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.

A research include of synthesized five member ring, which has been synthesized by condensation of 2-(1-(4- hydroxyphenyl) ethylidene)hydrazine-1-carbothioamide[I] with α-chloro ethylacetate in sodium acetate (fused) to form ethyl 2-(4-(1-((4-oxo-2-thioxopyrrolidin-3-ylidene)hydrazono) ethyl)phenoxy)acetate [II]. After that reacted [II]with hydrazine hydrate to resulting compound [III]. Compound [III] was refluxed with 4-aminobenzoicacid in excess of phosphorus oxy chloride give compound [IV],the later compound [IV] interact with acetyl acetone or ethylacetoacetate give to pyrazole and pyrazoline derivatives[V],[VI]. While when reacted with different aromatic aldehydes and one ketone consistence Schiff base derivatives [VII]a-e . The FTIR a

Mango fruit is one of the most nutritionally rich fruits with unique flavor, this fruit belonged to family of Anacardiaceae and it is an excellent source of vitamins specially vitamin A, carotene pigments and potassium. In this study the antimicrobial activity of mango seeds extract has been investigated against gram positive bacteria (Staphylococcus aureus and Bacillus spp.) and gram negative bacteria (Pseudomonas aeruginosa and E. coli) and yeast Candida albicans by well diffusion method in nutrient agar and the results were expressed as the diameter of bacterial inhibition zones surrounding the wells, and the antibiofilm of its extracts was observed against Staphylococcus aureus. The seeds extractions prepared by two solvents: 8

A research include of synthesized five member ring, which has been synthesized by condensation of 2-(1-(4- hydroxyphenyl) ethylidene)hydrazine-1-carbothioamide[I] with α-chloro ethylacetate in sodium acetate (fused) to form ethyl 2-(4-(1-((4-oxo-2-thioxopyrrolidin-3-ylidene)hydrazono) ethyl)phenoxy)acetate [II]. After that reacted [II]with hydrazine hydrate to resulting compound [III]. Compound [III] was refluxed with 4-aminobenzoicacid in excess of phosphorus oxy chloride give compound [IV],the later compound [IV] interact with acetyl acetone or ethylacetoacetate give to pyrazole and pyrazoline derivatives[V],[VI]. While when reacted with different aromatic aldehydes and one ketone consistence Schiff base derivatives [VII]a-e . The FTIR a

This study aimed to detect Anaplasma phagocytophilum in horses through hematological and molecular tests. The 16S rRNA gene of the Anaplasma phagocytophilum parasite was amplified by polymerase chain reaction (PCR), then sequenced, and subjected to phylogenetic analysis to explore "Equine Granulocytic Anaplasmosis" (EGA) infection in three important gathering race horses areas in Baghdad governorate, Iraq. Blood samples were obtained from 160 horses of varying ages, three breeds, and both sexes, between January and December 2021. Prevalence and risk variables for anaplasmosis were analyzed using statistical odds ratio and chi-square tests. Results demonstrated that clinical anaplasmosis symptoms comprised jaundice, wei

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p