Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

In light of today's business world, who faces challenges and intense competition as a result of the rapid evolution of technical and informational, organizations had to respond to variables through the adoption of modern management techniques that reduce the effects of risks and activating the role of the internal control system in order to contribute to the early detection of risks and reduce the negative results expected .The research is to address the problem faced by organizations which still follow the traditional methods in the control activities, and the lack of knowledge of the management and their staff of the importance of the existence of risk management and internal control system takes into account these risks, and the limit

   The most frequently diagnosed condition in women at the age of reproduction is the polycystic ovarian syndrome (PCOS).it could be related to a complex endocrine condition, due to its heterogeneity and uncertainty about its etiology, as the clinical highlights of PCOS incorporate those related to reproductive signs such as decreased frequency of ovulation, irregular menstrual cycles, decreased fertility. Carnitine plays a substantial role in weight loss, glucose tolerance, insulin function and fatty acid metabolism. Thus carnitine plays a crucial role in controlling  obesity, insulin resistance, oxidative stress that are  associated with PCOS .While, AGEs are a diverse group of reactive molecules that are formed end

Zeolite Y nanoparticles were synthesized by sol - gel method. Dffirent samples using two silica sources were prepared.
Sodium metasilicate (Na2SiO3) (48% silica) and silicic acid silica (H2SiO3) (75% silica) were employed as silica
source and aluminum nitrate (Al(NO3)3.9H2O) was the aluminum source with tetrapropylammonium hydroxide
(TPAOH) as templating agent.
The synihesized-samples were characterized by X-ray diffraction, showed the requirement of diffirent aging time for
complete crystallization to be achieved. Transmission Electronic Microscope (TEM) images, showed the particles were
in the same range of 30 - 75 nm. FT-IR spectroscory, showed the synthesized samples having the zeolite Y crystal
properties. The i

    Годы, принадлежащие концу XIX – началу XX столетия, вошли в русскую литературу под красивым названием Серебряный век. В это время в стране появился целый ряд выдающихся поэтов, имена которых навсегда останутся в русской и мировой литературе. Это Ахматова, Гумилев, Блок, Маяковский и многие другие. Все эти люди творили в нелегкое для России время. Началом Серебряного века условно считают 189

The study aims to discuss the relation between imported inflation and international trade of Iraqi economy for the period (1990-2015) by using annual data. To achieve the study aim, statistical and Econometrics methods are used through NARDL model to explain non-linear relation because it’s a model assigned to measure non-linear relations and as we know most economic relations are non-linear, beside explaining positive and negative effects of imported inflation, and to reach the research aim deductive approach was adopted through using descriptive method to describe and determine phenomenon. Beside the inductive approach by g statistical and standard tools to get the standard model explains the

Surface electromyography (sEMG) and accelerometer (Acc) signals play crucial roles in controlling prosthetic and upper limb orthotic devices, as well as in assessing electrical muscle activity for various biomedical engineering and rehabilitation applications. In this study, an advanced discrimination system is proposed for the identification of seven distinct shoulder girdle motions, aimed at improving prosthesis control. Feature extraction from Time-Dependent Power Spectrum Descriptors (TDPSD) is employed to enhance motion recognition. Subsequently, the Spectral Regression (SR) method is utilized to reduce the dimensionality of the extracted features. A comparative analysis is conducted between the Linear Discriminant Analysis (LDA) class