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Post COVID-19 Effect on Medical Staff and Doctors' Productivity Analysed by Machine Learning
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The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. These results reflect the overall impact observed following the entire course of the COVID-19 pandemic and are not specific to a particular wave. The analysis revealed that older participants experienced a more pronounced decline in productivity, with a mean decrease of 35% compared to younger participants. Female participants, on average, had a 28% decrease in productivity compared to their male counterparts. Moreover, individuals with lower socioeconomic status exhibited a substantial decline in productivity, experiencing an average decrease of 40% compared to those with higher socioeconomic status. Similarly, participants who slept for fewer hours per night had a significant decline in productivity, with an average decrease of 33% compared to those who had sufficient sleep. The machine learning analysis identified age, specialty, COVID-19 complications, socioeconomic status, and sleeping time as crucial predictors of productivity score. The study highlights the significant impact of post-COVID-19 on the productivity of medical staff and doctors in Iraq. The findings can aid healthcare organizations in devising strategies to mitigate the negative consequences of COVID-19 on medical staff and doctors' productivity.

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Publication Date
Tue Jan 02 2018
Journal Name
Journal Of Educational And Psychological Researches
Self-organized learning strategies and self-competence among talented students
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Investigating the strength and the relationship between the Self-organized learning strategies and self-competence among talented students was the aim of this study. To do this, the researcher employed the correlation descriptive approach, whereby a sample of (120) male and female student were selected from various Iraqi cities for the academic year 2015-2016.  the researcher setup two scales based on the previous studies: one to measure  the Self-organized learning strategies which consist of (47) item and the other to measure the self-competence that composed of (50) item. Both of these scales were applied on the targeted sample to collect the required data

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Effects of Nitrogen and Sulfur Sprays on the Growth and Production of Broccoli Brassica Oleracea var. Italica L.: nitrogen and sulfur spray enhance broccoli growth and production
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In order to achieve optimal plant growth and production, essential nutrients must be readily available in adequate quantities and in a balanced proportion to give a good yield, especially broccoli which has health benefits that may not be found in many other plants. For this purpose, this experiment was carried out during the seasons 2019/2020 in the botanical garden of the Department of Biology, College of Science for Women, University of Baghdad, to study the effects of nitrogen and sulphur and their interaction on eight parameters reflecting the overall traits of vegetative growth, yield, and chlorophyll content of broccoli Brassica oleracea L. (var. italic JASSMINE F1 Hybrid). A factorial design with three replicates was use

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Publication Date
Mon Sep 30 2024
Journal Name
نسق
تحليل تاثير الجهد البدني على الشقوق الطليقة ومضادات الاكسدة
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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Non-linear support vector machine classification models using kernel tricks with applications
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The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Microgrid Integration Based on Deep Learning NARMA-L2 Controller for Maximum Power Point Tracking
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This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

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Publication Date
Sat Dec 31 2011
Journal Name
Al-khwarizmi Engineering Journal
Effect of Mixed Corrosion Inhibitors in Cooling Water System
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The effect of mixed corrosion inhibitors in cooling system was evaluated by using carbon steel specimens and weight loss analysis. The carbon steel specimens immersed in mixture of sodium phosphate (Na2 HPO4) used as corrosion inhibitor and sodium glocunate (C6 H11 NaO7) as a scale dispersant at different concentrations (20,40, 60, 80 ppm) and at different temperature (25,50,75 and 100)ºC for (1-5) days. The corrosion inhibitors efficiency was calculated by using uninhibited and inhibited water to give 98.1%. The result of these investigations indicate that the corrosion rate decreases with the increase the corrosion inhibitors concentration at 80 ppm and at 100ºC for 5 days, (i.e,

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Publication Date
Mon Jan 01 2018
Journal Name
Journal Of The College Of Languages (jcl)
Analysis of the symbolic images in the work of Mexican theater of: "all cats are brown," the writer Carlos Fuentes and "Palinuro on the stairs," the writer Fernando del Paso
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 This article briefly analyzing contemporary works appeared in theater writer from Latin America, which comes within the theme of "power." Latin American Literature, such as two-way extremely clear: the vanguard of social and attention, have arrived at certain moments to some extent be regarded as a two-way rival. That desire to participate in the revolution of expression and artistic significance, has appeared evident in the literature of Latin America in the late nineteenth century and ended in the third decade of the twentieth century. The writers that stage would prefer not to serve the objectives of the revolution of Arts own but the objectives of social and political revolution that stimulate the world. These acts were issued

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Publication Date
Sun May 02 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Application of banking institutions' governance variables and their impact on financial performance as measured by (ROA & ROE): an applied study on a sample of local Islamic banks listed on the Iraq Stock Exchange
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The research seeks to achieve its goal of demonstrating the impact of applying banking governance variables on the financial performance of Islamic banks, and the independent research variables are represented by (X) by (the number of independent members in the board (X1), the number of directors in the board (X2), the number of committees emanating from the board ( X3), the percentage of shares owned by major shareholders in the board (X4), the number of members of the Sharia supervisory board (X5)), and the dependent variable (Y) is represented by (rate of return on assets (Y1), rate of return on equity (Y2)).

The research sample included (4) Islamic banks, namely (Iraqi Islamic Bank, National Islamic Bank, Jihan Islamic Bank,

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Improving Shear Strength of Soft Clay by Using Torn Belts Chips
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Random throwing of industrial waste has a significant impact on the environment unless it takes into account the conditions of engineered destroying and/or re-used. Taking the advantage of re-using waste materials in engineering projects represents a well-planned project in order to resolve a lot of engineering problems for some difficult soils. The objective of this study was to evaluate the capability and effects of Rubber Shreds (RS) from scrap torn belts towards improving the shear strength of soft clay. A direct shear tests were conducted on soft clay-RS mixture. The following parameters were investigated to study the influence of RS content, water content, normal stress, and dilation ratio. From experimental test results it was fou

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Publication Date
Sat Dec 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
The Cluster Analysis by Using Nonparametric Cubic B-Spline Modeling for Longitudinal Data
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Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.

In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.

The longitudinal balanced data profile was compiled into subgroup

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