Reciprocal Teaching is an interactive method that is used to improve reading comprehension. Using this teaching strategy, teachers and students take turns leading discussions regarding sections of text using the four strategies: predicting, questioning, clarifying and summarizing. This study is an attempt to investigate the effect of using reciprocal teaching on improving female college students' achievement in reading comprehension. To fulfill the aim of the study, the researcher has adopted two null hypotheses: first, there is no significant difference between the achievement of students' who practice the reciprocal teaching technique and that of students who do not practice it. Second, there is no statistically significant difference

Background: The protective roles of vitamin C and total proteins in gingival inflammation were reported by several studies. The aim of this study was to measure the concentration of salivary vitamin C, total protein and their relation to gingival health among dental students. Materials and methods: The sample consisted of 67 dental students (33 males and 34 females) from College of Dentistry, University of Baghdad. Sillness and Löe (1964) was used for recording of dental plaque, while the gingival index (GI) was measured according to Löe and Sillness criteria (1963). Stimulated salivary samples were collected and chemically analyzed in Poisoning Center/Surgical Specialty Hospital by using colorimetric method to measure the salivary v

Background: Dental caries is generally given the highest priority in national oral health services for adult populations. Yet, there is no study which has explored the impact on quality of life specifically related to dental caries in samples of dental students. The purpose of the current study was to assess the impact of caries experience on quality of life among dental students in three governorates in Iraq. Materials and Methods: This observational study included 1364 dental students aged 18–22 years old, from three governorates. Information on quality of life was obtained from a structured, self-administered questionnaire from the students who were willing to participate in the study. The data was collected, summarized and sta

The world faces, in the last years of the last century and the beginning
of the current century i.e. the 21st century, a great expansion and a large
openness on new worlds in studies differ in their development, detection of
thinking methods and practice of mental processes.
The recent studies have proved an increase in the scientific
achievement among students through the presence of new techniques one of
which is Landa Organizing and Exploring Model concerning Physiology that
deals with various body organs.
This research aims at identifying the effectiveness of Landa Model on
the achievement of the Technical Medicine Institute students in Physiology so
as to be sure of the following nil hypothesis: there i

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.       In this research, we pr

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

A Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton