Independent Visions of Marginal America: Reimagining a Nation Through Outsiders, Searching, and Non-Arrival

This thesis explores critical responses to American-ness, American identity, and most significantly American myth, in independent films about America in cultural terms, and their attempts to deconstruct the myths of nation and culture. The independent films about America analyzed in this thesis range from the 1960s to the 1990s, made by filmmakers across movements and cultures, but they all contain in some measure three key concepts: the “outsider,” the “search,” and a narrative “non-arrival.” Easy Rider (1969) will be explored as the prototype for this paradigm, contrasted with films that reinterpret the road-movie structure away from existential angst and toward richer ambiguities: Alambrista! (1977), Gummo, Stroszek, Chan is Missing, and The Watermelon Woman (1996). Transnationality reflects in the content and production of many “outsider” films; therefore my study replaces the category American films with films in and about America. These films about America are threaded together by the outsider as a position relative to social acceptance and unified identity (the “inside”), and the search as a yearning, a desire for peace, happiness, meaning, etc. molded by transience and instability. The search never yields the result or object the characters intend to find, and within this non-arrival the denial of resolution informs us about the unsurety of life for the outsider, and the elusiveness of the nation as a mythic construct. The unsettling of myth is interpreted as a kind of hauntology, as the ‘haunting’ or persistence of violence and myth is analyzed

Generalized SAR Processing and Motion Compensation

Application speci c algorithms for processing SAR data have been researched for many years, but a general theory is not well de ned. This paper presents a generalized way to look at SAR processing and uses the principles leared to develop an improved motion compensation method. The non-ideal motion of a SAR platform results in degraded image quality, but for known motion, corrections can be made. Traditional motion compensation requires a computationally costly interpolation step to correct translational motion greater than a single range bin. This paper presents an ef cient new motion compensation algorithm that corrects this range shift without interpolation. The new method is veri ed with simulated SAR data and data collected with the NuSAR

The BYU Micro-SAR: Theory and Application of a Small LFM-CW Synthetic Aperture Radar

The BYU microSAR is a new, low-cost Synthetic Aperture Radar (SAR) system developed by students at Brigham Young University. The simple design is based on a linear frequency modulated continuous wave signal (LFM-CW) which reduces the size and power compared to a conventional pulsed SAR system. The BYU microSAR is small enough to y on a small UAV, further reducing the cost of operation and extending the use of SAR into new areas. Due to the LFM-CW design, modi ed SAR processing algorithms are needed which account for the movement of the platform during data collection. SAR processing assumes that the sensor is moving in a straight line at a constant speed, but in actuality a UAV or airplane will deviate, often signi cantly, from this ideal. This non-ideal motion can seriously degrate the SAR image quality. This paper presents the design of the BYU microSAR, the theory of operation, and the modi ed processing algorithms which account for the continuous motion

Generalized Processing for Pulsed Synthetic Aperture Radar

The Range-Doppler Algorithm (RDA) and the Chirp-Scaling Algorithm (CSA) process Synthetic Aperture Radar (SAR) data with approximations to ideal SAR processing. These approximations are invalid for data from systems with wide bandwidths, large bandwidths, and/or low center frequencies. While simple and efficient, these frequency-domain methods are thus limited by the SAR parameters. This paper explores these limits and proposes a generalized chirp-scaling approach for extending the utility of frequency-domain processing. We demonstrate how different order approximations of the SAR signal in the two-dimensional frequency domain affect image focusing for varying SAR parameters. From these results, a guideline is set forth which suggests the required order of approximation terms for proper focusing. A proposed generalized frequency-domain processing approach is derived. This method is an efficient arbitrary-order chirp-scaling algorithm that processes the data using the appropriate number of approximation terms. The new method is demonstrated using simulated data

Fully Convolutional Networks for Semantic Segmentation

Convolutional networks are powerful visual models that yield hierarchies of features. We show that convolutional networks by themselves, trained end-to-end, pixels-to-pixels, exceed the state-of-the-art in semantic segmentation. Our key insight is to build "fully convolutional" networks that take input of arbitrary size and produce correspondingly-sized output with efficient inference and learning. We define and detail the space of fully convolutional networks, explain their application to spatially dense prediction tasks, and draw connections to prior models. We adapt contemporary classification networks (AlexNet, the VGG net, and GoogLeNet) into fully convolutional networks and transfer their learned representations by fine-tuning to the segmentation task. We then define a novel architecture that combines semantic information from a deep, coarse layer with appearance information from a shallow, fine layer to produce accurate and detailed segmentations. Our fully convolutional network achieves state-of-the-art segmentation of PASCAL VOC (20% relative improvement to 62.2% mean IU on 2012), NYUDv2, and SIFT Flow, while inference takes one third of a second for a typical image.Comment: to appear in CVPR (2015

Catastrophic production of slow gravitinos

We study gravitational particle production of the massive spin-$3/2$ Rarita-Schwinger field, and its close relative, the gravitino, in Friedmann-Robertson-Walker cosmological spacetimes. For masses lighter than the value of the Hubble expansion rate after inflation, $m_{3/2}≲H$, we find catastrophic gravitational particle production, wherein the number of gravitationally produced particles is divergent, caused by a transient vanishing of the helicity-1/2 gravitino sound speed. In contrast with the conventional gravitino problem, the spectrum of produced particles is dominated by those with momentum at the UV cutoff. This suggests a breakdown of effective field theory, which might be cured by new degrees of freedom that emerge in the UV. We study the UV completion of the Rarita-Schwinger field, namely $N=1$, $d=4$, supergravity. We reproduce known results for models with a single superfield and models with an arbitrary number of chiral superfields, find a simple geometric expression for the sound speed in the latter case, and extend this to include nilpotent constrained superfields and orthogonal constrained superfields. We find supergravity models where the catastrophe is cured and models where it persists. Insofar as quantizing the gravitino is tantamount to quantizing gravity, as is the case in any UV completion of supergravity, the models exhibiting catastrophic production are prime examples of four-dimensional effective field theories that become inconsistent when gravity is quantized, suggesting a possible link to the swampland program. We propose the gravitino swampland conjecture, which is consistent with and indeed follows from the Kachru-Kallosh-Linde-Trivedi and large volume scenarios for moduli stabilization in string theory

Economic Impacts of the Quality of Labor Market on Value-Added Agriculture and Economic Growth : Evidence from Malaysia

The main objective of this paper is to examine the impacts of quality of the labor market on value-added agriculture and economic growth of Malaysia during 1982-2019. The research methodologies adopted in this study are unit root and stationary test, Johansen and Juselius cointegration test, Granger causality test, variance decomposition, and generalized impulse response function. The empirical results of Model (1) indicate that low education level has negative relationship with value-added agriculture over period of 1982-2019. However, the graph of impulse responses analysis reveal that employed worker with tertiary education level has positive relationship with value-added agriculture but this positive effect does not happen during the period of study based on the Granger causality test. Nevertheless, the variance decomposition results further proves that most of employed foreign worker do not have high education level. Meanwhile, employed worker with tertiary education level only can affect a small percentage of the employed foreign worker in Malaysia. Besides, the empirical results of Model (2) reveal that labour force with tertiary education level does significant positive Granger cause the agricultural GDP especially at 4 th year reach its maximum while the labour force who have secondary education level does negative Granger cause the agricultural GDP in the first 6 years only. Hence, the significant positive effect of tertiary education level does reduce the impacts from negative effect of the secondary education level on agricultural GDP at the beginning period. The results also proves that foreign labour force does not much affect the Malaysia’s agricultural GDP