Objectives of the study: The main objective of the study is to assess the prevalence of hypertension among
cardiac diseases patients and to fiend out relation ship between hypertension and cardiovascular diseases.
Methodology: A descriptive study, using interviewer and questionnaire technique was conducted on cardiac
diseases inpatients of clinic unite at Kirkuk and Azady hospitals from 17th ,June ,2012 to 1st, March , 2013.
Non – probability (purposive) sample of (148) adult patients, (81) females and (67) males with heart disease are
selected from inpatients of clinic unite at Kirkuk and Azady hospitals at kirkuk city. Questionnaire was
developed to assess the items which are related to heart disease patient's (Disease, Signs and Symptoms ,
Antihypertensive Drugs , Blood Pressure , and Dietary Patterns). A calibrated mercury sphygmomanometer was
used to measure BP while the individual was seated and resting five minutes with the arm held at heart level. The
first reading were taken in both arms; unless there was a significant difference, the right arm was used for
subsequent reading. The mean of two consecutive measurements taken at two-minute intervals was recorded.
Weight was measured using a calibrated scale . The study instruments consist of total (44) items, which are
distributed though the following : Demographic data form consist of (10) items and questionnaire was
concerned with data to evaluate the criteria of cardiac diseases patients form consist of (34) items.
Results: The results of this study revealed that the mean age and standard division of study sample is
(63.1 11.3), the highest percentage 52(35.1%) of age factor for heart disease patients are reported at (70-79yrs.)
group .The majority of study sample are females 81( 54.7%), whereas, males are 67( 45.3%). High percent
46(31%)of participants are suffering from angina and 44(29.7%) had myocardial infarction. 40(27%) of the
patients had Prehypertension (120-139/60-100) while 29(19.6%) of patients had first stage of hypertension.
Recommendations : Educational programs should be designed to increase people knowledge and awareness
about the life style of hypertensive heart disease patients. Booklet should be prepared and presented to the
patients to advise them to leave high amount salt intake, give up exercise which is considered one of the
contributing factors for hypertension.
Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD
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One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th
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Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob
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The aim of this study is to uncover the views of female students of Shaqra University towards midterm tests. A survey of (42) items distributed in three fields. The study has been applied to a random sample of (421) students from two faculties. The results showed that all three fields have achieved an intermediate level. The results also indicated that there were no statistically significant differences in students’ views of midterm tests due to the specialization or academic level variables.
Background: To evaluate the bony supports of the teeth adjacent to the area of cleft in patient with unilateral cleft lip and palate and to compare these measurements with the measurements of the same teeth in non-cleft side by using CBCT. Materials and methods: The CBCT scans of 30 patients having cleft lip( unilateral) and palate(unilateral), were analyzed and the measurements of the alveolar bony support for teeth that are adjacent to the cleft area were measured with those teeth located on opposite side (non- clef) side. For each tooth, the measurements will taken for the distance between the( cementoenamel junction) (CEJ) and the bony crest (AC) at the( buccal area) was measured and the thickness of the buccal plate At zero, one, tw
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In this study, phosphorescence analysis (KPA) is used for determining soil collected from the Tigris River from Al- Karrada and Bab Al-Sharq in Baghdad and samples were taken from rainwater collected from Al-Rashad, Al-Obeidi, Al-Dora and Al-Sadr City in Baghdad. The measurements were carried out by the Iraqi Ministry of Health and Environment, in the Radiation Protection Center. The collection, removal and evaporation of the samples ranged from January to the end of March 2018. The results show the presents of concentration of 238U and 235U in soil samples and the rainwater samples. The conclusion of this work is the concentration of uranium in soil samples is more than recommendations by ICRP value of 1.9 μg /l. While all water sample
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