Network control for a multi-user transputer-based system.

A dissertation submitted to the Faculty of Engineering, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in EngineeringThe MC2/64 system is a configureable multi-user transputer- based system which was designed using a modular approach. The MC2/64 consists of MC2 Clusters which are connected using a modified Clos network. The MC2 Clusters were designed and realised as completely configurable modules using and extending an algorithm based on Eulerian cycles through a requested graph. This dissertation discusses the configuration algorithm and the extensions made to the algorithm for the MC2 Clusters. The total MC2/64 system is not completely configurable as a MC2 Cluster releases only a limited number of links for inter-cluster connections. This dissertation analyses the configurability of MC2/64, but also presents algorithms which enhance the usability of the system from the user's point of view. The design and the implementation of the network control software are also submitted as topics in this dissertation. The network control software must allow multiple users to use the system, but without them influencing each other's transputer domains. This dissertation therefore seeks to give an overview of network control problems and the solutions implemented in current MC2/64 systems. The results of the research done for this dissertation will hopefully aid in the design of future MC2 systems which will provide South Africa with much needed, low cost, high performance computing power.Andrew Chakane 201

Team design patterns for moral decisions in hybrid intelligent systems: A case study of bias mitigation

Increasing automation in the healthcare sector calls for a Hybrid Intelligence (HI) approach to closely study and design the collaboration of humans and autonomous machines. Ensuring that medical HI systems' decision-making is ethical is key. The use of Team Design Patterns (TDPs) can advance this goal by describing successful and reusable configurations of design problems in which decisions have a moral component and facilitating communication in multidisciplinary teams designing HI systems. For this research, TDPs were developed describing a set of solutions for a design problem in a medical HI system: mitigating harmful biases in machine learning algorithms. The Socio-Cognitive Engineering (SCE) methodology was employed, integrating operational demands, human factors knowledge, and a technological analysis into a set of TDPs. A survey was created to assess the usability of the patterns with regards to their understandability, effectiveness, and generalizability. Results showed that TDPs are a useful method to unambiguously describe solutions for diverse HI design problems with a moral component on varying abstraction levels, usable by a heterogeneous group of multidisciplinary researchers. Additionally, results indicated that the SCE approach and the developed questionnaire are suitable methods for creating and assessing TDPs