Laplace-domain analysis of fluid line networks with applications to time-domain simulation and system parameter identification.

Networks of closed conduits containing pressurised fluid flow occur in many different instances throughout the natural and man made world. The dynamics of such networks are dependent not only on the complex interactions between the fluid body and the conduit material within each fluid line, but also on the coupling between different lines as they influence each other through their common junctions. The forward modelling (time-domain simulation), and inverse modelling (system parameter identification) of such systems is of great interest to many different research fields. An alternative approach to time-domain descriptions of fluid line networks is the Laplace-domain representation of these systems. A long standing limitation of these methods is that the frameworks for constructing Laplace-domain models have not been suitable for pipeline networks of an arbitrary topology. The objective of this thesis is to fundamentally extend the existing theory for Laplace-domain descriptions of hydraulic networks and explore the applications of this theory to forward and inverse modelling. The extensions are undertaken by the use of graph theory concepts to construct network admittance matrices based on the Laplace-domain solutions of the fundamental pipeline dynamics. This framework is extended to incorporate a very broad class of hydraulic elements. Through the use of the numerical inverse Laplace transform, the proposed theory forms the basis for an accurate and computationally efficient hydraulic network time-domain simulation methodology. The compact analytic nature of the network admittance matrix representation facilitates the development of two successful and statistically based parameter identification methodologies, one based on an oblique filtering approach combined with maximum likelihood estimation, and the other based on the expectation-maximisation algorithm.Thesis (Ph.D.) -- University of Adelaide, School of Civil, Environmental and Mining Engineering, 201

Time inconsistency in monetary policy : a discussion of solutions

Kydland and Prescott (1977) demonstrate that the inability of a discretionary policymaker to commit to a future plan of action may lead to a suboptimal result. A promise to follow a better outcome is time-inconsistent: the policymaker has incentives to ex-post deviate from the announced policy. This study discusses how rules, rather than discretion, can mitigate the time-inconsistency problem in monetary policy. The second chapter builds a canonical model to demonstrate that the discretionary policy leads to inflation bias. The model is then modified to examine solutions suggested by the relevant literature. The third chapter discusses the trade-offs associated with institutional solutions, in which the policymaker alters the behavior of the monetary authority. More specifically, I consider three rule-based solutions: a zero-inflation rule, an independent central bank, and a state-contingent rule. Finally, I investigate how reputation can alleviate the time consistency problem even with a discretionary policymaker.Kydland and Prescott (1977) mostram que a incapacidade de um policymaker discricionário em se comprometer a um plano de ação futuro pode levar a um resultado subótimo. Prometer seguir um resultado melhor é temporalmente inconsistente: o policymaker tem incentivos para desviar, ex-post, da política anunciada. Esse estudo discute como regras, em vez de discrição, podem atenuar o problema de inconsistência temporal em política monetária. O segundo capítulo constrói um modelo canônico para demonstrar como a política discricionária leva a um viés inflacionário. O modelo é subsequentemente modificado para examinar soluções sugeridas pela literatura relevante. O terceiro capítulo discute os trade-offs associados a soluções institucionais, nas quais o policymaker altera o comportamento da autoridade monetária. Mais especificamente, considero três soluções: uma regra de inflação zero, um banco central independente, e uma regra condicional. Por último, investigo como reputação pode diminuir o problema de inconsistência temporal mesmo com uma política discricionária

Deixis social en la relación Odiseo/Iro en Odisea 18.1-157

El enfrentamiento entre Odiseo e Iro ha sido usualmente interpretado como una secuencia más en el itinerario de violencia que debe sufrir Odiseo hasta su restauración como basiléus. El presente artículo realiza una lectura descriptiva y analítica de los deícticos utilizados en el combate Odiseo/Iro; así como de la escena consecuente que le sigue. Ambos personajes hablan desde una posición social ajena al espacio en el que se inscriben y el campo verbal que generan resulta el recipiente de una lectura de clases sociales en Odisea. Analizaremos cómo las diversas categorías de la deixis - personal, temporal, espacial y discursiva- inciden en la deixis social que el texto de Odisea 18.1-157 expone.The fight between Odysseus and Irus has been usually interpreted as one more sequence in the itinerary of violence that Odysseus must suffer until his restoration as basileus. This article fulfils a descriptive and analytical study about the deixis used in the confrontation between Odysseus and Irus; it also studies the subsequent scene after the fight. Both characters speak from a social position not suitable to their proper space and their conversation shows an interpretation about the social classes of the Odyssey. We will analyze how several categories of deixis - personal, temporal, spatial and discoursive- influence the social deixis that the Odyssey exposes in Book 18.1-157.Fil: Zecchin de Fasano, Graciela C.. Universidad Nacional de La Plat

