906 resultados para Phonemic Segmentation


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Phonological processing skills have often been assumed to play a minimal role in skilled adult spelling despite evidence showing their importance in the development of spelling skills. The present study investigated the relationship between phonological awareness and spelling in adults. It was hypothesised that subjects demonstrating higher levels of spelling proficiency would also show superior phonological processing skills. This relationship was expected to be mediated by sound-spelling mapping knowledge. Given the irregularities of sound-spelling correspondences in English, it was also predicted that knowledge of orthographic conventions would be related to spelling competency. Two measures of each component skill were used on seventy three university students. As predicted, the importance of spelling-sound mapping skills in spelling were demonstrated, as was a relationship between phonological awareness and spelling-sound correspondences. In addition a moderate correlation was found between orthographic tasks and spelling performance. It was concluded that, among university students at least, phonological ability makes an important contribution to skilled adult spelling.

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The present study evaluated the benefits of phonological processing skills training for children with persistent reading difficulties. Children aged between 9-14 years, identified as having a specific reading disability, participated in the study. In a series of three experiments, pedagogical issues related to length of training time, model of intervention and severity of readers' phonological processing skills deficit prior to intervention, were explored. The results indicated that improvement in poor readers' phonological processing skills led to a dramatic improvement in their reading accuracy and reading comprehension performance. Increasing the length of training time significantly improved transfer effects to the reading process. Children with particularly severe phonological processing skill deficits benefited from art extended training period, and both individual and group intervention models for phonological processing training proved successful. Implications for speech and language therapists are discussed.

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Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ciências da Educação Especialidade Intervenção Precoce

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Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de Mestre em Ciências da Educação - Especialização em Educação Especial

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This study investigated the effects of an explicit individualized phonemic awareness intervention administered by a speech-language pathologist to 4 prekindergarten children with phonological speech sound disorders. Research has demonstrated that children with moderate-severe expressive phonological disorders are at-risk for poor literacy development because they often concurrently exhibit weaknesses in the development of phonological awareness skills (Rvachew, Ohberg, Grawburg, & Heyding, 2003).^ The research design chosen for this study was a single subject multiple probe design across subjects. After stable baseline measures, the participants received explicit instruction in each of the three phases separately and sequentially. Dependent measures included same-day tests for Phase I (Phoneme Identity), Phase II (Phoneme Blending), and Phase III (Phoneme Segmentation), and generalization and maintenance tests for all three phases.^ All 4 participants made substantial progress in all three phases. These skills were maintained during weekly and biweekly maintenance measures. Generalization measures indicated that the participants demonstrated some increases in their mean total number of correct responses in Phase II and Phase III baseline while the participants were in Phase I intervention, and more substantial increases in Phase III baseline while the participants were in Phase II intervention. Increased generalization from Phases II to III could likely be explained due to the response similarities in those two skills (Cooper, Heron, & Heward, 2007).^ Based upon the findings of this study, speech-language pathologists should evaluate phonological awareness in the children in their caseloads prior to kindergarten entry, and should allocate time during speech therapy to enhance phonological awareness and letter knowledge to support the development of both skills concurrently. Also, classroom teachers should collaborate with speech-language pathologists to identify at-risk students in their classrooms and successfully implement evidence-based phonemic awareness instruction. Future research should repeat this study including larger groups of children, children with combined speech and language delays, children of different ages, and ESOL students.^

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This study investigated the effects of an explicit individualized phonemic awareness intervention administered by a speech-language pathologist to 4 prekindergarten children with phonological speech sound disorders. Research has demonstrated that children with moderate-severe expressive phonological disorders are at-risk for poor literacy development because they often concurrently exhibit weaknesses in the development of phonological awareness skills (Rvachew, Ohberg, Grawburg, & Heyding, 2003). The research design chosen for this study was a single subject multiple probe design across subjects. After stable baseline measures, the participants received explicit instruction in each of the three phases separately and sequentially. Dependent measures included same-day tests for Phase I (Phoneme Identity), Phase II (Phoneme Blending), and Phase III (Phoneme Segmentation), and generalization and maintenance tests for all three phases. All 4 participants made substantial progress in all three phases. These skills were maintained during weekly and biweekly maintenance measures. Generalization measures indicated that the participants demonstrated some increases in their mean total number of correct responses in Phase II and Phase III baseline while the participants were in Phase I intervention, and more substantial increases in Phase III baseline while the participants were in Phase II intervention. Increased generalization from Phases II to III could likely be explained due to the response similarities in those two skills (Cooper, Heron, & Heward, 2007). Based upon the findings of this study, speech-language pathologists should evaluate phonological awareness in the children in their caseloads prior to kindergarten entry, and should allocate time during speech therapy to enhance phonological awareness and letter knowledge to support the development of both skills concurrently. Also, classroom teachers should collaborate with speech-language pathologists to identify at-risk students in their classrooms and successfully implement evidence-based phonemic awareness instruction. Future research should repeat this study including larger groups of children, children with combined speech and language delays, children of different ages, and ESOL students

