An illustration of variable precision rough set theory : The gender classification of the European barn swallow (Hirundo rustica)

This paper introduces a new technique in the investigation of object classification and illustrates the potential use of this technique for the analysis of a range of biological data, using avian morphometric data as an example. The nascent variable precision rough sets (VPRS) model is introduced and compared with the decision tree method ID3 (through a ‘leave n out’ approach), using the same dataset of morphometric measures of European barn swallows (Hirundo rustica) and assessing the accuracy of gender classification based on these measures. The results demonstrate that the VPRS model, allied with the use of a modern method of discretization of data, is comparable with the more traditional non-parametric ID3 decision tree method. We show that, particularly in small samples, the VPRS model can improve classification and to a lesser extent prediction aspects over ID3. Furthermore, through the ‘leave n out’ approach, some indication can be produced of the relative importance of the different morphometric measures used in this problem. In this case we suggest that VPRS has advantages over ID3, as it intelligently uses more of the morphometric data available for the data classification, whilst placing less emphasis on variables with low reliability. In biological terms, the results suggest that the gender of swallows can be determined with reasonable accuracy from morphometric data and highlight the most important variables in this process. We suggest that both analysis techniques are potentially useful for the analysis of a range of different types of biological datasets, and that VPRS in particular has potential for application to a range of biological circumstances.

Towards a set of priorities for bird conservation and research in Australia : the perceptions of ornithologists

Australian delegates at the Australasian Ornithological Conference (2007) were surveyed by questionnaire to determine their perceived research and conservation priorities for Australian birds (n = 134). Respondents were honours or postgraduate students (37.4%), academics (26.2%), wildlife managers (6.5%), land managers (6.5%), environmental consultants (5.6%), independent wildlife researchers (5.6%) or had ‘other’ occupations not relevant to birds or their management (12.1%). Respondents rated their priorities on a predetermined set of issues, and were invited to add additional priorities. ‘Conservation of threatened species’ was considered the highest priority, followed by ‘Conservation of birds and biodiversity in general’, ‘Monitoring’, ‘Management’ and ‘Working with communities’. ‘Animal welfare/rights’ was regarded as comparatively less important. Eight of 11 conservation strategies were regarded as of high importance, these included habitat protection and rehabilitation, threat abatement, research, advocacy and education. This study documents the view of the ornithological community with respect to priority issues facing birds and could potentially feed into government and other policies aimed at conserving and understanding Australia’s birds.

Abjection and midwifery : towards a revision of Julia Kristeva's theory of the maternal

This paper will develop a specific reading of Julia Kristeva’s analysis of the Mother in psychoanalytic contexts and artistic production. I want to suggest a particular connection between the Mother and a second figure closely associated with her: the Midwife. Such a move opens up the possibility for a new understanding of Kristeva’s correlation of the Mother with the psychoanalytic concept of “abjection”. I wish to identify the Midwife as the crucial intersection of a masculine and feminine subjectivity. I will undertake this project via a historical study of Midwifery, which will include an exploration of the Midwife’s relationship to masculine ideologies of medical thought, as well as an account of the problematic rise of the “Man-Midwife”. My strategy will be to extend the submerged historical and material content of Kristeva’s own theories, with particular reference to Powers of Horror: An Essay on Abjection.

Separating the contributions of hearing, lexical knowledge and speech production to speech perception scores in children with hearing impairments.

Open-set word and sentence speech-perception test scores are commonly used as a measure of hearing abilities in children and adults using cochlear implants and/or hearing aids. These tests are usually presented auditorily with a verbal response. In the case of children, scores are typically lower and more variable than for adults with hearing impairments using similar devices. It is difficult to interpret children's speech-perception scores without considering the effects of lexical knowledge and speech-production abilities on their responses. This study postulated a simple mathematical model to describe the effects of hearing, lexical knowledge, and speech production on the perception test scores for monosyllabic words by children with impaired hearing. Thirty-three primary-school children with impaired hearing, fitted with hearing aids and/or cochlear implants, were evaluated using speech-perception, reading-aloud, speech-production, and language measures. These various measures were incorporated in the mathematical model, which revealed that performance in an open-set word-perception test in the auditory-alone mode is strongly dependent on residual hearing levels, lexical knowledge, and speech-production abilities. Further applications of the model provided an estimate of the effect of each component on the overall speech-perception score for each child.

A rough set approach for selecting clustering attribute

A few of clustering techniques for categorical data exist to group objects having similar characteristics. Some are able to handle uncertainty in the clustering process while others have stability issues. However, the performance of these techniques is an issue due to low accuracy and high computational complexity. This paper proposes a new technique called maximum dependency attributes (MDA) for selecting clustering attribute. The proposed approach is based on rough set theory by taking into account the dependency of attributes of the database. We analyze and compare the performance of MDA technique with the bi-clustering, total roughness (TR) and min–min roughness (MMR) techniques based on four test cases. The results establish the better performance of the proposed approach.

Orientation-specific attentional set effects

The thesis is a theoretical and experimental exploration of visual attention: when and how does knowing a feature of something we are about to see help us to see that thing? Attentional benefits occurred under short inspection times with high distraction intensity, and long inspection times with low distraction intensity.

The efficiency of improved ranked set sampling methods

Ranked set sampling is a desirable sampling technique where the ranking of the sample observations does not require the actual measurement. This thesis develops new ranked set sampling techniques and determines the sampling characteristics required to best estimate the required population parameters, such as mean and variance.

Contracting-agency analysis of the association between firm risk, investment opportunity set, corporate governance and firm performance

Tests the efficiency of corporate controls (board monitoring and incentive contracts) for growth or risk firms. By exploring the implications of controls and studying their interactive effects on firm performance, this study demonstrates how and why different firms use corporate governance controls to align managers' and shareholders' interests.

Vision-based target tracking and surveillance with robust set-valued state estimation

Tracking a target from a video stream (or a sequence of image frames) involves nonlinear measurements in Cartesian coordinates. However, the target dynamics, modeled in Cartesian coordinates, result in a linear system. We present a robust linear filter based on an analytical nonlinear to linear measurement conversion algorithm. Using ideas from robust control theory, a rigorous theoretical analysis is given which guarantees that the state estimation error for the filter is bounded, i.e., a measure against filter divergence is obtained. In fact, an ellipsoidal set-valued estimate is obtained which is guaranteed to contain the true target location with an arbitrarily high probability. The algorithm is particularly suited to visual surveillance and tracking applications involving targets moving on a plane.

A robust set-valued state estimation approach to the problem of vision based SLAM for mobile robots

The problem of visual simultaneous localization and mapping (SLAM) is examined in this paper using ideas and algorithms from robust control and estimation theory. Using a stereo-vision based sensor, a nonlinear measurement model is derived which leads to nonlinear measurements of the landmark coordinates along with optical flow based measurements of the relative robot-landmark velocity. Using a novel analytical measurement transformation, the nonlinear SLAM problem is converted into the linear filter is guaranteed stable and the ALAM state estimation error is bounded within an ellipsoidal set. No similar results are available for the commonly employed extended Kalman filter which is known to exhibit divergent and inconsistency characteristics in practice.