An observer design procedure for a class of nonlinear time-delay systems

This paper considers a class of uncertain, nonlinear differential state delayed control systems and presents a reduced-order observer design procedure to asymptotically estimate any vector state functionals. The method proposed involves decomposition of the delayed portion of the system into two parts: a matched and mismatched part. Provided that the rank of the mismatched part is less than the number of the outputs, a reduced-order linear functional observer, with any prescribed stability margin, can be constructed by using a simple procedure. A numerical example is given to illustrate the new design procedure and its features.

Undergraduate pre-registration nursing education in Australia: a longitudinal examination of enrolment and completion numbers with a focus on students from rural and remote campus locations

Introduction: There is much evidence to indicate a shortage of Registered Nurses (RNs) in Australia and to suggest that the shortage may be more pronounced in rural and remote locations. Attracting RNs to work in rural and remote areas may not be as simple as increasing the intake of students into university undergraduate pre-registration nursing courses. There is some evidence indicating that student nurses may be more likely to enter the nursing workforce in rural and remote locations if they have existing associations with rural and remote areas and/or their undergraduate education provides opportunities to undertake supported placements in rural and remote settings. Two important difficulties have been associated with measuring outcomes in relation to rural and remote pre-registration nursing students. One is defining what constitutes a rural or remote location and the other is suspect data on the number of nursing students enrolled in, and completing, nursing courses. The aims of this study were to provide a longitudinal profile of the number of domestic students studying and completing undergraduate pre-registration nursing courses in Australia, with a particular emphasis on identifying those at rural and remote university campuses, and to compare results across States and Territories.
Method: This study presents the combined findings from two investigative reports. Data on undergraduate pre-registration nursing student numbers were collected via electronic survey instruments completed by staff at all Australian educational institutions offering undergraduate pre-registration nursing education programs in 2001 and 2002. Australian domestic students were the focus of this study. Data included the total number of domestic students enrolled in undergraduate pre-registration nursing courses in 2001 and 2002, the number of domestic students who successfully completed courses in 1999, 2000 and 2001, and estimates for the number expected to complete in 2002. Surveys were sent to course coordinators or other staff nominated by heads of divisions of nursing at each institution.
Results: There was a 100% response rate. Twenty-four rural and remote campus locations were identified using an adjusted form of the Rural, Remote and Metropolitan Areas (RRMA) classification system. The Australian Capital Territory and the Northern Territory did not have any rural or remote campus locations. In contrast, undergraduate pre-registration nursing in Tasmania was offered at a rural campus only (for the first 2 years). From 2001 to 2002, there was an increase of just over 5% in the total number of domestic students enrolled in undergraduate pre-registration nursing courses in Australia (2002 total = 22 811 students). Rural and remote location students accounted for slightly more than 25% of these students in 2001, and almost 27% in 2002. The States Victoria, New South Wales and Queensland had the highest percentage of students enrolled at rural and remote campus locations, greater than the Australian average for both years. In contrast, South Australia and Western Australia had less than 11% of students enrolled at rural and remote campus locations for each year. Total undergraduate pre-registration course completions increased by approximately 16% across Australia between 1999 (n = 4868) and 2002 (n = 5667), although for 2002, the figure was projected. Of these total course completions, the percentage of students completing at rural and remote campus locations increased from almost 23% to nearly 28% during the same period. Of the States/Territories with both metropolitan and rural/remote campus locations, only Victoria and Queensland had more than 25% of their total student completions consisting of students enrolled at rural and remote campus locations for each year. In contrast, South Australia and Western Australia had approximately 6% of student completions consisting of students enrolled at rural and remote campus locations in 1999, increasing to approximately 12% projected for 2002.
Conclusion: In this study, the authors attempted to improve the accuracy of data collection in relation to the number of domestic undergraduate pre-registration nursing students in Australia, which is representative of the potentially new Australian domestic RN workforce. There was a trend towards an increasing number of students being enrolled in undergraduate pre-registration nursing courses, and also toward an increasing number of course completions. From the perspective of the rural and remote RN workforce, the percentage of students enrolled and completing courses at rural and remote campus locations was found to be increasing. However, there may be some areas of concern for education and workforce planners in States and Territories that are providing a smaller percentage of their undergraduate pre-registration nursing courses in rural and remote areas. Several study limitations are discussed and suggestions made for future research.

