Counterstories: who counts as lesbian?

Coming out midlife is a profound and life‐changing experience—it is an experience of self‐shattering that entails the destabilisation of identity, and of family relationships. Entailing a displacement from social insider to outsider, it is a difficult, but also exhilarating, journey of self, and sexual, discovery. This thesis is an examination of the experiences of nine women who undertook that journey. This dissertation is very much a search for understanding—for understanding how one can be lesbian, and how one can not have known, following a lifetime of heterosexual identification—as well as a search for why those questions arise in the first place. I argue that the experience of coming out midlife exposes the fundamental ambiguity of sexuality; and has a significance that ranges beyond the particularity of the participants’ experiences and speaks to the limitations of the hegemonic sexual paradigm itself. Using the theoretical lens of three diverse conceptual approaches—the dynamic systems theory of sexual fluidity; liminality; and narrative identity—to illuminate their transition, I argue that the event of coming out midlife should be viewed not merely as an atypical experience, but rather we should ask what such events can tell us about women’s sexuality in particular, and the sexual paradigm more generally. I argue that women who come out midlife challenge those dominant discourses of sexuality that would entail that women who come out midlife were either in denial of their “true” sexuality throughout their adult lives; or that they are not really lesbian now. The experiences of the women I interviewed demonstrate the inadequacy of the sexual paradigm as a framework within which to understand and research the complexity of human sexuality; they also challenge hegemonic understandings of sexuality as innate and immutable. In this thesis, I explore that challenge.

Stochastic switching in infinite dimensions with applications to random parabolic PDE

© 2015 Society for Industrial and Applied Mathematics.We consider parabolic PDEs with randomly switching boundary conditions. In order to analyze these random PDEs, we consider more general stochastic hybrid systems and prove convergence to, and properties of, a stationary distribution. Applying these general results to the heat equation with randomly switching boundary conditions, we find explicit formulae for various statistics of the solution and obtain almost sure results about its regularity and structure. These results are of particular interest for biological applications as well as for their significant departure from behavior seen in PDEs forced by disparate Gaussian noise. Our general results also have applications to other types of stochastic hybrid systems, such as ODEs with randomly switching right-hand sides.

Application of regularization methods to damage detection in large scale plane frame structures using incomplete noisy modal data

This paper presents an approach for detecting local damage in large scale frame structures by utilizing regularization methods for ill-posed problems. A direct relationship between the change in stiffness caused by local damage and the measured modal data for the damaged structure is developed, based on the perturbation method for structural dynamic systems. Thus, the measured incomplete modal data can be directly adopted in damage identification without requiring model reduction techniques, and common regularization methods could be effectively employed to solve the developed equations. Damage indicators are appropriately chosen to reflect both the location and severity of local damage in individual components of frame structures such as in brace members and at beam-column joints. The Truncated Singular Value Decomposition solution incorporating the Generalized Cross Validation method is introduced to evaluate the damage indicators for the cases when realistic errors exist in modal data measurements. Results for a 16-story building model structure show that structural damage can be correctly identified at detailed level using only limited information on the measured noisy modal data for the damaged structure.

Blind Deconvolution for Two-thermocouple Sensor Characterisation

Thermocouples are one of the most popular devices for temperature measurement due to their robustness, ease of manufacture and installation, and low cost. However, when used in the harsh environment found in combustion systems and automotive engine exhausts, large wire diameters are required and consequently the measurement bandwidth is reduced. This paper describes two new algorithmic compensation techniques based on blind deconvolution to address this loss of high-frequency signal components using the measurements from two thermocouples. In particular, a continuous-time approach is proposed, combined with a cross-relation blind deconvolution for parameter estimation. A feature of this approach is that no a priori assumption is made about the time constant ratio of the two thermocouples. The advantages, including small estimation variance and limitations of the method, are highlighted using results from simulation and test rig studies.

A Fast Nonlinear Model Identification Method

The identification of nonlinear dynamic systems using linear-in-the-parameters models is studied. A fast recursive algorithm (FRA) is proposed to select both the model structure and to estimate the model parameters. Unlike orthogonal least squares (OLS) method, FRA solves the least-squares problem recursively over the model order without requiring matrix decomposition. The computational complexity of both algorithms is analyzed, along with their numerical stability. The new method is shown to require much less computational effort and is also numerically more stable than OLS.

