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Effective use of Machine Learning to support extracting maximal information from limited sensor data is one of the important research challenges in robotic sensing. This thesis develops techniques for detecting and characterizing patterns in noisy sensor data. Our Bayesian Aggregation (BA) algorithmic framework can leverage data fusion from multiple low Signal-To-Noise Ratio (SNR) sensor observations to boost the capability to detect and characterize the properties of a signal generating source or process of interest. We illustrate our research with application to the nuclear threat detection domain. Developed algorithms are applied to the problem of processing the large amounts of gamma ray spectroscopy data that can be produced in real-time by mobile radiation sensors. The thesis experimentally shows BA’s capability to boost sensor performance in detecting radiation sources of interest, even if the source is faint, partiallyoccluded, or enveloped in the noisy and variable radiation background characteristic of urban scenes. In addition, BA provides simultaneous inference of source parameters such as the source intensity or source type while detecting it. The thesis demonstrates this capability and also develops techniques to efficiently optimize these parameters over large possible setting spaces. Methods developed in this thesis are demonstrated both in simulation and in a radiation-sensing backpack that applies robotic localization techniques to enable indoor surveillance of radiation sources. The thesis further improves the BA algorithm’s capability to be robust under various detection scenarios. First, we augment BA with appropriate statistical models to improve estimation of signal components in low photon count detection, where the sensor may receive limited photon counts from either source and/or background. Second, we develop methods for online sensor reliability monitoring to create algorithms that are resilient to possible sensor faults in a data pipeline containing one or multiple sensors. Finally, we develop Retrospective BA, a variant of BA that allows reinterpretation of past sensor data in light of new information about percepts. These Retrospective capabilities include the use of Hidden Markov Models in BA to allow automatic correction of a sensor pipeline when sensor malfunction may be occur, an Anomaly- Match search strategy to efficiently optimize source hypotheses, and prototyping of a Multi-Modal Augmented PCA to more flexibly model background and nuisance source fluctuations in a dynamic environment.

South Korea’s security discourse on the nuclear threat posed by North Korea has been dichotomised by its position within the political spectrum between the progressives and conservatives. By drawing upon Securitisation Theory (ST), this study challenges the current security discourse in South Korea, which has divided and misled the public as well as securitising actors. This study examines the security discourses of the Roh Moo-hyun (2003–2008) and Lee Myung-bak (2008–2013) administrations, since they represent the archetypes of the progressives and conservatives respectively. The results of the analysis suggest that the current security discourses that have been prevalent in South Korea do not correspond with reality and, subsequently, the discourses were not able to deal with real challenges that the nuclear threat posed. This research also explains the root cause of the distorted security discourses by applying a ‘discursive chasm’ as a preliminary concept, which indicates a discursive structure that fundamentally impedes the performance of securitising actors’ articulation, and that distorts the discursive formation (securitisation processes). The chasms consist of three elusive discourses: first, a discourse on threats that cannot simply be said to be either imminent or not imminent (nuclear weapons as materiality and discourse); second, a discourse on the other that cannot easily be defined (the difficulty of representation of North Korea); and third, a discourse on measures that cannot easily be realised (intangible extraordinary measures).

South Korea’s security discourse on the nuclear threat posed by North Korea has been dichotomised by its position within the political spectrum between the progressives and conservatives. By drawing upon Securitisation Theory (ST), this study challenges the current security discourse in South Korea, which has divided and misled the public as well as securitising actors. This study examines the security discourses of the Roh Moo-hyun (2003–2008) and Lee Myung-bak (2008–2013) administrations, since they represent the archetypes of the progressives and conservatives respectively. The results of the analysis suggest that the current security discourses that have been prevalent in South Korea do not correspond with reality and, subsequently, the discourses were not able to deal with real challenges that the nuclear threat posed. This research also explains the root cause of the distorted security discourses by applying a ‘discursive chasm’ as a preliminary concept, which indicates a discursive structure that fundamentally impedes the performance of securitising actors’ articulation, and that distorts the discursive formation (securitisation processes). The chasms consist of three elusive discourses: first, a discourse on threats that cannot simply be said to be either imminent or not imminent (nuclear weapons as materiality and discourse); second, a discourse on the other that cannot easily be defined (the difficulty of representation of North Korea); and third, a discourse on measures that cannot easily be realised (intangible extraordinary measures).

Nuclear weapons remains in the security discourse of the United States for over 70 years. The threat of nuclear weapons changed its content several times since then. Our study examines how the nuclear threat was socially constructed and how different actors securitized the threat and to which purpose. Our Diploma thesis uses methodological framework of discourse analysis. We examine the political and social nuclear discourse in the U.S. along two levels of analysis: governmental level and nuclear disarmament level. The diploma thesis researches multiple governmental and societal sources in order to determine how different types of nuclear threat emerged within the discourse.

The cantata A World Without War (2009), by Armenian-born composer Edward Manukyan (b. 1981), was written, in part, to support increased awareness of human rights issues. Based on a quote from linguist and philosopher Noam Chomsky (b. 1928), the narrative of the cantata states: "We can, for example, be fairly confident that either there will be a world without war or there won't be a world." In addition to Chomsky's words, the cantata excerpts quotes of two additional literary giants advocating human rights, Bertrand Russell (1872-1970), and Andrei Sakharov (1921-1989). The purpose of this dissertation is to focus attention on human rights activism; using Manukyan's A World Without War, I highlight moral and ethical questions at the center of this work and explain how this cantata embraces the ideal of moral cosmopolitanism. I strongly believe in the importance of human rights for all citizens of the world, and the role music plays in advancing its cause through performance arts.