The present research has investigated the effect of microwave energy on improving the flow properties of heavy crude oil. The fragmentation of crude oil molecules was carried out with and without using 1 and 10 wt. % concentration of various types of H-donors like tetralin, cyclohexane, and naphtha.  Microwave power of 320, 385, and 540 W and radiation time 1-9 min, and temperature were studied. The kinematic viscosity and asphaltene content were measured for evaluation the improving of heavy crude oil.

   Results show that viscosity of crude oil decreased with increase H-donor concentration, a maximum percentage of viscosity reduction was10.63 % for tetralin at 6 min radiation time, while 8.67%, and 7.34% for cycl

The present research has investigated the effect of microwave energy on improving the flow properties of heavy crude oil. The fragmentation of crude oil molecules was carried out with and without using 1 and 10 wt. % concentration of various types of H-donors like tetralin, cyclohexane, and naphtha.  Microwave power of 320, 385, and 540 W and radiation time 1-9 min, and temperature were studied. The kinematic viscosity and asphaltene content were measured for evaluation the improving of heavy crude oil.    Results show that viscosity of crude oil decreased with increase H-donor concentration, a maximum percentage of viscosity reduction was10.63 % for tetralin at 6 min radiation time, while 8.67%, and 7.34% for cyclohexane a

Sentiment 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

This study investigates the role of Enterprise Resources Planning (ERP) systems in improving human resources management (HRM) processes. The rapid environmental changes led to increased demand on the ERP systems, which have changed the manual effort to technology-based processes, providing solutions focusing on the integration of all departments to achieve goals for the entire organization. HRM processes are mainly made up of two classes: strategic and operational HRM. An ERP system works to integrate both of them, making HRM processes more efficient, effective and feasible to provide support to the organization as a whole (inside and outside). In this article, a modest framework is proposed to describe HRM process integrity in relation to

This study aims to explain the role of green target costing technique in improving the relationship with suppliers in a sample of industrial companies listed on the Iraq Stock Exchange. The descriptive analytical approach was used, where a questionnaire was designed that included a set of questions that were directed to a sample of 84 individuals including production managers, finance managers, quality managers, and purchasing managers in these companies. The study uses some statistical analyzes such as correlation analysis and regression analysis to analyze the questionnaires. The study finds a positive impact of the green target costing technique on improving the relationship with suppliers. The results indicate that the relation

<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

As the demands of sixth-generation (6G) networks escalate towards achieving high speeds and improved energy efficiency, there is an increasing need for intelligent and real-time adaptive solutions within the physical processing layer. This study proposes an innovative engineering framework based on an encapsulated architecture utilising FBGA (micro-distributed spherical array) technology, integrated with an internal artificial intelligence module, to achieve adaptive beamforming with high efficiency in dense wireless environments. The primary objective of this research is to develop an intelligent communication architecture that determines the optimal transmission angles and regulates power consumption in real-time by integrating ar

There is no doubt that each of the arts has a material from which the aesthetic achievement is built, so the researcher found that the art of theater, especially the show, whose artistic achievement is based on the body of the actor who emits the formal language (body language), is the focus of interest and active presence, because the body possesses its spiritual qualities that made him and the ability to The formation of things by (his body language), so the researcher studied this theatrical phenomenon and divided it into four chapters. In the first chapter, the research problem included the following question: (Is there a phenomenon of body language in the contemporary theatrical show "Imagine that" as a model) so It is of cognitive