Timber ramp, Ocean View Farmhouse, Mt. Mee

Detail view of timber ramp and surrounding vegetation between ramp and house.

Gelatinisation of starch in mixtures of sugars. I. Dynamic rheological properties and behaviours of starch-honey systems

Dynamic rheological behaviour of starch-honey systems was studied using a strain-controlled rheometer. A dynamic temperature (30-130 degreesC) ramp test was used at 10 rad s(-1) frequency, 1% strain, 2 degreesC min(-1) ramp rate, 25 mm parallel plate, and 1.5 min gap, using Wheaten cornflour(TM) and five honeys to generate 25 formulations (0.34-0.80 g water/g dry starch). G', G, and eta* increased upon gelatinisation, and they reduced as the honey content was increased. For all the formulations, G' was higher than G, and tan 6 was generally less than 1.0. Key gelatinisation characterising temperatures (onset, peak and end) ranged from 96.0 to 122.3 degreesC, but did not vary much (CV < 5%) for each honey irrespective of the concentration. The influence of water, fructose and glucose, singly and in combination, on gelatinisation indices (temperature and rheological parameters) was investigated. An exponential equation was employed to describe the relationship, and relevant parameters were obtained. The consequences of the observations in the study are discussed particularly as they relate to extrusion of such systems, and possible interactions between fructose and glucose in the starch-honey systems. (C) 2003 Elsevier Ltd. All rights reserved.

Load profiling and data mining techniques in electricity deregulated market

This paper presents load profiles of electricity customers, using the knowledge discovery in databases (KDD) procedure, a data mining technique, to determine the load profiles for different types of customers. In this paper, the current load profiling methods are compared using data mining techniques, by analysing and evaluating these classification techniques. The objective of this study is to determine the best load profiling methods and data mining techniques to classify, detect and predict non-technical losses in the distribution sector, due to faulty metering and billing errors, as well as to gather knowledge on customer behaviour and preferences so as to gain a competitive advantage in the deregulated market. This paper focuses mainly on the comparative analysis of the classification techniques selected; a forthcoming paper will focus on the detection and prediction methods.

View along North-East elevation, Ocean View Farmhouse, Mount Mee

As seen from timber entrance ramp.

Main deck, Ocean View Farmhouse, Mt. Mee

View to main deck seating area and ramp to deck with landscape beyond.