Objectives: to assess nurses' knowledge toward infection control measures for hepatitis a virus in hemodialysis
units and to detemine the relationship between nurses' knowledge and their demographical characteristics.
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A non-probability `tturposive" sample of (51) nurses, who were working in hemodialysis units were selected
from Baghdad teaching hosphals. The data were collected through the use of constructed questionnaire, which
consists of two parts (I) Demographic data fom that consists of 10 items and (2) Nurses' knowledge form that
consists of 6 sections contain 79 items, by means of direct interview technique with the nurses. The validity of
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Descriptive statistical analysis procedures (frequency, percentage, mean of score) and inferential statistical
analysis procedures (person correlation coefficient, contingency coefficient) were used for the data analysis.
Results: The findings of the study indicated that there is a knowledge deficit of nurses in some aspects relative
to infection control measures. No sigrificant relationship was found between nurses' knowledge and their
gender, marital status and years of experience in hospital, while a significant relationship was found between
nurses' knowledge and their age, level of education, years of experience in hemodialysis unit, sharing in training
sessions and duration of training session that the nurses were engaged in it.
In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare
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