Introduction: Infection control or hospital-acquired infections are the major concern of the health care system and agencies. Critical care nurses are on the first-line contact with the patients, so on, they are most vulnerable to acquired infections. It is really important to regularly check their knowledge and practices concerning infection control. Objectives: The study aims to identify the impact of years’ experience on nurses’ knowledge and practices concerning infection control in three hospitals and center (Baghdad teaching hospital, Ibn Al-Nafees hospital, and Ibn al-Bitar center) Methodology: Cross-sectional study was conducted, the study starting from 4th of July 2020 to 13th of November 2020. Non-probability (purposive) sample was used to select 110 nurses who work at critical care units in three hospitals and center (Baghdad teaching hospital, Ibn Al-Nafees hospital, and Ibn al-Bitar center). The years of experience should no less than one year. The instrument was composed of two parts. Firstly, covers the nurses’ demographic characteristics. Secondly, included self-report questions about nurses’ knowledge and an evaluation sheet concerning nurses’ practices of infection control with 24 questions for knowledge and 12 questions for practices checklist. Results: The study revealed that the nurses’ knowledge toward infection control record 38%, 41%, and 21% for low, moderate, and high knowledge respectively. In comparison, nurses practices record 47%, 42%, and 11% for low, moderate, and high practices respectively. Most of the study sample 62% was females while 38 % of the subject was males. The age group (20-29) takes the highest percentage (38%), In addition, about (27.3%) of the nurses who works in critical care units have 1-5 years of experience. Significant statistical associations were found between nurses knowledge and practice from one hand and years’ experience on the other hands p ? 0.05. Recommendation: Based on this finding, the researcher recommended further studies involve more nurses and other health professionals regarding infection control and highlight the importance of infection control to nurses with (1-5) years’ experience by symposium or teaching programs.
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The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed
... Show Moreoday deep ocean life has not been discovered by humans including many secret world things to be explored. The researcher has focused on underwater optical wireless communications using various kinds of complex digital Signal processing most of them used in air and starting applied in underwater communication. The Internet of Things (IoT) uses underwater called Internet of Underwater Things (IoUT) applications to explore the underwater world with other devices. However, the difference in concentration between air and water surfaces is not easy making wireless communication more complicated. Visible light passes the water's surface with scattering and distortion inside the water and each color of light has different attenuation the blue laser
... Show MoreThis paper proposes feedback linearization control (FBLC) based on function approximation technique (FAT) to regulate the vibrational motion of a smart thin plate considering the effect of axial stretching. The FBLC includes designing a nonlinear control law for the stabilization of the target dynamic system while the closedloop dynamics are linear with ensured stability. The objective of the FAT is to estimate the cubic nonlinear restoring force vector using the linear parameterization of weighting and orthogonal basis function matrices. Orthogonal Chebyshev polynomials are used as strong approximators for adaptive schemes. The proposed control architecture is applied to a thin plate with a large deflection that stimulates the axial loadin
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