The plant Dianthus Orientalis that belongs to the Caryphyllaceae family is one of the useful plants in Iraq. Its seeds are commonly used for toothache. This project provides the first comprehensive research done in Iraq and the world to study the phytochemicals and the methods of extraction and isolation of active constituents from Dianthus orientalis wildly grown in Iraq. The plant was harvested from Penjwin in AL-Sulaymaniyah city, Iraq in September 2019.The whole plant were washed carefully, dried in shade area for two weeks, and milled in a mechanical grinder to a coarse powder. The plant was defatted by maceration with hexane for 7days and dried after that extracted by cold extraction methods using 80% methanol solvent for 9 days then fractionation with chloroform, ethyl acetate and n-butanol to separate the active constituents according to the change in polarities. The chloroform, ethyl acetate fractions were used for identification and isolation of phenolic compounds by TLC, PTLC, HPLC and LC/mass, FTIR. Results of the phytochemical screening exposed the presence of, phenols in the plant extract. The phenolic compound (vanillic acid, coumaric acid, cinnamic acid, genistein, oleuropein) were separated and purified by PTLC. The isolated compounds were subjected to several chemical, chromatographic and spectral analytical techniques for their identification such as TLC, HPLC, FTIR and LC/mass.
Modification of gas chromatographic technique for the separation and determination of methyl ethoy silane compounds which were synthesized by the addition of absolute ethanol to methyl chlorosilane compounds have been elaborated experimentally. The addition of absolute dry ethanol to methyl chlorosilane compounds in the presence of a dry stream of nitrogen gas led to sweep out the liberated HCl gas. This method was found to be the suitable method for the preparation of methyl ethoxy silane compounds. The optimum parameter selected after careful and precise studies was between 20 – 30 ml \ min to carrieir gas flow rate, while applied temperatures of detector and injection part were 250 Â
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For sparse system identification,recent suggested algorithms are -norm Least Mean Square (
-LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named
-ZA-LMS,
In this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.
These deposits take many forms like current acc, deposits in order to growth and serve national economy Various in varicose perspectives .
The problem of this paper its concern with un applied the mathematical models that used in profitability analysis of current acc , and deposits in view of risk, profit efficiency and financial leverage for this reason the paper discussion use the cumulate mathematical model to solve these problem, that content three variables that be used to measuring profitability by consequent replacement method by stable base and by moving base for 2007 – 2009 applied the data collect from Iraq middle east bank. &nbs
... Show MoreBiometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in
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