<div> Space operations from the dawn of the Space Age have resulted in a large, and growing, resident space object population. However, the availability of sensor resources is limited, which presents a challenge to Space Situational Awareness applications. When direct communication with an object is not possible, whether that is due to a lack of access for active satellites or due to the object being characterized as debris, the only independent information source for learning about the resident space object population comes from measurements. Optical measurements are often a cost-effective method for obtaining information about resident space objects.<br></div><div> This work uses observability analysis to investigate the relationship between desired resident space object characteristics and the information resulting from ground-based optical measurements. Observability is a concept developed in modern control theory for evaluating whether the information contained within measurements is sufficient to describe the dynamical progression of a system over time. In this work, observability is applied to Space Situational Awareness applications to determine what object characteristic information can be recovered from ground-based optical measurements and under which conditions these determinations are possible. In addition, the constraints and limitations of applying observability to Space Situational Awareness applications are assessed and quantified.<br></div>

<p>    </p> <p>Space has become ever more crowded since the launch of Sputnik. The need for predictions of possible collisions between space objects has only ever grown. The development of space, particularly around Earth, increases the density of space objects and skyrockets the number of close approaches between these objects, called conjunctions. This investigation is conducted in the context of probability dilution, a phenomenon leading to a false negative collision prediction where increasing positional uncertainty decreases the predicted likelihood of a collision. Dilution is investigated along two avenues: how to generate accurate collision predictions in an efficient manner and how to obtain better input data with which to make these predictions. Along the first avenue, this research presents a novel analytical rectan- gular probability of collision expression as well as a variety of new covariance scale factor formulations for maximum collision probability that indicate the maximum possible collision risk for any conjunction. Along the second avenue, this research tests new sensor tasking regimes to mitigate dilution, ultimately showing that while dilution can be reduced, shrink- ing the positional covariance through optimal measurement updates may not be enough to avoid false negatives in orbital conjunctions. </p>

To be a fully functioning theatre practitioner, the developing student artist becomes equipped with a practical skill set that is ordinarily cultivated through formal training and study. Typically, organized study leads him/her to focus on a specific facet of the business: acting, directing, design, etc. However, students often develop a vast array of talents and skills within the profession and find themselves standing at a crossroads between what "kind" of artist to be; what singular aspect of the arts on which to focus. Why not do it all? For those students who "do it all", there is an additional challenge: the artist who is a student immersed in daytime study and nighttime production obligations has to wear two caps. One is that of the learner and one is that of the employee, the producer, and perhaps even the teacher. When are these caps traded or are they both worn through all processes? This thesis will reveal my creative and practical processes from two productions at the University of Central Florida for which I played on- and offstage roles: I worked as a Sound Designer and featured actor in Sophie Treadwell's Machinal; I was the Vocal Director for Urinetown: The Musical, and also played Penelope Pennywise, a leading role. I will describe the challenges and successes of each project by examining the following evidence: my personal process with each piece, demonstrated through reflection and examples from the work; interviews with those involved in the productions as well as outside reviews and feedback; and research of each play. Research will include production history, intent of authors, and aspects that informed my work both onstage and off. Did multi-tasking sacrifice the quality of my work for any of my delegated tasks? Did I enjoy more success in my progress in time management, the ability to solve problems, and collaboration process with fellow artists, or in the actual on-stage products? What aspects of my training in my graduate program added to the quality of my work on these productions? Does being a multi-tasking artist help or hurt one's career in theatre?

In this thesis, we propose an approach to estimate the Worst Case Response Time (WCRT) of each task in a preemptive multi-tasking single-processor real-time system utilizing an L1 cache. The approach combines inter-task cache eviction analysis and intra-task cache access analysis to estimate the Cache Related Preemption Delay (CRPD). CRPD caused by preempting task(s) is then incorporated into WCRT analysis. We also propose a prioritized cache to reduce CRPD by exploiting cache partitioning technique. Our WCRT analysis approach is then applied to analyze the behavior of a prioritized cache. Four sets of applications with up to six concurrent tasks running are used to test our WCRT analysis approach and the prioritized cache. The experimental results show that our WCRT analysis approach can tighten the WCRT estimate by up to 32% (1.4X) over prior state-of-the-art. By using a prioritized cache, we can reduce the WCRT estimate of tasks by up to 26%, as compared to a conventional set associative cache.

