Dr Peter E. Ongley, Electronic Technology Services, Bristol. Uk.

Getters for Microelectronic & Semiconductor Hermetic Enclosures

The presentation reviews some history on Getter Materials for use in Microelectronic and Semiconductor Enclosures. The present needs for Hermetic Sealed Packages especially to secure longevity in performance in demanding and harsh environments is discussed. Recent developments in semiconductor technologies & packaging makes further demands. The increase in interest in use of Getters to further extend life-times has become prominent. The main types of Getters currently used are reviewed followed by a detailed assessment of the role of both Moisture & Hydrogen Getters for Advanced Applications.Three primary applications (markets) are addressed with particular focus on MEMS and Optical-MEMS hermetic packaging requirements having mirrors and lenses. Typical detrimental effects of contaminants inc. presence of moisture are discussed.Finally, typical applications inc. Aerospace & Military Microelectronic packages and increasing use of GaAs for Optical-Telecommunications are addressed in the presentation.

Dr Doug Mckinnon, University of New South Wales

Rapid parameter identification and efficiency evaluation methods for three-phase induction machines

With modern high speed measurement techniques, many of the old test methods need to be revisited. This presentation will cover two test methodologies that are being investigated at the University of New South Wales using modern digital signal processing techniques. The first methodology improves on the traditional technique for identifying induction machine parameters for use in the per-phase equivalent circuit model and the unified machine theory dynamic model for induction motors. The tests identify the relationships between the parameters and various input conditions, resulting in a set of variable parameters. Knowledge of these variations is important for designing high performance motor drives. Further to this the results have highlighted the ability of modern measurement and analysis techniques to identify transient phenomena and rotor eccentricity. The second test method stems from a criticism of current efficiency testing methods that are antiquated, expensive and time consuming. The Dual-Frequency, Sweep-Frequency and Constant Speed of Rotating Magnetic Field (CSORMF) methods of synthetic loading are investigated for their use in evaluating the efficiency of three-phase induction motors. Synthetic loading requires no mechanical load to be coupled to the machine under test, thus saving upon set-up time and equipment. The methods are analysed using accurate parameters obtained from a real machine using the test methods above and a dynamic induction machine model that includes iron loss.

Dr Chris Slinger, QinetiQ

Recent developments in computer generated holography: towards a practical electroholography system for interactive 3D visualisation

Reconfigurable computer generated holography - sometimes known as electroholography - is the only technique capable of using computer held data to generate interactive, high quality, 3D images containing all the depth cues used by the human visual system. Possible applications for electroholographic display systems include oil and gas, aerospace, automotive and medical data visualisation. The need for such displays is increasing as the ability of computers to gather and generate large multidimensional data sets continues to outstrip the capabilities of existing and planned display technologies. Practical applications of electroholography require computer generated hologram (CGH) patterns of between 10^9 to 10^10 pixels to be calculated and displayed at interactive rates. These pixel counts are necessary in order to generate images which are both big enough (upwards of 300 mm width) and possess a large enough field of view (FOV) to permit simultaneous, multiuser viewing. The latest developments in CGH design algorithms, computer performance and spatial light modulator systems now make it possible to anticipate building electroholography systems of practical utility. These advances will be described and illustrated with some recent results from demonstrations of aspects of the technology. These include monochrome and colour, static and dynamic, horizontal parallax only (HPO) and full parallax, 3D images, generated from true CGH systems with up to 24 billion pixels. The paper will also compare the attributes and status of electroholography with some other high performance display systems under development.

Research Interest

Dr Chris Slinger is a QinetiQ Fellow and former Chief Scientific Officer for Holographic Imaging LLC, the US based QinetiQ/Ford Motor Company joint venture set up to develop and exploit advanced visualisation technology. He is QinetiQ technical leader for holography, and technical director of the Photonics and Displays Group in QinetiQ Malvern. After completing his undergraduate and postgraduate degrees at Oxford University, he joined QinetiQ Malvern in 1985. Author or co-author of over 75 conference, open-literature publications and patents, his current research interests include computer generated holography and high performance 2D and 3D displays. He was made a QinetiQ Fellow in 1998 and awarded an inaugural QinetiQ Prize for Exceptional Innovation by Prince Michael of Kent in 1999 for his work on Advanced Liquid Crystal and Holographic Displays. In 2002 he was co-recipient of Institute of Physics Paterson Medal and Prize, for contributions to the utilization and application of physics and its commercial exploitation. He was elected as an Institute of Physics Fellow in 2003.

Dr Iris Firmin, Aston University

Spin-Model for Clustering Optical Flow

We can classify objects according to their motion; grouping static objects and moving objects, for instance. Such classification of image frame regions can be used for tasks such as surveillance systems, navigation and attention control for humanoid robots, among others. In this paper we present an approach for grouping image objects by motion decomposition, based on Potts model and Monte Carlo simulation of the spatial-temporal information. The temperature changes in the Potts model allow clustering the spins (pixels), thus at low temperature the spins that belong to the same cluster are aligned.

Research Interest

Cognition vision: understanding vision mechanism to provide models that allow solving problem related to object recognition. Motion understanding and estimation is my major research area. Additional I am interested in the integration of sensor information (tactile, auditory, and visual) and attention control.

Other interests: computational geometry, pattern recognition, robotics.

Dr Chris Solomon, University of Kent

The presentation will describe research being carried out at Kent which combines statistical models of facial appearance with evolutionary computational strategies. The approach lends itself to a variety of different applications in which both human and automatically derived fitness measures drive the procedure to convergence on a desired facial appearance. Some of these will be described and demonstrated.

Author Profile

Dr Chris Solomon graduated in physics from Durham University in 1983 and gained a Ph.D in tomographic medical imaging from the Royal Marsden Hospital, London in 1989. From 1989-1993, he conducted research into methods of image reconstruction and recovery for astronomical applications at Imperial College. Since 1994, he has been at the University of Kent, Canterbury where he currently leads the Forensic imaging group within the School of Physical Sciences at the University of Kent. His main specific research interest lie in modelling, encoding and reconstruction of the human face. The research group is currently supported by grants from the EPSRC, DTI and U.S. Navy.

Dr Solomon is a Technical Director of VisionMetric, a Kent University spin-out company specializing in forensic image analysis for Police Forces both in the U.K. and the U.S.

Algorithms for computer vision and applications

The presentation will cover research and experiments in computer vision systems recognising and tracking objects (especially cars in traffic and objects in medical imaging - x-ray films). The model-based computer vision systems will be discussed, based on attributed graph technique. For medical imaging the global and local tracking methods and experimentation based on these methods will be presented.