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Titlebook: Microcomputers and Laboratory Instrumentation; David J. Malcolme-Lawes Book 1988 Plenum Press, New York 1988 Laboratory.MSI.bandwidth.comm

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书目名称Microcomputers and Laboratory Instrumentation
编辑David J. Malcolme-Lawes
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图书封面Titlebook: Microcomputers and Laboratory Instrumentation;  David J. Malcolme-Lawes Book 1988 Plenum Press, New York 1988 Laboratory.MSI.bandwidth.comm
描述The invention of the microcomputer in the mid-1970s and its subsequent low-cost proliferation has opened up a new world for the laboratory scientist. Tedious data collection can now be automated relatively cheaply and with an enormous increase in reliability. New techniques of measurement are accessible with the "intelligent" instrumentation made possible by these programmable devices, and the ease of use of even standard measurement techniques may be improved by the data processing capabilities of the humblest micro. The latest items of commercial laboratory instrumentation are invariably "computer controlled", although this is more likely to mean that a microprocessor is involved than that a versatile microcomputer is provided along with the instrument. It is clear that all scientists of the future will need some knowledge of computers, if only to aid them in mastering the button pushing associated with gleaming new instruments. However, to be able to exploit this newly accessible computing power to the full the practising laboratory scientist must gain sufficient understanding to utilise the communication channels between apparatus on the laboratory bench and program within the
出版日期Book 1988
关键词Laboratory; MSI; bandwidth; communication; computer; control; data processing; high voltage; instruments; iro
版次1
doihttps://doi.org/10.1007/978-1-4613-1011-2
isbn_softcover978-1-4612-8291-4
isbn_ebook978-1-4613-1011-2
copyrightPlenum Press, New York 1988
The information of publication is updating

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David J. Malcolme-Lawestion is not as rich as many others but we have found it useful for uncovering higher-level concepts and structure that were not explicit in the performance data. If richer models are required our approach may provide a quick way of developing a first draft and gaining initial ontological commitment.
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David J. Malcolme-Lawestion is not as rich as many others but we have found it useful for uncovering higher-level concepts and structure that were not explicit in the performance data. If richer models are required our approach may provide a quick way of developing a first draft and gaining initial ontological commitment.
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David J. Malcolme-Lawesproof of the upper bound of the casebase cardinality shows that the casebase would in a long run grow too large and all possible solutions cannot be stored. In order to keep only the most efficient solutions the casebase has to be revised at run-time or some other measure of path difference has to b
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David J. Malcolme-Laweswe propose a method for identifying genes that might be significant for the particular tumour types. For SRBCTs, zero error on test data has been obtained for only 10 out of 2308 genes; for the ALL/AML problem, our results are competitive to the best results published in the literature, and we obtai
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David J. Malcolme-LawesHere, we present a relational learning system, ., that combines an analytical learning strategy, with an inductive strategy for incremental refinement of learned knowledge. We provide experimental results that show the effectiveness of such automatic acquisition approach. We compare its performance
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