No description available.

TDA mapper is an algorithm used to visualize and analyze big data. TDA mapper is applied to a dataset, X, equipped with a filter function f from X to R. The output of the algorithm is an abstract graph (or simplicial complex). The abstract graph captures topological and geometric information of the underlying space of X. One of the interests in TDA mapper is to study whether or not a mapper graph is stable. That is, if a dataset X is perturbed by a small value, and denote the perturbed dataset by X∂, we would like to compare the TDA mapper graph of X to the TDA mapper graph of X∂. Given a topological space X, if the cover of the image of f satisfies certain conditions, Tamal Dey, Facundo Memoli, and Yusu Wang proved that the TDA mapper is stable. That is, the mapper graph of X differs from the mapper graph of X∂ by a small value measured via homology. The goal of this thesis is three-fold. The first is to introduce a modified TDA mapper algorithm. The fundamental difference between TDA mapper and the modified version is the modified version avoids the use of filter function. In comparing the mapper graph outputs, the proposed modified mapper is shown to capture more geometric and topological features. We discuss the advantages and disadvantages of the modified mapper. Tamal Dey, Facundo Memoli, and Yusu Wang showed that a filtration of covers induce a filtration of simplicial complexes, which in turn induces a filtration of homology groups. While Tamal Dey, Facundo Memoli, and Yusu Wang focused on TDA mapper's application to topological space, the second goal of this thesis is to show DBSCAN clustering gives a filtration of covers when TDA mapper is applied to a point cloud. Hence, DBSCAN gives a filtration of mapper graphs (simplicial complexes) and homology groups. More importantly, DBSCAN gives a filtration of covers, mapper graphs, and homology groups in three parameter directions: bin size, epsilon, and Minpts. Hence, there is a multi-dimensional filtration of covers, mapper graphs, and homology groups. We also note that single-linkage clustering is a special case of DBSCAN clustering, so the results proved to be true when DBSCAN is used are also true when single-linkage is used. However, complete-linkage does not give a filtration of covers in the direction of bin, hence no filtration of simpicial complexes and homology groups exist when complete-linkage is applied to cluster a dataset. In general, the results hold for any clustering algorithm that gives a filtration of covers. The third (and last) goal of this thesis is to prove that two multi-dimensional persistence modules (one: with respect to the original dataset, X; two: with respect to the ∂-perturbation of X) are 2∂-interleaved. In other words, the mapper graphs of X and X∂ differ by a small value as measured by homology.

No description available.

Land-cover identification and mapping are an integral part of natural resource planning and management. Satellite imagery provides a way to obtain land cover information, particularly for large tracts of land such as those administered by federal and state agencies. This study assesses the usefulness of the Brightness/Greenness Transformation of Landsat Thematic Mapper data for differentiating conifer forest types in northern Utah. Satellite data for the Logan Ranger District of the Wasatch-Cache National Forest were classified into 27 vegetation classes. Of these, nine were determined to be conifer classes and were used in subsequent analyses. Ten sites of each conifer class type were field checked and vegetation and physical site characteristics recorded. The Brightness/Greenness Transformation was able to distinguish conifer areas from other vegetation types. High-density conifer classes were classified at 94 percent accuracy. Low-density conifer classes were classified correctly 65 percent of the time. The Brightness/Greenness Transformation alone met with limited success in distinguish ing between conifer species. Each class showed great variability with respect to major overstory species. Analysis of variance indicated that none of the site factors measured consistently corresponded with the spectrally designated classes. While several factors differed significantly among classes, no factor was significantly different for all c l ass-pair combinations. Correlation analysis revealed that brightness, greenness, and wetness values related more to environmental values than to conifer species. Brightness was highly correlated with percent of exposed soil on the site. Greenness was highly correlated to the presence of deciduous and herbaceous vegetation. Wetness was highly correlated to total tree and conifer cover values. Adding slope and aspect data to the Brightness/Greenness Transformation classes with the highest percentages of canopy cover did allow separation of lodgepole pine and Douglas fir. High percentagecanopy cover sites on slopes less than 35 percent were classified as lodgepole pine with 89 percent accuracy. On slopes greater than or equal to 35 percent, Douglas fir was found with 79 percent accuracy.

