Institution
University of South Australia
Education•Adelaide, South Australia, Australia•
About: University of South Australia is a education organization based out in Adelaide, South Australia, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 10086 authors who have published 32587 publications receiving 913683 citations. The organization is also known as: The University of South Australia & UniSA.
Topics: Population, Poison control, Health care, Mental health, Adsorption
Papers published on a yearly basis
Papers
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TL;DR: In this article, the authors present a textbook-style introduction to the processes required for use in university teaching and for self-study purposes by people working in the field of IT system development.
Abstract: This book concerns the process of designing IT systems for large, complex purposes. It is structured as a textbook-style introduction to the processes required for use in university teaching and for self-study purposes by people working in the field of IT system development. The content of the book is the fruit of a decade of research by the authors in their pursuit of a method to plan and design IT projects that will provide sustainable, useful solutions to the needs of the companies for which they are commissioned.
268 citations
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TL;DR: In this paper, the authors draw insights from the group value model as a theoretical extension to explain employees' negative responses to psychological contract breach, which results in less willingness on the part of the employees to engage in organizational citizenship behaviours (OCBs).
Abstract: Research on psychological contract breach has referenced social exchange as its dominant theoretical foundation. In this study, we draw insights from the group value model as a theoretical extension to explain employees’ negative responses to psychological contract breach. According to the group value model, fair treatment by group members communicates symbolic messages about the relationship between the organization and the employee, and has implications for whether employees can take pride in their organizational membership. When people are treated unfairly, they lose trust in the organization and dis-identify from the group. This in turn results in less willingness on the part of the employees to engage in organizational citizenship behaviours (OCBs). We tested these relationships across three studies. In Study 1, we conducted a longitudinal test of the role of trust as a mediator between breach and organizational identification. In Studies 2 (cross-sectional) and 3 (longitudinal), we tested the complete model in which we examined the role of trust and identification in mediating the link between breach and OCBs. All three studies provided support for the mediated model. Furthermore, as predicted by the group value model, the hypothesized relationships emerged in response to relational but not transactional contract breaches. Theoretical and applied implications are discussed.
267 citations
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TL;DR: Two simple ways to use a genetic algorithm (GA) to design a multiple-classifier system are suggested that can be made less prone to overtraining by including penalty terms in the fitness function accounting for the number of features used.
Abstract: We suggest two simple ways to use a genetic algorithm (GA) to design a multiple-classifier system. The first GA version selects disjoint feature subsets to be used by the individual classifiers, whereas the second version selects (possibly) overlapping feature subsets, and also the types of the individual classifiers. The two GAs have been tested with four real data sets: heart, Satimage, letters, and forensic glasses. We used three-classifier systems and basic types of individual classifiers (the linear and quadratic discriminant classifiers and the logistic classifier). The multiple-classifier systems designed with the two GAs were compared against classifiers using: all features; the best feature subset found by the sequential backward selection method; and the best feature subset found by a CA. The GA design can be made less prone to overtraining by including penalty terms in the fitness function accounting for the number of features used.
267 citations
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TL;DR: The shorter the task sampling time, the less sensitive the test is to sleepiness, and the 5-min PVT may provide a viable alternative to the 10- Min psychomotor vigilance task for some performance metrics.
Abstract: The 10-min psychomotor vigilance task (PVT) has often been used to assess the impact of sleep loss on performance. Due to time constraints, however, regular testing may not be practical in field studies. The aim of the present study was to examine the suitability of tests shorter than 10 min. in duration. Changes in performance across a night of sustained wakefulness were compared during a standard 10-min PVT, the first 5 min of the PVT, and the first 2 min of the PVT. Four performance metrics were assessed: (1) mean reaction time (RT), (2) fastest 10% of RT, (3) lapse percentage, and (4) slowest 10% of RT. Performance during the 10-min PVT significantly deteriorated with increasing wakefulness for all metrics. Performance during the first 5 min and the first 2 min of the PVT deteriorated in a manner similar to that observed for the whole 10-min task, with all metrics except lapse percentage displaying significant impairment across the night. However, the shorter the task sampling time, the less sensitive the test is to sleepiness. Nevertheless, the 5-min PVT may provide a viable alternative to the 10-min PVT for some performance metrics.
266 citations
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TL;DR: This study uses data from a regional planning study in Australia to describe and evaluate alternative methods for identifying land use conflict potential and demonstrates application of the conflict mapping model using residential and industrial development in the region.
265 citations
Authors
Showing all 10298 results
Name | H-index | Papers | Citations |
---|---|---|---|
Andrew P. McMahon | 162 | 415 | 90650 |
Timothy P. Hughes | 145 | 831 | 91357 |
Jeremy K. Nicholson | 141 | 773 | 80275 |
Peng Shi | 137 | 1371 | 65195 |
Daniel Thomas | 134 | 846 | 84224 |
Jian Li | 133 | 2863 | 87131 |
Matthew Jones | 125 | 1161 | 96909 |
Ulrich S. Schubert | 122 | 2229 | 85604 |
Elaine Holmes | 119 | 560 | 58975 |
Arne Astrup | 114 | 866 | 68877 |
Richard Gray | 109 | 808 | 78580 |
John B. Furness | 103 | 597 | 37668 |
Thomas J. Jentsch | 101 | 238 | 32810 |
Ben W.J. Mol | 101 | 1485 | 47733 |
John C. Lindon | 99 | 488 | 44063 |