The effects of normalisation on the ability of business end-users to detect data anomalies: An experimental evaluation

With the proliferation of relational database programs for PC's and other platforms, many business end-users are creating, maintaining, and querying their own databases. More importantly, business end-users use the output of these queries as the basis for operational, tactical, and strategic decisions. Inaccurate data reduce the expected quality of these decisions. Implementing various input validation controls, including higher levels of normalisation, can reduce the number of data anomalies entering the databases. Even in well-maintained databases, however, data anomalies will still accumulate. To improve the quality of data, databases can be queried periodically to locate and correct anomalies. This paper reports the results of two experiments that investigated the effects of different data structures on business end-users' abilities to detect data anomalies in a relational database. The results demonstrate that both unnormalised and higher levels of normalisation lower the effectiveness and efficiency of queries relative to the first normal form. First normal form databases appear to provide the most effective and efficient data structure for business end-users formulating queries to detect data anomalies.

Temperature variation within and between nests of the green sea turtle, Chelonia mydas (Chelonia : Cheloniidae) on Heron Island, Great Barrier Reef

Four temperature data-loggers were placed in each of five green sea turtle nests on Heron Island in the 1998-99 nesting season. Temperatures in all nests increased as incubation progressed due to general sand heating and increased metabolic heat production of the developing embryos. Even at the top of nests no daily diurnal fluctuation in temperature was evident. The temperature of eggs in the middle of the nest increased above those in the nest periphery during the last third of incubation. However, this metabolic nest heating would have little effect on hatchling sex ratio because it occurred after the sex-determining period. Small differences in temperature between regions of a nest persisted throughout incubation and may be important in ensuring the production of at least some individuals of the opposite sex in nests that have temperatures close to either the all-male or all-female determining temperatures. Location and degree of shading of nests had little effect on mean nest temperature, but deeper nests were generally cooler and therefore were predicted to produce a higher proportion of males than were shallower nests. Nest temperature profile data indicated that the 1998-99 nesting season on Heron Island would have produced a strongly female-biased sex ratio amongst hatchlings.

Incubation temperature, energy expenditure and hatchling size in the green turtle (Chelonia mydas), a species with temperature-sensitive sex determination

Eggs from the Heron Island, Great Barrier Reef, nesting population of green turtles (Chelonia mydas) were incubated at all-male-determining (26 degreesC) and all-female-determining (30 degreesC) temperatures. Oxygen consumption and embryonic growth were monitored throughout incubation, and hatchling masses and body dimensions were measured from both temperatures. Eggs hatched after 79 and 53 days incubation at 26 degreesC and 30 degreesC respectively. Oxygen consumption at both temperatures increased to a peak several days before hatching, a pattern typical of turtle embryos, and the rate of oxygen was higher at 30 degreesC than 26 degreesC. The total amount of energy consumed during incubation, and hatchling dimensions, were similar at both temperatures, but hatchlings from 26 degreesC had larger mass, larger yolk-free mass and smaller residual yolks than hatchlings from 30 degreesC. Because of the difference in mass of hatchlings, hatchlings from 30 degreesC had a higher production cost.

Specification, refinement and verification of concurrent systems - An integration of Object-Z and CSP

This paper presents a method of formally specifying, refining and verifying concurrent systems which uses the object-oriented state-based specification language Object-Z together with the process algebra CSP. Object-Z provides a convenient way of modelling complex data structures needed to define the component processes of such systems, and CSP enables the concise specification of process interactions. The basis of the integration is a semantics of Object-Z classes identical to that of CSP processes. This allows classes specified in Object-Z to he used directly within the CSP part of the specification. In addition to specification, we also discuss refinement and verification in this model. The common semantic basis enables a unified method of refinement to be used, based upon CSP refinement. To enable state-based techniques to be used fur the Object-Z components of a specification we develop state-based refinement relations which are sound and complete with respect to CSP refinement. In addition, a verification method for static and dynamic properties is presented. The method allows us to verify properties of the CSP system specification in terms of its component Object-Z classes by using the laws of the the CSP operators together with the logic for Object-Z.

Using clusters of computers for large QU-GENE simulation experiments

The QU-GENE Computing Cluster (QCC) is a hardware and software solution to the automation and speedup of large QU-GENE (QUantitative GENEtics) simulation experiments that are designed to examine the properties of genetic models, particularly those that involve factorial combinations of treatment levels. QCC automates the management of the distribution of components of the simulation experiments among the networked single-processor computers to achieve the speedup.

How should pathogen transmission be modelled?

Host-pathogen models are essential for designing strategies for managing disease threats to humans, wild animals and domestic animals. The behaviour of these models is greatly affected by the way in which transmission between infected and susceptible hosts is modelled. Since host-pathogen models were first developed at the beginning of the 20th century, the 'mass action' assumption has almost always been used for transmission. Recently, however, it has been suggested that mass action has often been modelled wrongly. Alternative models of transmission are beginning to appear, as are empirical tests of transmission dynamics.