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 %.
- coli K12 and B. subtilis 168 were investigated for their cadmium and mercury tolerance abilities. They were developed by UV mutagenesis technique to increase their tolerances either to cadmium or mercury, and their names then were designated depend on the name and concentration of metals. E. coli K12 Cd3R exhibited bioremediation amount of 6.5 mg Cd/g dry biomass cell. At the same time, its wild-type (E. coli K12 Cd3) was able to remove 5.2 mg Cd/g dry biomass cell in treatment of 17 mg Cd /L within 72 hours of incubation at 37 °C (pH=7) in vitro assays. The results show that E.coli K12 Hg 20 was able to remove 0.050 µg Hg/g dry biomass cell
This research aims to know the role and impact of participation in the capabilities of human resources programs, and for the purpose of measuring it has been determined the dimensions of these two variables by relying on standards for this purpose, was chosen as the Ministry of Higher Education and Scientific Research / device supervision and scientific calendar as one of the important departments in the ministry and includes a large number of individuals at different organizational levels for the purpose of answering a questionnaire prepared for the purpose of measurement and access to the results and the achievement of the objectives of the research and which ha
... Show MoreIn this article it is proved experimentally that the photon is a particle that has mass and constant wavelength by explaining the effect of refractive index on the wavelength and the natural mass of photon. It is very difficult to measure the mass of photon, a simple and easy process was proposed in this paper to calculate the mass length of photon in vacuum (Y) and in medium (Y*), by measuring the length of laser beam in air (Lair) and in medium (Lmed). A new method was postulated to calculate refractive index by using these relations (n = Y*/Y), and (n = Lmed / Lair) which supposed a new theory of light.
The study aimed to recognize the impact of polygamy on academic achievement and self-confidence among Sattam bin Abdul Aziz University students. To achieve this goal, the researchers used the Descriptive Analytical method using The Self Confidence measurement ,that has been prepared for the purposes of this study, consists set of 29 questions, then applied to the students sample that emerges from polygamy and one- wife families, study sample consists of randomly selected 230 students registered for the year .1435-1436
The results of the study showed presence of medium statistical impact on the significance level (a 4 0.05), this proof significant statistical effect of polygamy on self-confidence among the sample of Prince Sat-tam Univ
Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s
... Show MoreObjective: to evaluate body image and depression symptoms of children with precocious puberty, and find out association between children`s sociodemographic characteristics and their body image and depression signs. Methodology: A cross sectional study, sample of (80) child from both gender, > 7 years were included due to their ability to express their own feeling, diagnosed with precocious puberty, attending out-patient endocrine clinics at pediatric hospitals in Baghdad city. Data collected, during the period from May to November 2018. Consent form has taken from children and their guardians to participate in study. Child body image scale (CBIS) was used to evaluate children body satisfaction (1) and Mood and feeling questionnaire (M
... Show MoreThis study focused on spectral clustering (SC) and three-constraint affinity matrix spectral clustering (3CAM-SC) to determine the number of clusters and the membership of the clusters of the COST 2100 channel model (C2CM) multipath dataset simultaneously. Various multipath clustering approaches solve only the number of clusters without taking into consideration the membership of clusters. The problem of giving only the number of clusters is that there is no assurance that the membership of the multipath clusters is accurate even though the number of clusters is correct. SC and 3CAM-SC aimed to solve this problem by determining the membership of the clusters. The cluster and the cluster count were then computed through the cluster-wise J
... Show MoreThe study aims to explore the effect of cognitive behavioral therapy on internet addiction among university students. The experimental method was used. The study population consisted of (100) university students (50 males, 50 females). The Research sample included (13) University students at Baghdad University addicted to the Internet (9 males, 4 females), divided into two groups: a control group consisting of (6) individuals (4 males, 2 females) and an experimental sample consisting of (6) individuals (4 males, 2 females). The Scale of Internet Addiction by Young (1996), which was translated and modified into the Arabic language by (Moegel and Prism, 2016), was administered to the study sample. The sample was subjected to two sess
... Show MoreThe research aims to study and assess the effectiveness of preventive measures banking for the reduction of money laundering based on the checklist (Check list), which have been prepared based on the paragraphs of some of the principles and recommendations of international and Money Laundering Act No. 93 of 2004 and the instructions thereto, to examine and assess the application of these measures by Gulf Commercial Bank, which was chosen to perform the search.
I've been a statement the concept of money laundering in terms of the definition and characteristics, stages and effects of political, economic and social as well as the nature of banking supervision in terms of the definition and the most important
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