GYAN: A methodology for rule extraction from artificial neural networks

Artificial neural network (ANN) learning methods provide a robust and non-linear approach to approximating the target function for many classification, regression and clustering problems. ANNs have demonstrated good predictive performance in a wide variety of practical problems. However, there are strong arguments as to why ANNs are not sufficient for the general representation of knowledge. The arguments are the poor comprehensibility of the learned ANN, and the inability to represent explanation structures. The overall objective of this thesis is to address these issues by: (1) explanation of the decision process in ANNs in the form of symbolic rules (predicate rules with variables); and (2) provision of explanatory capability by mapping the general conceptual knowledge that is learned by the neural networks into a knowledge base to be used in a rule-based reasoning system. A multi-stage methodology GYAN is developed and evaluated for the task of extracting knowledge from the trained ANNs. The extracted knowledge is represented in the form of restricted first-order logic rules, and subsequently allows user interaction by interfacing with a knowledge based reasoner. The performance of GYAN is demonstrated using a number of real world and artificial data sets. The empirical results demonstrate that: (1) an equivalent symbolic interpretation is derived describing the overall behaviour of the ANN with high accuracy and fidelity, and (2) a concise explanation is given (in terms of rules, facts and predicates activated in a reasoning episode) as to why a particular instance is being classified into a certain category.

Imagination

Imagination is a capacity of internal visualization, concept creation and manipulation not directly dependent upon sensation. Imagination is associated with a range of phenomena: mental imagery, fancy, inventiveness, insight, counterfactual reasoning, pretence, simulation and conceivability.

Values, wellness and the social sciences curriculum

Recent initiatives in values education in Australia emphasise the importance of the process of valuing and general methodologies that foster this in the classroom. Although a range of strategies are available, this chapter argues that inquiry-based approaches in the Social Sciences play a significant role in linking valuing processes with decision making skills. Collectively, these approaches prompt the development of reasoning and self awareness which also impact on student wellness. This chapter proposes some curriculum approaches to foreground values education in the Australian Social Sciences classroom. It argues that valuing is an important life skill that can be cultivated in the classroom through specific valuing strategies. It contends that the development of the capacity to make informed value choices is a critical factor in promoting wellness and resilience in students and in preparing them for the decision making skills required for effective participation in society.

Political theory and theoretical physics

This paper argues, somewhat along a Simmelian line, that political theory may produce practical and universal theories like those developed in theoretical physics. The reasoning behind this paper is to show that the theory of ‘basic democracy’ may be true by way of comparing it to Einstein’s Special Relativity – specifically concerning the parameters of symmetry, unification, simplicity, and utility. These parameters are what make a theory in physics as meeting them not only fits with current knowledge, but also produces paths towards testing (application). As the theory of ‘basic democracy’ may meet these same parameters, it could settle the debate concerning the definition of democracy. This will be argued firstly by discussing what the theory of ‘basic democracy’ is and why it differs from previous work; secondly by explaining the parameters chosen (as in why these and not others confirm or scuttle theories); and thirdly by comparing how Special Relativity and the theory of ‘basic democracy’ may match the parameters.

Strategic infrastructure asset management: the way forward

Organisations owning and managing infrastructure asset are constantly striving to obtain the greatest lifetime value from their infrastructure assets. Many such organisations have adopted the concept of “asset management” with the aim of improving the performance of their infrastructure assets. This paper evaluates the adoption of asset management to improve performance in the context of organisations managing infrastructure assets. Relevant previous research studies on main barriers to the adoption of asset management are reviewed. Analysis of these findings, together with deductive reasoning, leads to the development of the proposed improvement strategies. Three issues were identified as barrier to the advancement of the concept of asset management. They are (1) lack of recognition, (2) fragmentation; and (3) growing complexity. To overcome these issues, this paper suggests that the organisations manage infrastructure assets must (1) adopt a more strategic approach in the management of infrastructure assets, (2) develop a framework of strategic infrastructure asset management processes, and (3) identify the core capabilities needed in the management of infrastructure assets. This paper presents the direction for further research to advance the concept of asset management in the management of infrastructure asset.

The role of emotional intelligence in moral judgement

In this study we investigated the potential role of emotional intelligence (EI) in moral reasoning (MR). A sample of 131 undergraduate students completed a battery of psychological tests, which included measures of EI, MR and the Big Five dimensions of personality. Results revealed support for a proposed model of the relationship between emotional intelligence, personality and moral reasoning. Specifically, emotional intelligence was found to be a significant predictor of four of the Big Five personality dimensions (extraversion, openness, neuroticism, agreeableness), which in turn were significant predictors of moral reasoning. These results have important implications in regards to our current understanding of the relationships between EI, moral reasoning and personality. We emphasise the need to incorporate the constructs of EI and moral reasoning into a broader, explanatory personality framework.

