Comparison of a centralised and distributed approach for a generic scheduling system

PEGS (Production and Environmental Generic Scheduler) is a generic production scheduler that produces good schedules over a wide range of problems. It is centralised, using search strategies with the Shifting Bottleneck algorithm. We have also developed an alternative distributed approach using software agents. In some cases this reduces run times by a factor of 10 or more. In most cases, the agent-based program also produces good solutions for published benchmark data, and the short run times make our program useful for a large range of problems. Test results show that the agents can produce schedules comparable to the best found so far for some benchmark datasets and actually better schedules than PEGS on our own random datasets. The flexibility that agents can provide for today's dynamic scheduling is also appealing. We suggest that in this sort of generic or commercial system, the agent-based approach is a good alternative.

Towards an intelligent score following system: Handling of mistakes and jumps encountered during piano practicing

Score following has been an important area of research in AI and music since the mid 80's. Various systems were developed, but they were predominantly for providing automated accompaniment to live concert performances, dealing mostly with issues relating to pitch detection and identification of embellished melodies. They have a big potential in the area of education where student performers benefit in practice situations. Current accompaniment systems are not designed to deal with errors that may occur during practising. In this paper we present a system developed to provide accompaniment for students practising at home. First a survey of score following will be given. Then the capabilities of the system will be explained, and the results from the first experiments of the monophonic score following system will be presented.

Radiotherapy in the presence of contrast agents: a general figure of merit and its application to gold nanoparticles

Delivering sufficient dose to tumours while sparing surrounding tissue is one of the primary challenges of radiotherapy, and in common practice this is typically achieved by using highly penetrating MV photon beams and spatially shaping dose. However, there has been a recent increase in interest in the possibility of using contrast agents with high atomic number to enhance the dose deposited in tumours when used in conjunction with kV x-rays, which see a significant increase in absorption due to the heavy element's high-photoelectric cross-section at such energies. Unfortunately, the introduction of such contrast agents significantly complicates the comparison of different source types for treatment efficacy, as the dose deposited now depends very strongly on the exact composition of the spectrum, making traditional metrics such as beam quality less valuable. To address this, a 'figure of merit' is proposed, which yields a value which enables the direct comparison of different source types for tumours at different depths inside a patient. This figure of merit is evaluated for a 15 MV LINAC source and two 150 kVp sources (both of which make use of a tungsten target, one with conventional aluminium filtration, while the other uses a more aggressive thorium filter) through analytical methods as well as numerical models, considering tissue treated with a realistic concentration and uptake ratio of gold nanoparticle contrast agents (10 mg ml(-1) concentration in 'tumour' volume, 10: 1 uptake ratio). Finally, a test case of human neck phantom is considered with a similar contrast agent to compare the abstract figure to a more realistic treatment situation. Good agreement was found both between the different approaches to calculate the figure of merit, and between the figure of merit and the effectiveness in a more realistic patient scenario. Together, these observations suggest that there is the potential for contrast-enhanced kilovoltage radiation to be a useful therapeutic tool for a number of classes of tumour on dosimetric considerations alone, and they point to the need for further research in this area.

Intelligent Assembly Time Analysis Using a Digital Knowledge-Based Approach

The implementation of effective time analysis methods fast and accurately in the era of digital manufacturing has become a significant challenge for aerospace manufacturers hoping to build and maintain a competitive advantage. This paper proposes a structure oriented, knowledge-based approach for intelligent time analysis of aircraft assembly processes within a digital manufacturing framework. A knowledge system is developed so that the design knowledge can be intelligently retrieved for implementing assembly time analysis automatically. A time estimation method based on MOST, is reviewed and employed. Knowledge capture, transfer and storage within the digital manufacturing environment are extensively discussed. Configured plantypes, GUIs and functional modules are designed and developed for the automated time analysis. An exemplar study using an aircraft panel assembly from a regional jet is also presented. Although the method currently focuses on aircraft assembly, it can also be well utilized in other industry sectors, such as transportation, automobile and shipbuilding. The main contribution of the work is to present a methodology that facilitates the integration of time analysis with design and manufacturing using a digital manufacturing platform solution.