Homologous DNA recombination and rearrangement has been modeled with a class of four-regular rigid vertex graphs called assembly graphs which can also be represented by double occurrence words. Various invariants have been suggested for these graphs, some based on the structure of the graphs, and some biologically motivated. In this thesis we use a novel method of data analysis based on a technique known as partial-clustering analysis and an algorithm known as Mapper to examine the relationships between these invariants. We introduce some of the basic machinery of topological data analysis, including the construction of simplicial complexes on a data set, clustering analysis, and the workings of the Mapper algorithm. We define assembly graphs and three specific invariants of these graphs: assembly number, nesting index, and genus range. We apply Mapper to the set of all assembly graphs up to 6 vertices and compare relationships between these three properties. We make several observations based upon the results of the analysis we obtained. We conclude with some suggestions for further research based upon our findings.

In the era of explosive information, storage subsystem is becoming more and more important in our daily life and commercial markets. Because more and more data are recorded in the digital form and stored in the storage device, an intelligent mechanism is required to make the management of the digital data and storage devices more eficiently rather than simply keep increasing more storage equipment into a system. The concept of storage virtualization was introduced to solve this problem, by aggregating all the physical devices into a single virtual storage device and hidding the complexity of underlying block devices. Through this virtual layer, users can dynamically allocate and resize their virtual storage device to satisfy their need, and they can also use the methods provided by the virtual layer to organize data more efficiently. Linux Logical Volume Manager 2 (LVM2) is an implementation of storage virtualization on the Linux operation system. It includes three components: the kernel-space devicemapper, the user-space device-mapper support library (libdevmapper), and the user-space LVM2 toolset. This thesis will focus on the kernel-space device-mapper, which provides virtualization mechanism for user-space logical volume manager. The organization of this thesis is composed of : (1) Introduce novel technologies in the recent years, (2) Provide an advanced document about the internals of device-mapper, (3) Try optimizing the mapping table algorithm, and (4) Evaluate the performance of device-mapper.

