Thesis (Ph. D.)--Boston University Includes bibliographical references (leaves 287-293). Abstract: leaves 294-301.

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This paper analyzes composer Aaron Cassidy’s 2014-2016 ensemble work The wreck of former boundaries, focusing on Cassidy’s compositional approach to sonically simulating interactive modes and sonic ideals featured prominently in mid-20th century recordings of free jazz artists such as Albert Ayler (Bells [1965]) and John Coltrane (Ascension [1965]). Because these musical conventions can be heard as socio-political simulacra in and of themselves, I argue that Wreck’s sonic simulations dissimulate the anti-hegemonic implications of the sound of free jazz, depicting spontaneous, hetero-original confrontations with socio-political constraint as symbolic and insubstantial. In my conclusion I argue that while an apparitional circulation of free jazz simulacra seems to de-politicize free jazz musical conventions, Wreck can be understood more precisely as critically analyzing the history of revolution. Heard through the interpretive lens of a broader history of hegemonic improvisations that absorb and displace open expressions of political defiance, Wreck appears to pessimistically reimagine free jazz as a novel form of symbolic, musical constraint.

Gravitational-wave astronomy is an emerging field in observational astrophysics concerned with the study of gravitational signals proposed to exist nearly a century ago by Albert Einstein but only recently confirmed to exist. Such signals were theorized to result from astronomical events such as the collisions of black holes, but they were long thought to be too faint to measure on Earth. In recent years, the construction of extremely sensitive detectors—including the Laser Interferometer Gravitational-Wave Observatory (LIGO) project—has enabled the first direct detections of these gravitational waves, corroborating the theory of general relativity and heralding a new era of astrophysics research. As a result of their extraordinary sensitivity, the instruments used to study gravitational waves are also subject to noise that can significantly limit their ability to detect the signals of interest with sufficient confidence. The detectors continuously record more than 200,000 time series of auxiliary data describing the state of a vast array of internal components and sensors, the environmental state in and around the detector, and so on. This data offers significant value for understanding the nearly innumerable potential sources of noise and ultimately reducing or eliminating them, but it is clearly impossible to monitor, let alone understand, so much information manually. The field of machine learning offers a variety of techniques well-suited to problems of this nature. In this thesis, we develop and present several machine learning–based approaches to automate the process of extracting insights from the vast, complex collection of data recorded by LIGO detectors. We introduce a novel problem formulation for transient noise detection and show for the first time how an efficient and interpretable machine learning method can accurately identify detector noise using all of these auxiliary data channels but without observing the noise itself. We present further work employing more sophisticated neural network–based models, demonstrating how they can reduce error rates by over 60% while also providing LIGO scientists with interpretable insights into the detector’s behavior. We also illustrate the methods’ utility by demonstrating their application to a specific, recurring type of transient noise; we show how we can achieve a classification accuracy of over 97% while also independently corroborating the results of previous manual investigations into the origins of this type of noise. The methods and results presented in the following chapters are applicable not only to the specific gravitational-wave data considered but also to a broader family of machine learning problems involving prediction from similarly complex, high-dimensional data containing only a few relevant components in a sea of irrelevant information. We hope this work proves useful to astrophysicists and other machine learning practitioners seeking to better understand gravitational waves, extremely complex and precise engineered systems, or any of the innumerable extraordinary phenomena of our civilization and universe.

