The thin films of cadmium oxide (CdO) were deposited using the SILAR (Successive ionic layer absorption and reaction) method at various deposition cycles. CdO thin films were made on glass substrates at a temperature of  95°C, using a cadmium acetate source material and an ammonium hydroxide solution. One of the main criteria that impact the quality of thin films is the number of deposition cycles. The size of the crystals decreases with the increase in the number of cycles from 33.7 nm at the immersion cycle 10 to 22.7 nm at the immersion cycle 20, as shown by the X-ray diffraction results. The optical band gap energy of the films reduces as the number of deposition cycles increases, while the transmittance of the Cadmium oxide film i

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This research was interested in studying the phrase “I don’t know” in the Lisan al-Arab dictionary, and Lisan al-Arab was based on collecting its material from five dictionaries, including: Tahdhib al-Lugha, al-Muqamah, al-Sahih, and the footnotes of Ibn Berri, al-Nihaya and Gharib al-Hadith. The objection to this phrase, and the discussion of its various implications among linguists and the clarification of the closest and most famous content to it according to the data presented to the researcher in his research journey, and to reach this goal, the research division into a preface, five demands and a conclusion and followed the list of sources and references. To define the lexicon of Lisan al-Ar

This research aims to know the effect of adopting IFRS 9 on the relevance of the value of the accounting information of the companies in the Iraqi Stock Exchange. Researchers relied on analyzing the financial statements of 10 listed companies for years 2016 – 2019. Researchers used the Ohlson price model to test the relationship between accounting information and value relevance. The research indicated that there is a significant relationship between the adoption of IFRS 9 and the relevance of the value of the earnings and the book value, but the earnings information is more relevance than the book value information, it is due to the interest of investors in the income statement in making investment decisions.

This paper aims to decide the best parameter estimation methods for the parameters of the Gumbel type-I distribution under the type-II censorship scheme. For this purpose, classical and Bayesian parameter estimation procedures are considered. The maximum likelihood estimators are used for the classical parameter estimation procedure. The asymptotic distributions of these estimators are also derived. It is not possible to obtain explicit solutions of Bayesian estimators. Therefore, Markov Chain Monte Carlo, and Lindley techniques are taken into account to estimate the unknown parameters. In Bayesian analysis, it is very important to determine an appropriate combination of a prior distribution and a loss function. Therefore, two different

In this study, the effect of glass fiber reinforced polymer (GFRP) section and compressive strength of concrete in composite beams under static and low velocity impact loads was examined. Modeling was performed and the obtained results were compared with the test results and their compatibility was evaluated.‎ Experimental tests of four composite beams were carried out, where two of them are control specimen with 20 MPa compressive strength of concrete deck slab and 50 MPa for other. Bending characteristics were affected by the strength of concrete under impact loading case, as it increased maximum impact force and damping time at a ratio of 59% and reduced the damping ratio by 47% compared to the reference hybrid beam. Under stat

Copper (I) complex containing folic acid ligand was prepared and characterized on the basis of metal analyses, UV-VIS, FTIR spectroscopies and magnetic susceptibility. The density functional theory (DFT) as molecular modeling calculations was used to determine the donor atoms of folic acid ligand which appear clearly at oxygen atoms binding to hydrogen. Detection of donation sights is supported by theoretical parameters such as geometry, mulliken population, mulliken charge and HOMO-LUMO gap obtained by DFT calculations.

Wisconsin Breast Cancer Dataset (WBCD) was employed to show the performance of the Adaptive Resonance Theory (ART), specifically the supervised ART-I Artificial Neural Network (ANN), to build a breast cancer diagnosis smart system. It was fed with different learning parameters and sets. The best result was achieved when the model was trained with 50% of the data and tested with the remaining 50%. Classification accuracy was compared to other artificial intelligence algorithms, which included fuzzy classifier, MLP-ANN, and SVM. We achieved the highest accuracy with such low learning/testing ratio.