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 b

Objective: The purpose of this study was to determine the association between caries related microorganisms in children’s saliva, such as Streptococcus mutans and lactobacilli, and their demographic factors. Methods: This study involved a sample of 135, both sexes with an age range between 3 and 10 years. Unstimulated saliva was obtained and diluted in normal saline. Saliva was then placed in selective media. Salivaris agar was used for mutans streptococci while Rogosa agar for lactobacilli. After incubation, Streptococcus mutans counting of CFU (colony forming units) with morphology characterization and numbers of CFU per milliliter of saliva for lactobacilli. Demographic factors information was collected using a questionnaire.

Abstract

     In this research, a study of the behavior and correlation between sunspot number (SSN) and solar flux (F10.7) have been suggested. The annual time of the years (2008-2017) of solar cycle 24 has been adopted to make the investigation in order to get the mutual correlation between (SSN) and (F10.7). The test results of the annual correlation between SSN & F10.7 is simple and can be represented by a linear regression equation. The results of the conducted study showed that there was a good fit between SSN and F10.7 values that have been generated using the suggested mutual correlation equation and the observed data.

Background: A carefully planned clinical medical education is critical for the provision of supportive clinical educational environment. The latter will ensure effective teaching, active learning and good attitudes and performance at the bedside. The aim of this study was to evaluate clinical learning environment at AL-Diwaniyah Teaching Hospital. Materials and Methods: A descripitive cross-sectional study involved resident doctors from Internal Medicine and Surgery departments who had six months or more residency training in the respective departments. Data were collected using the Postgraduate Hospital Educational Environment Measure. Data where analyzed using the Statistical Package for Social Sciences version 21.0 and presented us

Image processing applications are currently spreading rapidly in industrial agriculture. The process of sorting agricultural fruits according to their color comes first among many studies conducted in industrial agriculture. Therefore, it is necessary to conduct a study by developing an agricultural crop separator with a low economic cost, however automatically works to increase the effectiveness and efficiency in sorting agricultural crops. In this study, colored pepper fruits were sorted using a Pixy2 camera on the basis of algorithm image analysis, and by using a TCS3200 color sensor on the basis of analyzing the outer surface of the pepper fruits, thus This separation process is done by specifying the pepper according to the color of it

Medical images play a crucial role in the classification of various diseases and conditions. One of the imaging modalities is X-rays which provide valuable visual information that helps in the identification and characterization of various medical conditions. Chest radiograph (CXR) images have long been used to examine and monitor numerous lung disorders, such as tuberculosis, pneumonia, atelectasis, and hernia. COVID-19 detection can be accomplished using CXR images as well. COVID-19, a virus that causes infections in the lungs and the airways of the upper respiratory tract, was first discovered in 2019 in Wuhan Province, China, and has since been thought to cause substantial airway damage, badly impacting the lungs of affected persons.

In this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between every

In this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between ev