Requirements are a key aspect of software development. Requirements are also related with other software artefacts including designs, test cases and documentation. These artefacts are often captured with specialized models. However, many tools lack support for traceability relationships between requirements artefacts and model artefacts, leading to analysis issues. To establish traceability between models and other types of requirements artefacts, this thesis proposes a new Domain-Specific Language (DSL) for describing the concepts of a modeling language that would be intended to be traced using a Requirements Management System (RMS), with tool support handling the evolution of models and of their traceability links. In the first part of this thesis, the syntax and metamodel of the Model Traceability DSL (MT-DSL) are defined, together with an editor implemented using Xtext. In the second part of the thesis, a library of import and maintenance functions is generated automatically (using Xtend) from model traceability descriptions written using MT-DSL. The target language for this library is the DOORS eXtension Language (DXL), the scripting language of a leading commercial RMS with traceability support, namely IBM Rational DOORS. The implementation has been tested successfully for importing and evolution scenarios with two different modeling languages (User Requirements Notation and Finite State Machines). This work hence contributes a reliable mechanism to define and support traceability between requirements and models.

Requirements are a key aspect of software development. Requirements are also related with other software artefacts including designs, test cases and documentation. These artefacts are often captured with specialized models. However, many tools lack support for traceability relationships between requirements artefacts and model artefacts, leading to analysis issues. To establish traceability between models and other types of requirements artefacts, this thesis proposes a new Domain-Specific Language (DSL) for describing the concepts of a modeling language that would be intended to be traced using a Requirements Management System (RMS), with tool support handling the evolution of models and of their traceability links. In the first part of this thesis, the syntax and metamodel of the Model Traceability DSL (MT-DSL) are defined, together with an editor implemented using Xtext. In the second part of the thesis, a library of import and maintenance functions is generated automatically (using Xtend) from model traceability descriptions written using MT-DSL. The target language for this library is the DOORS eXtension Language (DXL), the scripting language of a leading commercial RMS with traceability support, namely IBM Rational DOORS. The implementation has been tested successfully for importing and evolution scenarios with two different modeling languages (User Requirements Notation and Finite State Machines). This work hence contributes a reliable mechanism to define and support traceability between requirements and models.

Over the past decade, there have been diverse theoretical perspectives and increasing empirical literature on bilingualism and specific language impairment (SLI), some of which highlighted the complex nature of accurately diagnosing SLI in bilingual populations. The goal of the current study is to enhance our understanding of morphosyntax development in an understudied bilingual population - Mandarin-English children who are growing up in an L2-dominant environment (English) in the United States. The study included a total of 55 bilingual Mandarin-English children between the ages of four and seven years, including 53 typically developing (TD) children and 2 children diagnosed with SLI. Using a newly developed screening test - the Bilingual English-Mandarin Oral Screener (BEMOS), we compared Mandarin performance in both TD and SLI children on 7 morphosyntax tasks which respectively measure passive -bei, possessive -de, prepositional phrases, noun classifiers, quantifier and scope, aspects (imperfective “-zai” and perfective “-le”), and sentence repetition. Our analysis of TD bilingual children revealed a trend towards a significant age effect in the total score and a near-significant effect in the preposition and the aspect sub-sections of the screener. When age was considered, perceived Mandarin proficiency by parents was associated with TD bilingual children’s performance. All students performed poorly on the classifier section, but our error analysis showed a predominant response pattern of imitation, suggesting bilingual children have growing sensitivity and are attentive to semantic similarity of nouns. Overgeneralized use of the general classifier “ge” was also observed in the errors. Both children with SLI scored lower overall compared to their age- and gender-matched TD peers, especially in the classifier and quantifier & scope sections. Reliable clinical markers were not identified due to the two SLI children’s distinct performance. Clinical implications and future research needs were also discussed. / text

This study examined the use of music as an intervention tool with primary school aged children with Specific Language Impairment, specifically in the linguistic areas of semantics, pragmatics and oral narrative. As teachers and speech pathologists have the most professional contact with children with language impairment, they would benefit from access to suitable music activities. As it cannot be assumed that they have musical training, activities must be designed to be easy to use and adapt. The main aims of the study were (1) to determine whether a range of music activities designed to teach specific language skills were suitable for language intervention programmes, and (2) to ascertain the extent to which teachers and speech pathologists could use these activities (and similar activities) in language intervention. A preliminary survey of Grade Two teachers in Language Development Centres (LDCs) in Perth, Western Australia provided the basis for specific skills to be targeted. Music activities were designed and implemented with a Grade Two class in a Language Development Centre. Four of the students were selected as case studies in order to evaluate the impact of the activities. The classroom teacher was also studied as a case example to determine the usefulness of the activities for professionals with no musical training. Additionally, surveys of teachers in LDCs and speech pathologists (both public facilities and private practice) working with children in the Perth metropolitan region were conducted. Evaluations by the researcher, classroom teacher, a speech pathologist and the four student case studies indicated that the activities designed in this study addressed the specific language goals appropriately, were suitable for use with groups, and that the students were learning and developing the targeted language skills. In addition, the activities were suitable for use by professionals with little musical background, and were perceived by the teacher to be adaptable for different skill levels and age groups. This suggests that music can be effectively used in semantic, pragmatic and oral narrative intervention for primary school aged children with specific language impairment.

