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Data Mining Methods for Extracting Rumors Using Social Analysis Tools
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       Rumors are typically described as remarks whose true value is unknown. A rumor on social media has the potential to spread erroneous information to a large group of individuals. Those false facts will influence decision-making in a variety of societies. In online social media, where enormous amounts of information are simply distributed over a large network of sources with unverified authority, detecting rumors is critical. This research proposes that rumor detection be done using Natural Language Processing (NLP) tools as well as six distinct Machine Learning (ML) methods (Nave Bayes (NB), random forest (RF), K-nearest neighbor (KNN), Logistic Regression (LR), Stochastic Gradient Descent (SGD) and Decision Tree (DT)). The data set size for the suggested experiment was 16,865 samples. For pre-processing tokenization was used to separates each one of the tokens from the others. Normalization that removes all non-word tokens, deleting stop words was utilized to remove all unnecessary words, and stemming was used to obtain the stem of the tokens. Prior to using the six classification algorithms, the major feature extraction approach Term Frequency- Inverse Document Frequency (TF-IDF) was applied. The RF classifier performed better compared to all other classifiers with an accuracy of 99%, according to the data.

Keywords: Machine learning, Text classification, Naïve Byes, RF, KNN, DT, Natural language processing, SGD).

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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
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Facial Expression Recognition Based on Deep Learning: An Overview
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      Recognizing facial expressions and emotions is a basic skill that is learned at an early age and it is important for human social interaction. Facial expressions are one of the most powerful natural and immediate means that humans use to express their feelings and intentions. Therefore, automatic emotion recognition based on facial expressions become an interesting area in research, which had been introduced and applied in many areas such as security, safety health, and human machine interface (HMI). Facial expression recognition transition from controlled environmental conditions and their improvement and succession of recent deep learning approaches from different areas made facial expression representation mostly based on u

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Publication Date
Tue May 30 2023
Journal Name
Iraqi Journal Of Science
Deep Convolutional Neural Network Architecture to Detect COVID-19 from Chest X-Ray Images
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      Today, the world is living in a time of epidemic diseases that spread unnaturally and infect and kill millions of people worldwide. The COVID-19 virus, which is one of the most well-known epidemic diseases currently spreading, has killed more than six million people as of May 2022. The World Health Organization (WHO) declared the 2019 coronavirus disease (COVID-19) after an outbreak of SARS-CoV-2 infection. COVID-19 is a severe and potentially fatal respiratory disease caused by the SARS-CoV-2 virus, which was first noticed at the end of 2019 in Wuhan city. Artificial intelligence plays a meaningful role in analyzing medical images and giving accurate results that serve healthcare workers, especially X-ray images, which are co

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
information and communication technologies and their impact on changed the financial reporting system In a Sample in Iraqi banks
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paid recent developments in the information and communications technology and the accompanying developments in the global market to pay particular accounting information users to demand more sophistication in terms of corporate financial reporting systems, which led to the emergence of a new type of reporting (financial reporting in real time). where is the information and communications technology mainstay Nations for the development and progress, thanks to the development of technology that have made the transmission of information easily conducted and high speed to all who need it, communication is instantaneous and the flow of information via the internet dramatically exceeded the border temporal and spatial anywhere in the w

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Publication Date
Wed Jun 29 2022
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
The Use Of Genetic Algorithm In Estimating The Parameter Of Finite Mixture Of Linear Regression
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The estimation of the parameters of linear regression is based on the usual Least Square method, as this method is based on the estimation of several basic assumptions. Therefore, the accuracy of estimating the parameters of the model depends on the validity of these hypotheses. The most successful technique was the robust estimation method which is minimizing maximum likelihood estimator (MM-estimator) that proved its efficiency in this purpose. However, the use of the model becomes unrealistic and one of these assumptions is the uniformity of the variance and the normal distribution of the error. These assumptions are not achievable in the case of studying a specific problem that may include complex data of more than one model. To

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Publication Date
Sun Aug 01 2021
Journal Name
The 4th International Virtual Conference In Educational And Human Sciences, Arts, And Languages
Measuring Situational Language Teaching to English Student's Speaking in Private Schools
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English teachers in Iraq and other countries around the world up to this time use traditional methods to help students memorize new vocabularies. The sense of words or structure is not to be given in either the native tongue or the target language by definition, but is induced by the way the form is used in the situation. Situational Language Teaching (SLT) has recently become the needed method for improving speaking skills. It indicates the application of learning the language in actual and social exchange expressions so as to let learners do as required in classroom and non-classroom circumstances. This pilot study seeks to answer the following questions: Can SLT improve English speaking skills of target learners? How SLT contribute to th

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Publication Date
Fri Jan 01 2021
Journal Name
Review Of International Geographical Education Online
Quality of Transition to E-Learning under Corona pandemic: An Application Study in College of Administration and Economics, Baghdad University
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E-learning is a lifeline for the educational process, which contributed to the sustainability of working educational organizations and prevented them from stopping, so the study came to measure the compatibility between E-learning quality dimensions (information technology, educational curricula, teaching methods, and intellectual capital of educational institution) as an independent variable, and educational services quality dimensions represented by (safety, tangibility, reliability and Confidence) as a dependent variable. The sample was 150 teachers was drawn from the College of Administration and Economics community of 293 teachers through the use of several statistical methods to measure the degree of correlation and impact between the

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Scopus
Publication Date
Tue Aug 23 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Face mask detection based on algorithm YOLOv5s
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Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

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Publication Date
Thu May 28 2020
Journal Name
Iraqi Journal Of Science
Synthetic Aperture Radar Image Classification: a Survey: Survey
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In this review paper, several studies and researches were surveyed for assisting future researchers to identify available techniques in the field of classification of Synthetic Aperture Radar (SAR) images. SAR images are becoming increasingly important in a variety of remote sensing applications due to the ability of SAR sensors to operate in all types of weather conditions, including day and night remote sensing for long ranges and coverage areas. Its properties of vast planning, search, rescue, mine detection, and target identification make it very attractive for surveillance and observation missions of Earth resources.  With the increasing popularity and availability of these images, the need for machines has emerged to enhance t

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