Bengali nasal vowels: Lexical representation and listener perception

publishedVersionPaid Open Acces

Retrospective and Recent Examples of Aircraft and Rotorcraft System Identification at DLR

Aircraft system identification has a five-decades-long tradition at German Aerospace Center (DLR). Over the last two decades, the research covered various topics related to system identification of fixed- and rotary-wing aircraft, nonconventional applications and atmospheric effects, the development of new flight-test procedures for system identification purposes, and specific aircraft model enhancements and corresponding parameter estimation. Comprehensive tools were developed that support this research and can be applied to a variety of different problems and types of vehicles. The paper starts with a short description of the different system identification methods used at DLR and the corresponding tools. The discussion of flight-test procedures and maneuver design as well as sensor fusion and flight-path reconstruction provides information on how to optimize the flight tests for system identification and to arrive at a consistent flight-test database. The examples for fixed-wing aircraft provide information on identification including abnormal conditions such as icing and interaction with atmospheric disturbances as well as modeling of structural mechanics and loads. The identification of high-order rotorcraft models that account for rotor and engine dynamics and even structural modes is discussed, and the identification of rotor mast moments as well as the identification of non-physics-based models and their integration into physics-based models are also covered. A final section shows that system identification can also be used to derive models for gyroplanes and parachutes as well as to derive control equivalent turbulence input models and to estimate complex wind field geometries. Thus, a broad overview of possible applications of system identification is given

AN INTELLIGENT NAVIGATION SYSTEM FOR AN AUTONOMOUS UNDERWATER VEHICLE

The work in this thesis concerns with the development of a novel multisensor data fusion (MSDF) technique, which combines synergistically Kalman filtering, fuzzy logic and genetic algorithm approaches, aimed to enhance the accuracy of an autonomous underwater vehicle (AUV) navigation system, formed by an integration of global positioning system and inertial navigation system (GPS/INS). The Kalman filter has been a popular method for integrating the data produced by the GPS and INS to provide optimal estimates of AUVs position and attitude. In this thesis, a sequential use of a linear Kalman filter and extended Kalman filter is proposed. The former is used to fuse the data from a variety of INS sensors whose output is used as an input to the later where integration with GPS data takes place. The use of an adaptation scheme based on fuzzy logic approaches to cope with the divergence problem caused by the insufficiently known a priori filter statistics is also explored. The choice of fuzzy membership functions for the adaptation scheme is first carried out using a heuristic approach. Single objective and multiobjective genetic algorithm techniques are then used to optimize the parameters of the membership functions with respect to a certain performance criteria in order to improve the overall accuracy of the integrated navigation system. Results are presented that show that the proposed algorithms can provide a significant improvement in the overall navigation performance of an autonomous underwater vehicle navigation. The proposed technique is known to be the first method used in relation to AUV navigation technology and is thus considered as a major contribution thereof.J&S Marine Ltd., Qinetiq, Subsea 7 and South West Water PL

