A design for business intelligence service in demand driven supply chain management

This paper discusses the problems inherent within traditional supply chain management's forecast and inventory management processes arising when tackling demand driven supply chain. A demand driven supply chain management architecture developed by Orchestr8 Ltd., U.K. is described to demonstrate its advantages over traditional supply chain management. Within this architecture, a metrics reporting system is designed by adopting business intelligence technology that supports users for decision making and planning supply activities over supply chain health.

Swarms of computational resources and swarms of tasks for building reliable systems

Space applications demand the need for building reliable systems. Autonomic computing defines such reliable systems as self-managing systems. The work reported in this paper combines agent based and swarm robotic approaches leading to swarm-array computing, a novel technique to achieve autonomy for distributed parallel computing systems. Two swarm-array computing approaches based on swarms of computational resources and swarms of tasks are explored. FPGA is considered as the computing system. The feasibility of the two proposed approaches that binds the computing system and the task together is simulated on the SeSAm multi-agent simulator.

A Gentle/S approach to robot assisted neuro-rehabilitation

Movement disorders (MD) include a group of neurological disorders that involve neuromotor systems. MD can result in several abnormalities ranging from an inability to move, to severe constant and excessive movements. Strokes are a leading cause of disability affecting largely the older people worldwide. Traditional treatments rely on the use of physiotherapy that is partially based on theories and also heavily reliant on the therapists training and past experience. The lack of evidence to prove that one treatment is more effective than any other makes the rehabilitation of stroke patients a difficult task. UL motor re-learning and recovery levels tend to improve with intensive physiotherapy delivery. The need for conclusive evidence supporting one method over the other and the need to stimulate the stroke patient clearly suggest that traditional methods lack high motivational content, as well as objective standardised analytical methods for evaluating a patient's performance and assessment of therapy effectiveness. Despite all the advances in machine mediated therapies, there is still a need to improve therapy tools. This chapter describes a new approach to robot assisted neuro-rehabilitation for upper limb rehabilitation. Gentle/S introduces a new approach on the integration of appropriate haptic technologies to high quality virtual environments, so as to deliver challenging and meaningful therapies to people with upper limb impairment in consequence of a stroke. The described approach can enhance traditional therapy tools, provide therapy "on demand" and can present accurate objective measurements of a patient's progression. Our recent studies suggest the use of tele-presence and VR-based systems can potentially motivate patients to exercise for longer periods of time. Two identical prototypes have undergone extended clinical trials in the UK and Ireland with a cohort of 30 stroke subjects. From the lessons learnt with the Gentle/S approach, it is clear also that high quality therapy devices of this nature have a role in future delivery of stroke rehabilitation, and machine mediated therapies should be available to patient and his/her clinical team from initial hospital admission, through to long term placement in the patient's home following hospital discharge.

Intelligent agents and distributed models for cooperative task support

Purpose – To describe some research done, as part of an EPSRC funded project, to assist engineers working together on collaborative tasks. Design/methodology/approach – Distributed finite state modelling and agent techniques are used successfully in a new hybrid self-organising decision making system applied to collaborative work support. For the particular application, analysis of the tasks involved has been performed and these tasks are modelled. The system then employs a novel generic agent model, where task and domain knowledge are isolated from the support system, which provides relevant information to the engineers. Findings – The method is applied in the despatch of transmission commands within the control room of The National Grid Company Plc (NGC) – tasks are completed significantly faster when the system is utilised. Research limitations/implications – The paper describes a generic approach and it would be interesting to investigate how well it works in other applications. Practical implications – Although only one application has been studied, the methodology could equally be applied to a general class of cooperative work environments. Originality/value – One key part of the work is the novel generic agent model that enables the task and domain knowledge, which are application specific, to be isolated from the support system, and hence allows the method to be applied in other domains.

Power to the people: working-class demand for household power in 1930s Britain

The 1930s witnessed an intense struggle between gas and electricity suppliers for the working class market, where the incumbent utility—gas—was also a reasonably efficient (and cheaper) General Purpose Technology for most domestic uses. Local monopolies for each supplier boosted substitution effects between fuel types—as alternative fuels constituted the only local competition. Using newly-rediscovered returns from a major national household expenditure survey, we employ geographically-determined instrumental variables, more commonly used in the industrial organization literature, to show that gas provided a significant competitor, tempering electricity prices, while electricity demand was also responsive to marketing initiatives.

The demand for a healthy diet: estimating the almost ideal demand system with infrequency of purchase

A Bayesian method of estimating multivariate sample selection models is introduced and applied to the estimation of a demand system for food in the UK to account for censoring arising from infrequency of purchase. We show how it is possible to impose identifying restrictions on the sample selection equations and that, unlike a maximum likelihood framework, the imposition of adding up at both latent and observed levels is straightforward. Our results emphasise the role played by low incomes and socio-economic circumstances in leading to poor diets and also indicate that the presence of children in a household has a negative impact on dietary quality.