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Technological instruments are used in sports to record and analyze data of performing athletes, in order to improve techniques and increase competitiveness. A method to allow for recording of data of a moving subject is by usage of a depth camera mounted on a drone that can track and follow a subject. The objective was to develop a drone system that was capable of autonomous operation based on follow-me mode. The original prototype lacked required hardware for reliable orientation in environments with varying air-pressure, and software for a follow-me mode-system. Height above ground was measured using a downward facing depth sensor and a 3D image of the subject was generated by a depth camera. The data was then used by the drone to navigate through the environment. Overall performance of the height adjustment would be sufficient to allow for autonomous operation according to test results. Testing of the follow-me mode showed that the current configuration was not capable of retaining a sufficiently consistent position relative to the subject, hence high video quality was not achieved. However, it gave a positive indication that autonomous operation based on a depth camera is possible. The concept has a high potential and if the system would be further developed it could allow athletes to record and analyze data in order to improve techniques and increase competitiveness. / Teknologiska instrument används inom sport för att samla in och analysera data om idrottare, detta för att kunna förbättra teknik och öka prestationsförmåga. En metod för att kunna samla in data från ett rörligt subjekt är genom användandet av en djupkamera monterad på en drönare som kan spåra och följa efter ett subjekt. Målet var att utveckla ett drönarsystem som är kapabel till autonom drift baserat på ett “följ mig-läge” (från engelskans follow-me mode). Den ursprungliga modellen saknade hårdvara som krävs för en pålitlig orientering i miljöer med varierande lufttryck samt mjukvara för följ mig-läge. Höjd över markytan mättes med en nedåtriktad djupsensor och en 3D-bild av ett subjekt genererades av en djupkamera. Datan användes sedan av drönaren för navigation i omgivningen. Övergripande prestandan för höjdjusteringen skulle vara tillräcklig för att möjliggöra autonom drift enligt testresultat. Testning av följ mig-läget visade att aktuell konfiguration ej är kapabel till att erhålla en tillräckligt konsekvent position relaterat till subjektet, därav var hög video kvalite ej uppnåelig. Däremot gavs en positiv indikation på att autonom drönarnavigering kan baseras på ett system med djupkamera. Konceptet har en hög potential och vid vidare utveckling skulle det kunna möjliggöra för idrottare att kunna samla in och analysera data för att kunna förbättra teknik och öka prestationsförmåga.

The study of neural and behavioural mechanisms of perceptual decision making is often done by experimental tasks involving the categorization of sensory stimuli. Among the key perceptual tasks that decision neuroscience researchers use are motion discrimination paradigms that include tracking and specifying the net direction of a single dot or a group of moving dots. These motion discrimination paradigms, such as the random-dot motion task, allow the measurement of the participant's perceptual decision making abilities in multiple task difficulty levels by varying the amount of noise in the sensory stimuli. Computational models of perceptual decision making, such as the drift-diffusion model, are widely used to analyze the behavioural measurements from these motion discrimination experiments. However, the standard drift-diffusion model can only analyze the average measures like reaction times or the proportion of correct decisions to explain the behavioural data. In the past decade, an emerging computational modeling approach was introduced to analyze the choice behaviour based on precise noise patterns in the sensory stimuli. These computational models that use spatiotemporal stimulus details have shown promise in the single-trial analysis of motion discrimination behaviour. In this thesis, I further develop the advanced computational models of perceptual decision making that use spatiotemporal dynamics of motion stimuli to provide detailed explanations of perceptual choice behaviour. First, I demonstrate the usefulness of equipping an extended Bayesian Model, equivalent to the extended drift-diffusion model, with trial-wise stimulus information leading to a significantly better explanation of behavioural data from a single-dot tracking experiment. Second, I show that the extended drift-diffusion model constrained by spatiotemporal stimulus details can explain the consistent biased choice behaviour in response to stochastic motion stimuli. Based on this model-based analysis, I provide evidence that the source of the observed biased choice behaviour is the presence of subtle motion information in the sensory stimuli. These results further emphasize the effectiveness of using spatiotemporal details of stochastic stimuli in detailed model-based analyses of the experimental data and provide computational interpretations of the data related to underlying mechanisms of perceptual decision making.

