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.
We can summarize the main risk factors for type 2 diabetes mellitus (T2DM) by looking at our nutrition, age, and lifestyle. β-cell dysfunction and insulin resistance (IR) are outcomes of the pathophysiology of type 2 diabetes. As an indirect result of IR on important metabolic enzymes, lipid and lipoprotein abnormalities are also a factor in T2DM patients. Recent research has indicated that lipid fluctuation may be the cause of poor glucose metabolism as well as one of its effects. Fatty acids (FAs) affect cell membrane fluidity and permeability, insulin receptor binding and signaling, and the translocation of glucose transporters. Therefore, it is suggested that FAs might play a crucial part in the emergence of IR and T2DM. The cu
... Show MoreThe problem of the damage caused by terrorist acts has raised many difficulties in many countries, including Iraq, which requires the existence of a law that sets out sufficient rules for compensating the victims of terrorist acts, in order to compensate them for the harm they have not suffered. It may be difficult or impossible for them to identify causing damage, and therefore unable to obtain compensation by applying the traditional rules of liability that require proof of fault and identify the culprit. The security funds come as an appropriate alternative that pays compensation in such cases for victims to reparation for the damage they suffered. Therefore, this problem remains one of the most problems that Iraq suffers from it, which
... Show MoreAn experiment was carried out evaluate the performance of RAU combined equipment under three levels of practical speed, (V1) 4.06 km. h-1, (V2) 4.43 km. hr-1 and (V3) 5.76 km. hr-1, and three levels of depth with 10,20and 30 cm. It is denoted by D1, D2, D3 respectively. A split plot design was used within the RCBD design with three replications. The experiment results showed that the first practical speed 4.06 km.hr-1 achieved the lowest slippage percentage from 9.61%, lowest traction power 14.65hp, lowest soil penetration resistance to1.34 kg.cm-2, and the highest total operating
Air pollution is one of the complex problems plaguing the environment at the present time
as a result of many liberation of gases, vapors and fumes of fuels and chemicals resulting
from industrial activities . It should be noted that there are some elements of the heavy
(Heavy Metals), including toxic in the air, with different concentrations in the air depending
on the nature of the area, for example be in rural areas is lower than in cities or industrial
areas as measured parts million (ppm ) or parts per billion (ppb). Some of these important
elements in the physiological processes and enzymatic organisms but become toxic and
Qatlhand-increase Tercisahaan the permissible limits Bhave nature ,The air contaminant
The study explored applications of artificial intelligence and its dialectical relationship with international human rights law of individuals, which requires assessing the effects of this technology on human rights and freedoms. The problem of privacy of humanity, as AI technologies can control human rights and freedoms, while monitoring potential violations in this context. The study use of documentary research and qualitative lens to analyze the data. In conclusion, unawareness of the use of AI may impose significant hurdles on future generations and may infringe on human rights across all sectors of society. The government should mandate obligations for artificial intelligence businesses concerning education, health, human right
... Show MoreHuman interferon as is the case in all kinds of interferon has complex effects but all share their impact on preventing the proliferation of viruses and preventing or reducing human Alantervjørn conversion occurs if the cell is in preventing the growth of the virus when interferon Balnmstqubl connects
Air pollution is one of the complex problems plaguing the environment at the present time
as a result of many liberation of gases, vapors and fumes of fuels and chemicals resulting
from industrial activities . It should be noted that there are some elements of the heavy (Heavy
Metals), including toxic in the air, with different concentrations in the air depending on the
nature of the area, for example be in rural areas is lower than in cities or industrial areas as
measured parts million (ppm ) or parts per billion (ppb). Some of these important elements in
the physiological processes and enzymatic organisms but become toxic and Qatlhand-increase
Tercisahaan the permissible limits Bhave nature ,The air contaminant co
In this study, we review the ARIMA (p, d, q), the EWMA and the DLM (dynamic linear moodelling) procedures in brief in order to accomdate the ac(autocorrelation) structure of data .We consider the recursive estimation and prediction algorithms based on Bayes and KF (Kalman filtering) techniques for correlated observations.We investigate the effect on the MSE of these procedures and compare them using generated data.