Thesis (Ph.D)--Boston University. / The primitive Christian hope of the immediate coming of the Kingdom of God was based on the memory of the teachings of Jesus. The fact that that hope remained unfulfilled forced a transformation of the Christian faith which enabled it to survive the failure of the original expectation. The place of Paul in this transformation has been uncertain. His early letters show a strong expectation of the Parousia, but scholarly opinion on the later letters remains contradictory. R.H. Charles has suggested that in Paul's later letters there is a noticeable decline in eschatological thought and, in effect, a transformation of Paul's original hope for the immediate Parousia. This transformation may be clearly shown by arranging Paul's letters into four stages on the basis of the diminishing emphasis of declining eschatology. Albert Schweitzer has held that Paul maintains a consistent eschatological hope throughout his letters. The background of Charles' position was rooted in the work of F.C. Baur and the Tubingen School and culminated with H.J. Holtzmann. This background centered about two questions of Pauline doctrine: 1. Its relationship to primitive Christianity, 2. Its relationship to Hellenistic ideas. The Tubingen School explained the decline of eschatology on the hypothesis that Paul introduced Hellenistic thought. Schweitzer regarded this explanation as unfounded and attempted to demonstrate that there were no clear affinities between the thought of Paul and the Hellenistic world. Paul's thought thus did not develop in any Hellenistic direction but remained consistently Jewish eschatological throughout his literary production. The purpose of this dissertation is to outline and criticize the Pauline eschatological theory of R.H. Charles in the light of Schweitzer's thorough-going eschatology with particular reference to the Parousia. The two positions are first compared on the basis of their relationship to critical norms regarding the Pauline corpus. These norms reject the authenticity of Ephesians and the Pastorals and establish the genuineness of nine letters. These genuine letters are chronologically arranged into three groups, each group being separated by a period of three or four years. The eschatological material in the letters is then isolated and analyzed under three headings: the imminent expectation of the Parousia, the immediate resurrection upon death, and the eschatological chronology. This last heading is subdivided into the problem of the temporary Messianic Kingdom and a dual resurrection. The results of this analysis are applied to an evaluation of the two positions with the following results: 1. There is a consistent imminent hope for the Parousia throughout Paul's letters sustaining Schweitzer's basic position. There is no evidence for a correlation of this hope with the dating of the letters. Charles' failure to acknowledge the eschatological evidence of Philippians is a primary objection to his developmental argument. 2. In the light of the possibility of his own death prior to the Parousia, Paul revises his concept of the time of the resurrection in the Imprisonment Letters, arriving at a new doctrine of immediate resurrection. It is uncertain whether or not Paul wishes to apply this new doctrine only to his own death. 3. Evidence for a Messianic Kingdom is limited to a single passage in I Corinthians which does not adequately support Schweitzer's theory, a theory which is based primarily on non-Pauline materials. 4. Paul believes in a single resurrection for the righteous only. Schweitzer's reconstruction of eschatological chronology, which includes a dual resurrection, is based on non-Pauline materials. Insofar as the eschatological evidence is concerned, Paul seems to stand apart from the process of Hellenization and, despite the possibility of his introduction of the doctrine of immediate resurrection, he remains within the Jewish eschatological framework. [TRUNCATED]

This paper analyzes and compares two photographs of women doing backbends. One is a modern Instagram photo of a female yogi by Alessandro Sigismondi and the other one of a patient diagnosed with hysteria at the Salpêtrières Hospital, photographed in Paris in the 19th century. The photographs are used as a starting point for further discussion about the meaning of images where women are doing backbends. The aim is to understand what these kinds of photographs represent and communicate. The theoretical framework is based on Roland Barthes idea of defining photography out of three perspectives as described in Camera Lucida, the referent’s, the photographer’s and the spectators. Laura Mulvey's thoughts on the male gaze in "Visual Pleasure and Narrative Cinema" is a theoretical complement. The method used is Roland Bathes semiotic method from the essay Rhetoric of the image. The study shows how the photographic occasion's imprint of reality is deeply colored by the events, relationships and expectations from outside. Despite the large difference in time, there are great similarities in how the ideal female body is exposed and how women manage and maneuver within the space constructed by the male gaze.

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There is a growing use of the internet and alongside that, there has been an increase in the use of toxic language towards other people that can be harmful to those that it targets. The usefulness of artificial intelligence has exploded in recent years with the development of natural language processing, especially with the use of transformers. One of the first ones was BERT, and that has spawned many variations including ones that aim to be more lightweight than the original ones. The goal of this project was to train three different kinds of transformer models, RoBERTa, ALBERT, and DistilBERT, and find out which one was best at identifying toxic language online. The models were trained on a handful of existing datasets that had labelled data as abusive, hateful, harassing, and other kinds of toxic language. These datasets were combined to create a dataset that was used to train and test all of the models. When tested against data collected in the datasets, there was very little difference in the overall performance of the models. The biggest difference was how long it took to train them with ALBERT taking approximately 2 hours, RoBERTa, around 1 hour and DistilBERT just over half an hour. To understand how well the models worked in a real-world scenario, the models were evaluated by labelling text as toxic or non-toxic on three different subreddits. Here, a larger difference in performance showed up. DistilBERT labelled significantly fewer instances as toxic compared to the other models. A sample of the classified data was manually annotated, and it showed that the RoBERTa and DistilBERT models still performed similarly to each other. A second evaluation was done on the data from Reddit and a threshold of 80% certainty was required for the classification to be considered toxic. This led to an average of 28% of instances being classified as toxic by RoBERTa, whereas ALBERT and DistilBERT classified an average of 14% and 11% as toxic respectively. When the results from the RoBERTa and DistilBERT models were manually annotated, a significant improvement could be seen in the performance of the models. This led to the conclusion that the DistilBERT model was the most suitable model for training and classifying toxic language of the lightweight models tested in this work.