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علاقة معاملات المرونة بالبنية البلورية للجسم الصلب

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 Publication date 2017
  fields Mathematics
and research's language is العربية
 Created by Shamra Editor




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منتجب الحسن و وعد سمير عطية : كمون جيبس الترموديناميكي والطاقة الداخلية في المرونة الحرارية اللاتناظرية قبول نشر في مجلة جامعة البعث 2018
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The radiating process of a crystalline sample cause damages in this sample .These damages composed mostly of displaced sample atoms from their regular position in lattice, and placed in irregular position, and of very less quantity from some beam par ticles ( strange particles ) , that placed inside of this sample. The depth and amount of these damages are correlating with radiating parameters. It's possible to estimate the depth distribution profiles of damages by RBS-Method, but the sensitivity of this method is not enough to determine the depth distribution of concentration of beam particles , that placed inside of the sample . The placement depth of RBS-Profiles top is strongly correlated with orientation angle of a sample's channel relative to radiating beam also to kind of channel ,whereas the RBS-Profiles top displaces in depth , in channel radiation compare with its counter part in random radiation and the displacement value correlates with radiation parameters The height of RBS-Profiles top increase by increasing of radiation dose, and height that can't be survived called amorph state , and the agreeing dose called ,amorph dose , the amorph dose correlates also with radiation parameters, special sample temperature.
This study include new algorithm for preliminary design of solid propellant motor, it starts with knowing the major parameters, which in this algorithmtwenty-three parameters,we joined it with ten equations.
Zinc Chromate was synthesised by Co-precipitation method, The synthesised samples were characterized using X-ray powder diffraction technology (XRD). Set temperature synthesis at 250 ℃ .
In this paper, we present the first statistical parser for Lambek categorial grammar (LCG), a grammatical formalism for which the graphical proof method known as *proof nets* is applicable. Our parser incorporates proof net structure and constraints into a system based on self-attention networks via novel model elements. Our experiments on an English LCG corpus show that incorporating term graph structure is helpful to the model, improving both parsing accuracy and coverage. Moreover, we derive novel loss functions by expressing proof net constraints as differentiable functions of our model output, enabling us to train our parser without ground-truth derivations.

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