A fast method for fuzzy neural modeling and refinement

In the identification of complex dynamic systems using fuzzy neural networks, one of the main issues is the curse of dimensionality, which makes it difficult to retain a large number of system inputs or to consider a large number of fuzzy sets. Moreover, due to the correlations, not all possible network inputs or regression vectors in the network are necessary and adding them simply increases the model complexity and deteriorates the network generalisation performance. In this paper, the problem is solved by first proposing a fast algorithm for selection of network terms, and then introducing a refinement procedure to tackle the correlation issue. Simulation results show the efficacy of the method.

History, an Exit Strategy: The Retrofuture Fabulations of kara lynch

A cartographer constructs a map of an individual creative history, that of the American artist kara lynch, as it emerges in connection to a collective history of African American cultural expression. Positioning history as complex, dynamic systems of interwoven memory networks, the map follows lynch’s traversals through various “zones of cultural haunting”: places where collective memories made invisible through systematic processes of cultural erasure may be recovered and revived. Through these traversals, which are inspired by lynch’s “forever project” Invisible, the map covers such terrains as haunted narratives, mechanisms of abstraction and coding within African American media production, water as an informational technology, the distribution of memory in blood, the dialectics of materiality and immateriality that frame considerations of black subjectivity, and the possibility that place of music might not be the site of sound but instead the social production of memory.

Automated nonlinear system modelling with multiple neural networks

This article discusses the identification of nonlinear dynamic systems using multi-layer perceptrons (MLPs). It focuses on both structure uncertainty and parameter uncertainty, which have been widely explored in the literature of nonlinear system identification. The main contribution is that an integrated analytic framework is proposed for automated neural network structure selection, parameter identification and hysteresis network switching with guaranteed neural identification performance. First, an automated network structure selection procedure is proposed within a fixed time interval for a given network construction criterion. Then, the network parameter updating algorithm is proposed with guaranteed bounded identification error. To cope with structure uncertainty, a hysteresis strategy is proposed to enable neural identifier switching with guaranteed network performance along the switching process. Both theoretic analysis and a simulation example show the efficacy of the proposed method.

Belief change with noisy sensing in the situation calculus

Situation calculus has been applied widely in arti?cial intelligence to model and reason about actions and changes in dynamic systems. Since actions carried out by agents will cause constant changes of the agents’ beliefs, how to manage
these changes is a very important issue. Shapiro et al. [22] is one of the studies that considered this issue. However, in this framework, the problem of noisy sensing, which often presents in real-world applications, is not considered. As a
consequence, noisy sensing actions in this framework will lead to an agent facing inconsistent situation and subsequently the agent cannot proceed further. In this paper, we investigate how noisy sensing actions can be handled in iterated
belief change within the situation calculus formalism. We extend the framework proposed in [22] with the capability of managing noisy sensings. We demonstrate that an agent can still detect the actual situation when the ratio of noisy sensing actions vs. accurate sensing actions is limited. We prove that our framework subsumes the iterated belief change strategy in [22] when all sensing actions are accurate. Furthermore, we prove that our framework can adequately handle belief introspection, mistaken beliefs, belief revision and belief update even with noisy sensing, as done in [22] with accurate sensing actions only.

Forward and backward least angle regression for nonlinear system identification

A forward and backward least angle regression (LAR) algorithm is proposed to construct the nonlinear autoregressive model with exogenous inputs (NARX) that is widely used to describe a large class of nonlinear dynamic systems. The main objective of this paper is to improve model sparsity and generalization performance of the original forward LAR algorithm. This is achieved by introducing a replacement scheme using an additional backward LAR stage. The backward stage replaces insignificant model terms selected by forward LAR with more significant ones, leading to an improved model in terms of the model compactness and performance. A numerical example to construct four types of NARX models, namely polynomials, radial basis function (RBF) networks, neuro fuzzy and wavelet networks, is presented to illustrate the effectiveness of the proposed technique in comparison with some popular methods.

