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This thesis describes the detailed modelling procedures for d-q axis representation of multi-machine electromechanical systems. It proposes two methods of connecting electrical machine models which have been formulated in various reference frames, to transmission network models. Investigation of these two methods was accomplished, and the effectiveness and merits of each are fully discussed. Conclusions are drawn which form the bases for recommendation of a connection method for developing a generalised multi-machine power system model. In addition two computer programs are written to provide means of simulating both large and limited capacity power systems on personal computers.

One of the most difficult problems in modern biochemistry is that of accurately predicting a protein's three dimensional structure from its sequence (the <I>protein folding problem</I>). This structure is essential for a proper understanding of how a protein functions. As experimental derivation of a protein's structure is far more time consuming than deriving a protein's sequence, prediction of structure from sequence is an important goal for many protein biochemists; several methods have been suggested for this. Given a protein of known structure of similar sequence to the protein you wish to model homology modelling is the method most likely to produce a fairly good model. In this work a tool was produced for examining the various stages of homology modelling and analysing how well various method for carrying out these stages perform. The tool produced consists of an object-oriented database of protein structures and testbed software written in a mixture of PROLOG and DAPLEX. Tests were carried out using this software to examine the predictivity of various guidelines suggested in the literature for the loop selection stage of cut and paste homology modelling. The results of these tests produced surprising new information on the relative importance of different factors which may be used to choose between candidate fragments for the variable regions of a protein being modelled. The results of the application of these automated modelling methods were then compared with a short series of modelling tests using human modellers in an attempt to measure how the usual modelling procedures using 'hand and eye' compare with automated measures. Finally the results of the tests carried out were used to guide the production of a model of a previously unmodelled serine proteinase.

A description of the development and subsequent use of an integrated and semi-stochastic computer simulation model, <I>GHAFORGROM</I> (Ghana Forest Growth and Yield Simulation Program), designed to investigate forest tree dynamics and also predict growth and yield of timber in the tropical forests of Ghana is presented. This simulator considers many aspects of natural forest growth including species-group-specific individual tree diameter growth based on competition, mortality and recruitment. The 687 tree species used in these studies have been aggregated into 13 species groups. The simulator is based on a new individual tree-based distance-dependent diameter increment model. Diameter increment of a tree is predicted by a multiplicative composite function of initial diameter, relative tree dominance index, and (or) categorical site index. The based function of diameter increment on diameter is an extension of a power-exponential growth function. The relative tree dominance index of a subject tree is defined in terms of a new competition index. This index is the sum of the ratios of volume of overtopping competing trees to the volume of the subject tree, where the competitor trees are within a radius of 20 m of the subject tree for large-sized trees and 1.5 m of the subject tree for medium- and small-sized trees. The probability of mortality of a tree is defined in the form of a logistic function based on the explanatory variables of functions of diameter and stand density, including basal area per hectare and volume per hectare for each species group. The total amount of recruitment at 10 cm diameter is predicted as a linear function of stand basal area, stand volume and categorical site variables. It is hoped that the model will provide practical steps to improved natural tropical forest management in Ghana, leading to higher sustainable timber yields.

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