Exploring genetic alternative concepts for FUELGEN

This paper describes new crossover operators and mutation strategies for the FUELGEN system, a genetic algorithm which designs fuel loading patterns for nuclear power reactors. The new components are applications of new ideas from recent research in genetic algorithms. They are designed to improve the performance of FUELGEN by using information in the problem as yet not made explicit in the genetic algorithm's representation. The paper introduces new developments in genetic algorithm design and explains how they motivate the proposed new components.

A generational scheme for partitioning graphs

Graph partitioning divides a graph into several pieces by cutting edges. Very effective heuristic partitioning algorithms have been developed which run in real-time, but it is unknown how good the partitions are since the problem is, in general, NP-complete. This paper reports an evolutionary search algorithm for finding benchmark partitions. Distinctive features are the transmission and modification of whole subdomains (the partitioned units) that act as genes, and the use of a multilevel heuristic algorithm to effect the crossover and mutations. Its effectiveness is demonstrated by improvements on previously established benchmarks.

The development of an advanced ship evacuation simulation software product and associated large scale testing facility for the collection of human shipboard behaviour data

When designing a new passenger ship or modifying an existing design, how do we ensure that the proposed design and crew emergency procedures are safe from an evacuation point of view? In the wake of major maritime disasters such as the Herald of Free Enterprise and the Estonia and in light of the growth in the numbers of high density, high-speed ferries and large capacity cruise ships, issues concerned with the evacuation of passengers and crew at sea are receiving renewed interest. In the maritime industry, ship evacuation models offer the promise to quickly and efficiently bring evacuation considerations into the design phase, while the ship is "on the drawing board". maritimeEXODUS-winner of the BCS, CITIS and RINA awards - is such a model. Features such as the ability to realistically simulate human response to fire, the capability to model human performance in heeled orientations, a virtual reality environment that produces realistic visualisations of the modelled scenarios and with an integrated abandonment model, make maritimeEXODUS a truly unique tool for assessing the evacuation capabilities of all types of vessels under a variety of conditions. This paper describes the maritimeEXODUS model, the SHEBA facility from which data concerning passenger/crew performance in conditions of heel is derived and an example application demonstrating the models use in performing an evacuation analysis for a large passenger ship partially based on the requirements of MSC circular 1033.

A case based model to assist in the design process in the manufacture of furniture products

This paper describes progress on a project to utilise case based reasoning methods in the design and manufacture of furniture products. The novel feature of this research is that cases are represented as structures in a relational database of products, components and materials. The paper proposes a method for extending the usual "weighted sum" over attribute similarities for a ·single table to encompass relational structures over several tables. The capabilities of the system are discussed, particularly with respect to differing user objectives, such as cost estimation, CAD, cutting scheme re-use, and initial design. It is shown that specification of a target case as a relational structure combined with suitable weights can fulfil several user functions. However, it is also shown that some user functions cannot satisfactorily be specified via a single target case. For these functions it is proposed to allow the specification of a set of target cases. A derived similarity measure between individuals and sets of cases is proposed.

Teaching, learning and assessment in MSc. Databases units at University of Greenwich

In this paper we look at ways of delivering and assessing learning on database units offered on higher degree programmes (MSc) in the School of Computing and Mathematical Sciences at the University of Greenwich. Of critical importance is the teaching methods employed for verbal disposition, practical laboratory exercises and a careful evaluation of assessment methods and assessment tools in view of the fact that databases involve not only database design but also use of practical tools, such as database management systems (DBMSs) software, human designers, database administrators (DBA) and end users. Our goal is to clearly identify potential key success factors in delivering and assessing learning in both practical and theoretical aspects of database course units.

A case study in the teaching of HCI

This poster describes a "real world" example of the teaching of Human-Computer Interaction at the final level of a Computer Science degree. It highlights many of the problems of the ever expanding HCI domain and the consequential issues of what to teach and why. The poster describes the conception and development of a new HCI course, its historical background, the justification for decisions made, lessons learnt from its implementation, and questions arising from its implementation that are yet to be addressed. For example, should HCI be taught as a course in its own right or as a component of another course? At what level is the teaching of HCI appropriate, and how is teaching influenced by industry? It considers suitable learning pedagogies as well as the demands and the contribution of industry. The experiences presented will no doubt be familiar to many HCI educators. Whilst the poster raises more questions than it answers, the resolution of some questions will hopefully be achieved by the workshop.

A combined evolutionary search and multilevel optimisation approach to graph-partitioning

The graph-partitioning problem is to divide a graph into several pieces so that the number of vertices in each piece is the same within some defined tolerance and the number of cut edges is minimised. Important applications of the problem arise, for example, in parallel processing where data sets need to be distributed across the memory of a parallel machine. Very effective heuristic algorithms have been developed for this problem which run in real-time, but it is not known how good the partitions are since the problem is, in general, NP-complete. This paper reports an evolutionary search algorithm for finding benchmark partitions. A distinctive feature is the use of a multilevel heuristic algorithm to provide an effective crossover. The technique is tested on several example graphs and it is demonstrated that our method can achieve extremely high quality partitions significantly better than those found by the state-of-the-art graph-partitioning packages.

A robust approach to subsequence matching

In terms of a general time theory which addresses time-elements as typed point-based intervals, a formal characterization of time-series and state-sequences is introduced. Based on this framework, the subsequence matching problem is specially tackled by means of being transferred into bipartite graph matching problem. Then a hybrid similarity model with high tolerance of inversion, crossover and noise is proposed for matching the corresponding bipartite graphs involving both temporal and non-temporal measurements. Experimental results on reconstructed time-series data from UCI KDD Archive demonstrate that such an approach is more effective comparing with the traditional similarity model based algorithms, promising robust techniques for lager time-series databases and real-life applications such as Content-based Video Retrieval (CBVR), etc.

Influence of a fed or fasted state on the s-IgA response to prolonged cycling in active men and women

This study investigated the effect of a fed or fasted state on the salivary immunoglobulin A (s-IgA) response to prolonged cycling. Using a randomized, crossover design, 16 active adults (8 men and 8 women) performed 2 hr of cycling on a stationary ergometer at 65% of maximal oxygen uptake on 1 occasion after an overnight fast (FAST) and on another occasion 2 hr after consuming a 2.2-MJ high-carbohydrate meal (FED). Timed, unstimulated whole saliva samples were collected immediately before ingestion of the meal, immediately preexercise, 5 min before cessation of exercise, immediately postexercise, and 1 hr postexercise. The samples were analyzed for s-IgA concentration, osmolality, and cortisol, and saliva flow rates were determined to calculate s-IgA secretion rate. Saliva flow rate decreased by 50% during exercise (p < .05), and s-IgA concentration increased by 42% (p < .05), but s-IgA secretion rate remained unchanged. There was a 37% reduction in s-IgA:osmolality postexercise (p < .05), and salivary cortisol increased by 68% (p < .05). There was no effect of FED vs. FAST on these salivary responses. The s-IgA concentration, secretion rate, and osmolality were found to be significantly lower in women than in men throughout the exercise protocol (p < .05); however, there was no difference between genders in saliva flow rate, s-IgA:osmolality ratio, or cortisol. These data demonstrate that a fed or fasted state 2 hr before exercise does not influence resting s-IgA or the response to prolonged cycling. Furthermore, these results show lower levels of s-IgA and osmolality in women than in men at rest.