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.
Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal. The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in
... Show MoreObjectives: The study aimed to assess the level of pediatric nurses' knowledge toward children with Guillain-Barre
syndrome (GBS) and to find out the relationships between nurses' knowledge and their demographic data.
Methodology: A purposive “non probability” sample of (30) nurses was selected from medical neurological wards and
Respiratory Care Units of Children Welfare Pediatric Teaching Hospital, Child’s Center Pediatric Teaching Hospital,
AL-Kadhemia Teaching Hospital, Baghdad Teaching Hospital, and Neurological Science Hospital which has started
from March 5
th 2009 to April 30th 2009. The study instrument consists of two parts. The first part is concerned with
nurses' demographical characteristic and the
The effect of superficial gas velocity within the range 0.01-0.164 m/s on gas holdup (overall, riser and down comer), volumetric oxygen mass transfer coefficient, liquid circulation velocity was studied in an internal loop concentric tubes airlift reactor (working volume 45 liters). It was shown that as the usg increases the gas holdup and also the liquid circulation velocity increase. Also it was found that increasing superficial gas velocity lead to increase the interfacial area that increases the overall oxygen mass transfer coefficient. The hydrodynamic experimental results were modeled with the available equations in the literature. The predicted data gave an acceptable accuracy with the empirical data.
The final
... Show MoreThe internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat
... Show MoreIn this work, pure and Ag-doped nickel oxide (NiO) thin films were deposited on glass substrates with different dopant concentrations (0.1, 0.2, 0.3 and 0.4 wt.%) by pulsed-laser deposition (PLD) technique at room temperature. These films were annealed at temperature of 450 °C. The structural and optical properties of the prepared thin films were studied. It was found that annealing process has lead to increase the transmittance of the deposited films. Also, the transmittance was found to increase with doping concentration of silver in the deposited NiO films. The optical energy gap was decreased from 3.5 to 3.2 eV as the doping concentration was increased to 0.4 %.
Fourier Transform-Infrared (FT-IR) spectroscopy was used to analyze gasoline engine oil (SAE 5W20) samples that were exposed to seven different oxidation times (0 h, 24 h, 48 h, 72 h, 96 h, 120 h, and 144 h) to determine the best wavenumbers and wavenumber ranges for the discrimination of the oxidation times. The thermal oxidation process generated oil samples with varying total base number (TBN) levels. Each wavenumber (400–3900 cm−1) and wavenumber ranges identified from the literature and this study were statistically analyzed to determine which wavenumbers and wavenumber ranges could discriminate among all oxidation times. Linear regression was used with the best wavenumbers and wavenumber ranges to predict oxidation time.
... Show MoreIn this research, design of advanced material for sunlight conversion requires focused research to obtain efficient photocatalytic system. Nanostructured ZnO was synthesized using spin coating technique. The structural, morphological and optical properties of annealed nanostructured ZnO thin film at 390 Co for 3 hours were characterized by x-ray diffraction, atomic force microscope AFM and UV-VIS spectrophotometer. Nanostructured ZnO was applied for removal Methylene Blue (MB) dye from water using sunlight induced photocatalytic process. Overall degradation of MB/ZnO was achieved after 120 minutes of sunlight irradiation while it needs more time for MB alone. The reaction rate constant fit pseudo first order for MB/ZnO degradation was 0.
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