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AIM: To evaluate the effects of meal size and three segmentations on intragastric distribution of the meal and gastric motility, by scintigraphy. METHODS: Twelve healthy volunteers were randomly assessed, twice, by scintigraphy. The test meal consisted of 60 or 180 mL of yogurt labeled with 64 MBq (99m)Tc-tin colloid. Anterior and posterior dynamic frames were simultaneously acquired for 18 min and all data were analyzed in MatLab. Three proximal-distal segmentations using regions of interest were adopted for both meals. RESULTS: Intragastric distribution of the meal between the proximal and distal compartments was strongly influenced by the way in which the stomach was divided, showing greater proximal retention after the 180 mL. An important finding was that both dominant frequencies (1 and 3 cpm) were simultaneously recorded in the proximal and distal stomach; however, the power ratio of those dominant frequencies varied in agreement with the segmentation adopted and was independent of the meal size. CONCLUSION: It was possible to simultaneously evaluate the static intragastric distribution and phasic contractility from the same recording using our scintigraphic approach. (C) 2010 Baishideng. All rights reserved.

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Positional information in developing embryos is specified by spatial gradients of transcriptional regulators. One of the classic systems for studying this is the activation of the hunchback (hb) gene in early fruit fly (Drosophila) segmentation by the maternally-derived gradient of the Bicoid (Bcd) protein. Gene regulation is subject to intrinsic noise which can produce variable expression. This variability must be constrained in the highly reproducible and coordinated events of development. We identify means by which noise is controlled during gene expression by characterizing the dependence of hb mRNA and protein output noise on hb promoter structure and transcriptional dynamics. We use a stochastic model of the hb promoter in which the number and strength of Bcd and Hb (self-regulatory) binding sites can be varied. Model parameters are fit to data from WT embryos, the self-regulation mutant hb(14F), and lacZ reporter constructs using different portions of the hb promoter. We have corroborated model noise predictions experimentally. The results indicate that WT (self-regulatory) Hb output noise is predominantly dependent on the transcription and translation dynamics of its own expression, rather than on Bcd fluctuations. The constructs and mutant, which lack self-regulation, indicate that the multiple Bcd binding sites in the hb promoter (and their strengths) also play a role in buffering noise. The model is robust to the variation in Bcd binding site number across a number of fly species. This study identifies particular ways in which promoter structure and regulatory dynamics reduce hb output noise. Insofar as many of these are common features of genes (e. g. multiple regulatory sites, cooperativity, self-feedback), the current results contribute to the general understanding of the reproducibility and determinacy of spatial patterning in early development.

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Today several different unsupervised classification algorithms are commonly used to cluster similar patterns in a data set based only on its statistical properties. Specially in image data applications, self-organizing methods for unsupervised classification have been successfully applied for clustering pixels or group of pixels in order to perform segmentation tasks. The first important contribution of this paper refers to the development of a self-organizing method for data classification, named Enhanced Independent Component Analysis Mixture Model (EICAMM), which was built by proposing some modifications in the Independent Component Analysis Mixture Model (ICAMM). Such improvements were proposed by considering some of the model limitations as well as by analyzing how it should be improved in order to become more efficient. Moreover, a pre-processing methodology was also proposed, which is based on combining the Sparse Code Shrinkage (SCS) for image denoising and the Sobel edge detector. In the experiments of this work, the EICAMM and other self-organizing models were applied for segmenting images in their original and pre-processed versions. A comparative analysis showed satisfactory and competitive image segmentation results obtained by the proposals presented herein. (C) 2008 Published by Elsevier B.V.

