An infant incubator in the neonatal intensive care unit (NICU) is a medical instrument of care that provides oxygen, warmth and moisture to a newborn baby. Due to environmental conditions affecting the infants foster babies may experience discomfort and pain at some point. Thus, this study aimed to assess ambient air quality in neonatal incubators to improve the environmental quality of neonatal intensive care units and safety. Air pollutants concentrations consisting of particulate matter (pm2.5, pm10), hydrocarbons (HOCH), volatile organic compounds (VOC), air quality index (AQI), humidity and temperature, were measured at four selected Baghdad hospitals (Al-Karkh and Rusafa) . The results showed that the increase in rela

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

Films of PMMA and copper sulphate doped PMMA have been prepared by casting method. Absorbance and transmittance spectra were recorded in the wavelength range (300-900) nm in order to calculate, single oscillator energy, dispersion energy, average oscillator strength, the refractive index at infinite wavelength, M-1 and M -3 moments of the optical spectra, it was found that all these parameters were effected by doping.

Most heuristic search method's performances are dependent on parameter choices. These parameter settings govern how new candidate solutions are generated and then applied by the algorithm. They essentially play a key role in determining the quality of the solution obtained and the efficiency of the search. Their fine-tuning techniques are still an on-going research area. Differential Evolution (DE) algorithm is a very powerful optimization method and has become popular in many fields. Based on the prolonged research work on DE, it is now arguably one of the most outstanding stochastic optimization algorithms for real-parameter optimization. One reason for its popularity is its widely appreciated property of having only a small number of par

Pareto distribution is used in many economic, financial and social applications. This distribution is used for the study of income and wealth and the study of settlement in cities and villages and the study of the sizes of oil wells as well as in the field of communication through the speed of downloading files from the Internet according to their sizes. This distribution is used in mechanical engineering as one of the distributions of models of failure, stress and durability. Given the practical importance of this distribution on the one hand, and the scarcity of sources and statistical research that deal with it, this research touched on some statistical characteristics such as derivation of its mathematical function , probability density

In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve