Efficiently computing weighted proximity relationships in spatial databases

Spatial data mining recently emerges from a number of real applications, such as real-estate marketing, urban planning, weather forecasting, medical image analysis, road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and complicated problems. In this paper, we investigate the problem of evaluating the top k distinguished “features” for a “cluster” based on weighted proximity relationships between the cluster and features. We measure proximity in an average fashion to address possible nonuniform data distribution in a cluster. Combining a standard multi-step paradigm with new lower and upper proximity bounds, we presented an efficient algorithm to solve the problem. The algorithm is implemented in several different modes. Our experiment results not only give a comparison among them but also illustrate the efficiency of the algorithm.

Clustering strategies for object databases

When object databases arrived on the scene some ten years ago, they provided database capabilities for previously neglected, complex applications, such as CAD, but were burdened with one inherent teething problem, poor performance. Physical database design is one tool that can provide performance improvements and it is the general area of concern for this thesis. Clustering is one fruitful design technique which can provide improvements in performance. However, clustering in object databases has not been explored in depth and so has not been truly exploited. Further, clustering, although a physical concern, can be determined from the logical model. The object model is richer than previous models, notably the relational model, and so it is anticipated that the opportunities with respect to clustering are greater. This thesis provides a thorough analysis of object clustering strategies with a view to highlighting any links between the object logical and physical model and improving performance. This is achieved by considering all possible types of object logical model construct and the implementation of those constructs in terms of theoretical clusterings strategies to produce actual clustering arrangements. This analysis results in a greater understanding of object clustering strategies, aiding designers in the development process and providing some valuable rules of thumb to support the design process.

Functional polymers for biomedical application : synthesis and applications

Aromatic and aliphatic diacid chlorides were used to condense naturally occurring diamino acids and their esterified derivatives. It was anticipated the resulting functional polyamides would biodegrade to physiologically acceptable compounds and show pH dependant solubility could be used for biomedical applications ranging from enteric coatings to hydrosoluble drug delivery vehicles capable of targeting areas of low physiological pH. With these applications in mind the polymers were characterised by infra red spectroscopy, gel permeation chromatography and in the case of aqueous soluble polymers by potentiometric titration. Thin films of poly (lysine ethyl ester isophthalamide) plasticised with poly (caprolactone) were cast from DMSO/chloroform solutions and their mechanical properties measured on a Hounsfield Hti tensiometer. Interfacial synthesis was investigated as a synthetic route for the production of linear functional polyamides. High molecular weight polymer was obtained only when esterified diamino acids were condensed with aromatic diacid chlorides. The method was unsuitable for the production of copolymers of free and esterified amino acids with a diacid chloride. A novel miscible mixed solvent single phase reaction was investigated for production of copolymers of esterified and non-esterified amino acids with diacid chlorides. Aliphatic diacid chlorides were unsuitable for condensing diamino acids using this technique because of high rates of hydrolysis. The technique gave high molecular weight homopolymers from esterified diamino acids and aromatic diacid chlorides.