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%.
Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med
... Show MoreTo date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip
... Show MoreThe study aims to identify the level of cognitive beliefs, as well as to identify the level of self-organized learning strategies among intermediate school students. The study also aims to identify the differences in the level of self-organized learning strategies among intermediate school students in term of gender, branch (scientific, literary). In order to achieve the research objectives, the researcher designed a scale to measure the cognitive beliefs. As for the scale of self-organized learning strategies, the researcher adopted a scale of (Pintrich et al. 1991), which was translated by (Izzat Abdelhamid, 1999) , For self-organized learning strategies, the sample consisted of (400) students from the research population, whic
... Show MoreThe research entitled "the attitudes of Iraqi People towards the Logic Propaganda for Terrorist Organization such as Daash Regulation, as-Qaida, and Jabhat al-Nasra". It is a field study on the professors and the students of the College of Mass Media at Baghdad University in 2014.
After the global war on terrorism declared on September 11, 2011, the researcher finds it is important to study such subject as it threats the unity and sovereignty of Iraq especially after th
... Show MoreThe present study has three objectives: 1) to investigate the prevalence of complex nominals in economic discourse represented via the selected business news texts, 2) to shed some light on the most common translation errors made by second year students in the Department of Translation in rendering complex nominals into Arabic, and 3) to detect the possible causes behind such translation errors and suggest some translation tips which might sound helpful to the students of translation to find the most suitable translation equivalent. The present study is based on an empirical survey in which a selective analysis of someeconomic texts represented in business news texts is made. A corpus of 159 complex nominals was selected from seven busin
... Show MoreThis study was conducted to investigate the presence of Staphylococcus aureus in the red and white meat available in local markets. They were selected ten samples of red and white meat randomly (Iraq, Saudi Arabia, Turkey, and Brazil) from different markets in Baghdad, and the results of reading the nutrition facts of media indication card showed that all models confirm to the Iraqi standard quality in terms of scanning all data of the media indication card, except for the birds of Bayader, where the date of expire & production date of the product was not mentioned. Also, the results of the study showed that there is no Staphylococcus aureus in local red and white meat as well as imported.
Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.
 
... Show MoreResearch aims to shed light on the concept of corporate failures , display and analysis the most distinctive models used to predicting corporate failure; with suggesting a model to reveal the probabilities of corporate failures which including internal and external financial and non-financial indicators, A tested is made for the research objectivity and its indicators weight and by a number of academics professionals experts, in addition to financial analysts and have concluded a set of conclusions , the most distinctive of them that failure is not considered a sudden phenomena for the company and its stakeholders , it is an Event passes through numerous stages; each have their symptoms that lead eve
... Show MoreThe ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communi
... Show MoreThe hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s
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