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This piece of research analyses lexical inferencing, the process of working out the meanings of unknown words using context clues. Three main aspects are considered: to what extent subjects succeed or fail in making plausible inferences about word meaning, their feelings and attitudes towards the process, and the techniques or strategies which they resQrt to. The thesis is structured as a research narrative, pre~ senting twelve studies dating from 1983 to 1989. Subjects were adult Brazilians, reading in English as a foreign language, and/or in their native language, Portuguese. Adult lexical inference is shown to be more successful than previous studies using children reading in their native language had suggested. Evidence is presented to suggest that subjects characteristically use~ a narrow context of a few words on either side of the target item in attempting lexical inference, and that this breadth of context was sufficient for most inferences. The suggestion that there may be a vocabulary 'threshold', below which lexical inference is impeded, is rejected. Implausible inferences came generally either from mis-recognition of word forms, or from ignoring wider amounts of context. Evidence is presented to suggest that familiarity of the underlying concept is a major variable. Subjects' hypotheses about word meaning were mostly at an appropriate level of specificity, and gradually refined as more evidehce became available. There was little evidence of over-certainty. Further variables of importance are subjects' beliefs about what "knowing" a word is, and their level of awareness about the lexical inference process. A wide range of feelings (positive, negative and of caution) were observed. No one pattern of strategy use was firmly aS$ociated with greater lexical inference success rates. Instead, subjects made great use of background knowledge and lexis-based strategies and little use of discoursal or grammatical features.

Matlab is a proprietary, interactive, dynamically-typed language for technical computing. It is widely used for prototyping algorithms and applications of scientific computations. Since it is a dynamically typed language, the execution of programs has to be analyzed and interpreted which results in lower computational performance. In order to increase the performance and integrate with Modelica applications it is useful to be able to translate Matlab programs to statically typed Modelica programs. This project presents the design and implementation of Matlab to Modelica translator. The Lexical and Syntax analysis is done with the help of the OMCCp (OpenModelica Compiler Compiler parser generator) tool which generates the Matlab AST, which is later used by the translator for generating readable and reusable Modelica code.

In New Zealand, approximately 10% of births are considered premature, that is less than 37 weeks gestation. With advances in medical technology, young infants are surviving gestation periods as few as 23 weeks. It is expected that many of these severely premature infants will demonstrate some problem in their academic, or cognitive function including language functioning. It is agreed that children who are born severely premature often present with language problems, the nature of the difficulties are not clear. Research examining language abilities that involve cognitive functions such as inference generation have demonstrated that children born prematurely exhibit difficulties with phonologic short-term memory and executive function. Language tasks such as inference understanding require children to integrate real-world knowledge with the linguistic information to generate and produce language that is more complex. The aim of this study was to discover if the language of children born severely premature differs from that of language-age matched peers. This study examined high-level language abilities of school-age children born severely prematurely, specifically, language tasks that involved executive functions including working memory, story inferencing, and recognising absurdities. Six children who were born less than 28 weeks gestation participated in this study. Their results on the above measures were compared to a language-aged matched comparison group, determined by performance on a standardised test. It was hypothesised that the children born severely premature would not differ from their language-age matched peers on measures of general language ability but differences would exist on measures of language processing and inferencing. The findings overall showed little difference between the preterm group and their language-age matched peers on measures except for the measure of chronological age. Although no group difference was found for the measure of working memory, a larger variance on this measure was observed in the preterm group.

In New Zealand, approximately 10% of births are considered premature, that is less than 37 weeks gestation. With advances in medical technology, young infants are surviving gestation periods as few as 23 weeks. It is expected that many of these severely premature infants will demonstrate some problem in their academic, or cognitive function including language functioning. It is agreed that children who are born severely premature often present with language problems, the nature of the difficulties are not clear. Research examining language abilities that involve cognitive functions such as inference generation have demonstrated that children born prematurely exhibit difficulties with phonologic short-term memory and executive function. Language tasks such as inference understanding require children to integrate real-world knowledge with the linguistic information to generate and produce language that is more complex. The aim of this study was to discover if the language of children born severely premature differs from that of language-age matched peers. This study examined high-level language abilities of school-age children born severely prematurely, specifically, language tasks that involved executive functions including working memory, story inferencing, and recognising absurdities. Six children who were born less than 28 weeks gestation participated in this study. Their results on the above measures were compared to a language-aged matched comparison group, determined by performance on a standardised test. It was hypothesised that the children born severely premature would not differ from their language-age matched peers on measures of general language ability but differences would exist on measures of language processing and inferencing. The findings overall showed little difference between the preterm group and their language-age matched peers on measures except for the measure of chronological age. Although no group difference was found for the measure of working memory, a larger variance on this measure was observed in the preterm group.