Au cours des cinquante dernières années, notre niveau de connaissance sur la Lune a fortement évolué. Les progrès en science lunaire sont survenus selon plusieurs phases. La première phase eut lieu pendant les missions Apollo et Luna dans les années 1960 et 1970, avec l’étude des échantillons de roches lunaires rapportées pendant les missions du même nom. La caractérisation pétrologique des échantillons lunaires a fait naître le concept d’Océan de Magma Lunaire, qui est à l’origine de la vue traditionnelle de la croûte et du manteau lunaires. Ce modèle prédit que la croûte lunaire est riche en plagioclase et que sa composition devient plus mafique en profondeur. Il est communément admis que le manteau lunaire est riche en olivine et qu’il contient du pyroxène, conformément au manteau terrestre. La seconde phase de l’exploration lunaire eut lieu dans les années 1990, lorsque des satellites lancés en orbite lunaire collectèrent les premiers jeux de données globaux de télédétection. En raison de leur couverture spatiale globale, les données de télédétection apportèrent une vision complémentaire à celle conférée par l’étude des échantillons lunaires. Pendant la troisième phase de l’exploration lunaire, qui a commencé dans les années 2000 et a toujours cours aujourd’hui, de nouveaux jeux de données ont été collectés par des satellites en orbite autour de la Lune. Les données de télédétection acquises durant ces deux dernières phases ont permis de prendre connaissance de processus complexes encore inconnus et de nuancer l’image initialement simple que les scientifiques se faisaient de la Lune. En effet, l’étude des jeux de données de haute résolution et des données radar a conduit à l’identification d’édifices volcaniques (dômes ; zones de mare irrégulières, dites irregular mare patches ou IMP), et à la découverte sans équivoque de volatils dans les régions ombragées en permanence. Des volatils ont également été découverts dans des échantillons lunaires issus de l’intérieur de la Lune, démontrant ainsi la complexité de l’histoire géologique de la Lune.Durant cette thèse, des cratères d’impact ont été utilisés comme forages naturels de la croûte lunaire. En effet, lors de l’impact, des roches profondes sont excavées et mises à l’affleurement dans le pic central du cratère par rebond élastique. Il est alors possible d’étudier la composition des roches crustales profondes en examinant le pic central d’un cratère à la surface d’une planète. Ici, le pic central de cratères échantillonnant la croûte lunaire a été étudié avec les données spectroscopiques de l’instrument Moon Mineralogy Mapper (Cartographe de la Minéralogie de la Lune, aussi noté M³) à bord de la mission Chandrayaan-1. Ce travail illustre l’utilisation de données de télédétection sur le pic central de cratères, dans l’optique de caractériser l’intérieur peu profond de la Lune. Les données de télédétection peuvent également être utilisées pour aider à cibler des régions à la surface de la Lune dont le retour d’échantillons pourrait donner des indices importants sur l’organisation de la croûte et du manteau supérieur lunaires / Over the past 50 years, our knowledge of the Moon has grown immensely. Progress in lunar science occurred through several phases. The first phase happened in the 1960s and 70s, during the Apollo and Luna missions, with the study of samples returned from the lunar surface. Petrological characterisation of lunar samples sparked the Lunar Magma Ocean concept, from which ensued the traditional view of the lunar crust and mantle organisation: the crust is plagioclase-rich, and its mafic content increases with increasing depth. The lunar mantle is commonly thought to be olivine-rich, like that of the Earth. The second lunar exploration phase happened in the 1990s, when satellites were launched into lunar orbit, collecting the first global remote sensing datasets. Owing to their wide to global coverage, remote sensing brought new insight into lunar science that is complementary to that provided by lunar samples. During the third, current phase of lunar exploration, new datasets were collected by spacecrafts orbiting the Moon between the 2000s and today. The remote sensing datasets acquired during the second and third phases of lunar exploration progressively complicated the initially simple picture that scientists drew from earlier studies. Indeed, high resolution remote sensing images and radar data led to the identification of volcanic features (domes, irregular mare patches), and the unambiguous discovery of volatiles in permanently shadowed regions and in lunar samples originating at depth in the Moon, demonstrating the Moon’s complex geological history. During this PhD, impact craters were used as natural drill holes through the lunar crust to sample material located underneath the surface. During impact, rocks from depth are emplaced in crater central peaks through elastic rebound, making it possible to investigate the composition of the crust at depth. Spectroscopic data from Chandrayaan-1’s Moon Mineralogy Mapper instrument were exploited to gather information on the composition of the crust in those central peaks. This work illustrates the use of remote sensing data on crater central peaks in order to constrain the shallow interior of the Moon. Remote sensing data can also be used to help locate which type of samples would need to be returned in the future from the lunar surface, in order to contribute to further elucidating the organisation of the lunar crust and upper mantle

