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Arabic Sentiment Analysis (ASA) Using Deep Learning Approach
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Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other languages like English. The proposed model tackles Arabic Sentiment Analysis (ASA) by using a DL approach. ASA is a challenging field where Arabic language has a rich morphological structure more than other languages. In this work, Long Short-Term Memory (LSTM) as a deep neural network has been used for training the model combined with word embedding as a first hidden layer for features extracting. The results show an accuracy of about 82% is achievable using DL method.

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Publication Date
Sun Apr 01 2012
Journal Name
Journal Of Educational And Psychological Researches
Effectiveness of at site electronic learning/teaching in educational development
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 This study investigated three aims for the extent of effectiveness of the two systems in educational development of educators. To achieve this, statistical analysis was performed between the two groups that consisted of (26) participants of the electronic teaching method and (38) participants who underwent teaching by the conventional electronic lecture. The results indicated the effectiveness of the “electronic teaching method” and the “electronic lecture method” for learning of the participants in educational development. Also, it indicated the level of equivalence from the aspect of effectiveness of the two methods and at a confidence level of (0.05). This study reached several conclusions, recommendations, and suggestio

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Publication Date
Fri Jan 07 2022
Journal Name
International Journal Of Early Childhood Special Education
Hierarchical learning and its effect on learning some basic skills in fencing for third stage students.
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MH Hamzah, AF Abbas, International Journal of Early Childhood Special Education, 2022

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
Optimizing genetic prediction: Define-by-run DL approach in DNA sequencing
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Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Exploring Important Factors in Predicting Heart Disease Based on Ensemble- Extra Feature Selection Approach
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Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of The College Of Languages (jcl)
The Characteristics of Advertising in Blurbs of Arabic and English novels
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The paper is concerned with a linguistic analysis of  the blurbs, used in advertising English and Arabic novels.  A blurb is an advertising persuasive text, written on the back cover of a book. Blurbs of selected novels are chosen as  representative examples. The selected blurbs belong to two languages, Arabic and English. The paper aims at studying the linguistic features that are characteristic of blurbs as advertising texts and making a sort of comparison between English blurbs and Arabic ones. A linguistic analysis on four levels is presented. Blurbs are tackled from the point of view of four linguistic disciplines that are phonology, syntax, semantics and discourse analysis. A reference is made to the linguistic featu

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Publication Date
Mon Feb 14 2022
Journal Name
Journal Of Educational And Psychological Researches
Trends of Arabic Language Teachers in the Secondary Stage towards Homework
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The problem of the research is indicated by answering the following questions: 1) what are the attitudes of the Arabic language teachers towards homework?

2) Do the Arabic language teachers differ in their attitudes towards homework according to their specialization? 3) Do the Arabic language teachers differ in their attitudes towards homework according to their gender (male and female)? According to the three questions asked above, we may state the following hypotheses. There is no statistically significant difference between the average of the marks of Arabic language teachers in the real practice of the scale of the attitudes towards their homework and their average in the hypothetical practice of the

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Publication Date
Tue Aug 31 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
FDPHI: Fast Deep Packet Header Inspection for Data Traffic Classification and Management
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Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Sun Oct 08 2023
Journal Name
الدراسات اللغوية والترجمية/translation Studies In Bait Al-hikma
Translating adjectives into Arabic in Chekhov’s story -ward No.6
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Chekhov is well known and perceived in Arab countries. His stories and plays are very popular. They translated it into Arabic by different translators from different languages of the world Many of his stories require new translation solutions to achieve partial, if not complete, equivalence. Chekhov's works are a very difficult subject to analyze and interpret, which is explained by the fact that Chekhov's collections are constantly republished in foreign languages. It is impossible to preserve in translation all the elements of the original text containing historical and national details but, of course, the reader should have the impression that they represent the historical and national situation. When translating, it makes sense to prese

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Publication Date
Wed Oct 11 2023
Journal Name
Journal Of Educational And Psychological Researches
The Relationship between Formal Thinking & Learning Styles for Kindergarten Department Students
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The current research aims to reveal the strength of education and the direction of the relationship between the formal thinking and learning methods of Kindergarten department students. To achieve this objective, the researcher developed a scale of formal thinking according to the theory of (Inhelder & Piaget 1958) consisting of (25) items in the form of declarative phrases derived from the analysis of formal thinking skills based on a professional situation that students are expected to interact with in a professional way. The research sample consisted of (100) female students selected randomly who were divided into four groups based on the academic stages, the results revealed that The level of formal thinking of the main sample is

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