriegeräten und des eigens für die höchstauflösende elastische Rückstoßanalyse entwickelten Detektors. Sowohl das umgebaute Spektrometer als auch der im Rahmen dieser Arbeit gebaute Detektor wurden speziell an experimentelle Bedingungen für die höchstauflösende Ionenstrahlanalytik leichter Elemente angepasst und erstmalig auf einen routinemäßigen Einsatz hin getestet. Der Detektor besteht aus zwei Komponenten. Zum einen befindet sich am hinteren Ende des Detektors eine Bragg-Ionisationskammer, die zur Teilchenidentifikation genutzt wird. Zum anderen dient ein Proportionalzähler, der eine Hochwiderstandsanode besitzt und direkt hinter dem Eintrittsfenster montiert ist, zur Teilchenpositionsbestimmung im Detektor. Die folgenden zwei Schwerpunkte beinhalten grundlegende Untersuchungen zur Ionen-Festkörper-Wechselwirkung. Durch die Verwendung eines Magnetspektrometers ist die Messung der Ladungszustandsverteilung der herausgestreuten Teilchen direkt nach einem binären Stoß sowohl möglich als auch für die Analyse notwendig. Aus diesem Grund werden zum einen die Ladungszustände gemessen und zum anderen mit existierenden Modellen verglichen. Außerdem wird ein eigens entwickeltes Modell vorgestellt und erstmals im Rahmen dieser Arbeit angewendet, welches den ladungszustandsabhängigen Energieverlust bei der Tiefenprofilierung berücksichtigt. Es wird gezeigt, dass ohne die Anwendung dieses Modells die Tiefenprofile nicht mit den quantitativen Messungen mittels konventioneller Ionenstrahlanalytikmethoden und mit der Dickenmessung mittels Transmissionselektronenmikroskopie übereinstimmen, und damit falsche Werte liefern würden. Der zweite für die Thematik wesentliche Aspekt der Ionen-Festkörper-Wechselwirkung, sind die Probenschäden und -modifikationen, die während einer Schwerionenbestrahlung auftreten. Dabei wird gezeigt, dass bei den hier verwendeten Energien sowohl elektronisches Sputtern als auch elektronisch verursachtes Grenzflächendurchmischen eintreten. Das elektronische Sputtern kann durch geeignete Strahlparameter für die meisten Proben ausreichend minimiert werden. Dagegen ist der Einfluss der Grenzflächendurchmischung meist signifikant, so dass dieser analysiert und in der Auswertung berücksichtigt werden muss. Schlussfolgernd aus diesen Untersuchungen ergibt sich für die höchstauflösende Ionenstrahlanalytik leichter Elemente am Rossendorfer 5-MV Tandembeschleuniger, dass die geeignetsten Primärionen Chlor mit einer Energie von 20 MeV sind. In Einzelfällen, wie zum Beispiel der Analyse von Bor, muss die Energie jedoch auf 6,5 MeV reduziert werden, um das elektronische Sputtern bei der notwendigen Fluenz unterhalb der Nachweisgrenze zu halten. Der vierte Schwerpunkt ist die Untersuchung von sowohl qualitativen als auch quantitativen Einflüssen bestimmter Probeneigenschaften, wie beispielsweise Oberflächenrauheit, auf die Form des gemessenen Energiespektrums beziehungsweise auf das analysierte Tiefenprofil. Die Kenntnis der Rauheit einer Probe an der Oberfläche und an den Grenzflächen ist für die Analytik unabdingbar. Als Resultat der genannten Betrachtungen werden die Einflüsse von Probeneigenschaften und Ionen-Festkörper-Wechselwirkungen auf die Energie- beziehungsweise Tiefenauflösung des Gesamtsystems beschrieben, berechnet und mit der konventionellen Ionenstrahlanalytik verglichen. Die Möglichkeiten der höchstauflösenden Ionenstrahlanalytik werden zudem mit den von anderen Gruppen veröffentlichten Komplementärmethoden gegenübergestellt. Der fünfte und letzte Schwerpunkt ist die Analytik leichter Elemente in ultradünnen Schichten unter Berücksichtigung aller in dieser Arbeit vorgestellten Modelle, wie die Reduzierung des Einflusses von Strahlschäden oder die Quantifizierung der Elemente im dynamischen Ladungszustandsnichtgleichgewicht. Es wird die Tiefenprofilierung von Mehrschichtsystemen, bestehend aus SiO2-Si3N4Ox-SiO2 auf Silizium, von Ultra-Shallow-Junction Bor-Implantationsprofilen und von ultradünnen Oxidschichten, wie zum Beispiel High-k-Materialien, demonstriert.

