Search Results - "Franklin, J.A."

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  1. 1

    Evaluation and Standardization of Enzyme-Linked ImmunoSpot (ELISPOT) Assay for Measurement of Pathogen-Specific T-cell Responses in Normal Donors by Yamshchikov, G.V, Franklin, J.A, Williams, C.D, Wathen, L.K, Halsey, J.F

    “…Peripheral blood mononuclear cells (PBMC) from 21 normal donors were evaluated for reactivity to common recall antigens (tetanus toxoid, Candida albicans,…”
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    Journal Article
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    MBE Growth of HgCdTe on Large-Area Si and CdZnTe Wafers for SWIR, MWIR and LWIR Detection by Reddy, M., Peterson, J.M., Lofgreen, D.D., Franklin, J.A., Vang, T., Smith, E.P.G., Wehner, J.G.A., Kasai, I., Bangs, J.W., Johnson, S.M.

    Published in Journal of electronic materials (01-09-2008)
    “…Molecular beam epitaxy (MBE) growth of HgCdTe on large-size Si (211) and CdZnTe (211)B substrates is critical to meet the demands of extremely uniform and…”
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    Journal Article Conference Proceeding
  3. 3

    The perceiving robot: What does it see? What does it do? by Selfridge, O.G., Franklin, J.A.

    “…The nature of robots in the future is examined, and it is proposed that they should fundamentally function as responsible agents for people and not merely as…”
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    Conference Proceeding
  4. 4

    Root temperature and aeration effects on the protein profile of canola leaves by Franklin, J.A, Kav, N.N.V, Yajima, W, Reid, D.M

    Published in Crop science (01-07-2005)
    “…Canola (Brassica napus L.) is planted in early spring and must survive both low soil temperatures and periods of wet weather. Shoot effects result from both…”
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    Journal Article
  5. 5

    Application of connectionist learning methods to manufacturing process monitoring by Franklin, J.A., Sutton, R.S., Anderson, C.W.

    “…It is demonstrated that connectionist learning networks can monitor manufacturing processes to determine causal relationships with an accuracy competitive with…”
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    Conference Proceeding
  6. 6

    Acquiring robot skills via reinforcement learning by Gullapalli, V., Franklin, J.A., Benbrahim, H.

    Published in IEEE control systems (01-02-1994)
    “…Skill acquisition is a difficult , yet important problem in robot performance. The authors focus on two skills, namely robotic assembly and balancing and on…”
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    Magazine Article
  7. 7

    Effects of consolidated tailings water on red-osier dogwood ( Cornus stolonifera Michx) seedlings by Renault, S, Croser, C, Franklin, J.A, Zwiazek, J.J, MacKinnon, M

    Published in Environmental pollution (1987) (01-01-2001)
    “…Salt resistance in red-osier dogwood seedlings appeared to be due to restriction of sodium transport from roots to shoots. As part of their tailings…”
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    Journal Article
  8. 8

    What is qualitative reasoning, and can we use it for control? by Franklin, J.A.

    “…The author presents the basic concepts of qualitative reasoning (QR) and then looks at what one needs to do to use it for control. In QR, physical problems are…”
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    Conference Proceeding
  9. 9

    Input space representation for refinement learning control by Franklin, J.A.

    “…A learning control approach called refinement, in which a fixed controller is first designed using analytic design tools is explored. This controller's…”
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    Conference Proceeding
  10. 10

    Refinement of robot motor skills through reinforcement learning by Franklin, J.A.

    “…An extension of earlier work in the refinement of robotic motor control using reinforcement learning is described. It is no longer assumed that the magnitude…”
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    Conference Proceeding
  11. 11

    Three applications of artificial neural networks for control by Franklin, J.A.

    “…Three systems which apply artificial neural network (ANNs) to the modeling and/or control of physical systems are discussed. Two of these systems are in…”
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    Conference Proceeding
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    Qualitative reinforcement learning control by Franklin, J.A.

    “…An attempt is made to develop a reinforcement learning controller for a system described in more abstract or behavioral terms than those addressed by most…”
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    Conference Proceeding
  15. 15

    Historical perspective and state of the art in connectionist learning control by Franklin, J.A.

    “…Connectionist learning control is surveyed, starting with work by learning control engineers in the sixties and early seventies. The controllers are reviewed…”
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    Conference Proceeding
  16. 16

    Learning channel allocation strategies in real time by Franklin, J.A., Smith, M.D., Yun, J.C.

    “…Preliminary investigations into using connectionist machine learning for dynamic channel allocation in real time are described. The algorithms were implemented…”
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    Conference Proceeding
  17. 17

    Real-time learning: a ball on a beam by Benbrahim, H., Doleac, J.S., Franklin, J.A., Selfridge, O.G.

    “…In the Real-Time Learning Laboratory at GTE Laboratories, machine learning algorithms are being implemented on hardware testbeds. A modified connectionist…”
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    Conference Proceeding
  18. 18

    Learning a nonlinear model of a manufacturing process using multilayer connectionist networks by Anderson, C.W., Franklin, J.A., Sutton, R.S.

    “…Control of a manufacturing process can be very risky when the process is incompletely understood. The risk of making adjustments can be deceased by building a…”
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    Conference Proceeding
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