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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 they got. Deep Learning (DL) and Machine Learning (ML) models were used to enhance text classification for Arabic language. Remarks for future work were concluded.

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Combining Several Substitution Cipher Algorithms using Circular Queue Data Structure
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With the revolutionized expansion of the Internet, worldwide information increases the application of communication technology, and the rapid growth of significant data volume boosts the requirement to accomplish secure, robust, and confident techniques using various effective algorithms. Lots of algorithms and techniques are available for data security.  This paper presents a cryptosystem that combines several Substitution Cipher Algorithms along with the Circular queue data structure. The two different substitution techniques are; Homophonic Substitution Cipher and Polyalphabetic Substitution Cipher in which they merged in a single circular queue with four different keys for each of them, which produces eight different outputs for

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Publication Date
Tue Mar 01 2011
Journal Name
Al-khwarizmi Engineering Journal
Noise Removal of ECG Signal Using Recursive Least Square Algorithms
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This paper shows an approach for Electromyography (ECG) signal processing based on linear and nonlinear adaptive filtering using Recursive Least Square (RLS) algorithm to remove two kinds of noise that affected the ECG signal. These are the High Frequency Noise (HFN) and Low Frequency Noise (LFN). Simulation is performed in Matlab. The ECG, HFN and LFN signals used in this study were downloaded from ftp://ftp.ieee.org/uploads/press/rangayyan/, and then the filtering process was obtained by using adaptive finite impulse response (FIR) that illustrated better results than infinite impulse response (IIR) filters did.

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Publication Date
Sun Dec 06 2009
Journal Name
Baghdad Science Journal
Automatic Block Selection for Synthesizing Texture Images using Genetic Algorithms
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Texture synthesis using genetic algorithms is one way; proposed in the previous research, to synthesis texture in a fast and easy way. In genetic texture synthesis algorithms ,the chromosome consist of random blocks selected manually by the user .However ,this method of selection is highly dependent on the experience of user .Hence, wrong selection of blocks will greatly affect the synthesized texture result. In this paper a new method is suggested for selecting the blocks automatically without the participation of user .The results show that this method of selection eliminates some blending caused from the previous manual method of selection.

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Publication Date
Wed Apr 28 2021
Journal Name
Misan Journal For Physical Education Sciences
The Effectiveness of Using Generative Learning Model in Learning Kinetic Series on Rings and Horizontal Bar In Artistic Gymnastics for men
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The aim of this study was to identify the effectiveness of using generative learning model in learning kinetic series on rings and horizontal bar in artistic gymnastics for men ,Also, the two groups were better in learning the two series of movements on the rings and horizontal bar . The experimental method was used to design two parallel groups with pretested and posttest .The sample included third graders at the College of Physical Education and Sports Sciences - University of Baghdad ,The third class (d) was chosen to represent the control group that applied the curriculum in the college, with (12) students per group. After conducting the tribal tests, the main experiment was carried out for (8) weeks at the rate of two units per week di

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Publication Date
Sun Jan 02 2022
Journal Name
Journal Of The College Of Languages (jcl)
Semantic relations in text and translation: Die semantischen Relationen im Text und Übersetzung
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       Based on the German language department’s theoretical and practical aspects as well as educational programs, the present study discusses the semantic relations in text sentences and their role in the science of translation.  Through clarifying the semantic relationship between the text sentence and the methods used to express a news item, a situation or an occurrence and through the statement of the multiple theoretical semantic structures of the text’s construction and interrelation, a translator can easily translate a text into the target language.

        It is known that language learners face multiple difficulties in writing and creating an inte

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Publication Date
Wed Jul 31 2019
Journal Name
Journal Of Engineering
A Comparative Study of Various Intelligent Optimization Algorithms Based on Path Planning and Neural Controller for Mobile Robot
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In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

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Publication Date
Fri Feb 10 2023
Journal Name
Dentistry Journal
The Role of Social Media in Communication and Learning at the Time of COVID-19 Lockdown—An Online Survey
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This study aimed to assess orthodontic postgraduate students’ use of social media during the COVID-19 lockdown. Ninety-four postgraduate students (67 master’s students and 27 doctoral students) were enrolled in the study and asked to fill in an online questionnaire by answering questions regarding their use of social media during the COVID-19 lockdown. The frequency distributions and percentages were calculated using SPSS software. The results showed that 99% of the students used social media. The most frequently used type of social media was Facebook, 94%, followed by YouTube, 78%, and Instagram, 65%, while Twitter and Linkedin were used less, and no one used Blogger. About 63% of the students used elements of social media to l

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Publication Date
Wed Jan 01 2025
Journal Name
Iraqi National Journal Of Earth Science (injes)
The Effect of Satellite Image Fusion on the Classification Process by Using Multiple Sensors
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Publication Date
Sun Jun 02 2019
Journal Name
Journal Of The College Of Languages (jcl)
Spacio-Temporal Relations in the Translated Text in Both Russian and Arabic: Временные и пространственные отношения с текстом перевода на русском и арабском языках
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 The present paper(Spacio-Temporal Relations in the Translated Text in Both Russian and Arabic) focuses on the spacio-temporal effect in the translated text; it is possible to compose the translation text simultaneously with the  process of the composing the original text. This is carried out during the simultaneous consecutive translation. And, the time and place of composing the translation might greatly differ from the time and place of composing the original textt. The translator may tackle a text of an ancient time and written in a language which might have changed, and may thus appear as another language where the author might have talked on behalf of a people who had lived or are living in apparently different geographic

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Physics: Conference Series
Improve topic modeling algorithms based on Twitter hashtags
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Abstract<p>Today with increase using social media, a lot of researchers have interested in topic extraction from Twitter. Twitter is an unstructured short text and messy that it is critical to find topics from tweets. While topic modeling algorithms such as Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are originally designed to derive topics from large documents such as articles, and books. They are often less efficient when applied to short text content like Twitter. Luckily, Twitter has many features that represent the interaction between users. Tweets have rich user-generated hashtags as keywords. In this paper, we exploit the hashtags feature to improve topics learned</p> ... Show More
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