Abstract processing of syllabic structure in early infancy

Syllables are the building blocks of early language acquisition. From birth onwards, infants preferentially segment, process and represent the speech into syllabic units, raising the question of what type of computations infants are able to perform on these perceptual units. Syllables are abstract phonological units structured in a way that allows to group speech sounds into sequences. The goal of the present research was to investigate 4-to-5-month-old infants’ ability to track the abstract internal structure of syllables, at a target age when the language system is not yet specialized on the sounds and the phonotactics of native languages. After familiarization to lists of syllables implementing either CVC (consonant-vowel-consonant) or CCV (consonant-consonant-vowel) structures, infants were presented with new syllables implementing both structures at test. Results showed that infants preferred test syllables that matched the familiar syllabic structure, especially the group of infants familiarized with CVC. Crucially, syllabic structures at test were implemented by new combinations of phonemes, forcing infants to encode some abstract properties of the familiarization stimuli, i.e., the internal syllabic structure.This study provides the first evidence of abstract processing of syllables as whole speech units in the first months of life. These findings contribute to advance our understanding of the type of computations young infants can perform on syllabic units.

XRAY MEDICAL IMAGE CHARACTERIZATION WITH SPARSE RADIATION BASED ON WAVELETS

In medical radiology there are large amounts of digital images in hospitals and health centers. Equipment that enables the acquisition of medical radiographs uses X-radiation sensor plates for image acquisition in medical diagnosis. Medical radiology equipment uses anti-scatter grids, which are physical devices, to avoid unwanted effects on imaging. In the present work, we analyse from a qualitative point of view the radiation scattering effect that is caused in images without the presence of the anti-scattering grid. In this research, the acquisition of radiological images was made by means of X-ray equipment with an anti-scattering grid, capturing images without scattering and others that only present radiation scattering as a point of comparison. The methodology uses the Wavelet transformation to image characterization in segment process that define the regions that affect the different types of dispersion presented in X radiation. The tool used for the analysis of the images is the multi-resolution Wavelet transform, specifically the Discrete Wavelet Transform (DWT). The methodology was applied to different 2D radiological images in shades of gray. In the images used, it showed a robustness in the differentiation of X radiation incidence zones. This work is the beginning of a distortion analysis for the reconstruction of this type of images.

ESTIMATION OF PARAMETERS IN A PLANAR SEGMENT PROCESS WITH A BIOLOGICAL APPLICATION

The paper deals with modeling of segment systems in a bounded planar set (a cell) by means of random segment processes. Two models with a density with respect to the Poisson process are presented. In model I interactions are given by the number of intersections, model II includes the length distribution and takes into account distances from the centre of the cell. The estimation of parameters of the models is suggested based on Takacz-Fiksel method. The method is tested first using simulated data. Further the real data from fluorescence imaging of stress fibres in mesenchymal human stem cells are evaluated. We apply model II which is inhomogeneous. The degree-of-fit testing of the model using various characteristics yields quite satisfactory results.

SECOND MOMENT MEASURE AND K-FUNCTION FOR PLANAR STIT TESSELLATIONS

For STIT tessellations – stationary tessellations that are stable under the operation iteration of tessellations – the second-ordermeasure of the edge system is studied. A result is that this measure coincides with that one of a Boolean segment process. In the isotropic case an explicit formula for the pair-correlation function is given. An estimator for the covariance function of the edge length measure is derived and adapted to digitized images of tessellations. For m pixels of an image the algorithm is of complexity O(mlogm).

Estimation variances for Poisson processes of compact sets

A complete and sufficient statistic is found for various stationary Poisson processes of compact sets with known primary grain. In the particular case of a segment process, the uniformly best unbiased estimator for the length density is the number of segments hitting the sampling window divided by a certain constant and multiplied by the mean segment length.

Estimation variances for Poisson processes of compact sets

A complete and sufficient statistic is found for various stationary Poisson processes of compact sets with known primary grain. In the particular case of a segment process, the uniformly best unbiased estimator for the length density is the number of segments hitting the sampling window divided by a certain constant and multiplied by the mean segment length.