Betting on the underdog : bricolage as an engine of resource advantage

Resource-based theory posits that firms achieve high performance by controlling resources that are rare, valuable and costly for others to duplicate or work around. Yet scholars have been less successful understanding processes and behaviours by which firms develop such resources. We draw on the behavioral theory of bricolage from the entrepreneurship literature to suggest one such mechanism by which firms may develop such resource-based advantages. The core of our argument is that idiosyncratic bundling processes synonymous with bricolage behavior may create advantageous resource positions by (i) allowing resource constrained firms to allocate more of their limited resources to activities that they view as more strategically important, and (ii) increasing the difficulties other firms face in trying to imitate these advantages. Based on this reasoning we develop several hypotheses which we test in the context of several samples from a large, longitudinal, Australian study of new firm development. The results support our arguments that bricolage will improve a firms’ overall resource positions while generating more areas of strong resource advantage and fewer areas of strong resource disadvantage. We find little support, however, for our arguments that bricolage will make a firms’ key resource advantages more difficult for other firms to imitate. We find some support for our argument that the role of bricolage in creating resource advantages will be enhanced by the quality of the opportunity with which a firm is engaged.

Three primary school students’ cognition about 3D rotation in a virtual reality learning environment

This paper reports on three primary school students’ explorations of 3D rotation in a virtual reality learning environment (VRLE) named VRMath. When asked to investigate if you would face the same direction when you turn right 45 degrees first then roll up 45 degrees, or when you roll up 45 degrees first then turn right 45 degrees, the students found that the different order of the two turns ended up with different directions in the VRLE. This was contrary to the students’ prior predictions based on using pen, paper and body movements. The findings of this study showed the difficulty young children have in perceiving and understanding the non-commutative nature of 3D rotation and the power of the computational VRLE in giving students experiences that they rarely have in real life with 3D manipulations and 3D mental movements.

A Bayesian approach for place recognition

This paper presents a robust place recognition algorithm for mobile robots. The framework proposed combines nonlinear dimensionality reduction, nonlinear regression under noise, and variational Bayesian learning to create consistent probabilistic representations of places from images. These generative models are learnt from a few images and used for multi-class place recognition where classification is computed from a set of feature-vectors. Recognition can be performed in near real-time and accounts for complexity such as changes in illumination, occlusions and blurring. The algorithm was tested with a mobile robot in indoor and outdoor environments with sequences of 1579 and 3820 images respectively. This framework has several potential applications such as map building, autonomous navigation, search-rescue tasks and context recognition.

Primary students’ interpretation of maps : gesture use and mapping knowledge

Maps are used to represent three-dimensional space and are integral to a range of everyday experiences. They are increasingly used in mathematics, being prominent both in school curricula and as a form of assessing students understanding of mathematics ideas. In order to successfully interpret maps, students need to be able to understand that maps: represent space, have their own perspective and scale, and their own set of symbols and texts. Despite the fact that maps have an increased prevalence in society and school, there is evidence to suggest that students have difficulty interpreting maps. This study investigated 43 primary-aged students’ (aged 9-12 years) verbal and gestural behaviours as they engaged with and solved map tasks. Within a multiliteracies framework that focuses on spatial, visual, linguistic, and gestural elements, the study investigated how students interpret map tasks. Specifically, the study sought to understand students’ skills and approaches used to solving map tasks and the gestural behaviours they utilised as they engaged with map tasks. The investigation was undertaken using the Knowledge Discovery in Data (KDD) design. The design of this study capitalised on existing research data to carry out a more detailed analysis of students’ interpretation of map tasks. Video data from an existing data set was reorganised according to two distinct episodes—Task Solution and Task Explanation—and analysed within the multiliteracies framework. Content Analysis was used with these data and through anticipatory data reduction techniques, patterns of behaviour were identified in relation to each specific map task by looking at task solution, task correctness and gesture use. The findings of this study revealed that students had a relatively sound understanding of general mapping knowledge such as identifying landmarks, using keys, compass points and coordinates. However, their understanding of mathematical concepts pertinent to map tasks including location, direction, and movement were less developed. Successful students were able to interpret the map tasks and apply relevant mathematical understanding to navigate the spatial demands of the map tasks while the unsuccessful students were only able to interpret and understand basic map conventions. In terms of their gesture use, the more difficult the task, the more likely students were to exhibit gestural behaviours to solve the task. The most common form of gestural behaviour was deictic, that is a pointing gesture. Deictic gestures not only aided the students capacity to explain how they solved the map tasks but they were also a tool which assisted them to navigate and monitor their spatial movements when solving the tasks. There were a number of implications for theory, learning and teaching, and test and curriculum design arising from the study. From a theoretical perspective, the findings of the study suggest that gesturing is an important element of multimodal engagement in mapping tasks. In terms of teaching and learning, implications include the need for students to utilise gesturing techniques when first faced with new or novel map tasks. As students become more proficient in solving such tasks, they should be encouraged to move beyond a reliance on such gesture use in order to progress to more sophisticated understandings of map tasks. Additionally, teachers need to provide students with opportunities to interpret and attend to multiple modes of information when interpreting map tasks.

Policy filtering with XACML

This paper presents a modified approach to evaluate access control policy similarity and dissimilarity based on the proposal by Lin et al. (2007). Lin et al.'s policy similarity approach is intended as a filter stage which identifies similar XACML policies that can be analysed further using more computationally demanding techniques based on model checking or logical reasoning. This paper improves the approach of computing similarity of Lin et al. and also proposes a mechanism to calculate a dissimilarity score by identifying related policies that are likely to produce different access decisions. Departing from the original algorithm, the modifications take into account the policy obligation, rule or policy combining algorithm and the operators between attribute name and value. The algorithms are useful in activities involving parties from multiple security domains such as secured collaboration or secured task distribution. The algorithms allow various comparison options for evaluating policies while retaining control over the restriction level via a number of thresholds and weight factors.