Objective : The study was carried out to construct an initial assessment documentation tool for nursing
recording system in Coronary Care Unit.
Methodology : A descriptive, purposive sample of (65) nurses was selected from CCU of main
teaching hospitals (Al Karama, Al Kindy, Al Kadimia, Al Yarmmok, Baghdad teaching hospital, Ibn
Al Naffis hospital) and Ibn-Al betar hospital in Baghdad city from the 15th of April 2004 to the 15th of
April 2006.
The instrument was constructed and comprised of two sections: section one included the
nurses' demographic characteristic; section two was the initial assessment documentation tool that
contained (2) parts including: General information form and the initial assessment form.

Monetary policy is an important part of the economic policy to influence the monetary aspect of stabilization, for this reason the research will seek to clarify the extent of the impact of monetary policy in achieving monetary stability in Iraq during the chosen research period, because the Iraqi economy suffers from monetary instability due to political and security turmoil, Therefore, an effective and effective monetary policy is required in terms of reducing inflationary pressures to reach the required monetary stability, in order to create the appropriate monetary environment for the work of the economic and productive sectors. Thus, the research adopted a basic hypothesis that monetary policy in Iraq has a clear impact on achieving mon

LED is an ultra-lightweight block cipher that is mainly used in devices with limited resources. Currently, the software and hardware structure of this cipher utilize a complex logic operation to generate a sequence of random numbers called round constant and this causes the algorithm to slow down and record low throughput. To improve the speed and throughput of the original algorithm, the Fast Lightweight Encryption Device (FLED) has been proposed in this paper. The key size of the currently existing LED algorithm is in 64-bit & 128-bit but this article focused mainly on the 64-bit key (block size=64-bit). In the proposed FLED design, complex operations have been replaced by LFSR left feedback technology to make the algorithm perform more e

Research in consumer science has proven that grocery shopping is a complex and distressing process. Further, the task of generating the grocery lists for the grocery shopping is always undervalued as the effort and time took to create and manage the grocery lists are unseen and unrecognized. Even though grocery lists represent consumers’ purchase intention, research pertaining the grocery lists does not get much attention from researchers; therefore, limited studies about the topic are found in the literature. Hence, this study aims at bridging the gap by designing and developing a mobile app (application) for creating and managing grocery lists using modern smartphones. Smartphones are pervasive and become a necessity for everyone tod

The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals

Theresearch took the spatial autoregressive model: SAR and spatial error model: SEM in an attempt to provide a practical evident that proves the importance of spatial analysis, with a particular focus on the importance of using regression models spatial andthat includes all of them spatial dependence, which we can test its presence or not by using Moran test. While ignoring this dependency may lead to the loss of important information about the phenomenon under research is reflected in the end on the strength of the statistical estimation power, as these models are the link between the usual regression models with time-series models. Spatial analysis had

Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp