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Linguistic Errors in second language learning through Error Analysis theory: هه‌ڵه‌ زمانییه‌كان له‌ فێربوونی زمانی دووه‌مدا (له‌ ڕوانگه‌ی تیۆری شیكاری هه‌ڵه‌ییه‌وه‌)
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Second language learner may commit many mistakes in the process of second language learning. Throughout the Error Analysis Theory, the present study discusses the problems faced by second language learners whose Kurdish is their native language. At the very stages of language learning, second language learners will recognize the errors committed, yet they would not identify the type, the stage and error type shift in the process of language learning. Depending on their educational background of English as basic module, English department students at the university stage would make phonological, morphological, syntactic, semantic and lexical as well as speech errors. The main cause behind such errors goes back to the cultural differences of the language learners. Other errors go back either to the spoken form of the second language itself or to the teacher teaching the second language.       

لە فێربوونی زمانی دووەمدا  فێرخوازی زمانی دووەم دووچاری هەڵەی جۆراوجۆر دەبنەوە، بۆ ئەم مەبەستە (لە ڕوانگەی  تیۆری شكاری هەڵەییەوە) لە هەڵەكانی فێرخوازی زمانی دووەم( ئینگلیزی) دەدوێین، كە زمانی یەكەمیان زمانی كوردییە. فێرخوازان لە سەرەتای فێربوونی زمانی دووەمدا درك بە هەڵەی فێربوونی زمانەكەیان دەكەن، بەڵام  درك بە جۆر و قۆناغ و  گۆڕانی جۆری هەڵەكان ناكەن. لە پڕۆسەی فێربوونی زمانی دووەمدا  فێرخوازان لە قۆناغەكانی خوێندنی زانكۆدا بەتایبەتی لەبەشی زمانی ئینگلیزیدا بە پشتبەستن بە پاشخانی چەند ساڵی ڕابردوویان، كە زمانی ئینگلیزیان وەكو بابەتێكی سەرەكی خوێندووە، ئەوا شێوازی هەڵەی تریان تیدا بەدیدەكرێت، بەتایبەتی لە هەڵەی فۆنەتیكی و مۆرفۆلۆژی و سینتاكسی و واتا سازی و فەرهەنگی، هەروەها لە دركاندنیشدا هەڵەیان هەیە. سەرچاوەی ئەم هەڵەكردنانەش  بۆ كاریگەری زمانی یەكەم، بۆ هه‌ڵه‌ پێشكه‌وتووه‌كان، كه‌  له‌ خودی زمانی دووه‌م به‌رهه‌م دێت، ئه‌و هه‌ڵانه‌ی سه‌رچاوه‌كه‌ی بۆ سروشتی زمانی زاره‌كی، ئه‌و هه‌ڵانه‌ی له‌ فێركاره‌وه‌ ڕووده‌ده‌ن ده‌گه‌ڕێته‌وه.‌       

 

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
GENERATION AND TOOTH CONTACT ANALYSIS (TCA) OF HYPOID GEAR DRIVE
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The present work covers the Face-Hobbing method for generation and simulation of meshing of Face hobbed hypoid gear drive. In this work the generation process of hobbed hypoid gear has been achieved by determination of the generation function of blade cutter. The teeth surfaces have been drawn depending on the simulation of the cutting process and the head cutter motion. Tooth contact analysis (TCA) of such gear drive is presented to evaluate analytically the transmission error function for concave and convex tooth side due to misalignment errors. TCA results show that the gear is very sensitive to misalignment errors and
the increasing of the gear teeth number decrease the transmission error for both concave and convex tooth sides a

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Econometrics analysis of the impact of external shocks on foreign direct investment in Iraq for the period (1995-2016)
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The external shocks are one of the phenomena that the Iraqi economy is exposed to over a period of time. It is referred to as changes and events that come from outside the economic system and extends to many economic variables. However, foreign direct investment may be severely affected due to the extreme sensitivity to changes and local and international developments. This type of trauma and its characteristics to help manage and cope with external shocks, and in order to avoid the standard problems experienced by some models of simple linear regression, multi-linear regression models were used with variables Scientific and other dummy variables .

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Publication Date
Mon Feb 01 2021
Journal Name
Meta Gene
Association analysis of FTO gene polymorphisms rs9939609 and obesity risk among the adults: A systematic review and meta-analysis
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Publication Date
Tue Jun 01 2021
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Al-khwarizmi Engineering Journal
Effect of Environmental Factors on the Accuracy of a Quality Inspection System Based on Transfer Learning
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In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo

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Publication Date
Sun Sep 06 2020
Journal Name
European Journal Of Dental Education
Evaluation of technology‐based learning by dental students during the pandemic outbreak of coronavirus disease 2019
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Publication Date
Sat Nov 22 2025
Journal Name
Journal Mustansiriyah Of Sports Science
The influence of excellent offensive basketball skill-learning activities based on sensory perceptions for female pupils.
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The aim of this research is to develop qualitative workouts based on certain sensory perceptions for the development of offensive basketball abilities and to determine their impact on female pupils. Several findings, based on the au-thor's extensive expertise instructing basketball materials and our closeness to the sample, revealed deficits in some sensory perceptions “in the game of basketball”, which impair the accuracy of passing the ball to the best team-mate. It also affects the pace of dribbling and the difficulty of selecting the op-timal moment and distance to fire. Therefore, the researcher designs qualita-tive activities based on many sensory experiences, including distance, speed, force, and direction shift. In addition, the

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
A new smart approach of an efficient energy consumption management by using a machine-learning technique
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Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s

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Publication Date
Tue Jun 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Effect of Environmental Factors on the Accuracy of a Quality Inspection System Based on Transfer Learning
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In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s

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Publication Date
Thu Aug 01 2024
Journal Name
Advances In Science And Technology Research Journal
Power Predicting for Power Take-Off Shaft of a Disc Maize Silage Harvester Using Machine Learning
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Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for</p> ... Show More
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