In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial lung CT-scans into two groups (COVID-19 and NonCOVID-19) had been proposed. A dataset used is 960 slices of CT scan collected from Iraqi patients /Ibn Al-Nafis teaching hospital. The performance metrics are used in this study (accuracy, recall, precision, and F1 scores). The results indicate that the proposed approach generated a high-quality model for the collected dataset, with an overall accuracy of 98.95% and an overall recall of 97 %.
Research Summary
It highlights the importance of assessing the demand for money function in Iraq through the understanding of the relationship between him and affecting the variables by searching the stability of this function and the extent of their influence in the Iraqi dinar exchange rate in order to know the amount of their contribution to the monetary policies of the Iraqi economy fee, as well as through study behavior of the demand for money function in Iraq and analyze the determinants of the demand for money for the period 1991-2013 and the impact of these determinants in the demand for money in Iraq.
And that the problem that we face is how to estimate the total demand for money in
... Show MoreConditional logistic regression is often used to study the relationship between event outcomes and specific prognostic factors in order to application of logistic regression and utilizing its predictive capabilities into environmental studies. This research seeks to demonstrate a novel approach of implementing conditional logistic regression in environmental research through inference methods predicated on longitudinal data. Thus, statistical analysis of longitudinal data requires methods that can properly take into account the interdependence within-subjects for the response measurements. If this correlation ignored then inferences such as statistical tests and confidence intervals can be invalid largely.
يشغل المجال النووي الايراني اهتمام دولي كبير الامر الذي جعل من الولايات المتحدة الامريكية تفرض قيودا اقتصادية على ايران لتحجيم دورها في المنطقة
In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N
... Show MoreSelf-repairing technology based on micro-capsules is an efficient solution for repairing cracked cementitious composites. Self-repairing based on microcapsules begins with the occurrence of cracks and develops by releasing self-repairing factors in the cracks located in concrete. Based on previous comprehensive studies, this paper provides an overview of various repairing factors and investigative methodologies. There has recently been a lack of consensus on the most efficient criteria for assessing self-repairing based on microcapsules and the smart solutions for improving capsule survival ratios during mixing. The most commonly utilized self-repairing efficiency assessment indicators are mechanical resistance and durab
... Show Moreمن المؤسف حقا ان نجد أنفسنا نعيش في ظروف عصيبة لم تشاهده أعيننا ولم تطرأ على مسامعنا من قبل، وجاء الاحتلال البغيض بكل تبعاته السلبية افرز عنه اليوم تفرقاً ملحوظا وصراعا اليماً وتناحراً أضر بمكانتنا ووحدتنا، ولنا في كل يوم مصيبة وعويل، حتى صارت عبارة عن مذاهب وطوائف وأشخاص، تتنازعهم الأهواء والخرافات والتقليد والتعصب وأمراض أخرى، وباتت تلك الأشلاء يلعن بعضها بعضاً وينفي أحدها الآخر.
وص
... Show MoreFind a study in the relationship between geography and medicine and a variety of sources, this study multiple. Valjgraveh is the image of the earth recipe haunted them and which of the seven regions and seas and mountains, prairies, rivers and cities geographical study of the Earth as the abode of the person or is the study of the natural environment of the human race and the geographical that analyzes the different factors that make up the natural environment and examines the impact of each factor separately and then the effects of all factors combined to human life and health and activity.