A comparison of pragmatic abilities of children who are deaf or hard of hearing and their hearing peers

Pragmatic skills are the key to a satisfying and sustained conversation. Such conversation is critical for the development of meaningful friendships. Previous studies have investigated the conversational skills of deaf children while interacting with adults or when interacting with peers in structured referential tasks. There are few published studies that have compared the pragmatic skills of children who are deaf or hard of hearing (D/HH) in free conversation with their hearing peers. In this study, the conversational skills of 31 children who are D/HH when interacting with a hearing friend were compared with those of 31 pairs of hearing children. Findings suggest that school-aged children (Years 3–6 of study; aged 8–12 years) who are D/HH have a wide range of pragmatic skills that they use effectively when conversing with their hearing peers. Specifically, these children asked more questions, made more personal comments, initiated more topics, and took longer turns in their conversations with a hearing friend. In contrast, the conversations between hearing peers were very balanced with similar topic initiation, length of turn, numbers of questions, personal comments, and minimal answers. These findings will help teachers to provide support for both pragmatic and social skills in children who are D/HH.

On the use of restricted dissimilarity and dissimilarity-like functions for defining penalty functions

In this work we study the relation between restricted dissimilarity functions-and, more generally, dissimilarity-like functions- and penalty functions and the possibility of building the latter using the former. Several results on convexity and quasiconvexity are also considered.

Multitasking: multiple, domain-specific cognitive functions in a virtual environment

Multitasking among three or more different tasks is a ubiquitous requirement of everyday cognition, yet rarely is it addressed in research on healthy adults who have had no specific training in multitasking skills. Participants completed a set of diverse subtasks within a simulated shopping mall and office environment, the Edinburgh Virtual Errands Test (EVET). The aim was to investigate how different cognitive functions, such as planning, retrospective and prospective memory, and visuospatial and verbal working memory, contribute to everyday multitasking. Subtasks were chosen to be diverse, and predictions were derived from a statistical model of everyday multitasking impairments associated with frontal-lobe lesions (Burgess, Veitch, de Lacy Costello, & Shallice, 2000b). Multiple regression indicated significant independent contributions from measures of retrospective memory, visuospatial working memory, and online planning, but not from independent measures of prospective memory or verbal working memory. Structural equation modelling showed that the best fit to the data arose from three underlying constructs, with Memory and Planning having a weak link, but with both having a strong directional pathway to an Intent construct that reflected implementation of intentions. Participants who followed their preprepared plan achieved higher scores than those who altered their plan during multitask performance. This was true regardless of whether the plan was efficient or poor. These results substantially develop and extend the Burgess et al. (2000b) model to healthy adults and yield new insight into the poorly understood area of everyday multitasking. The findings also point to the utility of using virtual environments for investigating this form of complex human cognition.

Image reduction operators based on non-monotonic averaging functions

Image reduction is a crucial task in image processing, underpinning many practical applications. This work proposes novel image reduction operators based on non-monotonic averaging aggregation functions. The technique of penalty function minimisation is used to derive a novel mode-like estimator capable of identifying the most appropriate pixel value for representing a subset of the original image. Performance of this aggregation function and several traditional robust estimators of location are objectively assessed by applying image reduction within a facial recognition task. The FERET evaluation protocol is applied to confirm that these non-monotonic functions are able to sustain task performance compared to recognition using nonreduced images, as well as significantly improve performance on query images corrupted by noise. These results extend the state of the art in image reduction based on aggregation functions and provide a basis for efficiency and accuracy improvements in practical computer vision applications.

Zeros of Dirichlet L-functions on the critical line with the accuracy of 40000 decimal places

The zeros of Dirichlet L-functions for various moduli and characters are being computed with very high accuracy on a cluster of workstations at Deakin University. This collection is growing to include more zeros (other moduli and characters).