Thesis (Ph. D.)--University of Wisconsin--Madison, 1981. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaf 106).

Thesis (M.S.)--Ohio University, November, 2004. / Title from PDF t.p. Includes bibliographical references (p. 76-77)

Fechamento de loops é um dos principais processos das estratégias de SLAM baseadas em grafos, usadas para estimar o erro de deslocamento acumulado à ser minimizado pela técnica. Neste sentido, boas correspondências de cenas permitem criar uma conexão entre dois nós do grafo que está sendo construído para representar o ambiente. Contudo, falsas correspondências podem levar essas estratégias a um estado irreversível de falsa representação do ambiente. Neste trabalho, um método robusto baseado em features que usa sequências de imagens para reconhecer áreas revisitadas é apresentado. Este método usa a abordagem de Bag-of-Words para reduzir efeitos de iluminação e uma ponderação TF-IDF para ressaltar as principais features que descrevem cada cena. Além disso, um algoritmo baseado na técnica de Mean Shift é usado sobre uma matriz de similaridade para identificar a possível trajetória seguida pelo robô e melhorar a detecção de fechamento de loop. O método apresentado foi testado em um ambiente aberto usando sequências de imagens coletadas com usando uma câmera de mão e um drone modelo Parrot ArDrone 2.0. / Loop closure recognition is one of the main processes of graph-based SLAM strategies, used to estimate the accumulated motion error to be minimized by the technique. Good scene correspondences allow to create constraints between two nodes in the graph that is currently being built to represent the environment that the robot is immersed. However, false correspondences can lead these strategies to an irreversible wrong environment representation. In this work, we present a robust feature-based loop closure approach that uses image sequence matching to recognize revisited areas. This approach uses Bag-of- Words to reduce the effects of lightning changes and a TF-IDF weighting to enhance the main features that describe each scene. Besides, an algorithm based on Mean Shift is used over a similarity matrix to identify the possible trajectory followed by the robot and improve the loop closure detection. Our method is tested in a GPS-denied outdoor environment using image sequences collected using a handheld camera and a Parrot ArDrone 2.0.

The thesis presents a syntactic and semantic analysis of selected problems in the analysis of transitivity in English, Japanese and Korean in terms of a system of 'thematic relations' adapted from the work of Gruber and Jackendoff. The system is introduced in Chapter One. One way in which it differs from those of Gruber and Jackendoff is that their ambiguous notion of Theme is replaced by two separate notions - Theme and semantic subject. Verbs are classified into 'univalent verbs', which have a single set of thematic relations, and 'ambivalent verbs', which have more than one set of thematic relations. It is claimed that syntactic alternations such as that between 'spray x on y' and 'spray y with x' are a reflection of the ambivalence of the verbs in question. Chapter Two reviews discourse approaches and semantic approaches to Dative-shift. On the basis of a comparison of English and Korean it argues that Dative-shift in these two languages is clearly a semantic process rather than pragmatically motivated. Moreover, like the 'spray' type alternation, Dative-shift is shown to be a reflection of the ambivalence of verbs expressing a change in possession. Chapter Three is devoted to double-nominative constructions in Japanese and Korean, which in the past have been considered to be syntactically and semantically equivalent. A careful study of data from the two languages shows that the double-nominative constructions in Korean are not homogeneous but are divided into two classes with distinct thematic relations, one of which is lacking in Japanese. Chapters Four and Five discuss the passive in Japanese and Korean, respectively, and propose a new classification of passives in the two languages. Three types are recognized: the passive of interest, the anti-causative passive and the attributive passive. Finally, Chapter Six presents some typological observations concerning the passive and Dative-shift. In particular, the English passive and the passives of Korean and Japanese are compared with regard to their relation to Dative-shift, and it is argued that Dative-shift and the passive are, in principle, independent grammatical processes.

