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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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Mon Sep 30 2024
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Thu Dec 26 2019
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Publication Date
Tue Jan 01 2019
Journal Name
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Wed Oct 17 2018
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Journal Of Economics And Administrative Sciences
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Sat Feb 21 2026
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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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Tue Jun 01 2021
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Sat Jan 01 2022
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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
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Al-khwarizmi Engineering Journal
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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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Thu Aug 01 2024
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