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. Descriptive and
inferential statistical procedures were used to analyze the data. Reliability of the instrument was
determined for the tool parts and it was (0.85), besides that a panel of experts determined the validity
of the tool.
Results : The findings revealed that the most of the study sample were young male with nursing
institute graduate and the majority of them employed with limited experience ranging between (1-5)
years as general and experience in CCU. In spite of that no one of them got a training course in
documenting their activities.
The present study revealed that, the distribution of nurses' responses to the health pattern indicated that
the (health perception, exchanging, subjective awareness of information, nutrition-metabolic,
elimination, activity and exercise, rest and sleep, cognitive-sensing, and relationship) patterns were the
most appropriate, clear and comprehensive patterns for them.
Most of the international nursing diagnosis items of the tool were clear for nurses except few items.
The results also showed that there was a statistically significant influence between the nurses' responses
to the (11) health patterns with the age variable except in the cognitive - sensing pattern. Moreover, the
level of education patterns significantly influences the entire sample responses.
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As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec
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This paper proposes a self organizing fuzzy controller as an enhancement level of the fuzzy controller. The adjustment mechanism provides explicit adaptation to tune and update the position of the output membership functions of the fuzzy controller. Simulation results show that this controller is capable of controlling a non-linear time varying system so that the performance of the system improves so as to reach the desired state in a less number of samples.
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This paper presents a fuzzy logic controller for a two-tank level control system, which is a process with a dead time. The fuzzy controller is a proportional-integral (PI-like) fuzzy controller which is suitable for steady state behavior of the system. Transient behavior of the system was improved without the need for a derivative action by suitable change in the rule base of the controller. Simulation results showed the step response of the two-tank level control system when this controller was used to control this plant and the effect of the dead time on the response of the system.
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Tested effective Alttafaria some materials used for different purposes, system a bacterial mutagenesis component of three bacterial isolates belonging to different races and materials tested included drug Briaktin
An intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used in this research, IoTID20, UNSW-NB15, and IoT-23. The results are compared with the three datasets men
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