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 research dealt with the subject of measuring the competitive performance of the National Insurance Company and some of its branches (Basra, Ninwa, Kirkuk and Babil), Depending on the Revenue Growth Index at the activity level, and the Revealed Comparative Advantage Index RCAIAt the branch level,To measure the competitiveness of the company And some branches, As the problem of research in the lack of adoption by some companies in the insurance service sector on scientific indicators to measure their competitive performance, The aims of the research is to measure the competitiveness of the National Insurance Company, as well as the competitiveness of its branches according to the scientific method, One of the main Conclusions of the re
... Show MoreThe proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.
In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete
... Show MoreThe question of estimation took a great interest in some engineering, statistical applications, various applied, human sciences, the methods provided by it helped to identify and accurately the many random processes.
In this paper, methods were used through which the reliability function, risk function, and estimation of the distribution parameters were used, and the methods are (Moment Method, Maximum Likelihood Method), where an experimental study was conducted using a simulation method for the purpose of comparing the methods to show which of these methods are competent in practical application This is based on the observations generated from the Rayleigh logarithmic distribution (RL) with sample sizes
... Show MoreAbstract: Background: Optical biosensors offer excellent properties and methods for detecting bacteria when compared to traditional analytical techniques. It allows direct detection of many biological and chemical materials. Bacteria are found in the human body naturally non-pathogenic and pathologically, as they are found in other living organisms. One of these bacteria is Escherichia coli (E. coli) which are found in the human body in its natural and pathogenic form. E.coli bacteria cause many diseases, including Stomach, intestines, urinary system infections, and others. The aim of this study: is sensing and differentiation between normal flora and pathogenic E.coli. Material and method:
... Show MoreThe partial level density PLD of pre-equilibrium reactions that are described by Ericson’s formula has been studied using different formulae of single particle level density . The parameter was used from the equidistant spacing model (ESM) model and the non- equidistant spacing model (non-ESM) and another formula of are derived from the relation between and level density parameter . The formulae used to derive are the Roher formula, Egidy formula, Yukawa formula, and Thomas –Fermi formula. The partial level density results that depend on from the Thomas-Fermi formula show a good agreement with the experimental data.
The research discusses the need to find the innovative structures and methodologies for developing Human Capital (HC) in Iraqi Universities. One of the most important of these structures is Communities of Practice (CoPs) which contributes to develop HC by using learning, teaching and training through the conversion speed of knowledge and creativity into practice. This research has been used the comparative approach through employing the methodology of Data Envelopment Analysis (DEA) by using (Excel 2010 - Solver) as a field evidence to prove the role of CoPs in developing HC. In light of the given information, a researcher adopted on an archived preliminary data about (23) colleges at Mosul University as a deliberate sample for t
... Show MoreLearning a foreign language is a highly interactive process, and a belief that communicative activities foster a great amount of linguistic production provides language practice and opportunities for negotiation of meaning during communicative exchanges. Thus, this study examines what benefits learner-centered classroom setting offers compared with that of teacher–centered classroom, and how less proficient learners accomplish their tasks and activities with scaffolded help during interaction with the help of proficient classmates and under the guidance of a skilful person, i.e., the teacher. The subjects participating in this study are 30 Iraqi 4th year college students in the Department of English, College of Arts , Univer
... Show MoreMany undergraduate learners at English departments who study English as a foreign language are unable to speak and use language correctly in their post -graduate careers. This problem can be attributed to certain difficulties, which they faced throughout their education years that hinder their endeavors to learn. Therefore, this study aims to discover the main difficulties faced by EFL students in language learning and test the difficulty variable according to gender and college variables then find suitable solutions for enhancing learning. A questionnaire with 15 items and 5 scales were used to help in discovering the difficulties. The questionnaire was distributed to the selected sample of study which consists of 90 (male and female) stud
... Show MoreWitnessing human societies with the turn of the century atheist twenty huge revolution in information , the result of scientific and technological developments rapidly in space science and communications , and that made the whole world is like a small village not linked by road as it was in ancient times, through the rapid transportation as was the case a few years ago , thanks to the remote sensing devices that roam in space observant everything on the ground , that the information networks that overflowed the world a tremendous amount of information provided for each inhabitants of the earth , which made this information requirement for human life and human survival and well-being , as it has allowed that information to humans opportun
... Show MoreImitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co
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