This thesis presents information on the subcellular localisation of two important trace elements, selenium and arsenic, in wheat, rice and rice roots for what is believed to be the first time. The general aim of this work was to illustrate the potential of using physical science techniques to solve biological problems. High resolution secondary ion mass spectrometry was undertaken using the CAMECA NanoSIMS50 with a sensitivity down to ppm concentrations and a lateral resolution of less than 100 nm. Selenium in wheat grain was found to be distributed across both the bran layer and the endosperm region with Se-rich hotspots found in the aleurone cells and a higher intensity of Se in the subaleurone region. Arsenic in rice grain was found in two key regions. In grains with high As and high dimethylarsinic acid (DMA) content, As was predominantly localised to the subaleurone region yet in lower concentration, hydroponically grown As(III)-treated grains the As was only localised to the aleurone layer near the ovular vascular trace (OVT). A combined NanoSIMS and S-XRF experiment revealed As hotspots near the OVT. A combination of high pressure freezing, high resolution secondary ion mass spectrometry and TEM was used to localise As in the roots of rice plants revealing a contrasting subcellular distribution of As and Si in the roots even though arsenite and silicic acid are transported across the plasma membranes by the same transporters. Fe plaque forms only on the root epidermis and was shown to be a strong sink for As. Colocalisation of S with As in the vacuoles of the endodermis, pericycle and xylem parenchyma supports the notion that As is stored as arsenite-phytochelatin complexes in the roots while Si is localised in the endodermis cell walls and is not strongly affected by the Lsi2 mutation.

O gênero Yersinia pertence à família Enterobacteriaceae e compreende 17 espécies. Y. pestis, Y. pseudotuberculosis e Y. enterocolitica são reconhecidamente patógenos de humanos e animais. Y. pestis cause a peste. Y. pseudotuberculosis e Y. enterocolitica são agentes causadores, sobretudo, de gastroenterites transmitidas por água e alimentos. As demais 14 espécies são, usualmente, consideradas não-patogênicas, com exceção de Y. ruckeri sorogrupo O:1 que causa infecções em peixes. Nas últimas décadas, a tipagem molecular tornou-se uma importante ferramenta nos estudos filogenéticos de numerosos micro-organismos e o desenvolvimento de sistemas de tipagem rápidos e baratos pode facilitar os estudos epidemiológicos de infecções bacterianas. No presente estudo objetivou-se desenvolver um método de genotipagem de Yersinia spp. baseado em high-resolution melting analysis (HRMA) para diferenciar os single-nucleotide polymorphisms (SNPs) presentes nas sequências dos genes 16S rRNA, glnA, gyrB, hsp60 e recA e aplicá-lo na tipagem de 40 linhagens de Y. pseudotuberculosis e 50 linhagens de Y. enterocolitica, bem como separar por HRMA as espécies Y. pseudotuberculosis e Y. enterocolitica. Os SNPs foram determinados nas sequências dos loci acima citados a partir de um conjunto de 119 linhagens de Yersinia spp. depositadas no GenBank/EMBL/DDBJ. Foram encontrados nas sequências dos genes analisados de Y. pseudotuberculosis, Y. enterocolitica, Y. bercovieri, Y. rohdei, Y. intermedia, Y. mollaretii e Y. ruckeri 10, 10, 9, 6, 4, 1 e 1 SNPs, respectivamente. Nenhum SNP foi encontrado nas sequências analisadas de Y. pestis e um grande número de SNPs foi encontrado nas sequências analisadas de Y. frederiksenii, Y. kristensenii e Y. massiliensis, o que impossibilitou a genotipagem dessas espécies por HRMA. As demais espécies não foram analisadas. Foram desenhados pares de primers para flanquear os SNPs encontrados em cada espécie de Yersinia testada. Usando um conjunto de primers espécie-específicos, a diversidade genética de cada espécie de Yersinia foi determinada por HRMA e a análise filogenética foi baseada na sequência concatenada composta pelos nucleotídeos identificados em cada fragmento analisado. O agrupamento foi realizado com o software BioNumerics usando o método UPGMA com 1.000 replicatas de bootstrap. A árvore filogenética ii construída para Y. pseudotuberculosis agrupou as linhagens em clusters bio-sorogrupo específicos. As linhagens do bio-sorogrupo 1/O:1 foram agrupadas em um cluster e as linhagens do bio-sorogrupo 2/O:3 em outro. A árvore filogenética construída para Y. enterocolitica agrupou as linhagens em três grupos. As linhagens altamente patogênicas, do biotipo 1B, foram