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Intravascular ultrasound (IVUS) image segmentation can provide more detailed vessel and plaque information, resulting in better diagnostics, evaluation and therapy planning. A novel automatic segmentation proposal is described herein; the method relies on a binary morphological object reconstruction to segment the coronary wall in IVUS images. First, a preprocessing followed by a feature extraction block are performed, allowing for the desired information to be extracted. Afterward, binary versions of the desired objects are reconstructed, and their contours are extracted to segment the image. The effectiveness is demonstrated by segmenting 1300 images, in which the outcomes had a strong correlation to their corresponding gold standard. Moreover, the results were also corroborated statistically by having as high as 92.72% and 91.9% of true positive area fraction for the lumen and media adventitia border, respectively. In addition, this approach can be adapted easily and applied to other related modalities, such as intravascular optical coherence tomography and intravascular magnetic resonance imaging. (E-mail: matheuscardosomg@hotmail.com) (C) 2011 World Federation for Ultrasound in Medicine & Biology.

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The task of segmenting cell nuclei from cytoplasm in conventional Papanicolaou (Pap) stained cervical cell images is a classical image analysis problem which may prove to be crucial to the development of successful systems which automate the analysis of Pap smears for detection of cancer of the cervix. Although simple thresholding techniques will extract the nucleus in some cases, accurate unsupervised segmentation of very large image databases is elusive. Conventional active contour models as introduced by Kass, Witkin and Terzopoulos (1988) offer a number of advantages in this application, but suffer from the well-known drawbacks of initialisation and minimisation. Here we show that a Viterbi search-based dual active contour algorithm is able to overcome many of these problems and achieve over 99% accurate segmentation on a database of 20 130 Pap stained cell images. (C) 1998 Elsevier Science B.V. All rights reserved.

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An important segmentation basis used by firms is related to consumers` personal values which are investigated in this study. It was used a descriptive research with the survey method of data collection in a sample of executives from Sao Paulo who are considered to be potential buyers of high value and innovative goods. An exploratory factor analysis was employed in order to reduce the values scale used and a cluster analysis was performed to identify the groups of executives according to the importance attached to different person values. Concluding, it was observed that there was a similarity among the three personal values dimensions, named as Civility (concerns about having a good conduct before society according to social rules of interaction), Self-Direction (intellectual aspects and practical orientation in their conducts) and Conformity (restriction of actions, inclinations and impulses, that are likely to harm others and would violate expectations) and the ones reported in the theory Rokeach`s theory about instrumental personal values. Furthermore, three groups of executives were identified (good conduct group, low restriction group and high restriction group). The differences observed in the importance of personal values here presented by the dimensions called Civility, Self-Direction and Conformity can lead to different buying behaviors and product preferences. From the results found in this study the companies could adapt their current and new products offers, as well as their communication in order to better serve these segments of executives from Sao Paulo.

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Targeting is increasingly used to manage people. It operates by segmenting populations and providing different levels of opportunities and services to these groups. Each group is subject to different levels of surveillance and scrutiny. This article examines the deployment of targeting in Australian social security. Three case studies of targeting are presented in Australia's management of benefit overpayment and fraud, the distribution of employment services and the application of workfare. In conceptualizing surveillance as governance, the analysis examines the rationalities, technologies and practices that make targeting thinkable, practicable and achievable. In the case studies, targeting is variously conceptualized and justified by calculative risk discourses, moral discourses of obligation and notions of welfare dependency Advanced information technologies are also seen as particularly important in giving rise to the capacity to think about and act on population segments.

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Objective: The aim of this article is to propose an integrated framework for extracting and describing patterns of disorders from medical images using a combination of linear discriminant analysis and active contour models. Methods: A multivariate statistical methodology was first used to identify the most discriminating hyperplane separating two groups of images (from healthy controls and patients with schizophrenia) contained in the input data. After this, the present work makes explicit the differences found by the multivariate statistical method by subtracting the discriminant models of controls and patients, weighted by the pooled variance between the two groups. A variational level-set technique was used to segment clusters of these differences. We obtain a label of each anatomical change using the Talairach atlas. Results: In this work all the data was analysed simultaneously rather than assuming a priori regions of interest. As a consequence of this, by using active contour models, we were able to obtain regions of interest that were emergent from the data. The results were evaluated using, as gold standard, well-known facts about the neuroanatomical changes related to schizophrenia. Most of the items in the gold standard was covered in our result set. Conclusions: We argue that such investigation provides a suitable framework for characterising the high complexity of magnetic resonance images in schizophrenia as the results obtained indicate a high sensitivity rate with respect to the gold standard. (C) 2010 Elsevier B.V. All rights reserved.