Class library ranlip for multivariate nonuniform random variate generation

This paper describes generation of nonuniform random variates from Lipschitz-continuous densities using acceptance/rejection, and the class library _ranlip which implements this method. It is assumed that the required distribution has Lipschitz-continuous density, which is either given analytically or as a black box. The algorithm builds a piecewise constant upper approximation to the density (the hat function), using a large number of its values and subdivision of the domain into hyperrectangles. The class library _ranlip provides very competitive preprocessing and generation times, and yields small rejection constant, which is a measure of efficiency of the generation step. It exhibits good performance for up to five variables, and provides the user with a black box nonuniform random variate generator for a large class of distributions, in particular, multimodal distributions. It will be valuable for researchers who frequently face the task of sampling from unusual distributions, for which specialized random variate generators are not available.

Training for the new work order : the adult classroom as a site of class(ed) work

This paper reports on a qualitative case study that investigated how the professional identities of trainers in the adult sector in Australia are shaped by intersecting relations of social class, ethnicity, gender and the discourses of vocational adult education. Interviews with two trainers as well as observations of them at work are analysed and presented here to illustrate how social class, considered in relation to gender and race, is played out through the trainers' identity investments in discourses of nurturance and care and economic rationalism. Such identity investments shape the relationships the trainers develop with their students and the training strategies and practices they privilege. The paper argues the need for trainers to develop critical reflective practices and to interrogate how their investments in particular classed identities shape their views about learning for work and training for work. It also argues the need for more research around social class and trainer identity within the adult sector.

Troubling identities: teacher education students` constructions of class and ethnicity

Working with diverse student populations productively depends on teachers and teacher educators recognizing and valuing difference. Too often, in teacher education programs, when markers of identity such as gender, ethnicity, 'race', or social class are examined, the focus is on developing student teachers' understandings of how these discourses shape learner identities and rarely on how these also shape teachers' identities. This article reports on a research project that explored how student teachers understand ethnicity and socio-economic status. In a preliminary stage of the research, we asked eight Year 3 teacher education students who had attended mainly Anglo-Australian, middle class schools as students and as student teachers, to explore their own ethnic and classed identities. The complexities of identity are foregrounded in both the assumptions we made in selecting particular students for the project and in the ways they constructed their own identities around ethnicity and social class. In this article we draw on these findings to interrogate how categories of identity are fluid, shifting and ongoing processes of negotiation, troubling and complex. We also consider the implications for teacher education.

Integrating local one-class classifiers for image retrieval

In content-based image retrieval, learning from users’ feedback can be considered as an one-class classification problem. However, the OCIB method proposed in [1] suffers from the problem that it is only a one-mode method which cannot deal with multiple interest regions. In addition, it requires a pre-specified radius which is usually unavailable in real world applications. This paper overcomes these two problems by introducing ensemble learning into the OCIB method: by Bagging, we can construct a group of one-class classifiers which emphasize various parts of the data set; this is followed by a rank aggregating with which results from different parameter settings are incorporated into a single final ranking list. The experimental results show that the proposed I-OCIB method outperforms the OCIB for image retrieval applications.

