Cultured fruits of theCorundum Coriandrum sativum were sown On 11/11 / 2008 in basins containing 15 kg of soil (Silty Loam) .Fruits were divided into two parts the first was soaked in normanl water and the second was magnetized for a period of 24 hours Irrigation was up to (75% of capacity field.Two types of water (normal water and magnetized water)with three repetitions were used the access to magnetic water was supplied from a special electric device. Recorded measurements were plant height the number of stems / plant, weight of plant, number of flowers, 1000 seed weight) during the cultivation period, which ended on 11/5/2009. Results indicated the absence of any effect of magnetic water on plant growth of Fenugreek while seeds tre

Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

In recent days, the escalating need to seamlessly transfer data traffic without discontinuities across the Internet network has exerted immense pressure on the capacity of these networks. Consequently, this surge in demand has resulted in the disruption of traffic flow continuity. Despite the emergence of intelligent networking technologies such as software-defined networking, network cloudification, and network function virtualization, they still need to improve their performance. Our proposal provides a novel solution to tackle traffic flow continuity by controlling the selected packet header bits (Differentiated Services Code Point (DSCP)) that govern the traffic flow priority. By setting the DSCP bits, we can determine the appropriate p

A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

Abstract

This Research aims for harnessing critical and innovative thinking approaches besides innovative problem solving tools in pursuing continual quality improvement initiatives for the benefit of achieving operations results effectively in water treatment plants in Baghdad Water Authority. Case study has been used in fulfilling this research in the sadr city water treatment plant, which was chosen as a study sample as it facilitates describing and analyzing its current operational situation, collecting and analyzing its own data, in order to get its own desired improvement opportunity be done. Many statistical means and visual thinking promoting methods has been used to fulfill research task.

The research aims to show the effect of some short-term debt instruments (central treasury transfers, cash credit granted to the government by commercial banks) on the production of the wheat crop in Iraq, through its effect on money supply during the period (1990-2018), As the study includes two models according to the statistical program (Eviews9), the first model included measuring the effect of short-term debt instruments on money supply, and the second measuring the extent of the money supply's impact on Wheat crop production, as the results of the standard analysis showed that the short-term debt instruments used in the model were Significant effect on wheat crop production indirectly through its effect on money supply, As

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.

Objectives: to assess nurses' knowledge toward infection control measures for hepatitis a virus in hemodialysis
units and to detemine the relationship between nurses' knowledge and their demographical characteristics.
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A non-probability `tturposive" sample of (51) nurses, who were working in hemodialysis units were selected
from Baghdad teaching hosphals. The data were collected through the use of constructed questionnaire, which
consists of two parts (I) Demographic data fom that consists of 10 items and (2) Nurses' knowledge form that
consists of 6 sections contain 79 items, by means of direct interview techniq