This research interested to study the structural configuration in the square kufi script, as the kufi script is one of the oldest Arabic fonts, and this name was named according to the city of Kufa, so its types, forms, and designations were numerous, including the square kufic script, which was characterized by being a very straightforward engineering script based on the principle of squaring in building letters to form an engineering body that governs its construction of a set of organizational relationships and design bases according to an engineering structural system. The researchers identified the problem of his research with the following question: What is the Structural configuration in the square Kufic script?
Therefore, the research interested to show the structural configuration in the kufi script, for the period from (1383 AH - 1963 AD) to (1432 AH - 2011 CE), in Iraq.
The second chapter included the theoretical framework, as the first topic dealt with the composition in the square kufic script. And as for the second topic include the structural anchors of the formation in the square kufic script, then followed by indicators of the theoretical framework and previous studies.
The third chapter included research procedures, as the descriptive analytical approach was adopted. The fourth chapter included analyzing the samples, presenting the results, conclusions
Regression models are one of the most important models used in modern studies, especially research and health studies because of the important results they achieve. Two regression models were used: Poisson Regression Model and Conway-Max Well- Poisson), where this study aimed to make a comparison between the two models and choose the best one between them using the simulation method and at different sample sizes (n = 25,50,100) and with repetitions (r = 1000). The Matlab program was adopted.) to conduct a simulation experiment, where the results showed the superiority of the Poisson model through the mean square error criterion (MSE) and also through the Akaiki criterion (AIC) for the same distribution.
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