Objectives: The study aim to evaluate nursing performance during nasogastric tube feeding in neonatal intensive care unit. Methodology: A descriptive study was carried out in Neonatal Intensive Care Unit at al–Batool Teaching Hospital, for the purpose of evaluate of quality of nursing performance for premature baby during nasogastric tube feeding in neonatal intensive care unit. The study consumed the period from 4th of December 2017 to the 24nd of April 2018, Non-probability purposive sample of (25) nurses working in the neonatal intensive care unit. The data were collected through the use of Observational instrument which consist of socio-demographic characteristics, quality of nursing care. Results: The study shows that the majority

Background. Najaf governorate was recorded as one of the most polluted Iraqi governorates with increased cancer, autoimmune, and abortion cases. Study Groups. A total of 88 adult volunteers from three test groups were divided based on their inhabitance in different geographical regions in Najaf governorate. Group 1 (G1; n, 29) inhabitants of Al‐Ansar, Al‐Abbaseyeh, and Al‐Manathera districts, Group 2 (G2; n, 27) inhabitants of 22 different scattered districts of the governorate, Group 3 (G3; n, 32) inhabitants of Kufa city and center districts in the old Najaf city. According to previous author

This study aims to explore the impact of the interaction of the university leadership and the university organizational environment on the performance level of the staff at Al-Maaqal university. This university was chosen as a field of study because it is a new university and needs studies that develops and contributes to improve its overall performance. The problem defined by the following question: to what extent does the interaction of the university leadership and the university organizational environment affect the performance level of the teaching staff at AlMaaqal University?). The method of this study adopted a major hypothesis in which there is a statistically significant effect of university leadership and university environment o

The uptake of Cd(II) ions from simulated wastewater onto olive pips was modeled using artificial neural network (ANN) which consisted of three layers. Based on 112 batch experiments, the effect of contact time (10-240 min), initial pH (2-6), initial concentration (25-250 mg/l), biosorbent dosage (0.05-2 g/100 ml), agitation speed (0-250 rpm) and temperature (20-60ºC) were studied. The maximum uptake (=92 %) of Cd(II) was achieved at optimum parameters of 60 min, 6, 50 mg/l, 1 g/100 ml, 250 rpm and 25ºC respectively.

Tangent sigmoid and linear transfer functions of ANN for hidden and output layers respectively with 7 neurons were sufficient to present good predictions for cadmium removal efficiency with coefficient of correlatio

The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

The proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed A

This research focuses on the services provided by news websites (IMN, Youm7, Huffington Post Arabic) to its audience of Internet users, as well as materials posted through its pages, trying to monitor and explain them to identify their types & features, and it›s functions, whether informational or non-informational, to know the technical potential of each of the news sites, with the entry of the latest technology information. The research used the analysis method to achieve the research objectives within the period from 1/1 to 31/1/2017. The researchers used the content analysis tool as a research tool to analyze the news sites and to know the services they provide through their pages. The research was divided into three parts, the

This work presents the use of laser diode in the fiber distributed data interface FDDI networks. FDDI uses optical fiber as a transmission media. This solves the problems resulted from the EMI, and noise. In addition it increases the security of transmission. A network with a ring topology consists of three computers was designed and implemented. The timed token protocol was used to achieve and control the process of communication over the ring. Nonreturn to zero inversion (NRZI) modulation was carried out as a part of the physical (PHY) sublayer. The optical system consists of a laser diode with wavelength of 820 nm and 2.5 mW maximum output power as a source, optical fiber as a channel, and positive intrinsic negative (PIN) photodiode

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.