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VISAGE uses HPCN to generate animated sequences of buildings using a computer model commissioned by Edinburgh Old Town Renewal Trust (EOTRT), an Edinburgh-based organisation with conservation interests in the Old Town. The resulting images are life-like and therefore believable and appealing to an audience. VISAGE demonstrates the uses of High-Performance Computing and Networking in Architectural Visualisation. The key to VISAGE's power in demonstrating the benefits of computer-based visualisation to the architecture and planning community is the Edinburgh Old Town computer model itself. The computer model was commissioned by Edinburgh Old Town Renewal Trust (EOTRT), an Edinburgh-based organisation with conservation interests in the Old Town. The results of the project include a number of animated sequences showing a 'fly-through' of the area. The model has been maintained and significantly developed and improved on EOTRT's personal computers using an Architectural Computer-Aided Design (CAD) package. EOTRT have benefited greatly from being able to demonstrate features of the Old Town to clients using the CAD package interactively and its ability to generate shaded colour images from a viewpoint of interest. In some respects, however, EOTRT cannot make use of the full extent and detail of their computer model. Even their most powerful PC has difficulty viewing the model in its entirety. There are three primary objectives to VISAGE: - To establish the requirements for computer-based visualisation in the architecture and planning community. - To tailor suitable rendering software to make best use of high-performance computing and networking resources. - To demonstrate the power of computer-based visualisation in the presentation of building and landscape developments, in isolation or within the existing environment. The results give architects and planners more cost-effective means for presenting high-quality animations showing the impact of architectural changes. Project URL :
PROSPECT is an ENTICE TTN (European Technology Transfer Node Activities) result concerning an automatic inspection system for carpets. Using digital signal processing (DSP) and vision systems, combined with High Performance Computing and Network (HPCN) techniques, the carpet can be inspected automatically for faults on the production line. Inspecting visually several thousands of meters of carpet a day is tiring and prone to human error. The key to the system is the use of powerful but inexpensive computing technology to analyze the image of the carpet. The system must be able to process the images quickly in order to keep up with the speed of the carpet as it comes off the production line. Linking together several similar components achieves this. The test system can easily be expanded by the addition of more processors, to bring more algorithms to bear and to handle the full set of user requirements. A study was undertaken, which showed how, by the use of HPCN techniques, it would be possible to extend the test system to cover the whole width of any carpet moving at higher speeds, and to detect all the types of faults required. If the PROSPECT product is developed to detect all faults, the system could be sold for a minimum of 300 000 Euros per system. This would easily be recovered as productivity could be raised by 20-30%.
IPO demonstrates the solution of real industrial scheduling and optimisation problems through the use of advanced software. The problems solved are taken from a variety of manufacturing industries, but come from a generic class of optimisation problems for which well understood, computationally intensive mathematical techniques exist. Scheduling a number of jobs to run their individual course through a manufacturing shop in an optimal way is a complex problem. Because of the complexity, solutions based on comparatively simple heuristic rules can be much more practical than classic mathematical optimisation techniques. General purpose tools (and commercially available Materials Requirement Planning products) have great difficulty addressing specific aspects of user scheduling needs. They cannot address issues such as supplier or machine performance characteristics; they cannot naturally support uncertainty or provide explanations for the choice of a particular solution. This means that standard MRP schedules inevitably have to be further refined by hand in order to produce a practical schedule. For large and complex problems this is an expensive, time consuming and error prone process. IPO automates this process through intelligent scheduling. IPO aims to model and solve typical manufacturing problems using rules-of-thumb and techniques for handling uncertainty, coupled with high-performance computational algorithms. To this end, three demanding and complex end-user applications have been addressed in order to prove the feasibility and generality of this approach and to ensure the tools and techniques developed can be exploited quickly for the potential benefit of a wide range of manufacturing companies. Project URL :

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