<p dir="ltr">The field of nanoclusters includes a broad range of sizes and structures that influence both their physical and chemical properties. Scientists use several techniques, such as atom-by-atom substitution, to synthesize atomically precise nanoclusters, and ligand shell mixing to protect nanoclusters from unwanted side reactions, while controlling their reactivity and solubility. These combined techniques can provide stable products, but isomers and structural analogs often remain in the product mixture, complicating the structural characterization of individual nanoclusters. Leading structural characterization techniques in nanocluster research are often limited in their ability to examine both the structure of the metal core and ligand shell in sufficient detail. The primary aim of this research is to systematically characterize the structures and chemical properties of several types of transition metal oxide nanoclusters of interest to applications in energy production, catalysis, and magnetic resonance imaging, without requiring purification. Specifically, this work focuses on 1) Polyoxovanadates (POV) with a mixture of methoxy, ethoxy, and ether ligands, 2) Fe- and W-substituted POV alkoxides, and 3) Octanuclear iron oxide clusters substituted with In atoms. Mass spectrometry techniques enable the structural characterization of individual clusters from multicomponent mixtures without interference. Specifically, we use ion mobility spectrometry to explore how surface ligands affect the metal core in mixed-ligand POV alkoxide species. We examine structure-specific fragments to identify the positions of ligands and heteroatoms within the metal core of mixed-ligand species and W and Fe-substituted POV methoxides. Additionally, we use ion soft-landing to purify W-substituted POV methoxide anions on surfaces for characterization using cyclic voltammetry and infrared spectroscopy. We discovered unique characteristics of each nanocluster including the position of heteroatoms, ligands shell mobilities, structures and collisional cross sections, and provided first insights into the redox properties of W-substituted POV alkoxide. These results highlight the growing influence of mass spectrometry in the field of nanocluster characterization and design.</p>

Equatorial plasma bubbles (EPBs) are large structures consisting of depleted plasma that generally form on the nightside of Earth's ionosphere along magnetic field lines in the upper thermosphere/ionosphere. While referred to as `bubbles', EPBs tend to be longer along magnetic latitudes and narrower along magnetic longitudes which are on the order of thousands and hundreds of kilometers, respectively. EPBs are a well documented occurrence with observations spanning many decades. As such, much is known about their general behavior, seasonal variation of occurrences, increasing/decreasing occurrences with increasing/decreasing solar activity, and their ability to interact and interfere with radio waves such as GPS. This dissertation expands on this understanding by focusing on the detection and tracking of EPBs in the upper thermosphere/ionosphere along equatorial to low latitudes. To do this, far ultraviolet (FUV) emission observations of the recombination of O$^+$ with electrons via the Global-Scale Observations of the Limb and Disk (GOLD) mission are analyzed. GOLD provides consistent data from geostationary orbit with the eastern region of the Americas, Atlantic, and western Africa. The optical data can be used to pick out gradients in brightness along the 135.6 nm wavelength which correlate with the location of EPBs in the nightside ionosphere. The dissertation provides a novel method to look at and analyze 2-dimensional data with inconsistent time-steps for EPB detection and tracking. During development, preprocessing of large scale (multiple years) data proved to be the largest time sync. To that end, this dissertation tests the possibility of using convolution neural networks for detection of EPBs with the end goal of reducing the amount of preprocessing necessary. Further, data from the Ionospheric Connection Explorer's (ICON's) ion velocity meter (IVM) are compared to EPBs detected via GOLD to understand how the ambient plasma around the EPBs behave. Along with the ambient plasma, zonal and meridional thermospheric winds observed by ICON's Michelson Interferometer for Global High-resolution Thermospheric Imaging (MIGHTI) instrument are analyzed in conjunction with the same EPBs to understand how winds coincident with EPBs behave. An analysis of winds before EPBs form is also done to observe the potential for both zonal and meridional winds' ability to suppress and amplify EPB formation. / Doctor of Philosophy / Equatorial plasma bubbles (EPBs) are large structures that generally form during post- sunset along Earth's magnetic equator. While referred to as `bubbles', EPBs tend to be thousands of kilometers from north to south and hundreds of kilometers from east to west and well over a thousands kilometers in altitude. EPBs are a well documented occurrence with observations spanning many decades. This includes their ability to interfere with radar and GPS. This dissertation expands on the scientific community's understanding by focusing on the detection and tracking of EPBs along the magnetic equator. To do this, observations from the NASA Global-Scale Observations of the Limb and Disk (GOLD) mission are analyzed. GOLD provides consistent observations looking over the eastern region of the Americas, Atlantic, and western Africa. A unique method to look at and analyze this data for EPB detection and tracking is developed. This dissertation also tests the possibility of using machine learning for detection of EPBs. Further, data from the NASA Ionospheric Connection Explorer (ICON) mission is compared to EPBs detected via GOLD to understand how the behavior of the upper atmosphere and the conductive region therein, known as the ionosphere, interact with the EBPs themselves.

