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

Thin films of pure polycarbonate (PC) with anthracene doping PC films for different doping ratios (10, 20, 30, 40, 50 and 60 ml) were prepared by using a casting method. The influence of anthracene doping ratio on photo-fries rearrangement of polycarbonate was systematic investigated. Furthermore, pure PC and anthracene doping PC films were irradiated via UV light at a wavelength (254 nm) for different periods (5, 240, 288, and 360 hrs). The photo-fries rearrangement occurring in pure PC and anthracene doping PC films were monitored using UV and FTIR spectroscopies. The photo-fries rearrangement leads to scission the carbonate linkage and formation phenylsalicylate and dihydroxybenzophenes. The result of the UV spectrum confirms disappea

The study aims to determine the organizational monitoring mechanism in target organization as well as knowing the suffocation of work. The study depends on a questionnaire as a tool of collecting data on distributed random sample involved (45) person from different   levels in manufacturing isphelt Dohuk. The study depends on some hypothesis, the most significant one is that there is not impact of organizational monitoring of suffocation especially on the target organization.

Abstract

 This work involves studying the effect of adding some selective organic component mixture on corrosion behavior of pure Al and its alloys in condensed synthetic automotive solution (CSAS) at room temperature. This mixture indicates the increasing of octane number in previous study and in this study show the increasing in corrosion resistance through the decreasing in corrosion rate values.

Electrochemical measurements were carried out by potentiostat at 3 mV/sec to estimate the corrosion parameters using  Tafel extrapolation method, in addition to cyclic polarization test to know the pitting susceptibility of materials in tested medium.

The cathodic Tafel slope

Abstract

Heavy-duty diesel vehicle idling consumes fossil fuel and reduces atmospheric quality at idle period, but its restriction cannot simply be proscribed. A comprehensive tailpipe emissions database to describe idling impacts is not yet available. This paper presents a substantial data set that incorporates results from DI multi-cylinders Fiat diesel engine. Idle emissions of CO, hydrocarbon (HC), oxides of nitrogen (NOx), smoke opacity, carbon dioxide (CO₂) and noise have been reported, when three EGR ratios (10, 20 and 30%) were added to suction manifold.

CO₂ concentrations increased with increasing idle time and engine idle speed, but it didn’t show clear effect for IT adva

This research seeks through the adoption of two basic variables, where he considered the actuarial experience as an independent variable, while the process of accepting the risk and dimensions related to it is a dependent variable, the research was adopted to present the data achieved by the company during the life insurance business during the adoption of actuarial experience at the beginning of its work where Adoption of the historical method in the analysis of those data to prove the researcher's opinion, through the analysis of data (5 years) for the first period, which extends between (1975-1979), the period during which the company adopted the actuarial experience at the time, also taken data for the same dimensions related to the

The following research has been dealing ( Undermining Humanism in Foucault's thought and its implications in the pop art. meanings and facts which become in the process of the post-modernist.So the research's problem is to ask for undermining Humanism in Foucault's thought and how it formed through the formality of processors and the technical and stylistic and contents in pop art.. How are these technical aspects interact with each other to undermine the humanism in Foucault's mind and with system humanity, intellectual and social relations in the post-modern society . The contents of the first chapter, is the aim of the research, which aims to undermine know humanism in Foucault's mind and its implications in pop art , within the limit

The main purpose of this work is to introduce some types of fuzzy convergence sequences of operators defined on a standard fuzzy normed space (SFN-spaces) and investigate some properties and relationships between these concepts. Firstly, the definition of weak fuzzy convergence sequence in terms of fuzzy bounded linear functional is given. Then the notions of weakly and strongly fuzzy convergence sequences of operators  are introduced and essential theorems related to these concepts are proved. In particular, if ( ) is a strongly fuzzy convergent sequence with a limit  where linear operator from complete standard fuzzy normed space  into a standard fuzzy normed space  then  belongs to the set of all fuzzy bounded linear operators

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

The research aims to identify the level of functional engagement and hope-based thinking of kindergarten teachers, identify if there is a significant difference in functional engagement and hope-based thinking in terms of specialization and years of service for kindergarten teachers, identify if there is a significant correlation between functional engagement and hope-based thinking of kindergarten teachers. The current research is determined by kindergarten teachers in the Second Rusafa Baghdad Education Directorate for the academic year (2022-2023). In order to achieve the objectives of the research, the researcher prepared a functional engagement scale, which consists of (45) items in three areas: Perceptual and functional engagement