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 annota

In this paper, some commonly used hierarchical cluster techniques have been compared. A comparison was made between the agglomerative hierarchical clustering technique and the k-means technique, which includes the k-mean technique, the variant K-means technique, and the bisecting K-means, although the hierarchical cluster technique is considered to be one of the best clustering methods. It has a limited usage due to the time complexity. The results, which are calculated based on the analysis of the characteristics of the cluster algorithms and the nature of the data, showed that the bisecting K-means technique is the best compared to the rest of the other methods used.

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing

The aim of the research is to determine the impact of profit management practices on the quality of profits through the use of flexibility in determining accounting methods and practices profit information is one of the most important information that concerns current users in general and observing users in particular. Some corporations managements manipulate the results of the company's profit or loss (income statement) and financial position statement with multiple reasons, including capital market motivations to raise their share prices in the stock market and attract investors, and on the other hand the motives of funding and borrowing loans, and the use of the flexibility in accounting policies and estimates to change the in

Laryngoscopy and tracheal intubation are considered the most invasive stimuli in anesthesia. They provoked cardiovascular responses that include hypertension, tachycardia and dysrhythmias. Various pharmacological approaches have been used to blunt or attenuate such pressor responses. The present study was designed to evaluate the effect of medazolom, lignocaine and propranolol as a valuable adjuvant to fentanyl in attenuating hemodynamic responses to endotracheal intubation in normotensive patients. Thirty two patient with physical status I or II according to the score of American Society of Anesthesiologist (ASA), scheduled for elective surgery under standard general anesthesia, were randomly allocated into four groups (8 patients in ea

the digital public relations aim at make the workers getting the necessary information about the governmental institutions where they work and the enveronment surrounding them. it also tries to let the workers get the special knowlege of tthe publich relations and their jobs like the works of planning , arranging the active communication and executive skills needed in their writing , editing , special art skills for designing , production and technological skills to deal with the computer.
the problem of the research includes some questions as :
1- what are the uses achieved by degetal public relations workers at Iraqi universities (Baghdad, Mustansiriya, and Iraqi)
2- what are the tools used to apply digital public relations