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Evaluation of College of Nursing Affiliates’ Knowledge about Lung Cancer and its Relationship with Smoking
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Objective: To evaluate knowledge towards smoking and its relationship with lung cancer among members of
Baghdad Nursing College.
Methodology: The study comprised 100 affiliates from the College of Nursing/ University of Baghdad that
included students, teaching staff and employees. All data was collected through a structured questionnaire
prepared by the National Cancer Research Center which were answered during a scientific symposium
organized by the center on lung Cancer Awareness in March 2016.The data were analyzed by using the SPSS,
version 22
Results: The age of the respondents ranged from (19-64 years); 76% were females and only 4% were smokers.
The results showed that the mean score for the level of knowledge was 65%. The correlation coefficient
between the response and the occupation was 0.03. Twenty-two percent of the participants were of average
grade while 20% of the responses were of acceptable level. The calculated rates for scores good, very good and
excellent responses were for 18%, 12% and 10% respectively. It was displayed that 41% expressed interest to
participate in the awareness campaign under the supervision of the National Cancer Research Program; females
expressed a desire for charity more than males (74%).
Recommendations: To promote public awareness about the harmful effects of tobacco and the importance of
preventing smoking, highlighting its relationship with lung cancer and other malignant diseases. Non
Governmental organization should collaborate with the health and educational institutions to raise the level of
knowledge among the Iraqi society

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Benchmarking Framework for COVID-19 Classification Machine Learning Method Based on Fuzzy Decision by Opinion Score Method
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     Coronavirus disease (COVID-19), which is caused by SARS-CoV-2, has been announced as a global pandemic by the World Health Organization (WHO), which results in the collapsing of the healthcare systems in several countries around the globe. Machine learning (ML) methods are one of the most utilized approaches in artificial intelligence (AI) to classify COVID-19 images. However, there are many machine-learning methods used to classify COVID-19. The question is: which machine learning method is best over multi-criteria evaluation? Therefore, this research presents benchmarking of COVID-19 machine learning methods, which is recognized as a multi-criteria decision-making (MCDM) problem. In the recent century, the trend of developing

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Publication Date
Tue Jan 18 2022
Journal Name
Materials Science Forum
The Effect of Gamma Radiation on the Manufactured HgBa<sub>2</sub>Ca<sub>2</sub>Cu<sub>2.4</sub>Ag<sub>0.6</sub>O<sub>8+δ</sub> Compound
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In this article four samples of HgBa2Ca2Cu2.4Ag0.6O8+δ were prepared and irradiated with different doses of gamma radiation 6, 8 and 10 Mrad. The effects of gamma irradiation on structure of HgBa2Ca2Cu2.4Ag0.6O8+δ samples were characterized using X-ray diffraction. It was concluded that there effect on structure by gamma irradiation. Scherrer, crystallization, and Williamson equations were applied based on the X-ray diffraction diagram and for all gamma doses, to calculate crystal size, strain, and degree of crystallinity. I

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