Generating rules with predicates, terms and variables from the pruned neural networks

Artificial neural networks (ANN) have demonstrated good predictive performance in a wide range of applications. They are, however, not considered sufficient for knowledge representation because of their inability to represent the reasoning process succinctly. This paper proposes a novel methodology Gyan that represents the knowledge of a trained network in the form of restricted first-order predicate rules. The empirical results demonstrate that an equivalent symbolic interpretation in the form of rules with predicates, terms and variables can be derived describing the overall behaviour of the trained ANN with improved comprehensibility while maintaining the accuracy and fidelity of the propositional rules.

Does the summative assessment of real world learning using criterion-referenced assessment need to be discipline specific?

This paper synthesises the existing literature on the contemporary conception of ‘real world’ and compares it with similar notions such as ‘authentic’ and ‘work integrated learning’. While the term ‘real world’ may be partly dependent on the discipline, it does not necessarily follow that the criterion-referenced assessment of ‘real world’ assessment must involve criteria and performance descriptors that are discipline specific. Two examples of summative assessment (court report and trial process exercise) from a final year core subject at the Queensland University of Technology, LWB432 Evidence, emphasise real world learning, are authentic, innovative and better prepare students for the transition into the workplace than more generic forms of assessment such as tutorial participation or oral presentations. The court report requires students to attend a criminal trial in a Queensland Court and complete a two page report on what they saw in practice compared with what they learned in the classroom. The trial process exercise is a 50 minute written closed book activity conducted in tutorials, where students plan questions that they would ask their witness in examination-in-chief, plan questions that they would ask their opponent’s witness in cross-examination, plan questions that they would ask in reexamination given what their opponent asked in cross-examination, and prepare written objections to their opponent’s questions. The trial process exercise simulates the real world, whereas the court report involves observing the real world, and both assessment items are important to the role of counsel. The design of the criterion-referenced assessment rubrics for the court report and trial process exercise is justified by the literature. Notably, the criteria and performance descriptors are not necessarily law specific and this paper highlights the parts that may be easily transferred to other disciplines.

The Criminal Codes : Commentary and Materials

This edition has been substantially revised to increase overall clarity and to ensure a balanced examination of the criminal law in the 'Code' states, Queensland and Western Australia. The work has been brought up-to-date in all areas and provides valuable comment on the recent wide-reaching reforms to the law of homicide in Western Australia. Significant developments in both states discussed in this edition include: The abolition of wilful murder and infanticide, and the new definition of murder (WA); The introduction of the new offence of unlawful assault causing death (WA); The abolition of provocation to murder (WA), and whether this excuse still has a part to play (Qld); The reformulation of the excuse of self-defence, and the introduction of excessive self-defence (WA); The creation of offences for drink spiking (Qld and WA); and Current and proposed sentencing considerations (Qld and WA). Fundamental principles of the criminal law are illustrated throughout the book by selected extracts from the Codes and case law, while additional materials foster critical reflection on the law and the need for reform.

Enhancing digital road map with lane details extracted from large-scale stereo aerial imagery using object-oriented image analysis

Precise, up-to-date and increasingly detailed road maps are crucial for various advanced road applications, such as lane-level vehicle navigation, and advanced driver assistant systems. With the very high resolution (VHR) imagery from digital airborne sources, it will greatly facilitate the data acquisition, data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lane information from aerial images with employment of the object-oriented image analysis method. Our proposed algorithm starts with constructing the DSM and true orthophotos from the stereo images. The road lane details are detected using an object-oriented rule based image classification approach. Due to the affection of other objects with similar spectral and geometrical attributes, the extracted road lanes are filtered with the road surface obtained by a progressive two-class decision classifier. The generated road network is evaluated using the datasets provided by Queensland department of Main Roads. The evaluation shows completeness values that range between 76% and 98% and correctness values that range between 82% and 97%.

Towards an automatic road lane marks extraction based on ISODATA segmentation and shadow detection from large-scale aerial images

The automatic extraction of road features from remote sensed images has been a topic of great interest within the photogrammetric and remote sensing communities for over 3 decades. Although various techniques have been reported in the literature, it is still challenging to efficiently extract the road details with the increasing of image resolution as well as the requirement for accurate and up-to-date road data. In this paper, we will focus on the automatic detection of road lane markings, which are crucial for many applications, including lane level navigation and lane departure warning. The approach consists of four steps: i) data preprocessing, ii) image segmentation and road surface detection, iii) road lane marking extraction based on the generated road surface, and iv) testing and system evaluation. The proposed approach utilized the unsupervised ISODATA image segmentation algorithm, which segments the image into vegetation regions, and road surface based only on the Cb component of YCbCr color space. A shadow detection method based on YCbCr color space is also employed to detect and recover the shadows from the road surface casted by the vehicles and trees. Finally, the lane marking features are detected from the road surface using the histogram clustering. The experiments of applying the proposed method to the aerial imagery dataset of Gympie, Queensland demonstrate the efficiency of the approach.

Leveraging managed frameworks from modular languages

Managed execution frameworks, such as the.NET Common Language Runtime or the Java Virtual Machine, provide a rich environment for the creation of application programs. These execution environments are ideally suited for languages that depend on type-safety and the declarative control of feature access. Furthermore, such frameworks typically provide a rich collection of library primitives specialized for almost every domain of application programming. Thus, when a new language is implemented on one of these frameworks it becomes necessary to provide some kind of mapping from the new language to the libraries of the framework. The design of such mappings is challenging since the type-system of the new language may not span the domain exposed in the library application programming interfaces (APIs). The nature of these design considerations was clarified in the implementation of the Gardens Point Component Pascal (gpcp) compiler. In this paper we describe the issues, and the solutions that we settled on in this case. The problems that were solved have a wider applicability than just our example, since they arise whenever any similar language is hosted in such an environment.

The costs arising from pressure ulcers attributable to malnutrition

Aim To estimate the economic consequences of pressure ulcers attributable to malnutrition. Method Statistical models were developed to predict the number of cases of pressure ulcer, associated bed days lost and the dollar value of these losses in public hospitals in 2002/2003 in Queensland, Australia. The following input parameters were specified and appropriate probability distributions fitted • Number of at risk discharges per annum • Incidence rate for pressure ulcer • Attributable fraction of malnutrition in the development of pressure ulcer • Independent effect of pressure ulcer on length of hospital stay • Opportunity cost of hospital bed day One thousand random re-samples were made and the results expressed as (output) probabilistic distributions. Results The model predicts a mean 16060 (SD 5 671) bed days lost and corresponding mean economic cost of AU$12 968 668 (SD AU$4 924 148) (EUROS 6 925 268 SD 2 629 495; US$ 7 288 391 SD 2 767 371) of pressure ulcer attributable to malnutrition in 2002/2003 in public hospitals in Queensland, Australia. Conclusion The cost of pressure ulcer attributable to malnutrition in bed days and dollar terms are substantial. The model only considers costs of increased length of stay associated with pressure ulcer and not other factors associated with care.

How well are Australian infants and children aged 4 to 5 years doing? Findings from the Longitudinal Study of Australian Children Wave 1

This report presents an analysis of the data from the first wave of the Longitudinal Study of Australian Children (LSAC) to explore the wellbeing of 5,107 children in the infant cohort of the study and the 4,983 children, aged 4 to 5 years, in the child cohort. Wave 1 of LSAC includes measures of multiple aspects of children’s early development. These developmental measures are summarised in the LSAC Outcome Index, a composite measure which includes an overall index as well as three separate domain scores, tapping physical development, social and emotional functioning, and learning and cognitive development.