تبنت العديد من المؤسسات الأكاديمية التعلم الإلكتروني منذ سنوات ، وقد أثبت فاعليته في كثير من هذه المؤسسات لاسيما تلك المهتمة بتعلم اللغات الاجنبية. الا انه مع انتشار جائحة كورونا اصبح التعليم الالكتروني ضرورة ملحة في الجامعات في جميع أنحاء العالم ، بما في ذلك الجامعات العراقية. تهدف الدراسة الحالية إلى تقصي أثر هذا الوباء على التعلم الإلكتروني في أحدى الكليات العراقية . يفترض الباحث أن تقبل الطلبة للتعلم الإلكتروني ، وكذلك أداءهم ، قد تحسن خلال هذه الأزمة . ولقياس فاعلية التعلم الإلكتروني أثناء الجائحة ، صممت الباحثة استبيانا وعرضته على 130 طالبة في قسم اللغة الإنجليزية في كلية التربية للبنات / جامعة بغداد . اضافة الى ذلك، تم إجراء مقابلة عبر الإنترنت مع نفس الطلاب لمناقشة موافقتهم أو عدم موافقتهم على أسئلة الاستبيان. أظهرت النتائج ما يلي: أولاً ، يمكن أن يكون التعلم الإلكتروني مفيدًا جدًا إذا تم استخدامه مع التعليم التقليدي. ثانيًا ،نظرة الطالبات للتعلم الالكتروني وكذلك ادائهن تغير تمامًا عندما أصبح التعلم الإلكتروني هو الحل الوحيد للتعلم خلال هذه الأزمة.
Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
... Show MoreThis study intends to examine the efficiency of student-centered learning (SCL) through Google classroom in enhancing the readiness of fourth stage females’ pre-service teachers. The research employs a quasi-experimental design with a control and experimental group to compare the teaching readiness of participants before and after the intervention. The participants were 30 of fourth stage students at the University of Baghdad - College of Education for Women/the department of English and data were collected through observation checklist to assess their teaching experience and questionnaires to assess their perceptions towards using Google Classroom. Two sections were selected, C as a control group and D as the experimental one each with (
... Show MoreThe majority of Arab EFL (English as a Foreign Language) learners struggle with speaking English fluency. Iraqi students struggle to speak English confidently due to mispronunciation, grammatical errors, short and long pauses while speaking or feeling confused in normal conversations. Collaborative learning is crucial to enhance student’s speaking skills in the long run. This study aims to state the importance of collaborative learning as a teaching method to EFL learners in the meantime. In this quantitative and qualitative study, specific focus is taken on some of Barros’s views of collaborative learning as a teamwork and some of Pattanpichet’s speaking achievements under four categories: academic benefits, social benefits,
... Show MoreAdverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD
... Show MoreThis research studies the comparison of deep neural network models and performance evaluation to predict the gold prices of time series, where the gold prices contain high fluctuations and non-linear patterns that are difficult to capture using traditional models, which makes predicting them a significant challenge. Therefore, the focus was on using deep learning models represented by (LSTM), (Bi-LSTM), (GRU) and (Bi-GRU). The results showed the superiority of the (Bi-GRU) model according to comparison criteria (MSE), (RMSE), (MAE), and (R∧2) compared to other models because it was able to understand the time patterns better by processing the data in both directions and provided superior performance, which indicates its effectiveness, eff
... Show MoreA new human-based heuristic optimization method, named the Snooker-Based Optimization Algorithm (SBOA), is introduced in this study. The inspiration for this method is drawn from the traits of sales elites—those qualities every salesperson aspires to possess. Typically, salespersons strive to enhance their skills through autonomous learning or by seeking guidance from others. Furthermore, they engage in regular communication with customers to gain approval for their products or services. Building upon this concept, SBOA aims to find the optimal solution within a given search space, traversing all positions to obtain all possible values. To assesses the feasibility and effectiveness of SBOA in comparison to other algorithms, we conducte
... Show MoreComputer-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
... Show MoreThis study aims to analyze the flow migration of individuals between Iraqi governorates using real anonymized data from Korek Telecom company in Iraq. The purpose of this analysis is to understand the connection structure and the attractiveness of these governorates through examining the flow migration and population densities. Hence, they are classified based on the human migration at a particular period. The mobile phone data of type Call Detailed Records (CDRs) have been observed, which fall in a 6-month period during COVID-19 in the year 2020-2021. So, according to the CDRs nature, the well-known spatiotemporal algorithms: the radiation model and the gravity model were applied to analyze these data, and they are turned out to be comp
... Show MoreThe Egyptian and Iraqi schools are one of the most important musical schools in the style of playing the oud. The influence of the style of these schools extended in the contemporary Arab world, and there were important names that emerged characterized with their style of playing. Thus, the ways of tuning the strings of oud varied between the two schools because of the difference in the ways of playing and the difference in the style of expression. The aim of the research was to identify the pluralism of the variable tunings of the strings of the contemporary Arab oud of the Egyptian and Iraqi schools, along the historical period extending from the late nineteenth and twentieth centuries to the present time. The oud has been classified i
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