Nest-tree selection by the threatened brush-tailed phascogale (phascogale tapoatafa) (marsupialia: dasyuridae) in a highly fragmented agricultural landscape

The conservation of roosting and nesting resources is of critical concern for many hollow-dependent species around the world. We investigated the nest-tree requirements of the threatened brush-tailed phascogale (Phascogale tapoatafa) in a highly cleared agricultural landscape in south-eastern Australia. We documented the physical characteristics of selected nest trees and describe the spatial and temporal patterns of nest-tree use as revealed by radio-tracking. Nine phascogales (seven females, two males) were radio-tracked between March and July 1999 in an area where most woodland habitat is confined to linear strips along roads and streams or small patches and scattered trees in cleared farmland. Female phascogales were monitored for 13–35 days over periods of 5–15 weeks and two males were monitored for 2 and 9 days respectively. A total of 185 nest-tree fixes was collected and all nests occupied by phascogales were in standing trees. Eighty-three nest trees were identified, ranging in diameter at breast height (dbh) from 25 to 171 cm, with a mean dbh for the trees used by each individual phascogale of >80 cm. Phascogales did not discriminate between canopy tree species in selecting nest trees, but showed highly significant selection for trees in the largest size class. All individuals used multiple nest trees, with the seven females occupying an average of 11.4 nest trees from a mean of 25 diurnal locations. The number of nest trees continued to increase throughout the study, suggesting that more would be identified during a longer or more intensive study. Occupied nest trees were located throughout each individual’s home range, highlighting the importance of a continuous spatial distribution of suitable nest trees across the landscape. Nest trees were also located in adjacent farmland up to 225 m from roadside vegetation, demonstrating the value that scattered clumps and even single trees in farmland can have for wildlife conservation.

Parameter optimization of kernel-based one-class classifier on imbalance learning

Compared with conventional two-class learning schemes, one-class classification simply uses a single class in the classifier training phase. Applying one-class classification to learn from unbalanced data set is regarded as the recognition based learning and has shown to have the potential of achieving better performance. Similar to twoclass learning, parameter selection is a significant issue, especially when the classifier is sensitive to the parameters. For one-class learning scheme with the kernel function, such as one-class Support Vector Machine and Support Vector Data Description, besides the parameters involved in the kernel, there is another one-class specific parameter: the rejection rate v. In this paper, we proposed a general framework to involve the majority class in solving the parameter selection problem. In this framework, we first use the minority target class for training in the one-class classification stage; then we use both minority and majority class for estimating the generalization performance of the constructed classifier. This generalization performance is set as the optimization criteria. We employed the Grid search and Experiment Design search to attain various parameter settings. Experiments on UCI and Reuters text data show that the parameter optimized one-class classifiers outperform all the standard one-class learning schemes we examined.

Parameter estimation of one-class SVM on imbalance text classification

Compared with conventional two-class learning schemes, one-class classification simply uses a single class for training purposes. Applying one-class classification to the minorities in an imbalanced data has been shown to achieve better performance than the two-class one. In this paper, in order to make the best use of all the available information during the learning procedure, we propose a general framework which first uses the minority class for training in the one-class classification stage; and then uses both minority and majority class for estimating the generalization performance of the constructed classifier. Based upon this generalization performance measurement, parameter search algorithm selects the best parameter settings for this classifier. Experiments on UCI and Reuters text data show that one-class SVM embedded in this framework achieves much better performance than the standard one-class SVM alone and other learning schemes, such as one-class Naive Bayes, one-class nearest neighbour and neural network.

Ian's story : the complex interaction of ethnicity, class and masculinities

In this paper, a narrative is used to convey the complex connectedness that exists between class, ethnicity and masculinity. The story is of Ian, a successful academic who describes himself as Eurasian, and traces his development through parts of his childhood and into his professional career, using what Gough (1994) describes as a 'realistic fiction'. Relevant literature on masculinities and ethnicity is considered. There is some evidence to suggest that Ian has developed a fluid version of masculinity as a result of his Asian-Australian upbringing, and that he expresses different masculinities according to the social settings in which he finds himself. The paper concludes, just as Ian's story does, that masculinity interacts with class and ethnicity. This accords with Connell's (1995) caution that it is dangerous to think that there is a colored masculinity or a working class masculinity, and that the milieux of class and race need to be considered as well.