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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
Sun May 12 2019
Journal Name
Al-khwarizmi Engineering Journal
Effect of Quenching Media Variations on the Mechanical Behavior of Martensitic Stainless Steel
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The purpose of this study is designate quenching and tempering heat treatment by using Taguchi technique to determine optimal factors of heat treatment (austenitizing temperature, percentage of nanoparticles, type of base media, nanoparticles type and soaking time) for increasing hardness, wear rate and impact energy properties of 420 martensitic stainless steel. An (L18) orthogonal array was chosen for the design of experiment. The optimum process parameters were determined by using signal-to-noise ratio (larger is better) criterion for hardness and impact energy while (Smaller is better) criterion was for the wear rate. The importance levels of process parameters that effect on hardness, wear rate and impact energy propertie

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Publication Date
Tue Oct 08 2002
Journal Name
Iraqi Journal Of Laser
Effect of Gas Mixture on the Output Characteristics of a CW CO2 Laser
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In this work, the effect of partial amounts of gases in gas mixture of a CW CO2 laser on the output power was investigated. Also their effect on the condition determining the glow-discharge self-sustaining required for pumping the active medium was studied. Two fit relations were derived to predict the output laser power and the electric field to unit pressure ratio as functions to the partial amounts of gases. Results presented in this work could be used fruitfully to determine some of the optimum operational conditions of glow-discharge low-power CW CO2 lasers.

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Publication Date
Tue Mar 01 2022
Journal Name
Iraqi Journal Of Physics
Effect of Carbon Nanoparticles on the Performance Efficiency of a Solar Water Heater
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Carbon nanoparticles are prepared by sonication using carbon black powder. The surface morphology of carbon black (CB) and carbon nanoparticles (CNPs) is investigated using scanning electron microscopy (SEM). The particles size ranges from 100 nm to 400 nm for CB and from 10 nm to 100 nm for CNPs. CNPs and CB are mixed with silicon glue of different ratios of 0.025, 0.2, 0.05, and 0.1 to synthesis films. The optical properties of the prepared films are investigated through reflectance and absorbance analyses. The ratio of 0.05 for CNPs and CB is the best for solar paint because of its higher solar water heater efficiency and is then added to the silicon glue . Temperature of cold water and temperature of hot water in storage tank were ta

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Publication Date
Tue Nov 01 2022
Journal Name
Al-adab Journal
A Pragmatic Analysis of Implicatures in Covid-19 Coronavirus English Jokes: A Neo-Gricean Approach
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Publication Date
Sun Apr 14 2024
Journal Name
Eastern Mediterranean Health Journal
Satisfaction of women with telehealth services during COVID-19 paves the way for wider implementation
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Background: Although underdeveloped in Iraq, telehealth was one tool used to continue health service provision during the COVID-19 pandemic. Aim: To assess women’s experiences and satisfaction with gynaecological and obstetric telehealth services in Iraq during the COVID-19 pandemic. Methods: Free telehealth services were provided by 4 obstetrician-gynaecologists associated with private clinics in 2020–2021. All patients who accessed the services between June 2020 and February 2021 were invited to complete a postconsultation survey on their experience and satisfaction with services. Results were analysed using descriptive statistics and logistic regression conducted using SPSS version 25. Results: A total of 151 (30.2%) women re

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Publication Date
Wed Jan 01 2020
Journal Name
Studies In Big Data
COVID-19 Diagnostics from the Chest X-Ray Image Using Corner-Based Weber Local Descriptor
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Corona Virus Disease-2019 (COVID-19) is a novel virus belongs to the corona virus's family. It spreads very quickly and causes many deaths around the world. The early diagnosis of the disease can help in providing the proper therapy and saving the humans' life. However, it founded that the diagnosis of chest radiography can give an indicator of coronavirus. Thus, a Corner-based Weber Local Descriptor (CWLD) for COVID-19 diagnostics based on chest X-Ray image analysis is presented in this article. The histogram of Weber differential excitation and gradient orientation of the local regions surrounding points of interest are proposed to represent the patterns of the chest X-Ray image. Support Vector Machine (SVM) and Deep Belief Network (DBN)

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Publication Date
Sun Jun 12 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Using Phone Calls to Promote Community Pharmacist Counselling during COVID-19 Pandemic in Baghdad, Iraq
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Drug consultation is an important part of pharmaceutical care. mobile phone call or text message can serve as an easy, effective, and implementable alternative to improving medication adherence and clinical outcomes by providing the information needed significantly for people with chronic illnesses like diabetes and hypertension particularly during pandemics like COVID-19 pandemic.

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Publication Date
Fri Apr 01 2022
Journal Name
Heliyon
Stigma towards health care providers taking care of COVID-19 patients: A multi-country study
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Publication Date
Tue Jun 30 2015
Journal Name
Al-khwarizmi Engineering Journal
Studying and Modeling the Effect of Graphite Powder Mixing Electrical Discharge Machining on the Main Process Characteristics
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Abstract

This paper concerned with study the effect of a graphite micro powder mixed in the kerosene dielectric fluid during powder mixing electric discharge machining (PMEDM) of high carbon high chromium AISI D2 steel. The type of electrode (copper and graphite), the pulse current and the pulse-on time and mixing powder in kerosene dielectric fluid are taken as the process main input parameters. The material removal rate MRR, the tool wear ratio TWR and the work piece surface roughness (SR) are taken as output parameters to measure the process performance. The experiments are planned using response surface methodology (RSM) design procedure. Empirical models are developed for MRR, TWR and SR, using the analysis

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Publication Date
Fri Feb 28 2025
Journal Name
Energies
Synergizing Machine Learning and Physical Models for Enhanced Gas Production Forecasting: A Comparative Study of Short- and Long-Term Feasibility
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

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