agrupadas em um cluster, as linhagens de média patogenicidade, dos biotipos 2, 3, 4 e 5, foram agrupadas em um segundo cluster e as linhagens consideradas nãopatogênicas, do biotipo 1A, foram agrupadas em um terceiro cluster. O agrupamento encontrado em Y. pseudotuberculosis e Y. enterocolitica foi consistente com o perfil patogênico característico dessas duas espécies. Nenhuma correlação epidemiológica significativa foi encontrada no agrupamento de Y. bercovieri, Y. rohdei, Y. intermedia, Y. mollaretii e Y. ruckeri de acordo com os resultados de HRMA. Ademais, o método de HRMA aqui desenvolvido foi capaz de separar as espécies Y. pseudotuberculosis e Y. enterocolitica. O método de HRMA desenvolvido nesse estudo pode ser usado como uma alternativa para a genotipagem e para a diferenciação de Y. pseudotuberculosis de Y. enterocolitica. Esse método também pode complementar os métodos baseados em sequências e facilitar os estudos epidemiológicos dessas duas espécies de Yersinia. / The genus Yersinia belongs to the family Enterobacteriaceae and comprises 17 species. Y. pestis, Y. pseudotuberculosis and Y. enterocolitica are well recognized human and animal pathogens. Y. pestis causes plague. Y. pseudotuberculosis and Y. enterocolitica are, usually, causative agents of food-waterborne gastroenteritis. The other 14 Yersinia species are considered to be non-pathogenic, with the exception of Y. ruckeri serogroup O:1 which causes infections in fishes. In the last few decades, molecular typing has become an important tool in phylogenetic studies of several microorganisms and the development of fast and inexpensive typing systems can facilitate epidemiological studies of bacterial infections. The present study aimed to develop a method of Yersinia spp. genotyping based on high-resolution melting analysis (HRMA) in order to differentiate the single-nucleotide polymorphisms (SNPs) present in the 16S rRNA, glnA, gyrB, hsp60 and recA sequences and apply it in the typing of 40 Y. pseudotuberculosis strains and 50 Y. enterocolitica strains, as well as, to separate by HRMA the Y. pseudotuberculosis and Y. enterocolitica species. The SNPs were determined in the sequences of the aforementioned loci using a set of 119 Yersinia strains deposited in the GenBank/EMBL/DDBJ database. It were found in the gene sequences analyzed of Y. pseudotuberculosis, Y. enterocolitica, Y. bercovieri, Y. rohdei, Y. intermedia, Y. mollaretii and Y. ruckeri 10, 10, 9, 6, 4, 1 and 1 SNPs, respectively. No SNPs was found in the analyzed sequences of Y. pestis and a large number of SNPs were found in the analyzed sequences of Y. frederiksenii, Y. kristensenii and Y. massiliensis what prevented their genotyping by HRMA. The remaining Yersinia species were not analyzed. It was designed primer pairs to flank the SNPs found in each Yersinia species tested. Using a specie-specific set of primers, the genetic diversity of each Yersinia species used was determined by HRMA and the phylogenetic analysis was based on the concatenated sequence composed by the nucleotides identified in each fragment analyzed. Clustering was performed with the software package BioNumerics using UPGMA method and 1,000 bootstrap replicates. The phylogenetic tree constructed for Y. pseudotuberculosis grouped the strains into bio-serogroups specific clusters. The strains of 1/O:1 bio-serogroup were grouped into one cluster and the strains of 2/O:3 bio-serogroup into iv other cluster. The phylogenetic tree constructed for Y. enterocolitica grouped the strains in three clusters. The highly pathogenic strains, of biotype 1B, were grouped into one cluster, the moderate pathogenic strains, of biotypes 2, 3, 4 and 5, were grouped into a second cluster and, the non-pathogenic strains, of biotype 1A, were grouped into a third cluster. The clusterization of Y. pseudotuberculosis and Y. enterocolitica were consistent with the pathogenic profile characteristic of these two Yersinia species. No significant epidemiological correlation was found in the grouping of Y. bercovieri, Y. rohdei, Y. intermedia Y. mollaretii and Y. ruckeri according to HRMA results. Moreover, the HRMA-based method develop here was able to separate the Y. pseudotuberculosis and Y. enterocolitica species. The HRMA assay developed in this study can be used as an alternative for the genotyping and the differentiation of Y. pseudotuberculosis and Y. enterocolitica. This method can also complement sequence-based methods and facilitate epidemiological studies of these two Yersinia species.