Language in Acquisition : Early Lexical Development and Associations between Lexicon and Grammar Findings from Full-Term and Very-Low-Birth-Weight Finnish Children

The aim was to analyse the growth and compositional development of the receptive and expressive lexicons between the ages 0,9 and 2;0 in the full-term (FT) and the very-low-birth-weight (VLBW) children who are acquiring Finnish. The associations between the expressive lexicon and grammar at 1;6 and 2;0 in the FT children were also studied. In addition, the language skills of the VLBW children at 2;0 were analysed, as well as the predictive value of early lexicon to the later language performance. Four groups took part in the studies: the longitudinal (N = 35) and cross-sectional (N = 146) samples of the FT children, and the longitudinal (N = 32) and cross-sectional (N = 66) samples of VLBW children. The data was gathered by applying of the structured parental rating method (the Finnish version of the Communicative Development Inventory), through analysis of the children´s spontaneous speech and by administering a a formal test (Reynell Developmental Language Scales). The FT children acquired their receptive lexicons earlier, at a faster rate and with larger individual variation than their expressive lexicons. The acquisition rate of the expressive lexicon increased from slow to faster in most children (91%). Highly parallel developmental paths for lexical semantic categories were detected in the receptive and expressive lexicons of the Finnish children when they were analysed in relation to the growth of the lexicon size, as described in the literature for children acquiring other languages. The emergence of grammar was closely associated with expressive lexical growth. The VLBW children acquired their receptive lexicons at a slower rate and had weaker language skills at 2;0 than the full-term children. The compositional development of both lexicons happened at a slower rate in the VLBW children when compared to the FT controls. However, when the compositional development was analysed in relation to the growth of lexicon size, this development occurred qualitatively in a nearly parallel manner in the VLBW children as in the FT children. Early receptive and expressive lexicon sizes were significantly associated with later language skills in both groups. The effect of the background variables (gender, length of the mother s basic education, birth weight) on the language development in the FT and the VLBW children differed. The results provide new information of early language acquisition by the Finnish FT and VLBW children. The results support the view that the early acquisition of the semantic lexical categories is related to lexicon growth. The current findings also propose that the early grammatical acquisition is closely related to the growth of expressive vocabulary size. The language development of the VLBW children should be followed in clinical work.

Online Handwritten Kannada Word Recognizer with Unrestricted Vocabulary

In this paper, we propose a novel heuristic approach to segment recognizable symbols from online Kannada word data and perform recognition of the entire word. Two different estimates of first derivative are extracted from the preprocessed stroke groups and used as features for classification. Estimate 2 proved better resulting in 88% accuracy, which is 3% more than that achieved with estimate 1. Classification is performed by statistical dynamic space warping (SDSW) classifier which uses X, Y co-ordinates and their first derivatives as features. Classifier is trained with data from 40 writers. 295 classes are handled covering Kannada aksharas, with Kannada numerals, Indo-Arabic numerals, punctuations and other special symbols like $ and #. Classification accuracies obtained are 88% at the akshara level and 80% at the word level, which shows the scope for further improvement in segmentation algorithm

Laser receptive polyelectrolyte thin films doped with biosynthesized silver nanoparticles for antibacterial coatings and drug delivery applications

We report a simple method to fabricate multifunctional polyelectrolyte thin films to load and deliver the therapeutic drugs. The multilayer thin films were assembled by the electrostatic adsorption of poly (allylamine hydrochloride) (PAH) and dextran sulfate (DS). The silver nanoparticles (Ag NPs) biosynthesized from novel Hybanthus enneaspermus leaf extract as the reducing agent were successfully incorporated into the film. The biosynthesized Ag NPs showed excellent antimicrobial activity against the range of enteropathogens, which could be significantly enhanced when used with commercial antibiotics. The assembled silver nano composite multilayer films showed rupture and deformation when they are exposed to laser. The Ag NPs act as an energy absorption center, locally heat up the film and rupture it under laser treatment. The antibacterial drug, moxifloxacin hydrochloride (MH) was successfully loaded into the multilayer films. The total amount of MH release observed was about 63% which increased to 85% when subjected to laser light exposure. Thus, the polyelectrolyte thin film reported in our study has significant potential in the field of remote activated drug delivery, antibacterial coatings and wound dressings. (C) 2013 Elsevier B.V. All rights reserved.

Recognition of open vocabulary, online handwritten pages in Tamil script

In this work, we describe a system, which recognises open vocabulary, isolated, online handwritten Tamil words and extend it to recognize a paragraph of writing. We explain in detail each step involved in the process: segmentation, preprocessing, feature extraction, classification and bigram-based post-processing. On our database of 45,000 handwritten words obtained through tablet PC, we have obtained symbol level accuracy of 78.5% and 85.3% without and with the usage of post-processing using symbol level language models, respectively. Word level accuracies for the same are 40.1% and 59.6%. A line and word level segmentation strategy is proposed, which gives promising results of 100% line segmentation and 98.1% word segmentation accuracies on our initial trials of 40 handwritten paragraphs. The two modules have been combined to obtain a full-fledged page recognition system for online handwritten Tamil data. To the knowledge of the authors, this is the first ever attempt on recognition of open vocabulary, online handwritten paragraphs in any Indian language.