C. elegans est infecté par divers agents pathogènes ; bactéries, champignons et virus. Lors d'une infection fongique, C. elegans surexprime de nombreux gènes codant pour des peptides antimicrobiens (AMP). Le principal objectif de ma thèse était de construire un réseau de régulation génique intégré représentant l'induction de ces gènes AMP pendant l'infection. Pour trouver les principales composantes du réseau de régulation, via un criblage ARNi du génome entier (Zugasti et al 2016), nous avons identifié 278 clones Nipi (pour "Absence d'induction de peptides antimicrobiens après infection") qui abrogent l’induction d’AMP. En utilisant "CloneMapper" (Thakur et al. 2014), nous avons identifié 338 gènes cibles pour ces clones. Nous avons montré que les voies de MAPK sont au cœur de l'induction des AMP. Parmi les 50 gènes arbitrairement sélectionnés et surexprimant les AMP, nous en avons validé 48 en utilisant Fluidigm. Pour attribuer des fonctions aux gènes identifiés dans ces études à haut débit, nous avons développé un outil d'enrichissement fonctionnel pour la communauté C.elegans (MS en préparation). Nous avons utilisé cet outil pour analyser les cibles du criblage ARNi sur le génome entier et sur d'autres bases de données concernant divers agents pathogènes. Nous avons fait une analyse de l'enrichissement fonctionnel des cibles ChIPseq de CEBP-1, un facteur de transcription lié à la régulation de la réponse immunitaire innée (Kim et al, Soumis). Enfin, pour mieux comprendre l'interaction entre l'hôte et le pathogène, nous avons séquencé, assemblé, annoté et analysé le génome de D. coniospora. Nous avons identifié plusieurs facteurs de virulence potentiels dans ce génome. / C. elegans is infected by diverse pathogens, including bacteria, fungi and viruses. Upon fungal infection, C. elegans up-regulates the expression of many antimicrobial peptide (AMP) genes. The main aim of my thesis was to build an integrated gene regulatory network representing the induction of these AMP genes upon infection. To find the main/backbone components of the regulatory network, through a genome-wide RNAi screen (Zugasti et al. 2016), we identified 278 Nipi (for “no induction of antimicrobial peptides after infection”) clones that abrogate AMP induction. Using “CloneMapper” (Thakur et al. 2014), we identified 338 target genes for these clones. We showed that MAPK pathways are central to the induction of AMPs. We also characterized the transcriptional changes provoked by infection using RNA-sequencing and identified more than 300 genes that are dynamically up-regulated after infection, including 13 AMPs. We validated 48 (96%) of 50 arbitrary selected up-regulated genes using Fluidigm. To assign functions to genes identified in these high-throughput studies, we developed a functional enrichment tool for C.elegans community (MS in preparation). We used this tool to analyse the genome-wide RNAi screen targets and other pathogen-related datasets. We did functional enrichment analysis of ChIPseq targets of CEBP-1, TF linked to the regulation of the innate immune response (Kim et al., submitted). Finally, to understand better the interaction between host and pathogen, we sequenced, assembled, annotated and analysed the D. coniospora genome (Lebrigand et al. 2016). We identified various potential virulence factors in the fungal genome.

Desert wetlands, in particular those slow moving bodies of water known as cienegas, are important sites for biodiversity in arid landscapes and serve as indicators of hydrological functioning on the landscape-level. One of the most extensive systems of cienegas, historical or extant, in southeastern Arizona lies along Cienega Creek, located southeast of Tucson, Arizona. Satellite imagery analysis is heavily utilized to determine landscape-level trends, but cienegas present a challenge to traditional analysis methods. The Normalized Difference Vegetation Index (NDVI), the classic measure of vegetation greenness, reacts counter-intuitively to open water and is affected by open ground, both common occurrences in cienega habitats. Additional remote sensing indices have been developed that balance sensitivity to these environmental elements. This research explores these remote sensing indices at Cienega Creek applying one topographic index to current elevation data and five spectral indices to Thematic Mapper imagery from 1984 to 2011. Temporal trends were identified for all spectral indices and all indices were compared for suitability in cienega habitats. Temporal trends were analyzed for spatial clustering and spatial trends identified. The Normalized Difference Infrared Index utilizing Landsat Thematic Mapper band 5 outperformed other indices at differentiating between cienega, riparian, and upland habitats and is more suitable than NDVI for analyzing cienega habitats in such circumstances.

The aim of this study is to disseminate a novel path planner which is particularly used for offline robots to build more efficient collision-free trajectories in terms of the length in more skilled fashion. Robotic path planning as one of the most important problems has been under investigation by a variety of researchers within the last few decades. Path planner refers to a unit which is responsible to perform a series of operations on the robots’ environment with the sole purpose of building proper trajectories from a start point to the goal configuration. A robot’s planner generally consists of some or all of the following units: analyzing the workspace, mapping the workspace into an alternative methodology such as a graph, optimizing the constructed map, and calculating and refining the desired trajectory. Various path planners have been proposed based on the different robots’ functionalities as well as the environmental specifications. A path planner basically uses a methodology inspiring a scientific theory or event to build optimal paths. This research tends to propose a novel path planner which is able to be successfully applied on a variety of workspaces with different constraints. Moreover, the presented planner successfully builds the shortest collision-free trajectories from an initial to the goal configurations. In addition, compared to the other majority of path planners, the illustrated path planner uses less environmental global information to build optimal paths. This leads the planner unit to allocate less of system resources such as memory, hence, increasing the performance of the planner in terms of preserving more system resources.