The research deals with the impact of the nature of social and political formation in the orientation towards extremism through tracking the institutions and beliefs that the individual is going through. The role of the family, the group, the school, education, and religion has been touched upon in acquiring the trends of extremism, whether publicly or covertly, Focusing on the social and economic contexts that are an incubator environment for extremism supported by the form of the group and the beliefs it espouses, whether direct through religion or indirectly through the nature of education, this study relied on political literature that addressed this The topic, which focused on the phenomenon of extremism that swept the world recentl

Every so often, a confluence of novel technologies emerges that radically transforms every aspect of the industry, the global economy, and finally, the way we live. These sharp leaps of human ingenuity are known as industrial revolutions, and we are currently in the midst of the fourth such revolution, coined Industry 4.0 by the World Economic Forum. Building on their guideline set of technologies that encompass Industry 4.0, we present a full set of pillar technologies on which Industry 4.0 project portfolio management rests as well as the foundation technologies that support these pillars. A complete model of an Industry 4.0 factory which relies on these pillar technologies is presented. The full set of pillars encompasses cyberph

Purpose:To evaluate knowledge, practice and attitude of community pharmacists in Basra regarding modified release dosage forms which are widely used for many therapeutic purposes in pharmacy practice.

Methods:The current study was conducted among certified pharmacists in Basra governorate- south of Iraq. Data collection was carried out by a questionnaire.

Results:A total number of 175 community pharmacists responded to the questionnaire. The majority worked in OTC based dispensing pharmacies located in the center of the city. Most respondents missed K1 and were unable to state the difference between different types of modified products. There was a major positive agreemen

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

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

The increasing demand for continual learning in sequential data processing has led to progressively complex training methodologies and larger recurrent network architectures. Consequently, this has widened the knowledge gap between continual learning with recurrent neural networks (RNNs) and their ability to operate on devices with limited memory and compute. To address this challenge, we investigate the effectiveness of simplifying RNN architectures, particularly gated recurrent unit (GRU), and its impact on both single-task and multitask sequential learning. We propose a new variant of GRU, namely the minion recurrent unit (MiRU). MiRU replaces conventional gating mechanisms with scaling coefficients to regulate dynamic updates of hidden

This research suggests a robust and systematic way for Arabic Sentiment Analysis using a vast dataset of 66,666 text reviews. One of the main advantages of this study is that the dataset was perfectly balanced (33,333 positive samples and 33,333 negative samples). In machine learning, this 50/50 split is important because it eliminates class bias and enables the predictive model to treat both sentiment classes equally. As shown in the values of the metrics — overall accuracy, weighted precision, weighted recall, and F1 score — there is great similarity among them, indicating a stable and reliable assessment of the model's real potential throughout the Arabic dataset. Based on data profile, the average word count per review is 42.3

Abstract

Purpose of this study is to investigate the relationship between Advertising Appeals, Attitudes toward Advertising, and Consumer Buying Behavior for Smart Phone The study was carried out on the students of Middle East University (MEU) In Amman- Jordan.  A measurement scales  with acceptable reliability and validity is developed to capture the dimensions of study variables.  Four hypotheses were tested using Statistical package (SPSS-17).  A two-step detailed statistical analysis of data was involved. First, descriptive statistics was performed to understand the underlying components of study variables; second, regression analysis and Path analysis using AMOS 7 were performed t