Global ETD Search

201	Probabilistic Sequence Models with Speech and Language Applications Henter, Gustav Eje January 2013 (has links) Series data, sequences of measured values, are ubiquitous. Whenever observations are made along a path in space or time, a data sequence results. To comprehend nature and shape it to our will, or to make informed decisions based on what we know, we need methods to make sense of such data. Of particular interest are probabilistic descriptions, which enable us to represent uncertainty and random variation inherent to the world around us. This thesis presents and expands upon some tools for creating probabilistic models of sequences, with an eye towards applications involving speech and language. Modelling speech and language is not only of use for creating listening, reading, talking, and writing machines---for instance allowing human-friendly interfaces to future computational intelligences and smart devices of today---but probabilistic models may also ultimately tell us something about ourselves and the world we occupy. The central theme of the thesis is the creation of new or improved models more appropriate for our intended applications, by weakening limiting and questionable assumptions made by standard modelling techniques. One contribution of this thesis examines causal-state splitting reconstruction (CSSR), an algorithm for learning discrete-valued sequence models whose states are minimal sufficient statistics for prediction. Unlike many traditional techniques, CSSR does not require the number of process states to be specified a priori, but builds a pattern vocabulary from data alone, making it applicable for language acquisition and the identification of stochastic grammars. A paper in the thesis shows that CSSR handles noise and errors expected in natural data poorly, but that the learner can be extended in a simple manner to yield more robust and stable results also in the presence of corruptions. Even when the complexities of language are put aside, challenges remain. The seemingly simple task of accurately describing human speech signals, so that natural synthetic speech can be generated, has proved difficult, as humans are highly attuned to what speech should sound like. Two papers in the thesis therefore study nonparametric techniques suitable for improved acoustic modelling of speech for synthesis applications. Each of the two papers targets a known-incorrect assumption of established methods, based on the hypothesis that nonparametric techniques can better represent and recreate essential characteristics of natural speech. In the first paper of the pair, Gaussian process dynamical models (GPDMs), nonlinear, continuous state-space dynamical models based on Gaussian processes, are shown to better replicate voiced speech, without traditional dynamical features or assumptions that cepstral parameters follow linear autoregressive processes. Additional dimensions of the state-space are able to represent other salient signal aspects such as prosodic variation. The second paper, meanwhile, introduces KDE-HMMs, asymptotically-consistent Markov models for continuous-valued data based on kernel density estimation, that additionally have been extended with a fixed-cardinality discrete hidden state. This construction is shown to provide improved probabilistic descriptions of nonlinear time series, compared to reference models from different paradigms. The hidden state can be used to control process output, making KDE-HMMs compelling as a probabilistic alternative to hybrid speech-synthesis approaches. A final paper of the thesis discusses how models can be improved even when one is restricted to a fundamentally imperfect model class. Minimum entropy rate simplification (MERS), an information-theoretic scheme for postprocessing models for generative applications involving both speech and text, is introduced. MERS reduces the entropy rate of a model while remaining as close as possible to the starting model. This is shown to produce simplified models that concentrate on the most common and characteristic behaviours, and provides a continuum of simplifications between the original model and zero-entropy, completely predictable output. As the tails of fitted distributions may be inflated by noise or empirical variability that a model has failed to capture, MERS's ability to concentrate on high-probability output is also demonstrated to be useful for denoising models trained on disturbed data. / <p>QC 20131128</p> / ACORNS: Acquisition of Communication and Recognition Skills / LISTA – The Listening Talker Time series acoustic modelling speech synthesis stochastic processes causal-state splitting reconstruction robust causal states pattern discovery Markov models HMMs nonparametric models Gaussian processes Gaussian process dynamical models nonlinear Kalman filters information theory minimum entropy rate simplification kernel density estimation time-series bootstrap
202	An investigation into the solving of polynomial equations and the implications for secondary school mathematics Maharaj, Aneshkumar 06 1900 (has links) This study investigates the possibilities and implications for the teaching of the solving of polynomial equations. It is historically directed and also focusses on the working procedures in algebra which target the cognitive and affective domains. The teaching implications of the development of representational styles of equations and their solving procedures are noted. Since concepts in algebra can be conceived as processes or objects this leads to cognitive obstacles, for example: a limited view of the equal sign, which result in learning and reasoning problems. The roles of sense-making, visual imagery, mental schemata and networks in promoting meaningful understanding are scrutinised. Questions and problems to solve are formulated to promote the processes associated with the solving of polynomial equations, and the solving procedures used by a group of college students are analysed. A teaching model/method, which targets the cognitive and affective domains, is presented. / Mathematics Education / M.A. (Mathematics Education) Solving of polynomial equations Historical perspective Subject didactical perspective Understanding in mathematics Procedural and structural thinking Mental schemata Approaches/methods of teaching Procedures in algebra Secondary school mathematics Factorisation and simplification Mathematics education 512.9420712 Polynomials Quintic equations Fundamental theorem of algebra Finite fields (Algebra) Factorization (Mathematics)
