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Chemico-Biological Interactions, 2021
Current regulatory cancer risk assessment principles and practices assume a linear dose-response relationship-the linear no-threshold (LNT) model-that theoretically estimates cancer risks occurring following low doses of carcinogens by linearly extrapolating downward from experimentally determined risks at high doses.
Edward J, Calabrese +2 more
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Current regulatory cancer risk assessment principles and practices assume a linear dose-response relationship-the linear no-threshold (LNT) model-that theoretically estimates cancer risks occurring following low doses of carcinogens by linearly extrapolating downward from experimentally determined risks at high doses.
Edward J, Calabrese +2 more
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Variable-Threshold Threshold Elements
IEEE Transactions on Computers, 1968Abstract—Variable-threshold threshold elements (V-T threshold elements) are threshold elements in which the weights are fixed while the threshold may be varied. When the threshold is varied, a set of functions is generated.
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Synthesis of Generalised Threshold Gates and Multi Threshold Threshold Gates
International Journal of Electronics and Telecommunications, 2011We present formal models and efficient synthesis algorithms for threshold gates of Generalised Threshold Gate (GTG) and Multi Threshold Threshold Gate (MTTG) structures. For GTG synthesis our method does not require to calculate thresholds, that separate function onset and offsets, which greatly simplifies and speeds up the synthesis algorithm.
Maciej Nikodem +2 more
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Threshold concepts and threshold skills in computing
Proceedings of the ninth annual international conference on International computing education research, 2012Threshold concepts can be used to both organize disciplinary knowledge and explain why students have difficulties at certain points in the curriculum. Threshold concepts transform a student's view of the discipline; before being learned, they can block a student's progress.In this paper, we propose that in computing, skills, in addition to concepts ...
Kate Sanders 0001 +6 more
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Classification by Thresholding
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1983A procedure is given which substantially reduces the processing time needed to perform maximum likelihood classification on large data sets. The given method uses a set of fixed thresholds which, if exceeded by one probability density function, makes it unnecessary to evaluate a competing density function.
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