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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
Sat Jan 01 2005
Journal Name
Iraqi Journal Of Science
Comparison between Zernike moment and central moments for matching problem
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Moment invariants have wide applications in image recognition since they were proposed.

Publication Date
Sat Jul 03 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Comparison between VG-levy and Kernel function estimation with application
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Publication Date
Fri May 01 2015
Journal Name
Journal Of Hazardous Materials
The removal of caesium ions using supported clinoptilolite
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Publication Date
Tue Dec 07 2021
Journal Name
2021 14th International Conference On Developments In Esystems Engineering (dese)
Object Detection and Distance Measurement Using AI
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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of Engineering
Efficient Intrusion Detection Through the Fusion of AI Algorithms and Feature Selection Methods
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With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

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Publication Date
Fri Aug 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Comparison between the Local Polynomial Kernel and Penalized Spline to Estimating Varying Coefficient Model
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Analysis the economic and financial phenomena and other requires to build the appropriate model, which represents the causal relations between factors. The operation building of the model depends on Imaging conditions and factors surrounding an in mathematical formula and the Researchers target to build that formula appropriately. Classical linear regression models are an important statistical tool, but used in a limited way, where is assumed that the relationship between the variables illustrations and response variables identifiable. To expand the representation of relationships between variables that represent the phenomenon under discussion we used Varying Coefficient Models

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Publication Date
Thu Oct 15 2015
Journal Name
Al Mustansyriah Journal Of Science
Comparison between (ARIMA) and (ANNs) models for estimating the relative humidity for Baghdad city
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The aim of the research is to study the comparison between (ARIMA) Auto Regressive Integrated Moving Average and(ANNs) Artificial Neural Networks models and to select the best one for prediction the monthly relative humidity values depending upon the standard errors between estimated and observe values . It has been noted that both can be used for estimation and the best on among is (ANNs) as the values (MAE,RMSE, R2) is )0.036816,0.0466,0.91) respectively for the best formula for model (ARIMA) (6,0,2)(6,0,1) whereas the values of estimates relative to model (ANNs) for the best formula (5,5,1) is (0.0109, 0.0139 ,0.991) respectively. so that model (ANNs) is superior than (ARIMA) in a such evaluation.

Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
Comparison of Groundwater Quality and Quantity between Al-Rahbah and Al-Haydariyah Regions
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This study focused on two areas in AL-Najaf city, AL-Ruhbah and Al-Haydariyah regions because of the importance and widespread use of groundwater in these areas. The two areas were compared quantitatively and qualitatively. For the quantitative approach, the GMS software was used in conjunction with the GIS software to simulate the groundwater flow behavior. The solid model for both areas was created, the geological formation was determined, and the hydraulic properties were identified using GMS software. To test the quantity of groundwater in both areas, the wells have been redistributed to a distance of 2000 m between them, and a period of 1000 days was chosen. When a discharge of 10 l/s and operation times of 4, 8, an

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Publication Date
Wed Jun 30 2021
Journal Name
Modern Sport
Motor capacity and its relationship with some indicators Albaiukinmetekih and performance of the wheel of human skill
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The research problem is represented in the weakness of reliance on the role of some motor abilities (flexibility, balance and compatibility) in biomechanical indicators and the performance of a large number of gymnastics skills, including the skill of the human wheel, in addition to the lack of reliance on the use of video imaging of the skill in order to analyze its path and identify its weaknesses. The research aimed to identify the relationship between motor abilities, biomechanical indicators and the degree of performance of the skill of the human wheel, and the descriptive method was used on its own, chosen in an intentional method, consisting of (10) students from the third stage in the Department of Physical Education and Sp

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Publication Date
Fri Jan 01 2016
Journal Name
Al-qadisiyah Medical Journal
Comparison between dome and wedge osteotomy in management of hallux valgus deformity
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Background: the condition of hallux valgus is considered as the most common deformities affecting females more than males, characteristically manifested as lateral deviation of the big toe and widening of first and second inter -metatarsal angle with a deformity of second toe in some severe cases. Objective: to make a radiological and clinical assessment of two surgical methods of osteotomy used in treatment of hallux valgu and to compare between them: first one is the distal dome osteotomy, and second one is a distal wedge metatarsal osteotomy. Patients and methods: a total of 36 feet of 28 patients suffer from hallux valgus, with mean age of 50.3 years were included in this study, followed for 6- 30 months ( mean follow-up of 8.8 months).

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