Objective: To assess the clinical learning environment and clinical training for students' in maternal and child
health nursing.
Methodology: A descriptive study was conducted on non probability sample (purposive) of (175) students' in
Nursing College/ University of Baghdad for the period of June 19th to July 18th 2013. A questionnaire was used as a
tool of data collection to fulfill with objective of the study and consisted of three parts, including demographic,
clinical learning environment and clinical training for students' in maternal and child health nursing. Descriptive
statistical analyses were used to analyze the data.
Results: The results of the study revealed that the 65.1% of student at age which ranged between (19-23) years
and 56% were male student, 66.9% were third year nursing students, and 59.4% were morning study. The study
revealed that there were high mean score response among study sample except item (11) the response was (No)
in which as (The learning environment in the hospital with a homogeneous environment college) at student's
attitude's regarding clinical learning environment. And the study revealed that there were high mean score
response among study sample at the clinical training.
Recommendations: The study recommended to need to conduct other the researches to evaluate the actual
clinical learning environment for nurse's skills and practices performance in the hospital. And to determine factors
influence student's during clinical learning environment and clinical training
Hepatitis B and C is a serious global public health problem that causes chronic liver disease and accelerates high risk of death from cirrhosis of the liver and liver cancer.
To determine the knowledge and attitude of nonmedical students at Baghdad University toward HBV and HCV infections and to find out the relationship between demographic characteristics.
The study w
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Abstract:
Witness the current business environment changes rapidly reflected on the performance of the facility wishing to stay , which is no longer style reaction enough to handle installations with their environment , and quickly began to lose its luster with the emergence of a message and the vision of contemporary business environment from a set of parts interacting with each other and the concept of behavioral includes all dimensions of performance, it is imperative to adopt a system installations influence variables and positive interaction through the development of strategic plans and the use of implementation and follow-up strategies to ensure the effectiveness of the method for meas
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Natural gas and oil are one of the mainstays of the global economy. However, many issues surround the pipelines that transport these resources, including aging infrastructure, environmental impacts, and vulnerability to sabotage operations. Such issues can result in leakages in these pipelines, requiring significant effort to detect and pinpoint their locations. The objective of this project is to develop and implement a method for detecting oil spills caused by leaking oil pipelines using aerial images captured by a drone equipped with a Raspberry Pi 4. Using the message queuing telemetry transport Internet of Things (MQTT IoT) protocol, the acquired images and the global positioning system (GPS) coordinates of the images' acquisition are
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This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength. This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.
Moreover, the proposed controller i
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The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre
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This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.
Objective(s): To determine the impact of the electronic Health Information Systems upon medical, medical Backing and administrativedecisions in Al-Kindy Teaching Hospital. Methodology: A descriptive analytical design is employed through the period of June 14th 2015 to August 15th 2015. A purposive "non- probability" sample of (50) subject is selected. The sample is comprised of (25) medical and medical backing staff and (25) administrative staff who are all involved in the process of decision making in Al-Kindy Teaching Hospital. A self-report questionnaire, of (68) item, is adopted and developed for the purpo
The study attempts to measure the level of shyness; the level of psychological isolation; to identify the relationship between shyness and psychological isolation; and to identify the differences between shyness and psychological isolation among first-intermediate students. To this end, a random sample comprised (187) male and female students was chosen for the academic year (2016-2017) from Baghdad \ Al-Rasafa. To measure the shyness and psychological isolation, the researcher designed two scales: one to measure the shyness composed of (37) items divided into four domains; and the other to measure the psychological isolation made of (56) items divided into three domains. The study concluded that the sample has a medium level of shyness;
... Show MoreThe aim of this research is to develop qualitative workouts based on certain sensory perceptions for the development of offensive basketball abilities and to determine their impact on female pupils. Several findings, based on the au-thor's extensive expertise instructing basketball materials and our closeness to the sample, revealed deficits in some sensory perceptions “in the game of basketball”, which impair the accuracy of passing the ball to the best team-mate. It also affects the pace of dribbling and the difficulty of selecting the op-timal moment and distance to fire. Therefore, the researcher designs qualita-tive activities based on many sensory experiences, including distance, speed, force, and direction shift. In addition, the
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