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Detecting Textual Propaganda Using Machine Learning Techniques
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Social Networking has dominated the whole world by providing a platform of information dissemination. Usually people share information without knowing its truthfulness. Nowadays Social Networks are used for gaining influence in many fields like in elections, advertisements etc. It is not surprising that social media has become a weapon for manipulating sentiments by spreading disinformation.  Propaganda is one of the systematic and deliberate attempts used for influencing people for the political, religious gains. In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms. Data was collected from the news sources from July 2018-August 2018. After annotating the text, feature engineering is performed using techniques like term frequency/inverse document frequency (TF/IDF) and Bag of words (BOW). The relevant features are supplied to support vector machine (SVM) and Multinomial Naïve Bayesian (MNB) classifiers. The fine tuning of SVM is being done by taking kernel Linear, Poly and RBF. SVM showed better results than MNB by having precision of 70%, recall of 76.5%, F1 Score of 69.5% and overall Accuracy of 69.2%.

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
The impact of organizational learning capabilities on the promotion of knowledge capital Applied research at Wasit University
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Abstract

      The current research aims at identifying any of the dimensions of organizational learning abilities that are more influential in the knowledge capital of the university and the extent to which they can be applied effectively at Wasit University. The current research dealt with organizational learning abilities as an explanatory variable in four dimensions (Experimentation and openness, sharing and transfer of knowledge, dialogue, interaction with the external environment ), and knowledge capital as a transient variable, with four dimensions (human capital, structural capital, client capital, operational capital). The problem of research is the following questio

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Publication Date
Wed Mar 02 2022
Journal Name
Journal Of Educational And Psychological Researches
King Khalid University towards Strategies Compatible with Brain-Based Learning (BBL)
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The study aimed to reveal the level of knowledge and tendencies of high- study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with brain-based learning (BBL). And Then, putting a proposed concept to develop knowledge and tendencies of high-study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with Brain-based learning (BBL). For achieving this goal, a cognitive test and a scale of tendency were prepared to apply harmonious strategies with brain-based learning. The descriptive approach was used because it suits the goals of the study. The study sample consisted of (70) male and female students of postgraduate

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Non-linear support vector machine classification models using kernel tricks with applications
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The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

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Publication Date
Sun Mar 30 2025
Journal Name
Iraqi Journal Of Science
Segmentation of Aerial Images Using Different Clustering Techniques
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The segmentation of aerial images using different clustering techniques offers valuable insights into interpreting and analyzing such images. By partitioning the images into meaningful regions, clustering techniques help identify and differentiate various objects and areas of interest, facilitating various applications, including urban planning, environmental monitoring, and disaster management. This paper aims to segment color aerial images to provide a means of organizing and understanding the visual information contained within the image for various applications and research purposes. It is also important to look into and compare the basic workings of three popular clustering algorithms: K-Medoids, Fuzzy C-Mean (FCM), and Gaussia

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Publication Date
Wed Jul 06 2022
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Image Compression using Polynomial Coding Techniques: A review
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Publication Date
Tue Oct 12 2021
Journal Name
Engineering, Technology And Applied Science Research
Automated Pavement Distress Detection Using Image Processing Techniques
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Pavement crack and pothole identification are important tasks in transportation maintenance and road safety. This study offers a novel technique for automatic asphalt pavement crack and pothole detection which is based on image processing. Different types of cracks (transverse, longitudinal, alligator-type, and potholes) can be identified with such techniques. The goal of this research is to evaluate road surface damage by extracting cracks and potholes, categorizing them from images and videos, and comparing the manual and the automated methods. The proposed method was tested on 50 images. The results obtained from image processing showed that the proposed method can detect cracks and potholes and identify their severity levels wit

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Publication Date
Sun Dec 01 2024
Journal Name
Al-khwarizmi Engineering Journal
Defect Detection Using Thermography Camera Techniques: A review
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Individuals across different industries, including but not limited to agriculture, drones, pharmaceuticals and manufacturing, are increasingly using thermal cameras to achieve various safety and security goals. This widespread adoption is made possible by advancements in thermal imaging sensor technology. The current literature provides an in-depth exploration of thermography camera applications for detecting faults in sectors such as fire protection, manufacturing, aerospace, automotive, non-destructive testing and structural material industries. The current discussion builds on previous studies, emphasising the effectiveness of thermography cameras in distinguishing undetectable defects by the human eye. Various methods for defect

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Publication Date
Mon Mar 15 2021
Journal Name
Al-academy
Making use of economical design techniques and materials in implementing cosmetic supplements to the interior spaces of the dwelling: رانيه علي احمد عبد الرحمن
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  This research aims to identify the economic design techniques and materials that can be used in the implementation of cosmetic supplements to the spaces of the dwelling. The research relied on the descriptive and analytical approach by describing and analyzing models of design techniques and materials that can be used in the production of cosmetic supplements in the interior spaces of the dwelling.
The results of the research concluded that the beautification of the spaces of the dwelling is one of the necessary and important pieces to add aesthetic touches to the internal spaces, and that the use of economic design techniques and materials contributes to the implementation of many pieces of complementary beautification of the

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Publication Date
Wed Jan 16 2019
Journal Name
Applied Physics A
Detecting the thermoplasmonic effect using ellipsometry parameters for self-assembled gold nanoparticles within a polydimethylsiloxane matrix
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Publication Date
Sun Jun 30 2019
Journal Name
Journal Of The College Of Education For Women
The Degree of Practicing of the Sixth Primary Social Studies’ Teachers in Iraq for the Principles of Active Learning from their Point of view
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This study aimed to explore The Degree of Practicing of the Sixth Primary Social Studies’ Teachers in Iraq for the Principles of Active Learning from their Point of view

The study society consisted of 230 male and femalesocial studiesteachers’ subjects for the sixth primary grade in Al-Anbar General Directorate of Education. 160 of them were selected to represent the sample of the study with a percent of (70%) from the original society. To achieve the aims of the study, the researchers prepared a questionnaire consisting of (43) items which represented the active learning principles. The validity and stability of the tool were verified. The researchers used the descriptive approach to suit the objectives of this study. &

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