The present study investigates the effect of furigana on lexical inferencing. After completing a pretest to determine their knowledge of the target words, participants read a passage and completed a think-aloud protocol and questionnaire. The experimental group read a passage with furigana over all kanji words while the control group read a passage without furigana. The protocols were evaluated to determine the rate and quality of lexical inferences of 16 target kanji words. The results of the questionnaire were evaluated to determine participant perception of passage and kanji difficulty, self-assessed percentage of the story that was understood, and the degree to which they liked the story. It was found that the group with furigana made more correct inferences than the control group. It was also found that the furigana group perceived the kanji in the passage to be easier than the control group did. Furigana did not seem to affect the degree to which the participants liked the story, their perception of the difficulty of the story or the percentage of the story that they understood. Implications for theory and pedagogy are discussed.

Yes / A Decision Support System (DSS) in tunnelling domain deals with identifying pathologies based on disorders present in various tunnel portions and contextual factors affecting a tunnel. Another key area in diagnosing pathologies is to identify regions of interest (ROI). In practice, tunnel experts intuitively abstract regions of interest by selecting tunnel portions that are susceptible to the same types of pathologies with some distance approximation. This complex diagnosis process is often subjective and poorly scales across cases and transport structures. In this paper, we introduce PADTUN system, a working prototype of a DSS in tunnelling domain using semantic technologies. Ontologies are developed and used to capture tacit knowledge from tunnel experts. Tunnel inspection data are annotated with ontologies to take advantage of inferring capabilities offered by semantic technologies. In addition, an intelligent mechanism is developed to exploit abstraction and inference capabilities to identify ROI. PADTUN is developed in real-world settings offered by the NeTTUN EU Project and is applied in a tunnel diagnosis use case with Société Nationale des Chemins de Fer Français (SNCF), France. We show how the use of semantic technologies allows addressing the complex issues of pathology and ROI inferencing and matching experts’ expectations of decision support.

Children with language impairment (LI) have demonstrated several language problems, including receptive and expressive deficits. A growing body of research has further demonstrated emotion understanding and, more specifically, emotion inferencing deficits that negatively affect the ability of this population to use language successfully in social interactions. Consequently, the present study examines social communication intervention focused on improving emotion inferencing for children with a diagnosis of LI or Autism Spectrum Disorder (ASD), as similar social communication deficits are occasionally seen in children with these diagnoses. Study participants were identified from the caseload of a practicing certified speech-language pathologist (SLP) and qualified for intervention based upon Comprehensive Assessment of Spoken Language (CASL) and Universal Nonverbal Intelligence Test (UNIT) scores. Participant ability to perform an emotion inferencing task was then compared pre- and post-treatment with descriptive statistics and presented as 6 individual case studies to determine the effectiveness of social communication intervention. Results are presented pre- and post-intervention and indicated that emotion inferencing capacities for a given scenario increased for some participants, while others demonstrated either modest gains or slight declines in performance after intervention.

Children with Developmental Language Disorder (DLD) often face problems in areas of social communication including negotiating with peers, entering ongoing interactions, and engaging in conflict resolution. A potential cause of these social communication difficulties is the decreased ability to make emotional inferences. This thesis investigates the effects of a social communication intervention on the ability of school-aged children with DLD to make inferences about emotions. Five children with DLD between the ages of 6;10 and 12;4 participated in a social communication intervention that highlighted principles of emotion understanding (recognizing emotions in facial expressions, inferring emotions with contextual information, and discussing reasoning behind emotions) using story books to illustrate concepts. Data were gathered before and after intervention using a psychometrically balanced measure of emotional inferencing ability. Results revealed notable improvements in three of the participants and consistent performance in two of the participants baseline to follow-up. While performance on the emotional inferencing task varied due to multiple factors, the participants that showed improvement produced real growth which encourages future research to be conducted.

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