In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca

Polycystic ovary syndrome (PCOS) referring to a syndrome that is recognized as a life-course disease and has both metabolic and reproductive signs; main pathophysiological cause includes insulin resistance, hyperandrogenism, and oxidative stress state. The study aimed to assess the impact of combining Myoinositol and Metformin, the main insulin-sensitizing drugs, on improving clinical, metabolic, and hormonal parameters in females with PCOS. A clinical trial that was prospective, randomized, and comparative on 54 patients (aged 18-40 y) are divided into three groups: group1 patients allocated to receive Myo-inositol(4g), group2 patients assigned to receive Metformin(1g) and group3 patients assigned to receive Myo-inositol(4g) + Metformin

The triggering effect for the face pumping of Nd:YVO₄ disc medium of 4×5×0.5 mm was investigated using bulk diode laser at different resonator cavity length in pulse mode and at repetition rate of 1.3kHz. The maximum emitted peak power was found to be 100, 82, and 66 mW for resonator lengths of 10, 13.5, and 17.5 cm respectively, while the threshold pumping power was found to be 41mW. The maximum emitted peak power obtained was 300 mW when using external triggering and 10cm length, with repetition of 3Hz.

Wars represent one of the most serious threats to the world order; It is considered a violation of international laws and norms, and humanitarian principles. From this point comes the study of the importance of the topic entitled (The Future of the Russian-Ukrainian war and the extent of its Reflection on the security of Eastern European countries after the year 2022). This study is based on reviewing future possibilities (scenarios) of war. The Russian-Ukrainian war, which was launched by the Russian government led by Russian President Vladimir Putin in February 2022, is still ongoing at the time of writing this research. This chapter includes three possibilities (scenarios). The first possibility deals with the development of the war t

المواقف افي الدول العربية قراءة تحليلية في مواقف لدولية من التغيير (الولايات المتحدة - الاتحاد الاوروبي - روسيا)

Afamin, which is a human plasma glycoprotein, a putative multifunctional transporter of hydrophobic molecules and a marker for metabolic syndrome. Afamin concentration have been proposed to have a significant role as a predictor of metabolic disorders. Since NAFLD is associated with metabolic risk factors, e.g., dyslipidemia, insulin resistance and visceral obesity, it is considered as the hepatic manifestation of the metabolic syndrome. The objective of this study is to determine Afamin levels in hypothyroid patients with and without fatty liver disease and compare the results with controls. Also to study the relationship of Afamin level with the Anthropometric and Clinical Features (Age, Gender, BMI and Duration of Hypothyroidism) , Serum

The purpose of this study was to measure serum levels of insulin-like growth factor-binding protein (IGFBP7), Insulin-like Growth Factor 1 (IGF-1), Growth Hormone (GH), Interleukin 6 (IL-6) and insulin in acromegaly patients and healthy controls. The acromegaly group had 60 patients, while the population group had 30 people who had never had acromegaly before. The concentration of IGFBP7, IGF-1, GH, IL-6, and insulin were determined. The results of the present study indicate that IGFBP7 level in the acromegaly group was significantly lower (1.690.07 ng/mL vs. 2.740.12 ng/mL, respectively, p = 0.001). IGF-1, GH, IL-6, and insulin concentrations were also significantly higher in acromegaly patients. The diagnostic accuracy (2.194) was exce

Abstract Metabolic syndrome (MS) is a group of clinical and biological abnormalities included risk of insulin resistance , disorders in glucose metabolism , abdominal obesity and abnormal lipid profile these features confer a greater risk of cardiovascular diseases . Anyway, the co-occurrence of diabetes mellitus and metabolic syndrome potentiates the cardiovascular risk associated with each of the two conditions. The present study aimed to determine a relationship between prolactin level in type -2- diabetic Iraqi women and metabolic syndrome, as well to find a relationship between prolactin level and other studied biochemical markers. seventy menopausal diabetic women with metabolic syndrome with age in range (45-50) years were enrolled i