Picasso ceramics represented illuminated sign in ceramic art and excelled in accord ceramic art dimension aesthetically, and put it in a new prospects, despite the simplicity of the forms turn into a magical images and multiple interpretations.
So the search deliberately to choose purposive (37) samples divided into four groups, as follows: -
A flat shapes / palets or saucers / the vases /modified vases .
benefiting from indicators were spawned from literature ,to analyzing samples within the totals for the identification systems act forming art work`s:-
(1)Picasso's ceramic work product of a deliberate process represented a capacity of technical experience, and formal
(2)The system configuration in the ceramic art works carried out in a form having (two or more) systems act`s in the same time, with the Dominance of one without the other, as follows:
(A) in the sample flat shapes, we find that there are three systems moved shapes, the system (Stenography) is dominant in addition to the system (geometrical), and (narrative), which contrast attending
(B) the system (regular narrative) essential front-line state in the forms in palets, and (Stenography) system Secondly supplement to image.
(C) in vases formed by wheel which dominates the (iconic character) of form, the system (magnifying) is prevailing with a (Stenograph) as a systematic art forming.
(D) in developed vases, the artist Override the (traditional) form to get a new relations (innovative), dominated by (Stenography) Producing shapes and (aesthetic)system of forms and line, and color in this group
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In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error ( λ ) in the model (SPSEM), estimated the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo
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