The port of Toledo; a descriptive handbook covering the Toledo Harbor and the area which it serves. A staff preparation.

Mode of access: Internet.

Globalisation and connectedness: A network approach to international business

There have been recent calls for the field of International Business to retool its routines by becoming genuinely interdisciplinary. This paper takes such an approach by using recent advances in the fields of evolutionary economics and applying them to IB. Evolutionary economists are now viewing the economy as an actual network. Consequently, one the key analytical tools in this approach is network analysis. Some of the basic methods in network analysis are reviewed. The paper then looks at how using these tools might be of use in IB studies. In particular, it outlines fruitful research paths in the areas of globalisation and regionalisation, and the measurement of performance in multi-national firms and alliances. In each case, propositions are put forward which can be analytically tested with the use of network analysis. The paper concludes with a brief outline of a research agenda which utilises this approach in International Business studies.

A design pattern for efficient retrieval of large data sets from remote data sources

Retrieving large amounts of information over wide area networks, including the Internet, is problematic due to issues arising from latency of response, lack of direct memory access to data serving resources, and fault tolerance. This paper describes a design pattern for solving the issues of handling results from queries that return large amounts of data. Typically these queries would be made by a client process across a wide area network (or Internet), with one or more middle-tiers, to a relational database residing on a remote server. The solution involves implementing a combination of data retrieval strategies, including the use of iterators for traversing data sets and providing an appropriate level of abstraction to the client, double-buffering of data subsets, multi-threaded data retrieval, and query slicing. This design has recently been implemented and incorporated into the framework of a commercial software product developed at Oracle Corporation.

Kitchen and dining area, Lahz House, Spring Hill

View to new kitchen and dining area, as seen from sitting room. Winner of the Robin Dods Award RAIA Queensland Chapter 1990

Multi-valued control problems and mixture density network

We have proposed a novel robust inversion-based neurocontroller that searches for the optimal control law by sampling from the estimated Gaussian distribution of the inverse plant model. However, for problems involving the prediction of continuous variables, a Gaussian model approximation provides only a very limited description of the properties of the inverse model. This is usually the case for problems in which the mapping to be learned is multi-valued or involves hysteritic transfer characteristics. This often arises in the solution of inverse plant models. In order to obtain a complete description of the inverse model, a more general multicomponent distributions must be modeled. In this paper we test whether our proposed sampling approach can be used when considering an arbitrary conditional probability distributions. These arbitrary distributions will be modeled by a mixture density network. Importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The effectiveness of the importance sampling from an arbitrary conditional probability distribution will be demonstrated using a simple single input single output static nonlinear system with hysteretic characteristics in the inverse plant model.