A case based model to assist in the design process in the manufacture of furniture products

This paper describes progress on a project to utilise case based reasoning methods in the design and manufacture of furniture products. The novel feature of this research is that cases are represented as structures in a relational database of products, components and materials. The paper proposes a method for extending the usual "weighted sum" over attribute similarities for a ·single table to encompass relational structures over several tables. The capabilities of the system are discussed, particularly with respect to differing user objectives, such as cost estimation, CAD, cutting scheme re-use, and initial design. It is shown that specification of a target case as a relational structure combined with suitable weights can fulfil several user functions. However, it is also shown that some user functions cannot satisfactorily be specified via a single target case. For these functions it is proposed to allow the specification of a set of target cases. A derived similarity measure between individuals and sets of cases is proposed.

Applying CBR to measure similarity of software design structures

This paper examines different ways for measuring similarity between software design models for the purpose of software reuse. Current approaches to this problem are discussed and a set of suitable similarity metrics are proposed and evaluated. Work on the optimisation of weights to increase the competence of a CBR system is presented. A graph matching algorithm and associated metrics capturing the structural similarity between UML class diagrams is presented and demonstrated through an example case.

A critical examination of node-similarity based graph matching algorithms

In this paper, we shall critically examine a special class of graph matching algorithms that follow the approach of node-similarity measurement. A high-level algorithm framework, namely node-similarity graph matching framework (NSGM framework), is proposed, from which, many existing graph matching algorithms can be subsumed, including the eigen-decomposition method of Umeyama, the polynomial-transformation method of Almohamad, the hubs and authorities method of Kleinberg, and the kronecker product successive projection methods of Wyk, etc. In addition, improved algorithms can be developed from the NSGM framework with respects to the corresponding results in graph theory. As the observation, it is pointed out that, in general, any algorithm which can be subsumed from NSGM framework fails to work well for graphs with non-trivial auto-isomorphism structure.

Measuring similarity of software designs using graph matching for CBR

This paper examines different ways of measuring similarity between software design models for Case Based Reasoning (CBR) to facilitate reuse of software design and code. The paper considers structural and behavioural aspects of similarity between software design models. Similarity metrics for comparing static class structures are defined and discussed. A Graph representation of UML class diagrams and corresponding similarity measures for UML class diagrams are defined. A full search graph matching algorithm for measuring structural similarity diagrams based on the identification of the Maximum Common Sub-graph (MCS) is presented. Finally, a simple evaluation of the approach is presented and discussed.

Intrinsic measure of diversity gains in generalised distributed antenna systems with cooperative users

The diversity gains achievable in the generalised distributed antenna system with cooperative users (GDAS-CU) are considered. A GDAS-CU is comprised of M largely separated access points (APs) at one side of the link, and N geographically closed user terminals (UTs) at the other side. The UTs are collaborating together to enhance the system performance, where an idealised message sharing among the UTs is assumed. First, geometry-based network models are proposed to describe the topology of a GDAS-CU. The mean cross-correlation coefficients of signals received from non-collocated APs and UTs are calculated based on the network topology and the correlation models derived from the empirical data. The analysis is also extendable to more general scenarios where the APs are placed in a clustered form due to the constraints of street layout or building structure. Subsequently, a generalised signal attenuation model derived from several stochastic ray-tracing-based pathloss models is applied to describe the power-decaying pattern in urban built-up areas, where the GDAS-CU may be deployed. Armed with the cross-correlation and pathloss model preliminaries, an intrinsic measure of cooperative diversity obtainable from a GDAS-CU is then derived, which is the number of independent fading channels that can be averaged over to detect symbols. The proposed analytical framework would provide critical insight into the degree of possible performance improvement when combining multiple copies of the received signal in such systems.