Cortical and subcortical contributions to human cognitive flexibility

Cognitive flexibility enables individuals to respond adaptively to an ever-changing world. Neurally, flexibility is underpinned by involvement from across the cerebrum, and there is evidence from animal and human neuroscience suggesting that integration of cortical and thalamic signals in the striatum is necessary for appropriate behavioural control. A commonly used assay of flexibility is reversal learning, an associative learning task with high inter-species translatability. Evidence from animal literature has clearly defined the importance of the striatal cholinergic system in regulating striatal activity and output from the basal ganglia, and there is nascent evidence suggesting this system operates in a similar way in humans. However, there is a need to further disentangle the role of cortical, striatal, and thalamic regions during reversal learning in humans to better understand how the system works, and whether it has heterogeneous functionality in different contexts. Furthermore, as studying these processes is not trivial, further methodological work is required to enable us to understand the system. In chapter two we systematically assess an automated parcellation technique for identifying specific thalamic nuclei. Despite generally being treated as a homologous structure in neuroimaging work, nuclei within the thalamus have dissociable roles, and have diverse contributions to cognitive functioning, including reversal learning. We found mixed efficacy for segmentations across the thalamus, with some regions being more accurately defined relative to a “gold standard” atlas than others. Crucially, we find that the centromedian and parafascicular nuclei, which have an important role in reversal learning, are clearly defined and have little overlap with contiguous regions. These results show we can use this automated parcellation technique to identify specific thalamic nuclei that are relevant for cognitive flexibility and use these parcellations to study functionally relevant processes. Recent work has demonstrated that the functional relevance of the striatal cholinergic system can be studied in vivo using magnetic resonance spectroscopy by separating the peaks of different metabolites. But this non-conventional approach has not yet been widely adopted, and work is needed to determine its reliability. Chapter three presents test-retest reliability data on the use of magnetic resonance spectroscopy to study cholinergic activity in the striatum and cortex. We find measures of choline containing compounds are highly correlated when peaks are separated and when they are not. Across time we find that choline concentrations are relatively inconsistent, and that this was due to changes in the functionally relevant metabolite choline. Conversely, metabolites that we think are not functionally relevant were stable over time. We believe these differences may underly differences in acetylcholine function over time and may explain some intra-individual behavioural variability. In chapter four we use functional magnetic resonance imaging and psychophysiological interaction analysis to study corticostriatal and thalamostriatal connectivity during serial reversal learning. Functional connectivity between the centromedian-parafascicular nuclei of the thalamus and the associative dorsal striatum, and between the lateral-orbitofrontal cortex and the associative dorsal striatum was related to processing feedback during reversal learning. Specifically, thalamostriatal connectivity was found across the task, and may reflect a general error signal used to identify potential changes in context. Conversely, corticostriatal connectivity was found to be specific to when behaviour changed and suggests this may be a mechanism for the implementing adaptive change. We also show findings from exploratory work that may explain further how the cortex supports flexibility during reversal learning. Lastly, we used magnetic resonance spectroscopy to investigate whether the state of the cholinergic system at rest is related to reversal learning performance and latent measures of behaviour using computational modelling. Choline concentrations at rest showed significant functional relevance to our measures of reversal learning. More specifically, we found that errors during reversal learning, and learning rates for positive and negative prediction errors, explained significant variance in choline. However, the relationship between choline levels and task performance presented here differ from previous work which instead used a multi-alternative reversal learning task, and suggests that the striatal cholinergic system may have dissociable roles in different contexts. Overall, we show that the striatum, its cholinergic interneuron system, and its afferent projections from the cortex and thalamus, are associated with performance during serial reversal learning. Moreover, these findings suggest that the system may operate in separable ways in different contexts which may be dependent on internal representations of task structure

Data Discovery and Anomaly Detection using Atypicality.

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2017

Composing darkness”: Romantic Prophecy and the Phenomenology of History

In contrast to the Greek concept of prophecy as a form of prediction, Romantic prophecy rehabilitates a version of Hebrew prophecy that involves a more ambivalent relationship to history and time. That is, while the rise of prophecy in Romanticism might—like the rise of historiography more broadly—seem to organize and contain political and epistemological revolution, closer examination reveals that, in fact, this very attempt at hyper-organization becomes necessary only because of a deep and pervasive sense of historical discontinuity. Hence, while prophecy might aim to ameliorate disorder, in fact it draws attention to and exacerbates this same disorder. This uncertainty stems from a new sense of time as a detotalizing and structurally ironic phenomenon. Hence, chapter one looks at Immanuel Kant’s ironic, non-predictive form of prophecy— what he calls the Sign of History—as an example of how prophecy becomes the infinite absolute negativity of history or the counter-science that displaces natural history through a history of nature. Chapter two considers William Wordsworth’s claims to special poetic election and his attempt to absorb trauma into historical and subjective Bildung. It turns out that while Wordsworth seems to invite what Georges Bataille calls a general economy of expenditure, in fact he restricts this energy in an effort to profit from prophecy. Chapter three looks at Percy Shelley’s play, Hellas, for how the synthesizing figures of prophecy—metaphor, memory, and history itself—are inverted and displaced by the Wandering Jew. Chapter four, on William Blake’s Milton, re-conceptualizes the preface as a mode of ambivalent prophecy and reads Milton’s ostensibly totalizing form in light of the absolute preface’s workelessness. Finally, chapter five uses Ernst Bloch’s concept of exodus to organize readings of Caroline Lamb’s Glenarvon and Mary Shelley’s Valperga and The Last Man in terms of how female prophecy, specifically, displaces forms of history that remain disabling for marginalized subjects. These works all do this through some version of double negation that inaugurates a negative dialectic, negating the present in an effort to open the future to a new concept of the future