Exploitation of symbolic information in interprocedural dependence analysis

The requirement for a very accurate dependence analysis to underpin software tools to aid the generation of efficient parallel implementations of scalar code is argued. The current status of dependence analysis is shown to be inadequate for the generation of efficient parallel code, causing too many conservative assumptions to be made. This paper summarises the limitations of conventional dependence analysis techniques, and then describes a series of extensions which enable the production of a much more accurate dependence graph. The extensions include analysis of symbolic variables, the development of a symbolic inequality disproof algorithm and its exploitation in a symbolic Banerjee inequality test; the use of inference engine proofs; the exploitation of exact dependence and dependence pre-domination attributes; interprocedural array analysis; conditional variable definition tracing; integer array tracing and division calculations. Analysis case studies on typical numerical code is shown to reduce the total dependencies estimated from conventional analysis by up to 50%. The techniques described in this paper have been embedded within a suite of tools, CAPTools, which combines analysis with user knowledge to produce efficient parallel implementations of numerical mesh based codes.

Upgrading automation for nuclear fuel in-core management: from the symbolic generation of configurations to the neural adaptation of heuristics

FUELCON is an expert system in nuclear engineering. Its task is optimized refueling-design, which is crucial to keep down operation costs at a plant. FUELCON proposes sets of alternative configurations of fuel-allocation; the fuel is positioned in a grid representing the core of a reactor. The practitioner of in-core fuel management uses FUELCON to generate a reasonably good configuration for the situation at hand. The domain expert, on the other hand, resorts to the system to test heuristics and discover new ones, for the task described above. Expert use involves a manual phase of revising the ruleset, based on performance during previous iterations in the same session. This paper is concerned with a new phase: the design of a neural component to carry out the revision automatically. Such an automated revision considers previous performance of the system and uses it for adaptation and learning better rules. The neural component is based on a particular schema for a symbolic to recurrent-analogue bridge, called NIPPL, and on the reinforcement learning of neural networks for the adaptation.

A novel neural/symbolic hybrid approach to heuristically optimized fuel allocation and automated revision of heuristics in nuclear engineering

FUELCON is an expert system for optimized refueling design in nuclear engineering. This task is crucial for keeping down operating costs at a plant without compromising safety. FUELCON proposes sets of alternative configurations of allocation of fuel assemblies that are each positioned in the planar grid of a horizontal section of a reactor core. Results are simulated, and an expert user can also use FUELCON to revise rulesets and improve on his or her heuristics. The successful completion of FUELCON led this research team into undertaking a panoply of sequel projects, of which we provide a meta-architectural comparative formal discussion. In this paper, we demonstrate a novel adaptive technique that learns the optimal allocation heuristic for the various cores. The algorithm is a hybrid of a fine-grained neural network and symbolic computation components. This hybrid architecture is sensitive enough to learn the particular characteristics of the ‘in-core fuel management problem’ at hand, and is powerful enough to use this information fully to automatically revise heuristics, thus improving upon those provided by a human expert.

FUELGEN: effective evolutionary design of refuellings for pressurized water reactors

The paper describes the design of an efficient and robust genetic algorithm for the nuclear fuel loading problem (i.e., refuellings: the in-core fuel management problem) - a complex combinatorial, multimodal optimisation., Evolutionary computation as performed by FUELGEN replaces heuristic search of the kind performed by the FUELCON expert system (CAI 12/4), to solve the same problem. In contrast to the traditional genetic algorithm which makes strong requirements on the representation used and its parameter setting in order to be efficient, the results of recent research results on new, robust genetic algorithms show that representations unsuitable for the traditional genetic algorithm can still be used to good effect with little parameter adjustment. The representation presented here is a simple symbolic one with no linkage attributes, making the genetic algorithm particularly easy to apply to fuel loading problems with differing core structures and assembly inventories. A nonlinear fitness function has been constructed to direct the search efficiently in the presence of the many local optima that result from the constraint on solutions.

When deterrence works - and when it doesn't: a comparison of Sweden's prostitution law and UK's Dangerous Dogs Act

Many pieces of legislation have been implemented with the anticipation - or justification - that they will have a deterrent effect. Deterrence was clearly argued in the debate preceding the Swedish prostitution law prohibiting the purchase of sexual services, but less so regarding the Dangerous Dogs Act, which was a very rapid response to a particular moral panic. As it turned out, the Swedish law has had a deterrent effect on street prostitution in that 'respectable' buyers were deterred. It will be argued that it is this very 'respectability' that makes deterrence work in this case. Regarding the Dangerous Dogs Act, the owners of Pit Bulls and other banned breeds are not considered 'respectable' and the banning might have had the reversed effect - increasing the attraction of these dogs, rather than deterring the ownership. Apart from deterrence and its consequences, the rendering invisible of key actors - buyers and owners respectively - and the use of symbolic legislation to promote moral messages will also be considered. [From the Author]

The interprofessional practitioner: changing professional identity in social work

Twenty years ago the first joint training programme in learning disability nursing and social work was established as a collaborative project to develop practitioners able to work holistically with people with learning disabilities. Since then a number of programmes have continued this work and more recently the approach has developed in the mental health specialism. These programmes have changed the nature of singular social work education and created a new region of knowledge (Bernstein, 2000) for those who have experienced them. What began as a radical experiment in interprofessional education has been sustained by a strong commitment to the belief that the practitioners who qualify from such programmes are well equipped to support people with learning disabilities in changing and multi-professional services. As with much interprofessional education, however, there is an ongoing need to build an evidence base linking such education with successful outcomes in practice. This paper presents and explores the outcomes of a doctoral research study aimed at evaluating the impact of joint training in learning disability nursing and social work on the professional identity, skills and working practices of practitioners who undertook it. The research was undertaken with almost fifty jointly trained practitioners and involved a national survey followed by semi-structured interviews. The results suggest that practitioners who experience the dual socialisation inherent in this type of training found both gains and losses in the process. They appear to emerge, however, with a confidence, resilience and breadth of knowledge which were part of the early vision for this transformative approach to professional training. Bernstein B. (2000). Pedagogy, Symbolic Control and Identity. Theory, Research, Critique. Revised Edition. Lanham: Rowman and Littlefield (USA).

Economic restructuring in New Zealand: A classical account

New Zealand's recent experiment with radical neoliberalism is well rehearsed in international policy circles. Yet, given the economic restructuring premise for the reforms, there has been little assessment of their structural impact. In this paper I take up this challenge, utilising [Shaikh, A., Tonak, E. Measuring the wealth of nations: the political economy of national accounts. Cambridge: Cambridge University Press; 1994] methodology for deriving classical value categories from official national accounts data but extending this to the industry level. This approach allows changes to the production and appropriation of surplus value in different industries during the period to be identified, underpinning a Marxian interpretation of restructuring. Beyond the methodology, the research makes four contributions. First, conventional analysis is found limited by its concentration on changes to the distribution of value rather than its creation. Second, land rents are significant. Third, the role of financial capital is found more complex than traditionally argued. Finally, the approach provides a firm grounding for the unfashionable concept of class fraction.