Objective(s): To assess nurses' practices for neurological unconscious patients in intensive care units.
Methodology: A descriptive study was conducted that included (50) nurse who are working in intensive care
units in hospitals and departments of the nervous system in (4) hospitals (neuroscience hospital, teaching
neurosurgical hospital, surgical specialist hospital, and sheck zaied hospital) in Baghdad city from March, 30th
,
2009 to July, 30th 2009 for the purpose of assessing their skills towards unconscious patients. A purposive "nonprobability
sample" was selected that consisted of (50) nurse who are working in intensive care units. A
questionnaire format and observational checklist were used which consist of (2) parts, the first part includes
demographic information of the sample and the second part includes tools which consists of the observation
(7) parts distributed to (64) items. Reliability and validity of questionnaire and observational checklist was
estimated through a pilot study and a panel of expert. The data were analyzed by using descriptive statistical
measures which included frequencies, percentages, and standard deviation, as well as the use of inferential
statistical measures which include the correlation coefficient and coefficient of probability.
Results: The results revealed the inadequacy of skills of nurses towards unconscious patients' care in the field
of airway care, observation and record level of consciousness, hygiene, stimulate the senses and care of urinary
and digestive tract and the adequacy of skills of nurses in the field of measuring and recording vital signs,
nutrition, and the environment.
Recommendations: Based on the results of research, the study recommends initiating training courses in the
field of intensive care and care of for unconscious patients as well as to design a special mini-booklet for the
purpose of care for unconscious patients.
Data Driven Requirement Engineering (DDRE) represents a vision for a shift from the static traditional methods of doing requirements engineering to dynamic data-driven user-centered methods. Data available and the increasingly complex requirements of system software whose functions can adapt to changing needs to gain the trust of its users, an approach is needed in a continuous software engineering process. This need drives the emergence of new challenges in the discipline of requirements engineering to meet the required changes. The problem in this study was the method in data discrepancies which resulted in the needs elicitation process being hampered and in the end software development found discrepancies and could not meet the need
... Show MoreEmergency vehicle (EV) services save lives around the world. The necessary fast response of EVs requires minimising travel time. Preempting traffic signals can enable EVs to reach the desired location quickly. Most of the current research tries to decrease EV delays but neglects the resulting negative impacts of the preemption on other vehicles in the side roads. This paper proposes a dynamic preemption algorithm to control the traffic signal by adjusting some cycles to balance between the two critical goals: minimal delay for EVs with no stop, and a small additional delay to the vehicles on the side roads. This method is applicable to preempt traffic lights for EVs through an Intelli
The using of recycled aggregates from construction and demolition waste (CDW) can preserve natural aggregate resources, reduce the demand for landfill, and contribute to a sustainable built environment. Concrete demolition waste has been proven to be an excellent source of aggregates for new concrete production. At a technical, economic, and environmental level, roller compacted concrete (RCC) applications benefit various civil construction projects. Roller Compacted Concrete (RCC) is a homogenous mixture that is best described as a zero-slump concrete placed with compacting equipment, uses in storage areas, dams, and most often as a basis for rigid pavements. The mix must be sufficiently dry to support
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Perhaps the methods of mask that Arab poets resorted to in our time are due to the conditions of oppression and political and social repression that the Arab poet suffered from; So he strived to circumvent it, and it became a justification for hiding behind it. The research is available on a number of topics that lead to the definition of the mask technique and the beginning of its prevalence in Arabic literature after the Second World War, especially in recent decades by benefiting from historical stories, fairy tales and legends of all kinds. As well as defining the mask idiomatically and linguistically, and the beginning of its use in ancient religious rituals, and the special place it had in Greek plays. Poets
... Show MoreIn data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.
The interest in art for young ages is seen as an obvious breakthrough and as revealing of psychological and health feelings in addition to emotions, and it is a treatment for those who suffer from behavioral disorders. The problem arose with the following question: What is the role of artistic expression in diagnosing behavioral disorders for primary school pupils? The aim of the research is to detect the behavioral disorders in the artistic expression of the female students' paintings from the teachers' point of view. The descriptive analytical approach was adopted as it is the appropriate method for identifying and estimating the characteristics and features related to people, places and things, and analyzing situations or phenomena as a
... Show MoreTo perform a secure evaluation of Indoor Design data, the research introduces a Cyber-Neutrosophic Model, which utilizes AES-256 encryption, Role-Based Access Control, and real-time anomaly detection. It measures the percentage of unpredictability, insecurity, and variance present within model features. Also, it provides reliable data security. Similar features have been identified between the final results of the study, corresponding to the Cyber-Neutrosophic Model analysis, and the cybersecurity layer helped mitigate attacks. It is worth noting that Anomaly Detection successfully achieved response times of less than 2.5 seconds, demonstrating that the model can maintain its integrity while providing privacy. Using neutrosophic sim
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