Culture-bound technological solutions: An artificial theoretic insight

Sometimes, technological solutions to practical problems are devised that conspicuously take into account the constraints to which a given culture is subjecting the particular task or the manner in which it is carried out. The culture may be a professional culture (e.g., the practice of law), or an ethnic-cum-professional culture (e.g., dance in given ethnic cultures from South-East Asia), or, again, a denominational culture prescribing an orthopraxy impinging on everyday life through, for example, prescribed abstinence from given categories of workday activities, or dietary laws. Massimo Negrotti's Theory of the artificial is a convenient framework for discussing some of these techniques. We discuss a few examples, but focus on the contrast of two that are taken from the same cultural background, namely, technological applications in compliance with Jewish Law orthopraxy. •Soya-, mycoprotein- or otherwise derived meat surrogates are an example ofnaturoid; they emulate the flavours and olfactory properties, as well as the texture and the outer and inner appearance, of the meat product (its kind, cut, form) they set out to emulate (including amenability to cooking in the usual manner for the model), while satisfying cultural dietary prohibitions. •In contrast, the Sabbath Notebook, a writing surrogate we describe in this paper, is atechnoid: it emulates a technique (writing to store alphanumeric information), while satisfying the prohibition of writing at particular times of the liturgical calendar (the Sabbath and the major holidays).

Guest editorial. [Computers and Artificial Intelligence. 1998. Vol. 17, No. 2-3]

Editorial

[Book Review] A database of North American tertiary mammals

Review of: Janis, C.M., Scott, K.M., & Jacobs, L.L. (eds.) 1998. Evolution of Tertiary Mammals of North America Volume 1: Terrestrial Carnivores, Ungulates, and Ungulatelike Mammals, i-x, 1491. Cambridge University Press, Cambridge, UK. £165

The Jama legal narrative part I: The JAMA Model and narrative interpretation patterns

For the purposes of starting to tackle, within artificial intelligence (AI), the narrative aspects of legal narratives in a criminal evidence perspective, traditional AI models of narrative understanding can arguably supplement extant models of legal narratives from the scholarly literature of law, jury studies, or the semiotics of law. Not only: the literary (or cinematic) models prominent in a given culture impinge, with their poetic conventions, on the way members of the culture make sense of the world. This shows glaringly in the sample narrative from the Continent-the Jama murder, the inquiry, and the public outcry-we analyse in this paper. Apparently in the same racist crime category as the case of Stephen Lawrence's murder (in Greenwich on 22 April 1993) with the ensuing still current controversy in the UK, the Jama case (some 20 years ago) stood apart because of a very unusual element: the eyewitnesses identifying the suspects were a group of football referees and linesmen eating together at a restaurant, and seeing the sleeping man as he was set ablaze in a public park nearby. Professional background as witnesses-cum-factfinders in a mass sport, and public perceptions of their required characteristics, couldn't but feature prominently in the public perception of the case, even more so as the suspects were released by the magistrate conducting the inquiry. There are sides to this case that involve different expected effects in an inquisitorial criminal procedure system from the Continent, where an investigating magistrate leads the inquiry and prepares the prosecution case, as opposed to trial by jury under the Anglo-American adversarial system. In the JAMA prototype, we tried to approach the given case from the coign of vantage of narrative models from AI.

Multicomponent gas-mixture measurements using an array of gas sensors and an artificial neural-network

An Electronic Nose is being jointly developed between the University of Greenwich and the Institute of Intelligent Machines to detect the gases given off from an oil filled transformer when it begins to break down. The gas sensors being used are very simple, consisting of a layer of Tin Oxide (SnO2) which is heated to approximately 640 K and the conductivity varies with the gas concentrations. Some of the shortcomings introduced by the commercial gas sensors available are being overcome by the use of an integrated array of gas sensors and the use of artificial neural networks which can be 'taught' to recognize when the gas contains several components. At present simulated results have achieved up to a 94% success rate of recognizing two component gases and future work will investigate alternative neural network configurations to maintain this success rate with practical measurements.

Artificial neural networks in modelling osmotic dehydration of foods

Artificial neural network (ANN) models for water loss (WL) and solid gain (SG) were evaluated as potential alternative to multiple linear regression (MLR) for osmotic dehydration of apple, banana and potato. The radial basis function (RBF) network with a Gaussian function was used in this study. The RBF employed the orthogonal least square learning method. When predictions of experimental data from MLR and ANN were compared, an agreement was found for ANN models than MLR models for SG than WL. The regression coefficient for determination (R2) for SG in MLR models was 0.31, and for ANN was 0.91. The R2 in MLR for WL was 0.89, whereas ANN was 0.84.Osmotic dehydration experiments found that the amount of WL and SG occurred in the following descending order: Golden Delicious apple > Cox apple > potato > banana. The effect of temperature and concentration of osmotic solution on WL and SG of the plant materials followed a descending order as: 55 > 40 > 32.2C and 70 > 60 > 50 > 40%, respectively.

Recovery of a biodiversity action plans species in northwest England: possible role of climate change, artificial habitat and water quality amelioration. Occasional Publication of the Marine Biological Association 16

The honeycomb reef worm Sabellaria alveolata is recognised as being an important component of intertidal communities. It is a priority habitat within the UK Biodiversity Action Plan and as a biogenic reef forming species is covered by Annex 1 of the EC habitats directive. S. alveolata has a lusitanean (southern) distribution, being largely restricted to the south and west coasts of England. A broad-scale survey of S. alveolata distribution along the north-west coasts was undertaken in 2003/2004. These records were then compared with previous distribution records, mainly those collected by Cunningham in 1984. More detailed mapping was carried out at Hilbre Island at the mouth of the River Dee, due to recent reports that S. alveolata had become re-established there after a long absence.