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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
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
The Effect of Adding Carboxymethyl Cellulose and Zinc Sulfate on the Corrosion Characteristics of the Drilling Fluid
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Drilling solutions can be considered as an intricate mixture comprising of number of chemical additives which aid specific needs such as controlling the rheological properties and reducing corrosion. Inhibitors are substances that are added in small concentrations to corrosive environment to decrease the corrosion. Their applications can be found in drilling equipments. The effect of adding Zinc Sulphate and Carboxymethyl Cellulose to study their influence on the corrosion of carbon steel in Bentonite mud has been evaluated using Weight Loss Technique. This study focuses on determining rheological properties and corrosion characteristics. Results show CMC and ZnSO4 work as inhibitors when added to the Bentonite with inhibition

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Publication Date
Sat Oct 01 2022
Journal Name
Al–bahith Al–a'alami
Language communication, and the impact of journalism after 2003 AD (a study in the two newspapers, Al-Takahi and Al-Sabah)
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The methods used by the print media (press) is varied in conveying its messages and its orientations to the readers. But language takes the leading method among these methods, or a real competitor - so far - due to the characteristics and advantages of languages, including: ease, abbreviation, and development, etc.

In the midst of such events, political tensions, and what they carry of the global developments, and among which was the most important the fall of the former Iraqi regime in the spring of 2003, the press had the greatest share, and a large portion on the level of monitoring, analyzing, and interpreting the various consequences of the event. The interpreting of the news varies according to the evolving political trends

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Publication Date
Fri Apr 16 2021
Journal Name
Turkish Journal Of Computer And Mathematics Education (turcomat)
The Impact Of Reflexive Learning Strategy On Mathematics Achievement By First Intermediate Class Students And Their Attitudes Towards E-Learning
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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Investigating the Sensitivity Effect of Actuarial Assumptions on Pension Liabilities in Malaysia
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Malaysia will be an ageing population by 2030 as the number of those aged 60 years and above has increased drastically from 6.2 percent in 2000 and is expected to reach 13.6 percent by 2030. There are many challenges that will be faced due to the ageing population, one of which is the increasing cost of pensions in the future. In view of that, it is necessary to investigate the effect of actuarial assumptions on pension liabilities under the perspective of ageing. To estimate the pension liabilities, the Projected Unit Credit method is used in the study and commutation functions are employed in the process. Demographic risk and salary risk have been identified as major risks in analyzing pension liabilities in this study. The sensitivity

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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
Effect of SnO2/In2O3 Atomic Ratio on the Structural and Optical Properties of ITO Thin Filmsof SnO2:In2O3 Thin Film Composite Ratio on Structural and Optical Properties
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In this work, the effect of atomic ratio on structural and optical properties of SnO2/In2O3 thin films prepared by pulsed laser deposition technique under vacuum and annealed at 573K in air has been studied.  Atomic ratios from 0 to 100% have been used. X-ray diffraction analysis has been utilized to study the effect of atomic ratios on the phase change using XRD analyzer and the crystalline size and the lattice strain using Williamson-Hall relationship. It has been found that the ratio of 50% has the lowest crystallite size, which corresponds to the highest strain in the lattice. The energy gap has increased as the atomic ratio of indium oxide increased.

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Publication Date
Sun Dec 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Effect of Pre-Tension and Orientation on the Springback Behavior of the Sheet Brass 65-35
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One of the most important phenomenon that occurs in sheet metal forming processes is the spring-back, which causes several geometrical alterations in the parts. The accurate prediction of springback after bending unloading is the key to the tool design, operation control, and precision estimate concerning the part geometry. This study investigated experimentally the effect of pretension in three rolling direction (0, 90, 45 degree) on the springback behavior of the yellow brass, sheet under V shape bending die. The pre-tension ranges from five different levels starting of 11% to 55% from the total strain in each rolling direction by regular increase of 11 %, then bent on a V-die 90 degree for the springback estimate. From experiment the

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Publication Date
Fri Sep 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Charge Stratification and Fuel/Air Ratio Effect on the Efficiency of (ICADE) I. C. Engine Cycle
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The Isolated Combustion and Diluted Expansion (ICADE) internal combustion engine cycle combines the advantages of constant volume combustion of the Otto cycle with the high compression ratio of the Diesel cycle.   This work studies the effect of isolated air mass (charge stratification) on the efficiency of the cycle; the analysis shows that the decrease of isolated air mass will increase the efficiency of the cycle and the large dilution air mass will quench all NOx forming reactions and reduce unburned hydrocarbons. Furthermore, the effect of Fuel / Air ratio on the efficiency shows that the increase of Fuel / Air ratio will increase efficiency of the cycle.

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Publication Date
Sat Apr 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Effect of Surface and Subsurface Drip Irrigation and Furrows Irrigation System on Water Productivity, Growth and Yield of Lettuce (Lactuca Sativa L)
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A field experiment was conducted in Al-Yusufiya district - Al-Mahmoudiya district, Baghdad province during the winter season 2021, to study improving the efficiency and management of water use and the productivity of lettuce under different irrigation systems. The Nested-Factorial Experiments design was used, where the main plots include the first factor, irrigation levels (I1) 50%, (I2) 75%, (I3) 100, (I4) 125%, (I5) 150% ETpan. After depleting 35% of the available water and in terms of climatic data from the American Evaporative Basin, Class A. Then the main factor is divided into three replicates, and the coefficients of the second factor are distributed randomly within each replicate, which includes the irrigation system: surface drip i

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Publication Date
Mon Oct 30 2023
Journal Name
Aro-the Scientific Journal Of Koya University
Enhancing Upper Limb Prosthetic Control in Amputees Using Non-invasive EEG and EMG Signals with Machine Learning Techniques
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Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte

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Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
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The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

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