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DESIGNING A HIGH-SPEED DATA ARCHIVE SYSTEMBain, R. S. 10 1900 (has links)
International Telemetering Conference Proceedings / October 26-29, 1992 / Town and Country Hotel and Convention Center, San Diego, California / Modern telemetry systems collect large quantities of data at high rates of speed.
To support near real-time analysis of this data, a sophisticated data archival
system is required. If the data is to be analyzed during the test, it must be
available via computer-accessible peripheral devices. The use of computer-compatible
media permits powerful “instant- replay-type” functions to be
implemented, allowing the user to search for events, blow-up time segments, or
alter playback rates. Using computer-compatible media also implies inexpensive
COTS devices with an “industry standard” interface and direct media compatibility
with host processing systems. This paper discusses the design and
implementation of a board-level archive subsystem developed by Veda Systems,
Incorporated.
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A resonant DC link power converter for future drive applicationsSebzali, Ahmad J. January 1996 (has links)
No description available.
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The nature and decomposition of volatile constituents in a carbonated beverageSumar, S. January 1988 (has links)
No description available.
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Flywheel energy storage and retrieval for support of power system frequency under generation fault conditionsMcArdle, John Malachy January 1990 (has links)
No description available.
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Memory and optimisation in neural network modelsForrest, B. M. January 1988 (has links)
A numerical study of two classes of neural network models is presented. The performance of Ising spin neural networks as content-addressable memories for the storage of bit patterns is analysed. By studying systems of increasing sizes, behaviour consistent with fintite-size scaling, characteristic of a first-order phase transition, is shown to be exhibited by the basins of attraction of the stored patterns in the Hopfield model. A local iterative learning algorithm is then developed for these models which is shown to achieve perfect storage of nominated patterns with near-optimal content-addressability. Similar scaling behaviour of the associated basins of attraction is observed. For both this learning algorithm and the Hopfield model, by extrapolating to the thermodynamic limit, estimates are obtained for the critical minimum overlap which an input pattern must have with a stored pattern in order to successfully retrieve it. The role of a neural network as a tool for optimising cost functions of binary valued variables is also studied. The particular application considered is that of restoring binary images which have become corrupted by noise. Image restorations are achieved by representing the array of pixel intensities as a network of analogue neurons. The performance of the network is shown to compare favourably with two other deterministic methods-a gradient descent on the same cost function and a majority-rule scheme-both in terms of restoring images and in terms of minimising the cost function. All of the computationally intensive simulations exploit the inherent parallelism in the models: both SIMD (the ICL DAP) and MIMD (the Meiko Computing Surface) machines are used.
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Biochemical markers for storage abuse in raw black tiger prawns (Penaeus monodon)Evason, David John January 1998 (has links)
No description available.
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Biochemical studies of the gluten proteins in developing spring wheat and environmental effects on the gluten proteins in winter wheatWright, Richard James January 2001 (has links)
No description available.
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Structural and dynamic properties of a methionine-rich protein from sunflower seedPandya, Maya Jay January 1998 (has links)
No description available.
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Transport applications of flywheel energy storageJefferson, C. M. January 1984 (has links)
No description available.
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Storage stability of low salt bacon : Microbiological, chemical and sensory aspectsApplegate, J. January 1989 (has links)
No description available.
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