A key concern for professionals in any industry is ensuring regulatory compliance. Regulations are often complex and require in depth technical knowledge of the domain in which they operate. The level of technical detail and complexity in regulations is a barrier to their automation due to extensive software development time and costs that are involved. In this paper we present a rulebased semantic approach formulated as a methodology to overcome these issues by allowing domain experts to specify their own regulatory compliance systems without the need for extensive software development. Our methodology is based on the key idea that three semantic contexts are needed to fully understand the regulations being automated: the semantics of the target domain, the specific semantics of regulations being considered, and the semantics of the data format that is to be checked for compliance. This approach allows domain experts to create and maintain their own regulatory compliance systems, within a semantic domain that is familiar to them. At the same time, our approach allows for the often diverse nature of semantics within a particular domain by decoupling the specific semantics of regulations from the semantics of the domain itself. This paper demonstrates how our methodology has been validated using a series of regulations automated by professionals within the construction domain. The regulations that have been developed are then in turn validated on real building data stored in an industry specific format (the IFCs). The adoption of this methodology has greatly advanced the process of automating these complex sets of construction regulations, allowing the full automation of the regulation scheme within 18 months. We believe that these positive results show that, by adopting our methodology, the barriers to the building of regulatory compliance systems will be greatly lowered and the adoption of three semantic domains proposed by our methodology provides tangible benefits.

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tDepartment ofElectrical Engineering, University ofLagos, Nigeria 1 INTRODUCTION Models are artifices which are widely used for various analyses. A model may be considered realistic if it lends itself to physical interpretations; and its accuracy may be judged by how its performance agrees with experimental evidence. A simple model is also desirable since this permits straightforward analyses. The problem of finding a model for the transistor has been extensively studied. It is generally agreed that different models must be used for different frequency ranges; and that a model's complexity increases with frequency.OUins and Ratner (1972) derived a three-section distributed transistor model over a frequency range of 0.1 to 1 GHz. Numerical values for the elements of the model were obtained by a computer program. The Sparameters predicted by this model were in good agreement with measurements. However, possessing 8 nodes and 22 elements, the model is a complex one. Another complex model was derived by Hartmann et al. (1972) over a frequency range of 4 to 8 GHz. This model has 11 nodes and 18 elements and numerical values for the elements were also obtained with the aid of a computer program. Hughes (1972) has derived a much simpler model which has 8 nodes and 11 elements; and the model's S-parameters agreed with measurements between 4 and 5 GHz.The transistor model presented here is even simpler than that of Hughes. Numerical values for the elements were obtained by using a general-purpose circuit analysis program; this makes the modelling technique readily applicable. Models were derived for two types of transistors -Hewlett-Packard's 35821 E and AEI's DC5410 -and the Sparameters predicted by these models were in good agreement with measurements between 0.8 and 2 GHz. THE PROPOSED MODEL TopologyThe topological derivation of the proposed model was quite straightforward. Beginning with the well-known hybrid-pi high-frequency model of Fig. 1, a few modifications were made in order to adapt it for the U.H.F. work. The first was the inclusion of excess phase shift (arising from the influence of drift field on carriers), by letting g.; become complex. The second was the addition of the base and emitter 327