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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
Mon Feb 28 2022
Journal Name
Journal Of Educational And Psychological Researches
A Suggested Proposal to Activate Educational Supervision Based on Professional Learning Societies
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Professional learning societies (PLS) are a systematic method for improving teaching and learning performance through designing and building professional learning societies. This leads to overcoming a culture of isolation and fragmenting the work of educational supervisors. Many studies show that constructing and developing strong professional learning societies - focused on improving education, curriculum and evaluation will lead to increased cooperation and participation of educational supervisors and teachers, as well as increases the application of effective educational practices in the classroom.

The roles of the educational supervisor to ensure the best and optimal implementation and activation of professional learning soci

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Publication Date
Mon Feb 28 2022
Journal Name
Journal Of Educational And Psychological Researches
The Counseling Needs of Behavioral Problems among Students with Academic Learning Disabilities
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Learning Disabilities are described as a hidden and puzzling disability. Children with these difficulties have the potential to hide weaknesses in their performance because they are a homogenous group of disorders that consist of obvious difficulties in acquiring and using reading, writing, Mathematical inference. Thus, the research aims to identify the disabilities of academic learning in (reading, writing, mathematics), identify the problems of behavior (general, motor, social). Identify the relationship among behaviour problems. The research also aims to identify the counseling needs to reduce the behavioral problems. The researcher adopted the analytical descriptive method by preparing two main tools for measuring learning disabiliti

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Publication Date
Mon Apr 26 2021
Journal Name
Journal Of Electrical Engineering & Technology
ANFIS Based Reinforcement Learning Strategy for Control A Nonlinear Coupled Tanks System
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Publication Date
Wed May 17 2023
Journal Name
International Journal Of Computational Intelligence Systems
Prediction of ROP Zones Using Deep Learning Algorithms and Voting Classifier Technique
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Abstract<p>Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th</p> ... Show More
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Publication Date
Sun Jan 30 2022
Journal Name
Iraqi Journal Of Science
A Survey on Arabic Text Classification Using Deep and Machine Learning Algorithms
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    Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th

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Publication Date
Tue Mar 01 2016
Journal Name
International Journal Of Engineering Research And Advanced Technology (ijerat)
Speeding Up Back-Propagation Learning (SUBPL) Algorithm: A New Modified Back_Propagation Algorithm
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The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.

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Publication Date
Sun Apr 02 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Traffic Classification of IoT Devices by Utilizing Spike Neural Network Learning Approach
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Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Information And Optimization Sciences
Hybrid deep learning model for Arabic text classification based on mutual information
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Publication Date
Mon Oct 30 2023
Journal Name
Traitement Du Signal
A Comprehensive Review on Machine Learning Approaches for Enhancing Human Speech Recognition
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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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