This diploma thesis deals with the design of a selected structural part of multi-tasking machine tool. The solved construction part is the design of a turning table with the possibility of positioning with specified parameters. The research part is focused on CNC machine tools, multi-tasking machine tools and individual parts of turning tables with possible positioning. In a design part, the design of design variants of possible solutions is made and the choice of the design solution is made with the help of multicriteria analysis. Subsequently, the selected design solution is processed with the help of the necessary technical calculations. The result of the work is then a 3D model and the required drawing documentation.

<pre>Because of the increasing population of space objects, there is an increasing necessity to monitor and predict the status of the near-Earth space environment, especially of critical regions like geosynchronous Earth orbit (GEO) and low Earth orbit (LEO) regions, for a sustainable future. Space Situational Awareness (SSA), however, is a challenging task because of the requirement for dynamically insightful fast orbit propagation models, presence of dynamical uncertainties, and limitations in sensor resources. Since initial parameters are often not known exactly and since many SSA applications require long-term orbit propagation, long-term effects of the initial uncertainties on orbital evolution are examined in this work. To get a long-term perspective in a fast and efficient manner, this work uses analytical propagation techniques. Existing analytical theories for orbital perturbations are investigated, and modifications are made to them to improve accuracy. While conservative perturbation forces are often studied, of particular interest here is the orbital perturbation due to non-conservative forces. Using the previous findings and the developments in this thesis, two SSA applications are investigated in this work. In the first SSA application, a sensor tasking algorithm is designed for the detection of new classes of GEO space objects. In the second application, the categorization of near-GEO objects is carried out by combining knowledge of orbit dynamics with machine learning techniques.</pre>

