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.
Nebivolol (NBH) is a third-generation B1-blocker with high selectivity and vasodilation activity. Nevertheless, nebivolol exhibits low oral bioavailability, which may adversely affect its efficacy. Recently, supersaturable self-nanoemulsion (Su-SNE) is an advanced SNE approach that can address low bioavailability The study aims to prepare nebivolol-loaded Su-SNE by reduction the amount of the prepared conventional SNE to half. Besides, an appropriate polymer type and concentration to prevent NBH precipitation upon oral administration have investigated.. A conventional self-nanoemulsion (formula A) was prepared by dissolving NBH in 500 mg vehicle mixture of imwitor®988: cremophor-EL: propylene glycol. Then, eight Su-SNE formul
... Show MoreNebivolol (NBH) is a third-generation B1-blocker with high selectivity and vasodilation activity. Nevertheless, nebivolol exhibits low oral bioavailability, which may adversely affect its efficacy. Recently, supersaturable self-nanoemulsion (Su-SNE) is an advanced SNE approach that can address low bioavailability The study aims to prepare nebivolol-loaded Su-SNE by reduction the amount of the prepared conventional SNE to half. Besides, an appropriate polymer type and concentration to prevent NBH precipitation upon oral administration have investigated.. A conventional self-nanoemulsion (formula A) was prepared by dissolving NBH in 500 mg vehicle mixture of imwitor®988: cremophor-EL: propylene glycol. Then, eight Su-SNE formulas wit
... Show MoreThe partial level density PLD of pre-equilibrium reactions that are described by Ericson’s formula has been studied using different formulae of single particle level density . The parameter was used from the equidistant spacing model (ESM) model and the non- equidistant spacing model (non-ESM) and another formula of are derived from the relation between and level density parameter . The formulae used to derive are the Roher formula, Egidy formula, Yukawa formula, and Thomas –Fermi formula. The partial level density results that depend on from the Thomas-Fermi formula show a good agreement with the experimental data.
The current study aims to compare between the assessments of the Rush model’s parameters to the missing and completed data in various ways of processing the missing data. To achieve the aim of the present study, the researcher followed the following steps: preparing Philip Carter test for the spatial capacity which consists of (20) items on a group of (250) sixth scientific stage students in the directorates of Baghdad Education at Al–Rusafa (1st, 2nd and 3rd) for the academic year (2018-2019). Then, the researcher relied on a single-parameter model to analyze the data. The researcher used Bilog-mg3 model to check the hypotheses, data and match them with the model. In addition
... Show MoreThis study aims to identify the impact of using the infrastructure of the Information Technology (IT) on the performance of human resources in the public universities. This process is done by doing research in the size, quality, and efficiency of the performance, also speed of achievement and simplification of procedures. Diyala University was chosen for the diagnosis through the opinions and attitudes of its employees. Consequently, suggestions that contribute to improve the performance of the employees and thus its overall performance are obtained. Another objective of this study is identifying the human resources which are currently used in academic institutions and educational services systems because the significant role of th
... Show MoreTraumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental
... Show MoreStudy of the development of an activated carbon nanotube catalyst for alkaline fuel cell technology. Through the prepared carbon nanotubes catalyst by an electrochemical deposition technique. Different analytical approaches such as X-ray diffraction (XRD) to determine the structural properties and Scanning Electron Microscope (SEM), were used to characterize, Mesh stainless steel catalyst substrate had an envelope structure and a large surface area. Voltages were also obtained at 1.83 V and current at 3.2 A of alkaline fuel cell. In addition, study the characterization of the electrochemical parameters.
There is an evidence that channel estimation in communication systems plays a crucial issue in recovering the transmitted data. In recent years, there has been an increasing interest to solve problems due to channel estimation and equalization especially when the channel impulse response is fast time varying Rician fading distribution that means channel impulse response change rapidly. Therefore, there must be an optimal channel estimation and equalization to recover transmitted data. However. this paper attempt to compare epsilon normalized least mean square (ε-NLMS) and recursive least squares (RLS) algorithms by computing their performance ability to track multiple fast time varying Rician fading channel with different values of Doppler
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