Novos saberes básicos dos alunos, novas competências dos professores : um estudo no âmbito da supervisão da formação de professores do 1º ciclo do ensino básico na Universidade de Aveiro

As mudanças sociais que, na actualidade, pressionam e desafiam a Escola, nomeadamente quanto aos papéis, funções e desempenho dos professores, implicam a necessidade de repensar a sua formação para que possam responder mais adequadamente aos desafios emergentes. Estes têm particularmente a ver com os novos saberes que essas condições exigem a todos os cidadãos e que são entendidos, do ponto de vista epistemológico, como saberes para agir responsavelmente. Assim, o principal objectivo deste estudo consiste em aprofundar o conhecimento acerca das ambiências e culturas de formação inicial de professores do 1. º Ciclo do Ensino Básico na Universidade de Aveiro, nomeadamente dos processos de supervisão ao nível da disciplina de Prática Pedagógica, tendo em consideração que as características de monodocência dos profissionais deste ciclo de ensino pressupõem um perfil de competência específico. A investigação, de natureza qualitativa, desenvolveu-se de acordo com as abordagens próprias da complexidade e da sistémica, das quais relevamos os princípios da totalidade em que os fenómenos são percebidos como sistemas globais e dinâmicos e da recursividade ao admitirmos a possibilidade de uma relação dialéctica entre os diversos subsistemas considerados. Do ponto de vista metodológico, no sentido de construir uma visão integrada do objecto em estudo, foi utilizado um conjunto de procedimentos específicos (mixed-methods), nomeadamente análise documental, inquirição por questionário e por entrevista semi-estruturada. O questionário foi aplicado à totalidade de licenciados em Ensino do 1.º Ciclo do Ensino Básico pela Universidade de Aveiro, compreendendo o período de 1998 até 2005. A entrevista foi realizada junto de supervisores (cooperantes e institucionais) que vêm acompanhando os núcleos de Prática Pedagógica, no decurso e ao longo do 4.º ano da referida Licenciatura. Quanto aos resultados do estudo, estes podem ser lidos em função de três eixos. Relativamente ao primeiro, que genericamente se refere à evolução dos saberes básicos dos alunos, os contributos parecem sugerir a necessidade de alicerçar os processos de ensino/aprendizagem não apenas nas literacias ler, escrever e contar, como também no desenvolvimento de saberes básicos de natureza geral e transversal, percebidos como competências, tais como aprender a pensar, aprender a aprender, aprender a comunicar e a resolver problemas, numa perspectiva de aprender a ser. O segundo eixo de leitura tem a ver com as competências requeridas aos professores para o desenvolvimento desses saberes estruturantes. De acordo com os dados recolhidos na fase extensiva do estudo, estes parecem coerentes com a revisão de literatura realizada, bem como com os normativos legais que, em Portugal, enquadram o perfil de desempenho dos professores do 1.º Ciclo. Porém, sugerem a necessidade de interligar as dimensões saber, saber-fazer e saber ser, com ênfase nesta última. À semelhança dos resultados referidos no ponto anterior, também o referencial de competências proposto para os professores integra as dimensões saber, saber fazer e saber ser, no qual são valorizadas as competências de reflexão crítica, de aprender a aprender e, de igual forma, o conhecimento profissional nas suas múltiplas dimensões. O terceiro eixo relaciona-se com a qualidade das ambiências e culturas de formação e supervisão. De forma geral, os dados apontam que ambientes que possibilitem uma dimensão de prática curricular alargada em contextos diversificados, que valorizem os princípios da pessoalidade e respeito pelo Outro e que estimulem a reflexão crítica, a auto-implicação dos formandos, o desenvolvimento de competências pessoais e de desenvolvimento profissional (destacando-se as competências para aprender a aprender, a comunicar, a investigar e reflectir), parecem adequar se melhor ao desenvolvimento pessoal e profissional destes professores, no contexto das sociedades contemporâneas. Assim, é possível verificar que os eixos considerados remetem para um conjunto recursivo de saberes e competências que, em diferentes níveis, implicam um compromisso com a acção, numa visão de mundo comprometida com as ideias de bem comum, ou seja, de cidadania universal.

Controlo preditivo distribuído em edifícios para conforto térmico e alocação de cargas

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial

Controlo preditivo distribuído para conforto térmico em edifícios

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial

A Fractional Perspective to the Bond Graph Modelling of World Economies

Inspired in dynamic systems theory and Brewer’s contributions to apply it to economics, this paper establishes a bond graph model. Two main variables, a set of inter-connectivities based on nodes and links (bonds) and a fractional order dynamical perspective, prove to be a good macro-economic representation of countries’ potential performance in nowadays globalization. The estimations based on time series for 50 countries throughout the last 50 decades confirm the accuracy of the model and the importance of scale for economic performance.