Severe acute respiratory corona viruses (SARS-COVs) are a particular category of RNA viruses that have emerged as a potential danger to the human population, triggering epidemics and pandemics that have resulted in catastrophic human mortality. The SARS-CoV2, responsible for the COVID-19 pandemic that began on December 12, 2019 in Wuhan, China, has been linked to bats. A new SARS-CoV-2 variant appeared in late December 2020. Mutations with variants continued to appear until the time of this study. Thus, this study aimed to provide a local database among Iraqi patients about SARS-COV-2 variants as there have been very few local studies documenting its existence and its relationship with the progression and severity of infection. For this study 234 nasal swabs were collected from COVID-19 positive individuals between March 2021 to March 2022. RNA was extracted and tested by using real-time reverse transcriptase polymerase chain reaction (rRT-PCR) assay to confirm infection, and the variants were detected by using a special kit that stratified the characteristic mutations. Results showed the presence of Alpha, Beta or Gamma and Omicron variants in our population at the same time as their global spread at high rates with different severity of cases. It increased in severity during infections with wild type 26/32 (81.25%) and Alpha 82/109 (75.23%) variants but a high incidence of Beta or Gamma 28/38 (73.68%) and Omicron 35/46 (76.09%) variants within mild-moderate infections. Moreover, there was a significant increase in severity in older age groups than younger. Hence, we can conclude that most severe infections with SARS-COV-2 appeared in wild type and during the appearance of Alpha variant which provided a unique database of variants of COVID-19 circulating in the Iraqi population and also assisted in determining the severity of disease. More research is needed on this subject.
Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a
... Show MorePalm vein recognition is a one of the most efficient biometric technologies, each individual can be identified through its veins unique characteristics, palm vein acquisition techniques is either contact based or contactless based, as the individual's hand contact or not the peg of the palm imaging device, the needs a contactless palm vein system in modern applications rise tow problems, the pose variations (rotation, scaling and translation transformations) since the imaging device cannot aligned correctly with the surface of the palm, and a delay of matching process especially for large systems, trying to solve these problems. This paper proposed a pose invariant identification system for contactless palm vein which include three main
... Show MoreMeans of communication has a great impact on all fields of awareness including health awareness by increasing the knowledge of community about health and developing their abilities to improve human health and cultural awareness. According to the importance of health awareness for a community to develop their intellectual and physical integrity, the researcher has found that it is essential to know the role of means of communication as a source of information for many students being active and main segments to build their society intellectually, socially and economically.
The research has focused on the study of health awareness among students and their health knowledge derived from the means of communicat
... Show MoreWater balance approaches are strategies for resolving key theoretical and practical hydrological issues. The major goals of this study are to examine climatic elements and conditions to calculate groundwater recharge using the water balance approach. The study area is located in Mandaly city, Diyala Governorate, eastern Iraq. The metrological data was gathered between 1994 and 2020 to evaluate the study area's climate. The annual rainfall rate has been 248.61 mm, with a relative humidity of 43.89%, a temperature of 24.41 oC, a wind speed of 1.99 m/sec, sunshine of 8.32 hours per day, and evaporation of (268.09 mm). The total amount of corrected evapotranspiration was 1010.09 mm, with a peak value of 225.29 mm in Jul
... Show MoreThis work addressed the assignment problem (AP) based on fuzzy costs, where the objective, in this study, is to minimize the cost. A triangular, or trapezoidal, fuzzy numbers were assigned for each fuzzy cost. In addition, the assignment models were applied on linguistic variables which were initially converted to quantitative fuzzy data by using the Yager’sorankingi method. The paper results have showed that the quantitative date have a considerable effect when considered in fuzzy-mathematic models.
Skin detection is classification the pixels of the image into two types of pixels skin and non-skin. Whereas, skin color affected by many issues like various races of people, various ages of people gender type. Some previous researchers attempted to solve these issues by applying a threshold that depends on certain ranges of skin colors. Despite, it is fast and simple implementation, it does not give a high detection for distinguishing all colors of the skin of people. In this paper suggests improved ID3 (Iterative Dichotomiser) to enhance the performance of skin detection. Three color spaces have been used a dataset of RGB obtained from machine learning repository, the University of California Irvine (UCI), RGB color space, HSV color sp
... Show MoreNew Schiff base ligand (E)-6-(2-(4-(dimethylamino)benzylideneamino)-2-(4-hydroxyphenyl)acetamido)-3,3- dimethyl-7-oxo-4-thia-1- azabicyclo[3.2.0]heptane-2-carboxylic acid = (HL) was synthesized via condensation of Amoxicillin and 4(dimethylamino)benzaldehyde in methanol. Figure -1 Polydentate mixed ligand complexes were obtained from 1:1:2 molar ratio reactions with metal ions and HL, 2NA on reaction with MCl2 .nH2O salt yields complexes corresponding to the formulas [M(L)(NA)2Cl],where M=Fe(II),Co(II),Ni(II),Cu(II),and Zn(II), A=nicotinamide .
In this paper , an efficient new procedure is proposed to modify third –order iterative method obtained by Rostom and Fuad [Saeed. R. K. and Khthr. F.W. New third –order iterative method for solving nonlinear equations. J. Appl. Sci .7(2011): 916-921] , using three steps based on Newton equation , finite difference method and linear interpolation. Analysis of convergence is given to show the efficiency and the performance of the new method for solving nonlinear equations. The efficiency of the new method is demonstrated by numerical examples.
Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS
... Show MoreThe corrosion behavior of 2024 aluminium alloy was investigated in alkaline medium (pH=13) containing 0.6 . in absence and presence of different concentrations of three amino acids separately [Methionine, Glutamice acid and Lysine] as environmentally friendly corrosion inhibitors over the temperature range (293-308)K. Electrochemical polarization method using potentiostatic technique was employed. The inhibition efficiency increased with an increase of the inhibitor concentration but decreased with increase in temperature . The maximum efficiency value was found with lysine =80.4 of 293 k and 10 . concentration of lysine. The adsorption of the amino acids was found to obey Langmuir adsorption isotherm . Some thermodynamic parameter âˆ
... Show More