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

Pathogenic microorganisms are becoming more and more resistant to antimicrobial agents. So the synthesis of new antimicrobial agents is very important. In this work, new 5-fluoroisatin-chalcone conjugates 5(a–g) were synthesized based on previous research that showed the modifications of the isatin moiety led to the synthesis of many derivatives that have antimicrobial activity. 4-aminoacetophenone reacts with 5-fluoroisatin to form Schiff base (3), which in turn reacts with two different groups of aromatic (carbocyclic and heterocyclic) aldehydes 4(a–g) separately to form the final compounds 5(a–g). Proton-nuclear magnetic resonance (¹H-NMR) and Fourier-transform infrared (FT-IR) spectroscopy were used to confirm the chemic

Some new complexes of 4-(5-(1,5-dimethyl-3-oxo-2-phenyl pyrazolidin-4- ylimino)-3,3-dimethyl cyclohexylideneamino) -1,5- dimethyl-2- phenyl -1H- pyrazol -3(2H) –one (L) with Mn(II), Fe(III), Co(II), Ni(II), Cu(II), Pd(II), Re(V) and Pt(IV) were prepared. The ligand and its metal complexes were characterized by phisco- chemical spectroscopic techniques. The spectral data were suggested that the (L) as a neutral tetradentate ligand is coordinated with the metal ions through two nitrogen and two oxygen atoms. These studies revealed Octahedral geometries for all metal complexes, except square planar for Pd(II) complex. Moreover, the thermodynamic activation parameters, such as ?E*, ?H, ?S, ?G and K are calculated from the TGA curves using Coa

Background: Hyperthyroidism refers to overactive of thyroid gland leading to excessive synthesis of thyroid hormones and accelerated metabolism in the peripheral tissue. Objective: The aim of this study is to evaluate a new member of the IL-1 super family of cytokines interleukin-33(IL-33) levels in serum .in order to evaluate its utility as clinical bio marker of autoimmune disease (i.e. hyperthyroidism) Methods: The present study was conducted on 30 patients from the Iraqi female patients with hyperthyroidism attending Baghdad teaching hospital, in addition to 30 healthy controls. All subjects were (35-65) years old. Parameters measured in the sera of patients and healthy groups, were interleukin -33 (IL-33), Thyroxin (T4), Thyroxin (T3)

أن إحدى اكبر مشاكل الصحة العالمية هي ظهور مقاومة الميكروبية للأدوية الشائعة لذلك هناك حاجة ملحة لمضادات جرثومية جديدة ذات نشاط أحيائي معزز .في هذا الدراسة, تم تحضير خمسة مشتقات جديدة من الكينولين  A,B,C,D  وEكمضادات جرثومية. تم فحص بنية المركبات المحضرة باستخدام  UV light , FTIR NMR  . تم استخدام طريقة الانتشار بالحفر في الطبق لاختبار الخصائص المضادة للبكتريا للمركبات المحضرة في المختبر ضد نوعين من البكتريا الموجبة

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

   This research deals with the financial reporting for non-current assets impairment from the viewpoint of international accounting standards, particularly IAS 36 "Impairment of non-current assets." The research problems focus on the presence of internal and external indicators on impairment of non-current assets in many of companies listed in Iraqi stock exchange. So it is required to apply IAS 36 to reporting for the impairment loss of assets since this impairment impact certain financial indicators. These indicators help users in their decision-making and forecasting future financial situation and the ability of the company to achieve future profits or maintain current profits. The research aims to shedding lig

The significance of the study lies in identifying a scientific and objective indicator that clarifies the extent to which key cognitive and visual abilities contribute to skill performance in tennis. This enables coaches and instructors to design scientifically based educational and training units that incorporate these abilities according to their level of contribution, thereby positively impacting technical performance. The abundance of stimuli in tennis and the difficulty of controlling performance, due to the sport's ongoing developments, require a high level of cognitive and visual abilities. The researchers aimed to examine the problem of inadequate organization in educational content, where one aspect is emphasized over other