Improving partial mutual information-based input variable selection by consideration of boundary issues associated with bandwidth estimation

Abstract not availableXuyuan Li, Aaron C. Zecchin, Holger R. Maie

Interpretation and stress

This study was carried out to analyze stress factors such as anxiety and depression on interpreters and interpreting students during simultaneous and remote interpreting. The study was taylored to interpeting conditions. The project was devided in two stages. During the first, data about the interpreters were collected to assess baseline values for psychological factors important for stress evaluation. In the second, the same group of interpreters underwent specific tests during simultaneous and remote interpreting.Psychometric instruments were chosen to this end. The results of the study show lower anxiety and depression values for interpreters than in the normal sample population, with interpeters being characterized by lower values than interpreting-students

Forking Uncertainties:Reliable Prediction and Model Predictive Control With Sequence Models via Conformal Risk Control

In many real-world problems, predictions are leveraged to monitor and control cyber-physical systems, demanding guarantees on the satisfaction of reliability and safety requirements. However, predictions are inherently uncertain, and managing prediction uncertainty presents significant challenges in environments characterized by complex dynamics and forking trajectories. In this work, we assume access to a pre-designed probabilistic implicit or explicit sequence model, which may have been obtained using model-based or model-free methods. We introduce probabilistic time series-conformal risk prediction (PTS-CRC), a novel post-hoc calibration procedure that operates on the predictions produced by any pre-designed probabilistic forecaster to yield reliable error bars. In contrast to existing art, PTS-CRC produces predictive sets based on an ensemble of multiple prototype trajectories sampled from the sequence model, supporting the efficient representation of forking uncertainties. Furthermore, unlike the state of the art, PTS-CRC can satisfy reliability definitions beyond coverage. This property is leveraged to devise a novel model predictive control (MPC) framework that addresses open-loop and closed-loop control problems under general average constraints on the quality or safety of the control policy. We experimentally validate the performance of PTS-CRC prediction and control by studying a number of use cases in the context of wireless networking. Across all the considered tasks, PTS-CRC predictors are shown to provide more informative predictive sets, as well as safe control policies with larger returns

In-Context Learning for MIMO Equalization Using Transformer-Based Sequence Models

Large pre-trained sequence models, such as transformer-based architectures, have been recently shown to have the capacity to carry out in-context learning (ICL). In ICL, a decision on a new input is made via a direct mapping of the input and of a few examples from the given task, serving as the task's context, to the output variable. No explicit updates of the model parameters are needed to tailor the decision to a new task. Pre-training, which amounts to a form of meta-learning, is based on the observation of examples from several related tasks. Prior work has shown ICL capabilities for linear regression. In this study, we leverage ICL to address the inverse problem of multiple-input and multiple-output (MIMO) equalization based on a context given by pilot symbols. A task is defined by the unknown fading channel and by the signal-to-noise ratio (SNR) level, which may be known. To highlight the practical potential of the approach, we allow the presence of quantization of the received signals. We demonstrate via numerical results that transformer-based ICL has a threshold behavior, whereby, as the number of pre-training tasks grows, the performance switches from that of a minimum mean squared error (MMSE) equalizer with a prior determined by the pre-trained tasks to that of an MMSE equalizer with the true data-generating prior

Leakage flow noise and related flow pattern in a low-speed axial fan with rotating shroud

The effect of rotational speed and pressure rise on the leakage flow noise radiated by a low-speed axial fan, provided with rotating shroud, has been systematically investigated. The leakage flow noise generally increases with the blade loading, with a trend which is qualitatively independent from the rotational speed but non-monotonic, as its growth is interrupted by local minima. As the loading increases, the SPL spectrum shows important modifications, since the characteristic frequency of the subharmonic narrowband humps related to the leakage noise decreases. The flow in the gap region has been studied by means of PIV measurements taken in the meridional plane. At low blade loading, the leakage flow is restrained close to the rotor ring and, at higher loading, it forms a wide recirculation zone. In the latter conditions, an unsteady flow separation likely takes place in the blade tip region which may be observed in the instantaneous flow field only. Possibly, it is responsible for the observed frequency shift of the humps