Score-level multibiometric fusion based on Dempster-Shafer theory incorporating uncertainty factors

While existing multi-biometic Dempster-Shafer the- ory fusion approaches have demonstrated promising perfor- mance, they do not model the uncertainty appropriately, sug- gesting that further improvement can be achieved. This research seeks to develop a unified framework for multimodal biometric fusion to take advantage of the uncertainty concept of Dempster- Shafer theory, improving the performance of multi-biometric authentication systems. Modeling uncertainty as a function of uncertainty factors affecting the recognition performance of the biometric systems helps to address the uncertainty of the data and the confidence of the fusion outcome. A weighted combination of quality measures and classifiers performance (Equal Error Rate) are proposed to encode the uncertainty concept to improve the fusion. We also found that quality measures contribute unequally to the recognition performance, thus selecting only significant factors and fusing them with a Dempster-Shafer approach to generate an overall quality score play an important role in the success of uncertainty modeling. The proposed approach achieved a competitive performance (approximate 1% EER) in comparison with other Dempster-Shafer based approaches and other conventional fusion approaches.

Robust iris recognition using decision fusion and degradation modelling

This thesis investigates the use of fusion techniques and mathematical modelling to increase the robustness of iris recognition systems against iris image quality degradation, pupil size changes and partial occlusion. The proposed techniques improve recognition accuracy and enhance security. They can be further developed for better iris recognition in less constrained environments that do not require user cooperation. A framework to analyse the consistency of different regions of the iris is also developed. This can be applied to improve recognition systems using partial iris images, and cancelable biometric signatures or biometric based cryptography for privacy protection.

Micro, small and medium enterprise in insolvency: An international perspective

UNCITRAL Working Group I is presently developing a legal framework dealing with the entire lifecycle of Micro, Small and Medium Enterprises. The central focus of this work is to guide MSMEs in developing countries out of the grey economy and into the regulated, tax-paying space where these business will also have greater access to legitimate finance. Insolvency is an important, perhaps inevitable aspect of the life cycle of these enterprises. The question that is yet to be considered is a simplified insolvency regime for MSMEs. While the Working Group I is focused on the development of a model for developing economies, MSMEs in robust, highly developed economies also face particular challenges when faced with a solvency crisis. The present one-fits-all approach to insolvency requires a rethink.

Development of an EMR implementation framework for public hospitals in Saudi Arabia

An Electronic Medical Record (EMR) is a system that has been embraced by healthcare providers worldwide. However, the implementation success of EMRs has varied widely. Studies have identified both barriers to and facilitators for implementing EMRs within healthcare organisations. In Saudi Arabia (SA), the majority of healthcare providers manage patient records manually. As public hospitals are a major provider of health services in SA and have been shown to face more EMR implementation barriers than private hospitals, there is a need for an implementation framework to guide EMR implementation in Saudi public hospitals. This doctoral project therefore aimed to develop an evidence-based EMR implementation framework for public hospitals in SA informed by those who work at the micro-implementation level and the macro-implementation level and the extant literature sensitive to the cultural, resource-related, and technological, organisational, and environmental issues of SA.