Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Previous studies on the synthesis and characterization of metal chelates with uracil by elemental analysis, conductivity, IR, UV-Vis, NMR spectroscopy, and thermal analysis were covered in this review article. Reviewing these studies, we found that uracil can be coordinated through the electron pair on the N1, N3, O2, or O4 atoms. If the uracil was a mono-dentate ligand, it will be coordinated by one of the following atoms: N1, N3 or O2. But if the uracil was bi-dentate ligand, it will be coordinated by atoms N1 and O2, N3 and O2 or N3 and O4. However, when uracil forms complexes in the form of polymers, coordination occurs through the following atoms: N1 and N3 or N1 and O4.

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

The coronavirus-pandemic has a major impact on women's-mental and physical-health. Polycystic-ovary-syndrome (PCOS) has a high-predisposition to many cardiometabolic-risk factors that increase susceptibility to severe complications of COVID-19 and also exhibit an increased likelihood of subfertility. The study includes the extent of the effect of COVID-19-virus on renin-levels, glutathione-s-transferase-activity and other biochemical parameters in PCOS-women. The study included 120 samples of ladies that involved: 80 PCOS-patients, and 40 healthy-ladies. Both main groups were divided into subgroups based on COVID-19 infected or not. Blood-samples were collected from PCOS-patients in Kamal-Al-Samara Hospital, at the period between Decembe

تعد لعبة كرة السلة من الألعاب الرياضية التي تحتاج متطلبات بدنية ووظيفية خاصة بها، وذلك من خلال الانتقال داخل الملعب بالكرة أو بدونها والسبل للتخلص من ملاحقة الخصم أثناء الدفاع وكيفية المناورة أثناء الهجوم مع إجادة التصويب بكافة أنواعه داخل الملعب، ومن هنا تكونت مشكلة البحث في كيفية تطوير تلك العوامل الوظيفية والتي لها الأثر في الارتقاء بمستوى أداء اللاعب أثناء اللعب، وعن طريق استخدام الباحثان لطريقة جهاز ا

Abstract

This paper discusses the essence of the developmental process in auditing firms and offices at the world today. This process is focused on how to adopt the audit concepts which is based on Information and Communication Technology (ICT), including the Continuous Auditing (CA) in particular. The purpose of this paper is to design a practical model for the adoption of CA and its requirements according to the Technology Acceptance Model (TAM). This model will serve as a road map for manage the change and development in the Iraqi auditing firms and offices. The paper uses the analytical approach in reaching to the target results. We design the logical and systematic relations between the nine variable