Diese Dissertation enthält vier Aufsätze zur Theorie der Anreizsetzung bei nicht-verifizierbaren Leistungsmaßen. Es werden positive Dominanzanalysen für Anreizmechanismen durchgeführt, die in realen wirtschaftlichen Situationen Anwendung finden. Der erste Aufsatz analysiert zwei Bonus-Wettbewerbe in Unternehmen. Der Prinzipal kann entweder einen Bonuspool festlegen, dessen Aufteilung von der Leistung der Agenten abhängt, oder bereits ex ante die Höhe der Boni fixieren. Eine höhere Präzision der Leistungsmessung führt nur im zweiten Fall zu stärkeren Anreizen. Die optimale Wahl des Wettbewerbs hängt von den Präferenzen der Agenten, ihren Liquiditätsbeschränkungen und den Kosten der Leistungsmessung ab. Der zweite Aufsatz untersucht die optimale Zuordnung von Aufgaben auf Stellen wenn relationale Verträge basierend auf subjektiven Leistungsmaßen explizite Anreizverträge ergänzen können. Die Spaltung von Aufgaben ist optimal, wenn die glaubhafte Bindung an relationale Verträge nicht möglich ist. Dagegen sollten Aufgaben immer dann gebündelt werden, wenn relationale Verträge bereits bestehen. Im dritten Aufsatz möchte ein Käufer eine Innovation erwerben. Um qualitätssteigernde Investitionen bei potentiellen Anbietern zu induzieren, kann der Käufer entweder einen fixen Preis ausschreiben oder einen Auktionsmechanismus nutzen. Obwohl Investitionen unter der Auktion immer höher sind, bevorzugt der Käufer einen fixen Preis wenn die Grenzkosten der Qualitätsmessung hoch sind oder die Produktionstechnologie starken Zufallseinflüssen unterliegt. Im letzten Aufsatz möchte ein Prinzipal das Produktionsergebnis zweier Agenten maximieren, die vor der Produktion in eine kostenreduzierende Innovation investieren können. Dabei kommt es zu Spillover-Effekten. Bei einer allgemeinen Preissubvention sind Investitionen stets zu gering, während ein Innovationswettbewerb zu Unter- und Überinvestitionen führen kann. Der Prinzipal bevorzugt eine Preissubvention bei starken Spillover-Effekten. / This thesis consists of four self-contained essays that compare real-world incentive schemes used to mitigate moral hazard problems under non-verifiable performance. The first essay contrasts the impact of the precision of performance measurement on wage costs in U- and J-type tournaments. In U-type tournaments prizes are fixed. In J-type tournaments only an overall wage sum is specified. The principal prefers a U-type tournament if workers receive a rent under limited liability and the costs of increasing precision are low. However, if workers are inequity-averse and have unlimited liability, the J-type tournament leads to lower wage costs. The second essay analyzes optimal job design when there is only one contractible and imperfect performance measure for all tasks whose contribution to firm value is non-verifiable. Task splitting is optimal when relational contracts based on firm value are not feasible. By contrast, if an agent who performs a given set of tasks receives an implicit bonus, the principal always benefits from assigning an additional task to this agent. The third essay compares an auction and a tournament in a procurement setting with non-contractible quality signals. Signals are affected by firms' non-observable investments in R&D and the procurer's precision of quality measurement. Although investments are always higher with the auction, the procurer may prefer the tournament if marginal costs of quality measurement are high or the production technology for quality is highly random. In the last essay, a principal wants to induce two agents to produce an output. Agents can undertake non-contractible investments to reduce production cost of the output. Part of this "innovation" spills over and also reduces production cost of the other agent. Agents always underinvest with a general output price subsidy, while they may or may not do so with an innovation tournament. Strong spillovers tend to favor a general output price subsidy.

L’objectif que nous nous sommes fixés dans ce travail est la conception d’algorithmes d’ordonnancement temps réel en-ligne faisables optimisant l’utilisation de la plate-forme d’exécution et/ou des critères applicatifs de qualité de service propres à l’application. Nous avons en particulier étudié l’ordonnancement d’activités sur une ressource unique. Deux cas ont été analysés : le cas de tâches indépendantes périodiques s’exécutant sur un processeur et le cas de flux de messages indépendants périodiques sur un réseau de terrain avec accès au médium priorisé. Nos contributions reposent sur le “modèle classique” de l’ordonnancement temps réel où le système est représenté par un ensemble d’activités périodiques indépendantes et deux problématiques ont été abordées : • optimisation de l’utilisation de la plate-forme d’exécution : utiliser au mieux le potentiel de la plate-forme d’exécution tout en garantissant le respect des contraintes temporelles imposées au système ; ceci optimise le nombre de configurations faisables, • optimisation des critères applicatifs de qualité de service propres à l’application (i.e., pris en compte des performances de l’application autre que la faisabilité) : garantir les contraintes de temps tout en optimisant les performances de l’application. Nous avons donc proposé : • des méthodes de configurations permettant d’optimiser l’utilisation de la plate-forme d’exécution (i.e., maximiser faisabilité) en fixant les paramètres des politiques ou des systèmes considérés d’une manière appropriée. Deux études ont été conduites dans ce cadre : • allocation des “offsets” dans les systèmes “offset free”, • allocation de priorités, de politiques et de quantum dans les systèmes conformes au standard Posix 1003.1b, • une nouvelle classe de politiques d’ordonnancement permettant d’optimiser des critères de performances propres à l’application. De plus, une analyse d’ordonnancement générique pour cette classe a été proposée / Our goal is to come up with feasible (i.e., all required time constraints are met) on-line real-time scheduling algorithms. These algorithms have to optimise 1) the utilisation of the execution platform (i.e., meet time constraints and use platform at its fullest potential) and/or 2) optimise the application dependent performance criteria. We study two cases : the case of independent periodic tasks scheduled on a processor and the case of periodic traffic streams scheduled on a priority bus. To deal with these two problems, we propose : • Configuration methods to allow to optmlise the utilisation rate of the execution platform by setting the parameters of the policies or of the activities of the considered system. We perform two studies : the allocation of offsets in "Offset free" systems (I.E., offsets can be chosen off-line) and the priorities, policies and quantum allocations in systems compliant to the standard Posix 1003.1B, • A new class of scheduling policies to allow optimising application performance dependent criteria

