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Shades of meanings of letters in Arabic (Some double and triple letters are an example)
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Meaning letters in Arabic are characterized by the diversity and abundance of their linguistic material, and are also distinguished by their large number and types, to the point that some of them have reached a hundred letters confined to five categories

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Publication Date
Mon Aug 16 2021
Journal Name
TÜrkÇe SÖzlÜkte Tdk Yer Alan ArapÇa Kelİmeler Üzerİne Bİr Anlam Bİlİmİ İncelemesİ
A SEMANTICS REVIEW ON THE ARABIC WORDS IN THE TURKISH DICTIONARY (TDK)
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Publication Date
Mon Sep 03 2018
Journal Name
Al-academy
The Use of Light Text in Arab TV Shows (The Voice TV Program) -A Model
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The research tackles an important subject, namely, the light text and how it works well in the Arab television programs. The methodological framework of the research     presents the research problem stated in the following question: How can the text be used and what is its impact in the Arab TV programs? The importance of this research is that it deals with the subject of light text and its impact on Arab television programs.

This study is useful to the workers and scholars in the field of lighting as well as the goal of the research in (studying of the employment of light text in Arab television programs).

The limits of research were manifested in the study of the light text and how to make use of it

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Publication Date
Tue Oct 27 2020
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
AUTOMATIC ARABIC KEYWORD EXTRACTION USING LOGISTIC REGRESSION
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Publication Date
Wed Jul 17 2019
Journal Name
Advances In Intelligent Systems And Computing
A New Arabic Dataset for Emotion Recognition
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In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N

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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Radioactivity and annual effective dose in some types of drug
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The aim of this research is to know danger of radioactive isotopes
that are found in samples of drugs traded in Iraqi markets. The
samples are Iraqi Amoxicillin, English Amoxicillin, UAE
Amoxicillin, Indian Amoxicillin, Iraqi Paracetamol, English
Paracetamol, UAE Paracetamol and Indian Paracetamol. By high
purity germanium the activity of the following isotopes 40K, 214Pb,
228Ac and 137Cs is measured and the specific activity was used to
calculate the annual effective dose. Then the calculated annual
effective dose values are compared with the allowable annual
effective dose values of each part of digestive channel. This research
concluded that the measured annual effective dose values are not
dangerous.<

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Publication Date
Mon Feb 01 2016
Journal Name
Asian Biomedicine
The prevalence of some gastrointestinal nematodes and cestodes in Iraqis
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Abstract Background Infections with helminths are associated with deficient sanitary facilities, unsafe human waste disposal, inadequate and lack of safe drinking water, and low socioeconomic status. Objective To determine the prevalence of some gastrointestinal helminths among Iraqi people, and association of infections with age, sex, and region in Iraq. Method This study is retrospective, including reported cases of infections using an available surveillance database from January 2013 to December 2013 of all provinces of Iraq by the Ministry of Health. Result The overall prevalence of gastrointestinal helminthiasis was 1.39%. Enterobius vermicularis found to be the predominant helminth parasite. No significant (P &lt; 0.05) rel

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
A Novel Gravity ‎Optimization Algorithm for Extractive Arabic Text Summarization
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An automatic text summarization system mimics how humans summarize by picking the most ‎significant sentences in a source text. However, the complexities of the Arabic language have become ‎challenging to obtain information quickly and effectively. The main disadvantage of the ‎traditional approaches is that they are strictly constrained (especially for the Arabic language) by the ‎accuracy of sentence feature ‎functions, weighting schemes, ‎and similarity calculations. On the other hand, the meta-heuristic search approaches have a feature tha

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
An Approximate solution for two points oundary value problem corresponding to some optimal control
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this paper presents a novel method for solving nonlinear optimal conrol problems of regular type via its equivalent two points boundary value problems using the non-classical

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Publication Date
Mon Apr 15 2024
Journal Name
Journal Of Engineering Science And Technology
Text Steganography Based on Arabic Characters Linguistic Features and Word Shifting Method
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In the field of data security, the critical challenge of preserving sensitive information during its transmission through public channels takes centre stage. Steganography, a method employed to conceal data within various carrier objects such as text, can be proposed to address these security challenges. Text, owing to its extensive usage and constrained bandwidth, stands out as an optimal medium for this purpose. Despite the richness of the Arabic language in its linguistic features, only a small number of studies have explored Arabic text steganography. Arabic text, characterized by its distinctive script and linguistic features, has gained notable attention as a promising domain for steganographic ventures. Arabic text steganography harn

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Arabic Speech Classification Method Based on Padding and Deep Learning Neural Network
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Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

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