Writing coherent essays is evidence of a university student's discourse competence and is important in terms of academic success. An analytical taxonomy of coherence breaks {both topic-related and cohesion-related), based on Wikborg (1985; 1990), was used to determine the frequency of coherence breaks in essays written by first-year English Second Language (ESL) students. A subset of these essays was selected for assessment of their holistic coherence (HCR) by raters. The major finding of the statistical tests is that there is a significant relationship between the frequency of coherence breaks, particularly topic-related coherence breaks, and holistic coherence. Furthermore, the relationship between the coherence of essays and marks awarded them was established. Tutor intervention was also found to have had a positive impact when draft and final versions were compared: in general, there was a decrease in the frequency of coherence breaks, and a greater perception of coherence in the final versions. / Linguistics and Modern Languages / M.A. (Linguistics)

My thesis addresses a systematic approach to stochastic models in population genetics; in particular, the Wright-Fisher models affected only by the random genetic drift. I used various mathematical methods such as Probability, PDE, and Geometry to answer an important question: \"How do genetic change factors (random genetic drift, selection, mutation, migration, random environment, etc.) affect the behavior of gene frequencies or genotype frequencies in generations?”. In a Hardy-Weinberg model, the Mendelian population model of a very large number of individuals without genetic change factors, the answer is simple by the Hardy-Weinberg principle: gene frequencies remain unchanged from generation to generation, and genotype frequencies from the second generation onward remain also unchanged from generation to generation. With directional genetic change factors (selection, mutation, migration), we will have a deterministic dynamics of gene frequencies, which has been studied rather in detail. With non-directional genetic change factors (random genetic drift, random environment), we will have a stochastic dynamics of gene frequencies, which has been studied with much more interests. A combination of these factors has also been considered. We consider a monoecious diploid population of fixed size N with n + 1 possible alleles at a given locus A, and assume that the evolution of population was only affected by the random genetic drift. The question is that what the behavior of the distribution of relative frequencies of alleles in time and its stochastic quantities are. When N is large enough, we can approximate this discrete Markov chain to a continuous Markov with the same characteristics. In 1931, Kolmogorov first introduced a nice relation between a continuous Markov process and diffusion equations. These equations called the (backward/forward) Kolmogorov equations which have been first applied in population genetics in 1945 by Wright. Note that these equations are singular parabolic equations (diffusion coefficients vanish on boundary). To solve them, we use generalized hypergeometric functions. To know more about what will happen after the first exit time, or more general, the behavior of whole process, in joint work with J. Hofrichter, we define the global solution by moment conditions; calculate the component solutions by boundary flux method and combinatorics method. One interesting property is that some statistical quantities of interest are solutions of a singular elliptic second order linear equation with discontinuous (or incomplete) boundary values. A lot of papers, textbooks have used this property to find those quantities. However, the uniqueness of these problems has not been proved. Littler, in his PhD thesis in 1975, took up the uniqueness problem but his proof, in my view, is not rigorous. In joint work with J. Hofrichter, we showed two different ways to prove the uniqueness rigorously. The first way is the approximation method. The second way is the blow-up method which is conducted by J. Hofrichter. By applying the Information Geometry, which was first introduced by Amari in 1985, we see that the local state space is an Einstein space, and also a dually flat manifold with the Fisher metric; the differential operator of the Kolmogorov equation is the affine Laplacian which can be represented in various coordinates and on various spaces. Dynamics on the whole state space explains some biological phenomena.

