Robotics and Sensor Networks

Robotics in mines, aerospace, underwater, everyday unstructured environments and sensor networks with communicating devices that collect data.

How nonprofit boards monitor, judge and influence organisational performance

The law and popular opinion expect boards of directors will actively monitor their organisations. Further, public opinion is that boards should have a positive impact on organisational performance. However, the processes of board monitoring and judgment are poorly understood, and board influence on organisational performance needs to be better understood. This thesis responds to the repeated calls to open the ‘black box’ linking board practices and organisational performance by investigating the processual behaviours of boards. The work of four boards1 of micro and small-sized nonprofit organisations were studied for periods of at least one year, using a processual research approach, drawing on observations of board meetings, interviews with directors, and the documents of the boards. The research shows that director turnover, the difficulty recruiting and engaging directors, and the administration of reporting, had strong impacts upon board monitoring, judging and/or influence. In addition, board monitoring of organisational performance was adversely affected by directors’ limited awareness of their legal responsibilities and directors’ limited financial literacy. Directors on average found all sources of information about their organisation’s work useful. Board judgments about the financial aspects of organisational performance were regulated by the routines of financial reporting. However, there were no comparable routines facilitating judgments about non-financial performance, and such judgments tended to be limited to specific aspects of performance and were ad hoc, largely in response to new information or the repackaging of existing information in a new form. The thesis argues that Weick’s theory of sensemaking offers insight into the way boards went about the task of understanding organisational performance. Board influence on organisational performance was demonstrated in the areas of: compliance; instrumental influence through service and through discussion and decision-making; and by symbolic, legitimating and protective means. The degree of instrumental influence achieved by boards depended on director competency, access to networks of influence, and understandings of board roles, and by the agency demonstrated by directors. The thesis concludes that there is a crowding out effect whereby CEO competence and capability limits board influence. The thesis also suggests that there is a second ‘agency problem’, a problem of director volition. The research potentially has profound implications for the work of nonprofit boards. Rather than purporting to establish a general theory of board governance, the thesis embraces calls to build situation-specific mini-theories about board behaviour.

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.

Browser security : a requirements-based approach

A browser is a convenient way to access resources located remotely on computer networks. Security in browsers has become a crucial issue for users who use them for sensitive applications without knowledge ofthe hazards. This research utilises a structure approach to analyse and propose enhancements to browser security. Standard evaluation for computer products is important as it helps users to ensure that the product they use is appropriate for their needs. Security in browsers, therefore, has been evaluated using the Common Criteria. The outcome of this was a security requirements profile which attempts to formalise the security needs of browsers. The information collected during the research was used to produce a prototype model for a secure browser program. Modifications to the Lynx browser were made to demonstrate the proposed enhancements.