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Computer-based plagiarism detection techniques: A comparative study
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Plagiarism is becoming more of a problem in academics. It’s made worse by the ease with which a wide range of resources can be found on the internet, as well as the ease with which they can be copied and pasted. It is academic theft since the perpetrator has ”taken” and presented the work of others as his or her own. Manual detection of plagiarism by a human being is difficult, imprecise, and time-consuming because it is difficult for anyone to compare their work to current data. Plagiarism is a big problem in higher education, and it can happen on any topic. Plagiarism detection has been studied in many scientific articles, and methods for recognition have been created utilizing the Plagiarism analysis, Authorship identification, and Near-duplicate detection (PAN) Dataset 2009- 2011. Verbatim plagiarism, according to the researchers, plagiarism is simply copying and pasting. They then moved on to smart plagiarism, which is more challenging to spot since it might include text change, taking ideas from other academics, and translation into a more difficult-to-manage language. Other studies have found that plagiarism can obscure the scientific content of publications by swapping words, removing or adding material, or reordering or changing the original articles. This article discusses the comparative study of plagiarism detection techniques.

Publication Date
Mon Jan 01 2018
Journal Name
Journal Of The College Of Languages (jcl)
The Word " בַּיִת " (House) in the Book of Joshua A Comparative Semitic Linguistic Study
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In this paper we have dealt with the word "  בַּיִת" in the Book of Joshua because it makes one of those that highly employed the  word    בַּיִת"  " in the Old Testament. The Book of Joshua comes  sixth   in the order of tanakh wich was written by Joshua son of  Noon in Palestine during the fifteenth century  B.C. and it covers a three-decade era extending from the death  of Moses til the death of Joshua son of Noon.

      The word " בַּיִת " in this paper refers to the place, where expressions are made by a noun modified by a noun . The modifier is"" בַּיִת , and the modified is another noun. Herein, we

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Publication Date
Wed Sep 30 2026
Journal Name
Al–bahith Al–a'alami
CARTOON SEMIOTIC ABOUT MARCH OF RETURN IN THE PALESTINIAN NEWSPAPERS: : (A Comparative Analytical Study)
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This study aims to reveal the semiotic of “March of Return” cartoon in the Palestinian journalism, topics, Symbols and semantics that were covered.
This study is descriptive. It uses the survey method. Content analysis, and methodological comparison was also used.

The researcher chose an intentional sample of Palestine and Al-Hayat Al-Jadida newspapers for one year from March 30, 2018 to March 31, 2019, through a comprehensive inventory of all cartoons of the return marches during this period, which amounted to 59 cartoons.

The study has reached the following findings:

Newspapers cartoons focused on the topics of durability of the protester

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Publication Date
Sun Jan 01 2017
Journal Name
البحوث التربويةوالنفسية
Preparing a teacher’s guide for computer books for the intermediate stage according to learning styles
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Publication Date
Sat Apr 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Using PCR and Gel Electrophoresis Techniques to Molecular Confirm and Detection for Flowering Gene Presence in Maize Hybrids
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Abstract<p>The laboratory experiment was conducted in the laboratories of the Musayyib Bridge Company for Molecular Analyzes in the year 2021-2022 to study the molecular analysis of the inbreed lines and their hybrids F1 to estimate the genetic variation at the level of DNA shown by the selected pure inbreed lines and the resulting hybrids F1 of the flowering gene. Five pure inbreed lines of maize were selected (ZA17WR) Late, ZM74, Late, ZM19, Early ZM49WZ (Zi17WZ, Late, ZM49W3E) and their resulting hybrids, according to the study objective, from fifteen different inbreed lines with flowering time. The five inbreed lines were planted for four seasons (spring and fall 2019) and (spring and fall 2</p> ... Show More
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Publication Date
Wed Sep 07 2022
Journal Name
2022 Iraqi International Conference On Communication And Information Technologies (iiccit)
Construct an Efficient DDoS Attack Detection System Based on RF-C4.5-GridSearchCV
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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
IFFT-Based Microwave Non-Destructive Testing for Delamination Detection and Thickness Estimation
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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Fast Shot Boundary Detection Based on Separable Moments and Support Vector Machine
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Publication Date
Fri Apr 30 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
SMS Spam Detection Based on Fuzzy Rules and Binary Particle Swarm Optimization
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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Proposed Face Detection Classification Model Based on Amazon Web Services Cloud (AWS)
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One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Proposed Face Detection Classification Model Based on Amazon Web Services Cloud (AWS)
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One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca

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Scopus (13)
Crossref (7)
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