The effects of L1 orthography on processing an artificial logographic script

To date, studies have focused on the acquisition of alphabetic second languages (L2s) in alphabetic first language (L1) users, demonstrating significant transfer effects. The present study examined the process from a reverse perspective, comparing logographic (Mandarin-Chinese) and alphabetic (English) L1 users in the acquisition of an artificial logographic script, in order to determine whether similar language-specific advantageous transfer effects occurred. English monolinguals, English-French bilinguals and Chinese-English bilinguals learned a small set of symbols in an artificial logographic script and were subsequently tested on their ability to process this script in regard to three main perspectives: L2 reading, L2 working memory (WM), and inner processing strategies. In terms of L2 reading, a lexical decision task on the artificial symbols revealed markedly faster response times in the Chinese-English bilinguals, indicating a logographic transfer effect suggestive of a visual processing advantage. A syntactic decision task evaluated the degree to which the new language was mastered beyond the single word level. No L1-specific transfer effects were found for artificial language strings. In order to investigate visual processing of the artificial logographs further, a series of WM experiments were conducted. Artificial logographs were recalled under concurrent auditory and visuo-spatial suppression conditions to disrupt phonological and visual processing, respectively. No L1-specific transfer effects were found, indicating no visual processing advantage of the Chinese-English bilinguals. However, a bilingual processing advantage was found indicative of a superior ability to control executive functions. In terms of L1 WM, the Chinese-English bilinguals outperformed the alphabetic L1 users when processing L1 words, indicating a language experience-specific advantage. Questionnaire data on the cognitive strategies that were deployed during the acquisition and processing of the artificial logographic script revealed that the Chinese-English bilinguals rated their inner speech as lower than the alphabetic L1 users, suggesting that they were transferring their phonological processing skill set to the acquisition and use of an artificial script. Overall, evidence was found to indicate that language learners transfer specific L1 orthographic processing skills to L2 logographic processing. Additionally, evidence was also found indicating that a bilingual history enhances cognitive performance in L2.

GYAN: A methodology for rule extraction from artificial neural networks

Artificial neural network (ANN) learning methods provide a robust and non-linear approach to approximating the target function for many classification, regression and clustering problems. ANNs have demonstrated good predictive performance in a wide variety of practical problems. However, there are strong arguments as to why ANNs are not sufficient for the general representation of knowledge. The arguments are the poor comprehensibility of the learned ANN, and the inability to represent explanation structures. The overall objective of this thesis is to address these issues by: (1) explanation of the decision process in ANNs in the form of symbolic rules (predicate rules with variables); and (2) provision of explanatory capability by mapping the general conceptual knowledge that is learned by the neural networks into a knowledge base to be used in a rule-based reasoning system. A multi-stage methodology GYAN is developed and evaluated for the task of extracting knowledge from the trained ANNs. The extracted knowledge is represented in the form of restricted first-order logic rules, and subsequently allows user interaction by interfacing with a knowledge based reasoner. The performance of GYAN is demonstrated using a number of real world and artificial data sets. The empirical results demonstrate that: (1) an equivalent symbolic interpretation is derived describing the overall behaviour of the ANN with high accuracy and fidelity, and (2) a concise explanation is given (in terms of rules, facts and predicates activated in a reasoning episode) as to why a particular instance is being classified into a certain category.

Probabilistic visual recognition of artificial landmarks for simultaneous localization and mapping

Probabilistic robotics, most often applied to the problem of simultaneous localisation and mapping (SLAM), requires measures of uncertainly to accompany observations of the environment. This paper describes how uncertainly can be characterised for a vision system that locates coloured landmark in a typical laboratory environment. The paper describes a model of the uncertainly in segmentation, the internal camera model and the mounting of the camera on the robot. It =plains the implementation of the system on a laboratory robot, and provides experimental results that show the coherence of the uncertainly model,

Identification and control of induction machines using artificial neural networks