Fechamento de loops é um dos principais processos das estratégias de SLAM baseadas em grafos, usadas para estimar o erro de deslocamento acumulado à ser minimizado pela técnica. Neste sentido, boas correspondências de cenas permitem criar uma conexão entre dois nós do grafo que está sendo construído para representar o ambiente. Contudo, falsas correspondências podem levar essas estratégias a um estado irreversível de falsa representação do ambiente. Neste trabalho, um método robusto baseado em features que usa sequências de imagens para reconhecer áreas revisitadas é apresentado. Este método usa a abordagem de Bag-of-Words para reduzir efeitos de iluminação e uma ponderação TF-IDF para ressaltar as principais features que descrevem cada cena. Além disso, um algoritmo baseado na técnica de Mean Shift é usado sobre uma matriz de similaridade para identificar a possível trajetória seguida pelo robô e melhorar a detecção de fechamento de loop. O método apresentado foi testado em um ambiente aberto usando sequências de imagens coletadas com usando uma câmera de mão e um drone modelo Parrot ArDrone 2.0. / Loop closure recognition is one of the main processes of graph-based SLAM strategies, used to estimate the accumulated motion error to be minimized by the technique. Good scene correspondences allow to create constraints between two nodes in the graph that is currently being built to represent the environment that the robot is immersed. However, false correspondences can lead these strategies to an irreversible wrong environment representation. In this work, we present a robust feature-based loop closure approach that uses image sequence matching to recognize revisited areas. This approach uses Bag-of- Words to reduce the effects of lightning changes and a TF-IDF weighting to enhance the main features that describe each scene. Besides, an algorithm based on Mean Shift is used over a similarity matrix to identify the possible trajectory followed by the robot and improve the loop closure detection. Our method is tested in a GPS-denied outdoor environment using image sequences collected using a handheld camera and a Parrot ArDrone 2.0.

In this letter, we propose all-dielectric Huygens' metasurface structures to construct high numerical aperture flat lenses and beam deflecting devices. The designed metasurface consists of two-dimensional array of all dielectric nanodisk resonators with spatially varying radii, thereby introducing judiciously designed phase shift to the propagating light. Owing to the overlap of Mie-type magnetic and electric resonances, high transmission was achieved with rigorous design analysis. The designed flat lenses have numerical aperture value of 0.85 and transmission values around 80%. It also offers easy fabrication and compatibility with available semiconductor technology. This spectrally and physically scalable, versatile design could implement efficient wavefront manipulation or beam shaping for high power laser beams, as well as various optical microscopy applications without requiring plasmonic structures that are susceptible to ohmic loss of metals and sensitive to the polarization of light.

This study investigated the effects of night work on performance efficiency. Night work is generally acknowledged to impair performance, yet much research has contradicted this assertion. The feasibility of including brief periods of physical activity to stimulate arousal within mentally demanding work shifts was also evaluated. Thirty six postgraduate volunteers were assigned to either the cognitive tasks (CT) or cognitive and motor tasks (CMT) group. All subjects performed three psycho-motor tests, using the Vienna Test System, at midday and midnight. The CMT group performed a short cycling activity before each test. Heart rate responses served as physiological measures, the Perceived Strain Scale was used to quantify individual perceptions of strain and performance efficiency was assessed in terms of speed and accuracy. Although several trends were apparent, no significant differences (p < 0.05) were revealed with respect to the three performance variables between the midday and midnight test sessions, or between the CT and CMT subjects, other than the higher heart rates recorded in the CMT group. In summary, neither time of day nor physical activity were found to affect performance within the controlled environment of this study.

No description available.

