Economic growth and energy consumption in the UK, 1700–1975

This paper attempts to trace the development of energy consumption in the UK during the process of industrialization. First a quantitative overview of the relationship between energy consumption and economic growth for the period 1700–1975 is presented. An examination of the factors affecting relations between economic growth and energy consumption is then presented. This is divided into two main periods: pre-1800 and 1800–1975. The discussion of pre-1800 energy consumption is mainly concerned with coal use, while a more detailed account is given of developments in the later period.     

Mesure du Débit d’Absorption Spécifique (das) des téléphones mobiles — contribution du projetcomobio à la normalisation internationale

Human exposure to electromagnetic fields emitted by mobile phones is characterised by the Specific Absorption Rate (sar). This value corresponds to therf power absorbed by unitary mass of the equivalent tissue. It represents the basic restriction used to define limit of human exposure torf electromagnetic fields. Academic and industrial labs have contributed through thecomobio project to define international standards for mobile phones certification.     

Statistical Models for Data Mining

We review the background to the papers presented in this special issue and give a short introduction to each. We also briefly describe the workshop on Statistical models for data mining, held in Pavia (Italy), in October 2000, where the papers were presented.     

Agent-based simulation of electricity markets: a survey of tools

Agent-based simulation has been a popular technique in modeling and analyzing electricity markets in recent years. The main objective of this paper is to study existing agent-based simulation packages for electricity markets. We first provide an overview of electricity markets and briefly introduce the agent-based simulation technique. We then investigate several general-purpose agent-based simulation tools. Next, we review four popular agent-based simulation packages developed for electricity markets and several agent-based simulation models reported in the literature. We compare all the reviewed packages and models and identify their common features and design issues. Based on the study, we describe an agent-based simulation framework for electricity markets to facilitate the development of future models for electricity markets.     

Embracing and Extending 20th-Century Instruction Set Architectures

A vector case study shows how new functionality can be added to extend the 80times86 and PowerPC architectures to support a full vector architecture, primarily by enhancing their multimedia extensions to provide a better model for compilers and an easier-to-understand model for programmers     

A stochastic optimization model for real-time ambulance redeployment

When ambulances are engaged in responding to emergency calls, the ability to respond quickly to future calls is considerably compromised. The available ambulances are typically relocated to reestablish maximal coverage. We present a two-stage stochastic optimization model for the ambulance redeployment problem that minimizes the number of relocations over a planning horizon while maintaining an acceptable service level. We conduct computational testing based on the real historical data from the Region of Waterloo Emergency Medical Services. The results show that the optimal relocation strategies can be computed within 40 s of computational time for a desired service level of 90%.     

Cross-cultural IS adoption in multinational corporations: A study of rationality

A common claim in the literature on Information Systems' implementation in the context of less developed economies or so-called “developing countries” is that the “Western” technology is at odds with the local cultural context, in particular it is believed to mismatch local rationality in the sense of the accepted ways of doing things. In this paper we investigate IS implementation in a company based in a “non-Western” context compared with IS adoption in another company in a “Western” country context. Seen as a particular form of decision-making, the adoption and implementation processes are analysed drawing on the literature on decision-making, rationality in “Western” and “non-Western” contexts. Presenting evidence from these two contexts we argue that multiple forms of rationality exist in any context and that national culture is only one aspect of actors' as well as researchers' sense-making of activities in any given context. Linking the cases back the literature we reflect on the implications of our findings for cross-cultural research of IT implementation.     

On the selection of variables for qualitative modelling of dynamical systems

Behavioural modelling of physical systems from observations of their input/output behaviour is an important task in engineering. Such models are needed for fault monitoring as well as intelligent control of these systems. The paper addresses one subtask of behavioural modelling, namely the selection of input variables to be used in predicting the behaviour of an output variable. A technique that is well suited for qualitative behavioural modelling and simulation of physical systems is Fuzzy Inductive Reasoning (FIR), a methodology based on General System Theory. Yet, the FIR modelling methodology is of exponential computational complexity, and therefore, it may be useful to consider other approaches as booster techniques for FIR. Different variable selection algorithms: the method of the unreconstructed variance for the best reconstruction, methods based on regression coefficients (OLS, PCR and PLS) and other methods as Multiple Correlation Coefficients (MCC), Principal Components Analysis (PCA) and Cluster analysis are discussed and compared to each other for use in predicting the behaviour of a steam generator. The different variable selection algorithms previously named are then used as booster techniques for FIR. Some of the used linear techniques have been found to be non-effective in the task of selecting variables in order to compute a posterior FIR model. Methods based on clustering seem particularly well suited for pre-selecting subsets of variables to be used in a FIR modelling and simulation effort.