The use of artificial neural networks (ANNs) to identify and control induction machines is proposed. Two systems are presented: a system to adaptively control the stator currents via identification of the electrical dynamics, and a system to adaptively control the rotor speed via identification of the mechanical and current-fed system dynamics. Both systems are inherently adaptive as well as self-commissioning. The current controller is a completely general nonlinear controller which can be used together with any drive algorithm. Various advantages of these control schemes over conventional schemes are cited, and the combined speed and current control scheme is compared with the standard vector control scheme

Identification and control of induction machines using artificial neural networks

This paper proposes the use of artificial neural networks (ANNs) to identify and control an induction machine. Two systems are presented: a system to adaptively control the stator currents via identification of the electrical dynamics; and a system to adaptively control the rotor speed via identification of the mechanical and current-fed system dynamics. Various advantages of these control schemes over other conventional schemes are cited and the performance of the combined speed and current control scheme is compared with that of the standard vector control scheme

New edition leaves scope for "human factor" in research

The Media and Communications in Australia, edited by Stuart Cunningham and Graeme Turner (3rd edition). Sydney: Allen and Unwin, 2010, 362 pp. ISBN 978-1 74237-064-4; reviewed by Lee Duffield, Queensland University of Technology.

Broad Bean Stain Virus: Identification, Detectability with ELISA in Faba Bean Leaves and Seeds, Occurrence in West Asia and North Africa and Possible Wild Hosts

Abstract During a survey of faba bean viruses in West Asia and North Africa a virus was identified as broad bean stain virus (BBSV) based on host reactions, electron microscopy, physical properties and serology. An antiserum to a Syrian isolate was prepared. With this antiserum both the direct double antibody sandwich ELISA (DAS-ELISA) and dot-ELISA were very sensitive in detecting BBSV in leaf extracts, ground whole seeds and germi nated embryos. Sens it i vity was not reduced when the two-day procedure was replaced by a one-day procedure. us i ng ELISA the vi rus was detected in 73 out of 589 faba bean samples with virus-like symptoms collected from Egypt (4 out of 70 samples tested), Lebanon (6/44) , Morocco (017), Sudan (19/254), Syria (36/145) and Tunisia (8/69). This is the first report of BBSV infection of faba bean in Lebanon, Sudan, Syria and Tunisia. speci es i ndi genous to Syri a were Fourteen wild legume susceptible to BBSV infection, with only two producing obvious symptoms. The virus was found to be seed transmitted ~n Vicia palaestina.

Accumulation of recombinant cellobiohydrolase and endoglucanase in the leaves of mature transgenic sugar cane

A major strategic goal in making ethanol from lignocellulosic biomass a cost-competitive liquid transport fuel is to reduce the cost of production of cellulolytic enzymes that hydrolyse lignocellulosic substrates to fermentable sugars. Current production systems for these enzymes, namely microbes, are not economic. One way to substantially reduce production costs is to express cellulolytic enzymes in plants at levels that are high enough to hydrolyse lignocellulosic biomass. Sugar cane fibre (bagasse) is the most promising lignocellulosic feedstock for conversion to ethanol in the tropics and subtropics. Cellulolytic enzyme production in sugar cane will have a substantial impact on the economics of lignocellulosic ethanol production from bagasse. We therefore generated transgenic sugar cane accumulating three cellulolytic enzymes, fungal cellobiohydrolase I (CBH I), CBH II and bacterial endoglucanase (EG), in leaves using the maize PepC promoter as an alternative to maize Ubi1 for controlling transgene expression. Different subcellular targeting signals were shown to have a substantial impact on the accumulation of these enzymes; the CBHs and EG accumulated to higher levels when fused to a vacuolar-sorting determinant than to an endoplasmic reticulum-retention signal, while EG was produced in the largest amounts when fused to a chloroplast-targeting signal. These results are the first demonstration of the expression and accumulation of recombinant CBH I, CBH II and EG in sugar cane and represent a significant first step towards the optimization of cellulolytic enzyme expression in sugar cane for the economic production of lignocellulosic ethanol.