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%.
The accession of countries to the World Trade Agreement and the openness of markets to each other without restrictions led to the emergence of the philosophy of "a world without borders and business units without countries", which required adapting the modern business environment to that philosophy, which is considered as objectives for the activities of the units that must be implemented in order to achieve competition. The objective of the units has changed from making profit to meeting the desires of customers, which is what imposed a new role for management accounting as a field of knowledge renewed in it visions of competitiveness between units. Because of the increasing needs for information in light of environmental change
... Show MoreThe 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
... Show MoreEmpirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
... Show MoreAdvanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
... Show MoreThis 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. &
... Show MoreSentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l
... Show MoreThe present study aims to identify the most and the least common teaching practices among faculty members in Northern Border University according to brain-based learning theory, as well as to identify the effect of sex, qualifications, faculty type, and years of experiences in teaching practices. The study sample consisted of (199) participants divided into 100 males and 99 females. The study results revealed that the most teaching practice among the study sample was ‘I am trying to create an Environment of encouragement and support within the classroom which found to be (4.4623). As for the least teaching practice was ‘I use a natural musical sounds to create student's mood to learn’ found to be (2.2965). The study results also in
... Show MoreThe provided research paper offers a thorough analysis of the semiotic analysis present in tobacco-free initiative advertisements from the year 2021. The study delves into the intricate process of decoding the diverse signs, symbols, and visual components integrated into these anti-smoking campaigns. The core aim of this investigation is to comprehend and explore the semiotic tactics that underlie these advertisements, with a particular emphasis on visual communication as a pivotal tool in shaping the public's attitudes and behaviors towards tobacco usage. The research introduces a significant theoretical framework, the "Taxonomy of Image-Text Relations and Functions" theory, as proposed by Emily E. Marsh and Marilyn Dom
... Show MoreReading roles as the third skill in the range of English as a Foreign Language (EFL) learning. Although the capability of reading in both academic and non-academic texts is assessed on standardized tests, few of oral interpretation of written language excludes images from estimating literary knowledge. This paper highlights strategies of reading comprehension and visual literacy. It aims to investigate either textual or visual reading in EFL can make an impact on students' comprehension. The effective use of visuals changes instructing reading comprehension recently.The imagery-text model can affect developing reading comprehension and enhancing intellectual thinking. The study hypothesizes that there is no relationship between reading and
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