Síndrome de Kelly

Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Medicina Dentária

Estudo da prevalência das alterações biológicas e mecânicas associadas à reabilitação com prótese parcial removível nas clínicas pedagógicas de Medicina Dentária da FCS-UFP

Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Medicina Dentária

On Clustering Images Using Compression

The need for the ability to cluster unknown data to better understand its relationship to know data is prevalent throughout science. Besides a better understanding of the data itself or learning about a new unknown object, cluster analysis can help with processing data, data standardization, and outlier detection. Most clustering algorithms are based on known features or expectations, such as the popular partition based, hierarchical, density-based, grid based, and model based algorithms. The choice of algorithm depends on many factors, including the type of data and the reason for clustering, nearly all rely on some known properties of the data being analyzed. Recently, Li et al. proposed a new universal similarity metric, this metric needs no prior knowledge about the object. Their similarity metric is based on the Kolmogorov Complexity of objects, the objects minimal description. While the Kolmogorov Complexity of an object is not computable, in "Clustering by Compression," Cilibrasi and Vitanyi use common compression algorithms to approximate the universal similarity metric and cluster objects with high success. Unfortunately, clustering using compression does not trivially extend to higher dimensions. Here we outline a method to adapt their procedure to images. We test these techniques on images of letters of the alphabet.

Generalized Methods for Discovering Frequent Poly-Regions in DNA

The problem of discovering frequent poly-regions (i.e. regions of high occurrence of a set of items or patterns of a given alphabet) in a sequence is studied, and three efficient approaches are proposed to solve it. The first one is entropy-based and applies a recursive segmentation technique that produces a set of candidate segments which may potentially lead to a poly-region. The key idea of the second approach is the use of a set of sliding windows over the sequence. Each sliding window covers a sequence segment and keeps a set of statistics that mainly include the number of occurrences of each item or pattern in that segment. Combining these statistics efficiently yields the complete set of poly-regions in the given sequence. The third approach applies a technique based on the majority vote, achieving linear running time with a minimal number of false negatives. After identifying the poly-regions, the sequence is converted to a sequence of labeled intervals (each one corresponding to a poly-region). An efficient algorithm for mining frequent arrangements of intervals is applied to the converted sequence to discover frequently occurring arrangements of poly-regions in different parts of DNA, including coding regions. The proposed algorithms are tested on various DNA sequences producing results of significant biological meaning.

Discovering Frequent Poly-Regions in DNA Sequences

The problem of discovering frequent arrangements of regions of high occurrence of one or more items of a given alphabet in a sequence is studied, and two efficient approaches are proposed to solve it. The first approach is entropy-based and uses an existing recursive segmentation technique to split the input sequence into a set of homogeneous segments. The key idea of the second approach is to use a set of sliding windows over the sequence. Each sliding window keeps a set of statistics of a sequence segment that mainly includes the number of occurrences of each item in that segment. Combining these statistics efficiently yields the complete set of regions of high occurrence of the items of the given alphabet. After identifying these regions, the sequence is converted to a sequence of labeled intervals (each one corresponding to a region). An efficient algorithm for mining frequent arrangements of temporal intervals on a single sequence is applied on the converted sequence to discover frequently occurring arrangements of these regions. The proposed algorithms are tested on various DNA sequences producing results with significant biological meaning.

A Neural Network Model of Speech Acquisition and Motor Equivalent Speech Production

This article describes a neural network model that addresses the acquisition of speaking skills by infants and subsequent motor equivalent production of speech sounds. The model learns two mappings during a babbling phase. A phonetic-to-orosensory mapping specifies a vocal tract target for each speech sound; these targets take the form of convex regions in orosensory coordinates defining the shape of the vocal tract. The babbling process wherein these convex region targets are formed explains how an infant can learn phoneme-specific and language-specific limits on acceptable variability of articulator movements. The model also learns an orosensory-to-articulatory mapping wherein cells coding desired movement directions in orosensory space learn articulator movements that achieve these orosensory movement directions. The resulting mapping provides a natural explanation for the formation of coordinative structures. This mapping also makes efficient use of redundancy in the articulator system, thereby providing the model with motor equivalent capabilities. Simulations verify the model's ability to compensate for constraints or perturbations applied to the articulators automatically and without new learning and to explain contextual variability seen in human speech production.

Questions of 'h' in Northern Ireland: Breathing New Life on the Aspiration Theory

This paper considers existing ideas concerning pronunciation of the letter name for (LNH) in Northern Irish English (NIE). Traditionally, the status of LNH realisation as an ethnic marker has gone unquestioned: Catholics are thought to say [het&Mac186;] while the Protestant norm is assumed to be [etS]. The phonetic difference between these realisations is consistently described as word-initial aspiration versus non-aspiration, with aspiration attributed exclusively to Irish language influence. Here, we show that an explanation based on aspiration alone is phonologically unsatisfying and question whether aspiration is, in fact, an Irish language or ethnically dictated phenomenon. It is further suggested here that the overwhelming stigmatisation of LNH realisation may be responsible for blocking a potential sound change in NIE. While this paper is not intended as a detailed account of ethnolinguistic differences in NI phonology, it engages critically with the over-simplistic and widespread notion that LNH realisation is a result of transfer from the Irish language to the English used by Catholics in Northern Ireland.

Annotating an Oral Corpus using the Text Encoding Initiative. Methodology, Problems, Solutions

The objective of this paper is to describe and evaluate the application of the Text Encoding Initiative (TEI) Guidelines to a corpus of oral French, this being the first corpus of oral French where the TEI has been used. The paper explains the purpose of the corpus, both in creating a specialist corpus of néo-contage that will broaden the range of oral corpora available, and, more importantly, in creating a dataset to explore a variety of oral French that has a particularly interesting status in terms of factors such as conception orale/écrite, réalisation médiale and comportement communicatif (Koch and Oesterreicher 2001). The linguistic phenomena to be encoded are both stylistic (speech and thought presentation) and syntactic (negation, detachment, inversion), and all represent areas where previous research has highlighted the significance of factors such as medium, register and discourse type, as well as a host of linguistic factors (syntactic, phonetic, lexical). After a discussion of how a tagset can be designed and applied within the TEI to encode speech and thought presentation, negation, detachment and inversion, the final section of the paper evaluates the benefits and possible drawbacks of the methodology offered by the TEI when applied to a syntactic and stylistic markup of an oral corpus.

Rise time and formant transition duration in the discrimination of speech sounds: The Ba–Wa distinction in developmental dyslexia

Across languages, children with developmental dyslexia have a specific difficulty with the neural representation of the sound structure (phonological structure) of speech. One likely cause of their difficulties with phonology is a perceptual difficulty in auditory temporal processing (Tallal, 1980). Tallal (1980) proposed that basic auditory processing of brief, rapidly successive acoustic changes is compromised in dyslexia, thereby affecting phonetic discrimination (e.g. discriminating /b/ from /d/) via impaired discrimination of formant transitions (rapid acoustic changes in frequency and intensity). However, an alternative auditory temporal hypothesis is that the basic auditory processing of the slower amplitude modulation cues in speech is compromised (Goswami , 2002). Here, we contrast children's perception of a synthetic speech contrast (ba/wa) when it is based on the speed of the rate of change of frequency information (formant transition duration) versus the speed of the rate of change of amplitude modulation (rise time). We show that children with dyslexia have excellent phonetic discrimination based on formant transition duration, but poor phonetic discrimination based on envelope cues. The results explain why phonetic discrimination may be allophonic in developmental dyslexia (Serniclaes , 2004), and suggest new avenues for the remediation of developmental dyslexia. © 2010 Blackwell Publishing Ltd.