The entropy of all systems is supposed to increase with time, this is also observed in the hydroclimatic records as increased variability. The current dissertation is primarily focused on the hydrologic variability of the hydrologic records in the climate regions across Continental United States. The study evaluated the effects of serial correlation in the historical streamflow records on both gradual trend and abrupt shift in streamflow. The study also evaluated the trend before and after the shift occurrence to validate whether the observed changes in streamflow is a result of long-term variability or climate regime shift. Secondly, the current dissertation evaluated the variability within western US hydrology which is highly driven by the oscillation of Pacific Ocean such as El Niño – Southern Oscillation (ENSO). The dissertation evaluated the variability in snow water equivalent (SWE) of western US as the winter snow accumulation of the region drives the spring-summer streamflow in the region which contributes to the major portion of yearly streamflow. The SWE variability during the individual phases of ENSO were analyzed to reveal the detailed influence of ENSO on historic snow accumulations. The study is not solely limited to the hydrologic variability evaluation rather; it also delves into obtaining the time lagged spatiotemporal teleconnections between large scale climate variables and streamflow and forecast the later based on the obtained teleconnections. To accomplish the research goals the current dissertation was subdivided into three research tasks. First task dealt with the streamflow records of 419 unimpaired streamflow records which were grouped into seven climate regions based on National Climate Assessment, to evaluate the regional changes in both seasonal streamflow and yearly streamflow percentiles. Non-parametric Mann-Kendall test and Pettitt’s test were utilized to evaluate the streamflow variability as gradual trend and abrupt shift, respectively. Walker test was performed to test the global significance of the streamflow variability within each climate regions based on local trend and shift significance of each streamflow stations. The task also evaluated the presence of serial correlation in the streamflow records and its effects on both trend and shift within the climate regions of continental United States for the first time. Maximum variability in terms of both trend and shift were observed for summer as compared to other seasons. Similarly, greater number of stations showed streamflow variability for 5th and 50th percentile streamflow as compared to 95th and 100th percentile streamflow. It was also observed that serial correlation affected both trend and step while, accounting for the lag-1 autocorrelation improved shift results. The results indicated that the streamflow variability has more likely occurred as shift as compared to the gradual trend. The outcomes of the current result detailing historic variability may help to envision future changes in streamflow. The second task evaluated the spatiotemporal variability of western US SWE over 58 years (1961–2018) as a trend and a shift. The task tested whether the SWE is consistent during ENSO phases utilizing the Kolmogorov – Smirnov (KS) test. Trend analysis was performed on the SWE data of each ENSO phase. Shift analysis was performed in the entire time series of 58 years. Additionally, the trend in the SWE data was evaluated before and after shift years. Mann- Kendal and Pettit's tests were utilized for the detection of trend and shift, respectively. The serial correlation was considered during the trend evaluation, while Thiel-Sen approach was used for the evaluation of the trend magnitude. The serial correlation in time series which is the potential cause of overestimation and underestimation of the trend evaluation was found to be absent in the SWE data. The results suggested a negative trend and a shift during the study period. The negative trend was absent during neutral years and present during El Niño and La Niña years. The trend magnitudes were maximum during La Niña years followed by those during El Niño years and the entire length of the data. It was also observed that if the presence of negative shift in the SWE was considered, then most of the stations did not show a significant trend before and after the occurrence of a shift. The third task forecasted the streamflow at a regional scale within Sacramento San Joaquin (SSJ) River Basin with largescale climate variables. SSJ is an agricultural watershed located in the drought sensitive region of California. The forecast techniques involved a hybrid statistical framework that eliminates the bias resulting from predefined indices at regional scale. The study was performed for eight unimpaired streamflow stations from 1962 to 2016. First, the Singular Valued Decomposition (SVD) teleconnections of the streamflow corresponding to 500 mbar geopotential height, sea surface temperature, 500 mbar specific humidity (SHUM500), and 500 mbar U-wind (U500) were obtained. Second, the skillful SVD teleconnections were screened non-parametrically. Finally, the screened teleconnections were used as the streamflow predictors in the non-linear regression models (K-nearest neighbor regression and data-driven support vector machine). The SVD results identified new spatial regions that have not been included in existing predefined indices. The nonparametric model indicated the teleconnections of SHUM500 and U500 being better streamflow predictors compared to other climate variables. The regression models were capable to apprehend most of the sustained low flows, proving the model to be effective for drought-affected regions. It was also observed that the forecasting approach showed better forecasting skills with preprocessed large-scale climate variables rather than using the predefined indices. The techniques involved in this task was simple, yet robust in providing qualitative streamflow forecasts that may assist water managers in making policy-related decisions when planning and managing watersheds.

<p> When a beam of electromagnetic radiation, limited by an aperture, undergoes total internal reflection, a sideways displacement of the reflected beam results. This displacement is known as the Goos-Hänchen Shift. </p> <p> In this work the Goos-Hänchen Shift is studied with 3.2 cm microwaves. The observed shifts disagree with three existing theories. For this reason a modified theory is developed in this work. The throey regards the beam from a pyramidal horn antenna as a superposition of a large number of plane waves. The shift is calculated on this basis. Agreement between experiment and theory is good. </p> / Thesis / Doctor of Philosophy (PhD)