Integrating Aircraft Cost Modelling into Conceptual Design

The article presents cost modeling results from the application of the Genetic-Causal cost modeling principle. Industrial results from redesign are also presented to verify the opportunity for early concept cost optimization by using Genetic-Causal cost drivers to guide the conceptual design process for structural assemblies. The acquisition cost is considered through the modeling of the recurring unit cost and non-recurring design cost. The operational cost is modeled relative to acquisition cost and fuel burn for predominately metal or composites designs. The main contribution of this study is the application of the Genetic-Causal principle to the modeling of cost, helping to understand how conceptual design parameters impact on cost, and linking that to customer requirements and life cycle cost.

A History of Women in Ireland, 1500-1800

The first general survey of the history of women in early modern Ireland. Based on an impressive range of source material, it presents the results of original research into women’s lives and experiences in Ireland from 1500 to 1800. This was a time of considerable change in Ireland as English colonisation, religious reform and urbanisation transformed society on the island. Gaelic society based on dynastic lordships and Brehon Law gave way to an anglicised and centralised form of government and an English legal system.

'Dare the boist'rous main': the role of the Belfast Newsletter in the process of emigration from Ulster to North America 1760-1800

Before the mass migrations from Ireland in the nineteenth century, earlier waves of migration in the eighteenth century saw significant numbers of people leave Ireland, predominantly from Ulster, to settle in North America. This article, using as its principal data source the Belfast News Letter ( BNL), its letters, advertisements and reports, focuses firstly on reconstructing the late eighteenth-century migration process and voyage, highlighting the barriers represented by the Atlantic Ocean. In addition to the challenges of the sea, there were problems with the ships, the ever-present danger of disease and also threats from other vessels, from privateers to press gangs. The voyage was recognized as a ‘universal dread’, and the risks taken to ‘dare the boist’rous main’ were perhaps not minimized in the pages of the BNL, whose editorial stance was antipathetic to the migration for the potential harm it caused to Ulster by removing so many of its industrious young. The second part of this article goes on to consider the newspaper’s and others’ vested interests in the emigration process, demonstrates how these were manifested in the press and sets the coverage of this very significant early emigration flow within the context of contemporary religious and colonial discourses at a period of very lively transatlantic interactions.

Model selection approaches for non-linear system identification: a review

The identification of non-linear systems using only observed finite datasets has become a mature research area over the last two decades. A class of linear-in-the-parameter models with universal approximation capabilities have been intensively studied and widely used due to the availability of many linear-learning algorithms and their inherent convergence conditions. This article presents a systematic overview of basic research on model selection approaches for linear-in-the-parameter models. One of the fundamental problems in non-linear system identification is to find the minimal model with the best model generalisation performance from observational data only. The important concepts in achieving good model generalisation used in various non-linear system-identification algorithms are first reviewed, including Bayesian parameter regularisation and models selective criteria based on the cross validation and experimental design. A significant advance in machine learning has been the development of the support vector machine as a means for identifying kernel models based on the structural risk minimisation principle. The developments on the convex optimisation-based model construction algorithms including the support vector regression algorithms are outlined. Input selection algorithms and on-line system identification algorithms are also included in this review. Finally, some industrial applications of non-linear models are discussed.

A taxonomy for wavelet neural networks applied to nonlinear modelling

This article presents a novel classification of wavelet neural networks based on the orthogonality/non-orthogonality of neurons and the type of nonlinearity employed. On the basis of this classification different network types are studied and their characteristics illustrated by means of simple one-dimensional nonlinear examples. For multidimensional problems, which are affected by the curse of dimensionality, the idea of spherical wavelet functions is considered. The behaviour of these networks is also studied for modelling of a low-dimension map.