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jperc-1377
Vocabulary Learning Strategies Employed by English as Foreign Language Students at NBU University
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ABSTRACT

Learning vocabulary is a challenging task for female English as a foreign language (EFL) students. Thus, improving students’ knowledge of vocabulary is critical if they are to make progress in learning a new language. The current study aimed at exploring the vocabulary learning strategies used by EFL students at Northern Border University (NBU). It also aimed to identify the mechanisms applied by EFL students at NBU University to learn vocabulary. It also aimed at evaluating the approaches adopted by EFL female students at Northern Border University (NBU) to learn a language. The study adopted the descriptive-analytical method. Two research instruments were developed to collect data namely, a survey questionnaire on vocabulary learning strategies was used to collect data from the students on the strategies that they used to learn vocabulary. Also, the researcher used a semi-structured interview to assess and collect qualitative data about the effectiveness of the vocabulary learning strategies used by EFL students at NBU University. Results of this study revealed that the students preferred the cognitively demanding techniques over the techniques currently in use, along with the memory strategies. The study also showed that social strategies are rarely implemented in teaching vocabulary these days.

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Publication Date
Sun Jan 01 2023
Journal Name
Corporate And Business Strategy Review
The role of learning organizations in crisis management strategy: A case study
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The problem of the paper focused on the role of the learning organization in the crisis management strategy, and the extent of the actual interest in both the learning organization and the crisis management and aimed at diagnosing and analyzing that and surrounding questions. The Statistical Package for the Social Sciences (SPSS) program was used to calculate the results and the correlation coefficient between the two main variables. The methodology was descriptive and analytical. The case study was followed by a questionnaire that was distributed to a sample of 31 teachers. The paper adopted a seven-dimensional model of systemic thinking that encourages questioning, empowerment, provision of advanced technologies, and strategic lea

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Publication Date
Fri Feb 04 2022
Journal Name
Neuroquantology
Detecting Damaged Buildings on Post-Hurricane Satellite Imagery based on Transfer Learning
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In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

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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
Mon Aug 01 2022
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
A survey of deepfakes in terms of deep learning and multimedia forensics
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Artificial intelligence techniques are reaching us in several forms, some of which are useful but can be exploited in a way that harms us. One of these forms is called deepfakes. Deepfakes is used to completely modify video (or image) content to display something that was not in it originally. The danger of deepfake technology impact on society through the loss of confidence in everything is published. Therefore, in this paper, we focus on deepfakedetection technology from the view of two concepts which are deep learning and forensic tools. The purpose of this survey is to give the reader a deeper overview of i) the environment of deepfake creation and detection, ii) how deep learning and forensic tools contributed to the detection

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Publication Date
Tue Jul 01 2025
Journal Name
Mastering The Minds Of Machines
Unsupervised Learning: Discovering Patterns without Labels: Health Care, E-Commerce, and Cybersecurity
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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
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Sun Sep 15 2019
Journal Name
Route Education And Social Science Journal
The influence of textual and visual reading on EFL Iraqi students' comprehension
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Reading roles as the third skill in the range of English as a Foreign Language (EFL) learning. Although the capability of reading in both academic and non-academic texts is assessed on standardized tests, few of oral interpretation of written language excludes images from estimating literary knowledge. This paper highlights strategies of reading comprehension and visual literacy. It aims to investigate either textual or visual reading in EFL can make an impact on students' comprehension. The effective use of visuals changes instructing reading comprehension recently.The imagery-text model can affect developing reading comprehension and enhancing intellectual thinking. The study hypothesizes that there is no relationship between reading and

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Publication Date
Mon Mar 15 2021
Journal Name
Iraqi National Journal Of Nursing Specialties
Evaluation of Staff Nurses’ performance at Primary Health Care Centers in Baghdad City
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Objectives: This study aimed to evaluate the performance of staff nurses at primary health care centers in Baghdad city and to compare them with their demographic characteristics of age, gender and education.
Methodology: A descriptive design was carried out at Baghdad City’s primary health care centers from January 2nd 2019 to May 1st 2020. An instrument was developed for the purpose of the study. A non-probability, multi-stage purposive sample of (52) staff nurses was recruited from nurses working at primary health care centers in Baghdad City. The instrument is used to evaluate staff nurses’ performance which includes (62) items. These items are divided to (13) main domains related to evaluation of work quantity, work quality,

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Publication Date
Sun Jun 30 2024
Journal Name
مجلة الفارابي للعلوم النسانية
اثر استراتيجية نجمتين وامنية في تحصيل مادة الكيمياء عند طلاب الصف الثاني المتوسط م . د . انور عباس محمد
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يهدف البحث الى التعرف على اثر استراتيجية نجمتين وامنية في تحصيل مادة الكيمياء عند طلاب الصف الثاني المتوسطولتحقيق هدف البحث تم اتباع المنهج التجريبي ذو الضبط الجزئي وتم تحديد مجتمع البحث بطلاب الصف الثاني المتوسط لجميع المدارس الثانموية والمتوسط التابعة لمديرية تربية الكرخ الثانية وتم اخنيار احد هذه المداس بصورة قصدية لتطبيق تجربة ابلبحث الحالي

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