This thesis first explored the effects of concurrent spatial attention and working memory task performance on over-ground gait in healthy young and older adults. It then compared over-ground gait parameters and working memory performance in mild Alzheimer’s Disease (AD) and normal controls (NC) and investigated costs of dual-tasking on working memory performance and cadence during treadmill walking at preferred walking speed in the two groups. Furthermore, it explored these differences in AD and NC groups in relation to their subcortical hyperintensities (SH) that were rated using standardized scales on MRI. Reaction times and accuracy on working memory performance measures were collected under single and dual task conditions. Over-ground gait parameters were measured on an automated walkway. Costs of dual-tasking on gait parameters and working memory performance were measured at a constant velocity on a treadmill. The hypotheses that working memory influences gait performance and that a higher SH burden negatively influences over-ground gait and costs of dual-task conditions, were supported in a series of experiments. Gait slowed down while performing working memory and spatial attention tasks in young and older adults. Patients with mild AD, compared to NC, had a slower gait velocity, shorter stride length and lower cadence on the walkway. When the two groups were subdivided into higher and lower SH groups based on their median SH score, the NC group with lower SH burden walked significantly faster with a higher cadence and a longer stride length than the other three groups. Lastly, a higher SH burden negatively influenced working memory performance in NC while in mild AD patients, it had negative influences on adaptive changes in gait while dual-tasking. These results suggest that, in dual-task condition, SH interfere with processing speed in NC and on gait in AD. These findings provide new insights in to tradeoffs during dual tasking in relation to cerebrovascular disease. This has ecological implications because of the prevalence of small vessel disease in aging and dementia, may impact on predicting falls in AD.

This thesis first explored the effects of concurrent spatial attention and working memory task performance on over-ground gait in healthy young and older adults. It then compared over-ground gait parameters and working memory performance in mild Alzheimer’s Disease (AD) and normal controls (NC) and investigated costs of dual-tasking on working memory performance and cadence during treadmill walking at preferred walking speed in the two groups. Furthermore, it explored these differences in AD and NC groups in relation to their subcortical hyperintensities (SH) that were rated using standardized scales on MRI. Reaction times and accuracy on working memory performance measures were collected under single and dual task conditions. Over-ground gait parameters were measured on an automated walkway. Costs of dual-tasking on gait parameters and working memory performance were measured at a constant velocity on a treadmill. The hypotheses that working memory influences gait performance and that a higher SH burden negatively influences over-ground gait and costs of dual-task conditions, were supported in a series of experiments. Gait slowed down while performing working memory and spatial attention tasks in young and older adults. Patients with mild AD, compared to NC, had a slower gait velocity, shorter stride length and lower cadence on the walkway. When the two groups were subdivided into higher and lower SH groups based on their median SH score, the NC group with lower SH burden walked significantly faster with a higher cadence and a longer stride length than the other three groups. Lastly, a higher SH burden negatively influenced working memory performance in NC while in mild AD patients, it had negative influences on adaptive changes in gait while dual-tasking. These results suggest that, in dual-task condition, SH interfere with processing speed in NC and on gait in AD. These findings provide new insights in to tradeoffs during dual tasking in relation to cerebrovascular disease. This has ecological implications because of the prevalence of small vessel disease in aging and dementia, may impact on predicting falls in AD.