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Comparison Between the Performance of Human Translators and AI-Supported Applications
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This study aims to conduct an exhaustive comparison between the performance of human translators and artificial intelligence-powered machine translation systems, specifically examining the top three systems: Spider-AI, Metacate, and DeepL. A variety of texts from distinct categories were evaluated to gain a profound understanding of the qualitative differences, as well as the strengths and weaknesses, between human and machine translations. The results demonstrated that human translation significantly outperforms machine translation, with larger gaps in literary texts and texts characterized by high linguistic complexity. However, the performance of machine translation systems, particularly DeepL, has improved and in some contexts approached that of human performance. The distinct performance differences across various text categories suggest the potential for developing systems tailored to specific fields. These findings indicate that machine translation has the capacity to bridge the gap in translation productivity inefficiencies inherent in human translation, yet it still falls short of fully replicating human capabilities. In the future, a combination of human translation and machine translation systems is likely to be the most effective approach for leveraging the strengths of each and ensuring optimal performance. This study contributes empirical support and findings that can aid in the development and future research in the field of machine translation and translation studies. Despite some limitations associated with the corpus used and the systems analysed, where the focus was on English and texts within the field of machine translation, future studies could explore more extensive linguistic sampling and evaluation of human effort. The collaborative efforts of specialists in artificial intelligence, translation studies, linguistics, and related fields can help achieve a world where linguistic diversity no longer poses a barrier.

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Publication Date
Fri Nov 09 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Effectiveness of Continuing Nursing Education Program on Nursing Staffs, Knowledge at Kidney Transplantation Units in Baghdad Teaching Hospitals
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Objective: The study aims to determine the effectiveness of the continuing nursing education
program on nursing staffs knowledge in kidney transplantation unit and to find out the relationship
between nursing staffs knowledge and demographic characteristics (age, gender, education level, and
years of experiences in kidney transplantation unit).
Methodology: A quasiexperemental design (One-group Pretest - Posttest design) was carried out in
kidney transplantation units at Baghdad Teaching Hospitals, from December 2011 to July 2012. A nonprobability
(purposive sample) of (16) nurses were selected from kidney transplant units at Baghdad
teaching hospitals, the choice was based on the study criteria. The data were collec

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Publication Date
Fri Dec 20 2013
Journal Name
Journal Of The College Of Basic Education
Determination of Some heavy metals in Different vinegar Samples Applied in folk medicine by flame atomic absorption Spectrophotometry
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A study was carried out to analysis of some heavy metals in nine different types of vinegar, belong to Grape, Apple, Synthetic White, Date, Hawthorn, Garlic, Cactus, Pomegranate and Ginger vinegar, which are locally available in Iraqi folk medicine markets. The concentrations of heavy metals in the studied samples including, Cr, Mg, Mn, Zn, Fe, Cd, Ni, Pb and Ag, were determining by using flame atomic absorption spectrophotometry. All data were subjected to statistical analysis by calculating accuracy, precision and correlation coefficient for each concentrations level. The results indicate that Ni was recorded the highest concentration in all studied samples except, Ginger and cactus vinegar, each one receded the highest concentration valu

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Publication Date
Wed Jan 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Analyzing big data sets by using different panelized regression methods with application: Surveys of multidimensional poverty in Iraq
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Poverty phenomenon is very substantial topic that determines the future of societies and governments and the way that they deals with education, health and economy. Sometimes poverty takes multidimensional trends through education and health. The research aims at studying multidimensional poverty in Iraq by using panelized regression methods, to analyze Big Data sets from demographical surveys collected by the Central Statistical Organization in Iraq. We choose classical penalized regression method represented by The Ridge Regression, Moreover; we choose another penalized method which is the Smooth Integration of Counting and Absolute Deviation (SICA) to analyze Big Data sets related to the different poverty forms in Iraq. Euclidian Distanc

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Publication Date
Thu Dec 24 2020
Journal Name
Advances In Civil Engineering
Analytical study on torsional behavior of concrete beams strengthened with fiber reinforced polymer laminates using softened truss model
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This study aimed at evaluating the torsional capacity of reinforced concrete (RC) beams externally wrapped with fiber reinforced polymer (FRP) materials. An analytical model was described and used as a new computational procedure based on the softened truss model (STM) to predict the torsional behavior of RC beams strengthened with FRP. The proposed analytical model was validated with the existing experimental data for rectangular sections strengthened with FRP materials and considering torque-twist relationship and crack pattern at failure. The confined concrete behavior, in the case of FRP wrapping, was considered in the constitutive laws of concrete in the model. Then, an efficient algorithm was developed in MATLAB environment t

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Publication Date
Tue Nov 09 2021
Journal Name
Energies
Natural Convection Effect on Solidification Enhancement in a Multi-Tube Latent Heat Storage System: Effect of Tubes’ Arrangement
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The solidification process in a multi-tube latent heat energy system is affected by the natural convection and the arrangement of heat exchanger tubes, which changes the buoyancy effect as well. In the current work, the effect of the arrangement of the tubes in a multi-tube heat exchanger was examined during the solidification process with the focus on the natural convection effects inside the phase change material (PCM). The behavior of the system was numerically analyzed using liquid fraction and energy released, as well as temperature, velocity and streamline profiles for different studied cases. The arrangement of the tubes, considering seven pipes in the symmetrical condition, are assumed at different positions in the system, i

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Design of a Kinematic Neural Controller for Mobile Robots based on Enhanced Hybrid Firefly-Artificial Bee Colony Algorithm
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The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme

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Publication Date
Tue Jan 01 2019
Journal Name
Chemical Industry And Chemical Engineering Quarterly
Optimization of dye adsorption process for Albizia lebbeck pods as a biomass using central composite rotatable design model
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Albizia lebbeck biomass was used as an adsorbent material in the present study to remove methyl red dye from an aqueous solution. A central composite rotatable design model was used to predict the dye removal efficiency. The optimization was accomplished under a temperature and mixing control system (37?C) with different particle size of 300 and 600 ?m. Highest adsorption efficiencies were obtained at lower dye concentrations and lower weight of adsorbent. The adsorption time, more than 48 h, was found to have a negative effect on the removal efficiency due to secondary metabolites compounds. However, the adsorption time was found to have a positive effect at high dye concentrations and high adsorbent weight. The colour removal effi

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Publication Date
Wed Aug 30 2023
Journal Name
Al-kindy College Medical Journal
Assessment of Thyroid Functions in Multiple Sclerosis Patients Treated with Disease Modifying Therapies: Thyroid Functions in Multiple Sclerosis
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Background:

Multiple sclerosis is a chronic disease believed to be the result of autoimmune disorders of the central nervous system, characterised by inflammation, demyelination, and axonal transection, affecting primarily young adults. Disease modifying therapies have become widely used, and the rapid development of these drugs highlighted the need to update our knowledge on their short- and long-term safety profile.

Objective:

The study aim is to evaluate the impact of disease-modifying treatments on thyroid functions and thyroid autoantibodies with subsequent effects on the outcome of the disease.

Materials and Methods:

A retro prospective study

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Publication Date
Fri Apr 07 2017
Journal Name
Oncology Letters
AURKA mRNA expression is an independent predictor of poor prognosis in patients with non-small cell lung cancer
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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Study of (Zn0.7 Mn0.3-x Ag0.3 Fe2O4) ferrite nanoparticles synthesized by auto combustion method for NO2 gas sensing
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