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.
A cost-effective and efficient detector was created to conduct thorough turbidimetric measurements by reaction of Co (II) ion with calcium ferro cyanide to form bright green particulate, using the method of continuous flow injection analysis, the use of NAG-5SX1-1D-SSP Analyzer in determining cobalt (II) ion in a test for the validity of the new design. The NAG-5SX1-1D-SSP Analyzer is composed of five irradiation sources of white snow leds having the diameter of 10 mm with one solar cell of 55 mm length, 13.5 mm width. Using a selector switch to select the optimum voltage to be used which was 2.7 VDC. Under conditions of optimization, cobalt (II) ion was determined at 0.005–20 mmol. L–1(n = 23) while linearity dynamic range 0.005–7 mm
... Show MoreReading is one of the essential components of the English language. Countries that use English as a second language (ESL) sometimes have difficulties in reading and comprehension. According to many researches, mother tongue has proved some interferences with learning a second language. This study investigated the results of reading difficulties of young second language learners in terms of accuracy, comprehension, and rate using the Neale Analysis of Reading Ability test. The study was carried out in one of the High Schools for Boys in Hyderabad, India and included Grade five, aged 10-12 years. In order to understand the reading difficulties of English as a second language, a qualitative approach was employed. Interview, reading tes
... Show MoreThe study employs Critical Discourse Analysis (CDA) to analyze how technological discourses are influenced by AI-generate d English texts. The research marries Fairclough’s three-dimensional discourse analysis, Van Dijk’s socio-cognitive approach, and Corpus-Assisted Discourse Studies (CADS) in the use of mixed-methods research, integrating primarily qualitative analysis with quantitative corpus-based data, to perform a thorough analysis of twenty AI-produced English texts. The findings identify the sophisticated linguistic mechanisms through which AI language employs modality, nominalization, passive voice, and interdiscursive blending to normalize and legitimize dominant contemporary ideologies. These mechanisms serve to legitimize te
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The research stems from the problem that focuses on a number of questions. They are as follows: What is the extent of interest in the topic of efficiency by the banks and their role in raising the efficiency of the banking business and its development? Is the banking efficiency used in Iraqi banks clear and specific for the Iraqi banking sector? How the banking sector efficiency is measured and what are the approaches adopted in determining the banking inputs and outputs? What is the level of efficiency in the research sample of the banks and what are the causes of its decline or rise in private banks individually and in the Iraqi banking sector in general?
The re
... Show MoreThis paper focuses on Load distribution factors for horizontally curved composite concrete-steel girder bridges. The finite-element analysis software“SAP2000” is used to examine the key parameters that can influence the distribution factors for horizontally curved composite steel
girders. A parametric study is conducted to study the load distribution characteristics of such bridge system due to dead loading and AASHTO truck loading using finite elements method. The key parameters considered in this study are: span-to-radius of curvature ratio, span length, number of girders, girders spacing, number of lanes, and truck loading conditions. The results have shown that the curvature is the most critical factor which plays an important
The aim of this research is to determine the most important and main factors that lead to Preeclampsia. It is also about finding suitable solutions to eradicate these factors and avoid them in order to prevent getting Preeclampsia. To achieve this, a case study sample of (40) patients from Medical City - Oncology Teaching Hospital was used to collect data by a questionnaire which contained (17) reasons to be investigated. The statistical package (SPSS) was used to compare the results of the data analysis through two methods (Radial Bases Function Network) and (Factorial Analysis). Important results were obtained, the two methods determined the same factors that could represent the direct reason which causes Preecla
... Show MoreMultivariate Non-Parametric control charts were used to monitoring the data that generated by using the simulation, whether they are within control limits or not. Since that non-parametric methods do not require any assumptions about the distribution of the data. This research aims to apply the multivariate non-parametric quality control methods, which are Multivariate Wilcoxon Signed-Rank ( ) , kernel principal component analysis (KPCA) and k-nearest neighbor ( −
The study explores the use of ergative verbs in constructing clauses and their impact on the backgrounding of the agent's role in two selected short stories. Contrary to hypothesis No. 1, the research indicates that changes in sentence patterns don't affect the meaning of the process. Additionally, hypothesis No. 2 is refuted as the middle structure is found to highlight the agent's role in the science fiction short story, Terra Infirmum, rather than concealing it as hypothesized for "The Invisible Man." The analysis uncovers that writers utilize ergative processes to narrate stories in various ways, including transitive/active voice, intransitive/active voice, and transitive/passive voice. Furthermore, the findings suggest that writers emp
... Show MoreThe research problem revolves around the failure of Maysan Oil Company to have a strategy that enables it to keep up with work in a mysterious and highly dynamic environment. Therefore, the research aims to present a proposed strategy that is comprehensive and realistic to the Maysan Oil Company for the next five years (2020-2024) based on the position and conditions of the company Current and future by adopting the scientific foundations for formulating the strategy, and the importance of research lies in the company's situational analysis to know its internal capabilities from strengths or weaknesses and diagnosing the surrounding elements of opportunities or threats so that this analysis represents a s
... Show MoreFace Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d
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