Structural equation modelling of complex sample survey : an application to brand signalling data

The purpose of this paper is to present an empirical analysis of complex sample data with regard to the biasing effect of nonindependence of observations on standard error parameter estimates. In a two-factor confirmatory factor analysis model, using real data, we show how the bias in standard errors can be derived when the nonindependence is ignored. We demonstrate that the standard error bias produced by the nonindependence of observations can be considerable and we briefly discuss solutions to overcome the problem.

Intelligent assistant to re-configure parameter-driven systems

Parameter-Driven Systems (PDS) are widely used in commerce for large-scale applications. Reusability is achieved with a PDS design by relocating implicit control structures in the software and the storage of explicit data in database files. This approach can accommodate various user requirements without tedious modification of the software. In order to specify appropriate parameters in a system, knowledge of both business activities and system behaviour are required. For large, complex software packages, this task becomes time consuming and requires specialist knowledge, yet the consistency and correctness still cannot be guaranteed. My research studied the types of knowledge required and agents involved in the PDS customisation. The work also identified the associated problems and constraints. A solution is proposed and implemented as an Intelligent Assistant prototype than a manual approach. Three areas of achievement have been highlighted: 1. The characteristics and problems of maintaining parameter instances in a PDS are defined. It is found that the verification is not complete with the technical/structural knowledge alone, but a context is necessary to provide semantic information and related business activities (thus the implemented parameters) so that mainline functions can relate with each other. 2. A knowledge-based modelling approach has been proposed and demonstrated via a practical implementation. A Specification Language was designed which can model various types of knowledge in a PDS and encapsulate relationships. The Knowledge-Based System (KBS) developed verifies parameters based on the interpreted model of a given context. 3. The performance of the Intelligent Assistant prototype was well received by the domain specialist from the participating organisation. The modelling and KBS approach developed in my research offers considerable promise in solving practical problems in the software industry.

Why do Australians, New Zealanders and Americans travel to Fiji? Evidence from cointegration, unit roots and parameter stability tests

The aim of this study was to estimate the demand for Fiji’s tourism from its three main source markets—Australia, New Zealand, and the US—using the bounds testing approach to cointegration. Our main finding was that visitor arrivals to Fiji and its key determinants are cointegrated over the 1970–2000 period. We then used the autoregressive distributed lag model to estimate short-run and long-run elasticities and found that income in origin countries, transport costs, and prices were significant determinants of Fiji’s tourism demand. We also found that coups negatively impact visitor arrivals from all markets. In testing for parameter stability, we established that the series were integrated of order one in the presence of a structural break. We then used the Hansen test for parameter stability and found that the parameters of our long-run model are stable over time.

Integrated fluid-thermal-structural numerical analysis for the quenching of metallic components

The quenching of a metal component with a channel section in a water tank is numerically simulated. Computational fluid dynamics (CFD) is used to model the multiphase flow and the heat transfer in film boiling, nucleate boiling and convective cooling processes to calculate the difference in heat transfer rate around the component and then combining with the thermal simulation and structure analysis of the component to study the effect of heat transfer rate on the distortion of the U-channel component. A model is also established to calculate the residual stress produced by quenching. The coupling fluid-thermal-structural simulation provides an insight into the deformation of the component and can be used to perform parameter analysis to reduce the distortion of the component. © 2011 Shanghai Jiaotong University and Springer-Verlag Berlin Heidelberg.

Automatically learning structural units in educational videos with the hierarchical hidden Markov models

In this paper we present a coherent approach using the hierarchical HMM with shared structures to extract the structural units that form the building blocks of an education/training video. Rather than using hand-crafted approaches to define the structural units, we use the data from nine training videos to learn the parameters of the HHMM, and thus naturally extract the hierarchy. We then study this hierarchy and examine the nature of the structure at different levels of abstraction. Since the observable is continuous, we also show how to extend the parameter learning in the HHMM to deal with continuous observations.