Objective: The descriptive study was used to evaluate nursing staff performance in cardiac care units at teaching
and non teaching hospitals in kirkuk city: A comparative study.
Methodology: A descriptive study was used to evaluate nursing staff performance in cardiac care units. The study
was conducted from December 29th
, 2013 up to the 27th of Apr. 2014. A non-probability (purposive) sample of
(44) nurses who work in cardiac care unit at Azady teaching Hospital and Kirkuk general Hospital was evaluated by
a questionnaire which consisted of two parts; the first part is concerned with the demographic characteristics of
the nurses and the second part concerned Observation check list for evaluation nursing staff Performance in
Cardiac Care. Validity of the observational check list performed through a panel of (02) experts and the reliability of
the questionnaire is determined through the pilot study. Descriptive and inferential statistical used to analysis of
data.
Results: the study shows that (61.4%) of the samples age were (20-30) years old, (63.6%) were male. (68.2%) of
them Graduate B.Sc. of Nursing. most of the samples has (1-5) Years of experience in Nursing. the results shows
that a high assessment of observational Check List are reported for the following domains: Maintenance respiration
by adequate O2 supply, Decrease SVR (systematic vascular resistance), Monitor ABGs (Arterial blood gases)
frequently. Also the study reveals that moderate assessments of observational Check List are reported for reaming
domains.
Recommendations : Providing opportunity for nurses in cardiac care units to continuing updating their education
to maintain knowledge and skills.
The purpose of this research paper is to present the second-order homogeneous complex differential equation , where , which is defined on the certain complex domain depends on solution behavior. In order to demonstrate the relationship between the solution of the second-order of the complex differential equation and its coefficient of function, by studying the solution in certain cases: a meromorphic function, a coefficient of function, and if the solution is considered to be a transformation with another complex solution. In addition, the solution has been provided as a power series with some applications.
The objective of this paper is to improve the general quality of infrared images by proposes an algorithm relying upon strategy for infrared images (IR) enhancement. This algorithm was based on two methods: adaptive histogram equalization (AHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE). The contribution of this paper is on how well contrast enhancement improvement procedures proposed for infrared images, and to propose a strategy that may be most appropriate for consolidation into commercial infrared imaging applications.
The database for this paper consists of night vision infrared images were taken by Zenmuse camera (FLIR Systems, Inc) attached on MATRIC100 drone in Karbala city. The experimental tests showed sign
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The effective insulation design of the stress grading (SG) system in form-wound stator coils is essential for preventing partial discharges and excessive heat generation under pulse-width modulation excitation. This paper proposes a method to find the optimal insulation design of the SG system aimed at reducing the dielectric and thermal stresses in the machine coil. The non-uniform transmission line model is used to predict the voltage propagation along the overhang, SG, and slot regions considering the variation in the physical properties of the insulation layers. The machine coil parameters for different insulation materials are calculated by using the finite element method. Two optimization algorithms, fmincon and particle swarm optimiz
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We are used Bayes estimators for unknown scale parameter when shape Parameter is known of Erlang distribution. Assuming different informative priors for unknown scale parameter. We derived The posterior density with posterior mean and posterior variance using different informative priors for unknown scale parameter which are the inverse exponential distribution, the inverse chi-square distribution, the inverse Gamma distribution, and the standard Levy distribution as prior. And we derived Bayes estimators based on the general entropy loss function (GELF) is used the Simulation method to obtain the results. we generated different cases for the parameters of the Erlang model, for different sample sizes. The estimates have been comp
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t-Self-Compacting Concrete (SCC) reduces environmental noise and has more workability. This research presents an investigation of the behavior of SCC under mechanical loading (impact loading). Two types of cement have been used to produce SCC mixtures, Ordinary Portland Cement (OPC) and Portland Limestone Cement (PLC), which reduces the emission of carbon dioxide during the manufacturing process. The mixes were reinforced with Carbon Fiber Reinforced Polymer (CFRP) which is usually used to improve the seismic performance of masonry walls, to replace lost steel reinforcements, or to increase column strength and ductility. Workability tests were carried out for fresh SCC. Prepared concrete slabs of 500×500×50mm were tested for lo
... Show MoreBearing capacity of soil is an important factor in designing shallow foundations. It is directly related to foundation dimensions and consequently its performance. The calculations for obtaining the bearing capacity of a soil needs many varying parameters, for example soil type, depth of foundation, unit weight of soil, etc. which makes these calculation very variable–parameter dependent. This paper presents the results of comparison between the theoretical equation stated by Terzaghi and the Artificial Neural Networks (ANN) technique to estimate the ultimate bearing capacity of the strip shallow footing on sandy soils. The results show a very good agreement between the theoretical solution and the ANN technique. Results revealed that us
... Show MoreA particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.