In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

Cox regression model have been used to estimate proportion hazard model for patients with hepatitis disease recorded in Gastrointestinal and Hepatic diseases Hospital in Iraq for (2002 -2005). Data consists of (age, gender, survival time terminal stat). A Kaplan-Meier method has been applied to estimate survival function and hazerd function.

An integrated lithofacies and mineralogical assemblage was used to describe a depositional model and sequence stratigraphic framework of the Maastrichtian–Danian succession in the Western Desert of Iraq and eastern Jordan. Fifteen lithofacies types were grouped into three associations recognized in a distally steepened ramp characterized by an apparent, distinct increase in a gradient paleobathymetric deepening westward. The clay and nonclay minerals are dominated by smectite and palygorskite, with trace amounts of kaolinite, sepiolite, illite and chlorite. Meanwhile, quartz, calcite, dolomite, opal CT (Cristobalite - Tridymite), and apatite are the main nonclay minerals. The widely dominated smectite in the Western Phosphatic Basin of Ir

    The emergence of COVID-19 has resulted in an unprecedented escalation in different aspects of human activities, including medical education. Students and educators across academic institutions have confronted various challenges in following the guidelines of protection against the disease on one hand and accomplishing learning curricula on the other hand. In this short view, we presented our experience in implementing e-learning to the undergraduate nursing students during the present COVID-19 pandemic emphasizing the learning content, barriers, and feedback of students and educators. We hope that this view will trigger the preparedness of nursing faculties in Iraq to deal with this new modality of learning and improve it should t

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

This study aims to identify the issue of observing media publishing and its importance for public relations in the management of special events; and its role in building the positive image of the target audience through communication messages that illustrate the political, economic and diplomatic importance of the Arab Summit. As such Summit is one of the conferences that Iraq sought to secure the requirements of its convening to re-activate its political and diplomatic role in the Arab Ocean, especially after the circumstances and crises that Iraq went through.

The convening of the Arab Summit under the auspices of Iraq was a qualitative transition, during which Iraq sought to achieve some gains b