203	Towards Next Generation Sequential and Parallel SAT Solvers Manthey, Norbert 01 December 2014 (has links) This thesis focuses on improving the SAT solving technology. The improvements focus on two major subjects: sequential SAT solving and parallel SAT solving. To better understand sequential SAT algorithms, the abstract reduction system Generic CDCL is introduced. With Generic CDCL, the soundness of solving techniques can be modeled. Next, the conflict driven clause learning algorithm is extended with the three techniques local look-ahead, local probing and all UIP learning that allow more global reasoning during search. These techniques improve the performance of the sequential SAT solver Riss. Then, the formula simplification techniques bounded variable addition, covered literal elimination and an advanced cardinality constraint extraction are introduced. By using these techniques, the reasoning of the overall SAT solving tool chain becomes stronger than plain resolution. When using these three techniques in the formula simplification tool Coprocessor before using Riss to solve a formula, the performance can be improved further. Due to the increasing number of cores in CPUs, the scalable parallel SAT solving approach iterative partitioning has been implemented in Pcasso for the multi-core architecture. Related work on parallel SAT solving has been studied to extract main ideas that can improve Pcasso. Besides parallel formula simplification with bounded variable elimination, the major extension is the extended clause sharing level based clause tagging, which builds the basis for conflict driven node killing. The latter allows to better identify unsatisfiable search space partitions. Another improvement is to combine scattering and look-ahead as a superior search space partitioning function. In combination with Coprocessor, the introduced extensions increase the performance of the parallel solver Pcasso. The implemented system turns out to be scalable for the multi-core architecture. Hence iterative partitioning is interesting for future parallel SAT solvers. The implemented solvers participated in international SAT competitions. In 2013 and 2014 Pcasso showed a good performance. Riss in combination with Copro- cessor won several first, second and third prices, including two Kurt-Gödel-Medals. Hence, the introduced algorithms improved modern SAT solving technology. info:eu-repo/classification/ddc/004 ddc:004
204	Operators for Multi-Resolution Morse and Cell Complexes / Оператори за мулти-резолуционе комплексе Морза и ћелијске комплексе / Operatori za multi-rezolucione komplekse Morza i ćelijske komplekse Čomić Lidija 03 March 2014 (has links) <p>The topic of the thesis is analysis of the topological structure of scalar fields and<br />shapes represented through Morse and cell complexes, respectively. This is<br />achieved by defining simplification and refinement operators on these<br />complexes. It is shown that the defined operators form a basis for the set of<br />operators that modify Morse and cell complexes. Based on the defined<br />operators, a multi-resolution model for Morse and cell complexes is constructed,<br />which contains a large number of representations at uniform and variable<br />resolution.</p> / <p>Тема дисертације је анализа тополошке структуре скаларних поља и<br />облика представљених у облику комплекса Морза и ћелијских комплекса,<br />редом. То се постиже дефинисањем оператора за симплификацију и<br />рафинацију тих комплекса. Показано је да дефинисани оператори чине<br />базу за скуп оператора на комплексима Морза и ћелијским комплексима.<br />На основу дефинисаних оператора конструисан је мулти-резолуциони<br />модел за комплексе Морза и ћелијске комплексе, који садржи велики број<br />репрезентација униформне и варијабилне резолуције.</p> / <p>Tema disertacije je analiza topološke strukture skalarnih polja i<br />oblika predstavljenih u obliku kompleksa Morza i ćelijskih kompleksa,<br />redom. To se postiže definisanjem operatora za simplifikaciju i<br />rafinaciju tih kompleksa. Pokazano je da definisani operatori čine<br />bazu za skup operatora na kompleksima Morza i ćelijskim kompleksima.<br />Na osnovu definisanih operatora konstruisan je multi-rezolucioni<br />model za komplekse Morza i ćelijske komplekse, koji sadrži veliki broj<br />reprezentacija uniformne i varijabilne rezolucije.</p>
205	Structural Similarity: Applications to Object Recognition and Clustering Curado, Manuel 03 September 2018 (has links) In this thesis, we propose many developments in the context of Structural Similarity. We address both node (local) similarity and graph (global) similarity. Concerning node similarity, we focus on improving the diffusive process leading to compute this similarity (e.g. Commute Times) by means of modifying or rewiring the structure of the graph (Graph Densification), although some advances in Laplacian-based ranking are also included in this document. Graph Densification is a particular case of what we call graph rewiring, i.e. a novel field (similar to image processing) where input graphs are rewired to be better conditioned for the subsequent pattern recognition tasks (e.g. clustering). In the thesis, we contribute with an scalable an effective method driven by