This thesis describes and evaluates how extending Intel's Concurrent Collections (CnC) programming model can address the problem of hybrid programming with high performance and low energy consumption, while retaining the ease of use of data-flow programming. The CnC model is a declarative, dynamic light-weight task based parallel programming model and is implicitly deterministic by enforcing the single assignment rule, properties which ensure that problems are modelled in an intuitive way. CnC offers a separation of concerns by allowing algorithms to be expressed as a two stage process: first by decomposing a problem into components and specifying how components interact with each other, and second by providing an implementation for each component. By facilitating the separation between a domain expert, who can provide an accurate problem specification at a high level, and a tuning expert, who can tune the individual components for better performance, we ensure that tuning and future development, such as replacement of a subcomponent with a more efficient algorithm, become straightforward. A recent trend in mainstream desktop systems is the use of graphics processor units (GPUs) to obtain order-of-magnitude performance improvements relative to general-purpose CPUs. In addition, the use of FPGAs has seen a significant increase for applications that can take advantage of such dedicated hardware. We see that computing is evolving from using many core CPUs to ``co-processing" on the CPU, GPU and FPGA, however hybrid programming models that support the interaction between multiple heterogeneous components are not widely accessible to mainstream programmers and domain experts who have a real need for such resources. We propose a C-based implementation of the CnC model for enabling parallelism across heterogeneous processor components in a flexible way, with high resource utilization and high programmability. We use the task-parallel HabaneroC language (HC) as the platform for implementing CnC-HabaneroC (CnC-HC), a language also used to implement the computation steps in CnC-HC, for interaction with GPU or FPGA steps and which offers the desired flexibility and extensibility of interacting with any other C based language. First, we extend the CnC model with tag functions and ranges to enable automatic code generation of high level operations for inter-task communication. This improves programmability and also makes the code more analysable, opening the door for future optimizations. Secondly, we introduce a way to specify steps that are data parallel and thus are fit to execute on the GPU, and the notion of task affinity, a tuning annotation in the specification language. Affinity is used by the runtime during scheduling and can be fine-tuned based on application needs to achieve better (faster, lower power, etc.) results. Thirdly, we introduce and develop a novel, data-driven runtime for the CnC model, using HabaneroC (HC) as a base language. In addition, we also create an implementation of the previous runtime approach and conduct a study to compare the performance. Next, we expand the HabaneroC dynamic work-stealing runtime to allow cross-device stealing based on task affinity. Cross-device dynamic work-stealing is used to achieve load balancing across heterogeneous platforms for improved performance. Finally, we implement and use a series of benchmarks for testing the model in different scenarios and show that our proposed approach can yield significant performance benefits and low power usage when using a hybrid execution.

Thesis (M.S.)--Brigham Young University. Dept. of Communication Disorders, 2008. / Includes bibliographical references (p. 30-33).

Thesis (M.S.)--Brigham Young University. Dept. of Communication Disorders, 2008. / Includes bibliographical references (p. 37-44).

Thesis (M.A.)--University of Missouri-Columbia, 2003. / Typescript. Includes bibliographical references (leaves 63-66). Also available on the Internet.

Thesis (M.A.)--University of Missouri-Columbia, 2003. / Typescript. Includes bibliographical references (leaves 63-66). Also available on the Internet.

This thesis extends a previous pilot study with children who stutter (CWS) to include children with specific language impairment (CSLI). The current study examines lexical-semantic organization in these two clinical populations in hopes of comparing and contrasting behavioral profiles. The study employed a list-recall task to assess the lexical-semantic organization of 9 CWS, 5 CSLI, and 20 typically developing children matched for age and vocabulary. Similar to previous investigations, our child participants demonstrated the well-documented list position effects. With regard to recall accuracy, by-participant analyses revealed significant differences between CSLI and their age-matched peers; however, they did not reveal significant differences between the CWS and either of their control groups nor between the CSLI and CWS groups. Further, inspection of error distribution suggested significant differences in the number and types of errors the CSLI and control groups produced. The prevalence of unrelated and previous list errors in CSLI suggest that deficits in inhibitory processes as well as perseveration may have affected their performance. Areas of overlap and divergence in the profiles of CWS and CSLI indicate continuity in the degree of lexical-semantic weakness as well as differences in lexical retrieval and executive functions among CSLI and CWS. / text