Effektiviteten av automatiserade reningsprocesser inom avloppsreningsverk beror ytterst på kvaliteten av de mätdata som fås från installerade instrument. Givarfel påverkar verkens styrning och är ofta anledningen till att olika reglerstrategier fallerar. Idag saknas standardiserade riktlinjer för hur instrumenteringsarbetet på svenska reningsverk bör organiseras vilket ger begränsade förutsättningar för reningsverken att resurseffektivt nå sina utsläppskrav. Mycket forskning har gjorts på att optimera olika reglerstrategier men instrumentens roll i verkens effektivitet har inte givits samma uppmärksamhet. Syftet med detta examensarbete har varit att undersöka hur instrumentering på reningsverk kan organiseras och struktureras för att säkerställa mätdata av god kvalitet och att undersöka effekter av givarfel på reningsprocessen. Inom arbetet genomfördes en litteraturstudie där instrumentering på reningsverk under-söktes. Effekter av givarfel på reningsprocessen undersöktes genom att simulera en fördenitrifikationsprocess i Benchmark Simulation Model no. 2 där bias och drift implementerades i olika givare. Simuleringar visade att positiva bias (0,10–0,50 mg/l) i en ammoniumgivare inom en kaskadreglering bidrar till att öka luftförbrukningen med cirka 4–25 %. Vidare resulterade alla typer av fel i DO-givare i den sista aeroba bassängen i en markant större påverkan på reningsprocessen än samma fel i DO-givare i någon av de tidigare aeroba bassängerna. Om den sista aeroba bassängen är designad för att hålla lägre syrehalter är DO-givaren i den bassängen den viktigaste DO-givaren att underhålla. Positiva bias (200–1 000 mg/l) i TSS-givare som används för att styra uttaget av överskottsslam bidrog till kraftiga ökningar av mängden ammonium med cirka 29–464 % i utgående vatten. Negativ drift i DO-givare visade att stora besparingar i luftningsenergi, cirka 4 %, var möjliga genom ett mer frekvent underhåll av DO-givarna. Huruvida ett instrument lider av ett positivt eller negativt givarfel, bias eller drift, kommer att påverka hur mycket och i vilken mån reningsprocessen påverkas. Studien av givarfel visade att effekten av ett positivt eller ett negativt fel varierade och att effekten på reningsprocessen inte var linjär. Effekten av givarfel på reningsprocessen kommer i slutändan att bero på den implementerade reglerstrategin, inställningar i regulatorerna och på den styrda processen. / The effectiveness of automated treatment processes within wastewater treatment plants ultimately depend on the quality of the measurement data that is given from the installed sensors. Sensor faults affect the control of the treatment plants and are often the reason different control strategies fail. Today there is a lack of standardized guidelines for how to organize and work with online sensors at Swedish wastewater treatment plants which limits the opportunities for treatment plants to reach their effluent criteria in a resource efficient manner. Much research has been done on ways to optimize control strategies but the role of sensors in the efficiency of the treatment plants has not been given the same level of attention. The purpose of this thesis has been to examine how instrumentation at wastewater treatment plants can be organized and structured to ensure good quality measurement data and to examine how sensor faults affect the treatment process. Within the thesis a literature study was conducted where instrumentation at wastewater treatment plants was examined. The effects of sensor faults were examined by simulating a pre-denitrification process in Benchmark Simulation Model no. 2 where off-sets (biases) and drift where added to measurements from different implemented sensors. The simulations showed that positive off-sets (0.10–0.50 mg/l) in an ammonium sensor within a cascaded feedback-loop adds to the energy consumption used for aeration by roughly 4-25%. It could further be shown that all types of faults in a DO sensor in the last aerated basin had significantly larger effect on the treatment process than the same fault in any of the other DO sensors in the preceding basins. If the last aerated basin is designed to have low DO concentrations the DO sensor in that basin is the most important DO sensor to maintain. Positive off-sets (200–1 000 mg TSS/l) in suspended solids sensors used for control of waste activated sludge flow contributed to large increases of ammonia, by 29-464%, in effluent waters. Negative drift in DO sensors showed that significant savings in aeration energy, roughly 4%, was possible to achieve with more frequent maintenance. Whether a sensor is affected by a positive or a negative fault, be it off-set or drift, will affect how much and in what way the treatment process will be affected. The study of sensor faults showed that the effect of a positive or a negative fault varied and that the effect on the treatment process was not linear. The effect of a sensor fault on the treatment process will ultimately depend on the implemented control strategy, settings in the controllers and on the controlled process.