Dirichlet processes. We propose both a completely unsupervised and a semi-supervised approach for Dirichlet densification. We also contribute with new random walkers (Return Random Walks) that are useful structural filters as well as asymmetry detectors in directed brain networks used to make early predictions of Alzheimer's disease (AD). Graph similarity is addressed by means of designing structural information channels as a means of measuring the Mutual Information between graphs. To this end, we first embed the graphs by means of Commute Times. Commute times embeddings have good properties for Delaunay triangulations (the typical representation for Graph Matching in computer vision). This means that these embeddings can act as encoders in the channel as well as decoders (since they are invertible). Consequently, structural noise can be modelled by the deformation introduced in one of the manifolds to fit the other one. This methodology leads to a very high discriminative similarity measure, since the Mutual Information is measured on the manifolds (vectorial domain) through copulas and bypass entropy estimators. This is consistent with the methodology of decoupling the measurement of graph similarity in two steps: a) linearizing the Quadratic Assignment Problem (QAP) by means of the embedding trick, and b) measuring similarity in vector spaces. The QAP problem is also investigated in this thesis. More precisely, we analyze the behaviour of $m$-best Graph Matching methods. These methods usually start by a couple of best solutions and then expand locally the search space by excluding previous clamped variables. The next variable to clamp is usually selected randomly, but we show that this reduces the performance when structural noise arises (outliers). Alternatively, we propose several heuristics for spanning the search space and evaluate all of them, showing that they are usually better than random selection. These heuristics are particularly interesting because they exploit the structure of the affinity matrix. Efficiency is improved as well. Concerning the application domains explored in this thesis we focus on object recognition (graph similarity), clustering (rewiring), compression/decompression of graphs (links with Extremal Graph Theory), 3D shape simplification (sparsification) and early prediction of AD. / Ministerio de Economía, Industria y Competitividad (Referencia TIN2012-32839 BES-2013-064482) Graph densification Cut similarity Spectral clustering Dirichlet problems Random walkers Commute Times Graph algorithms Regular Partition Szemeredi Alzheimer's disease Graphs Return Random Walk Net4lap Directed graphs Spectral graph theory Graph entropy Mutual information Manifold alignment m-Best Graph Matching Binary-Tree Partitions QAP Graph sparsification Shape simplification Alpha shapes
206	Birds, bats and arthropods in tropical agroforestry landscapes: Functional diversity, multitrophic interactions and crop yield Maas, Bea 20 November 2013 (has links) No description available. 630 birds bats arthropods multitrophic interactions agroforestry tropical landscape forest margin landscape functional diversity crop yield exclosure experiments experimental exclusion arthropod suppression avian predation ecosystem services mist netting point counts artificial plasticine caterpillar dummy experiment biological control monitoring mapping Lemon-bellied White-eye Grosbeak Starling Zosterops chloris Scissiostrum dubium Theobroma cacao cacao agroforestry cacao diseases cacao harvest cacao pests flying vertebrates aerial insectivores volant vertebrates logging breeding colony flower herbivory mesopredator release predatory insects ants spiders aphids Lepidoptera Coleoptera Lepidopteran larvae sustainable agriculture sustainable agroforestry management implications management recommendations applied managament extensive land use management landscape management conservation biodiversity-friendly dbh distance to forest forest proximity habitat conversion herbivory Indonesia insectivorous bats insectivorous birds invertebrates Central Sulawesi Napu valley leaf gleaning leaf herbivory pests insects phytophagous insects plant productivity remnant forest trees shade tree managament South-east Asia Paleotropics tropical landscape tree height landscape gradient local shade management Cacao Pod Borer Cherelle Wilt fruit abortion Helopeltis sulawesi deforestation habitat fragmentation land use intensification forest margin species critical decline predation experiment species-specific functions Southeast Asia biodiversity conservation mesopredators food security human welfare human well-being poverty alleviation poverty reduction smallholder cacao smallholder plantation cacao farmers sustainable cacao management landscape perspective landscape scale large scale field experiment long term field experiment human wellbeing economic importance economic value valuation ecosystem services landscape matrix yield quality yield quantity fruit productivity species identity species diversity species richness ecosystem functioning pesticide use chemical compounds complex food web tritrophic interactions wildlife-friendly rural livelihoods endangered bird species endangered bat species endemic endemic birds endemic bats beneficial impact IUCN Lore Lindu National Park bioindicator indicator species forest margin agricultural habitat agroforestry systems population density predation activity species activity cacao flower cacao pod Orthoptera linear mixed effect models Tukey Post Hoc Test AICc model selection generalized least squares restricted maximum likelihood model simplification species richness estimator species accumulation linear mixed-effects models Likelihood Ratio Test Maximum Likelihood nocturnal insects diurnal arthropods nocturnal arthropods diurnal insects landscape context Land- und Forstwirtschaft (PPN621302791)

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