Mindfulness is considered a process to draw an image of the active event and to creat new social varieties which leaves the individuals open to modernity and to be sensitive towards the context. in contrast, when individuals act with less attention, they need to be more determined concerning the varieties and events of the past . and as a result , they become unaware of the characteristics that creat the individual condition .The problem of the current study is represented in asking about the nature of the possible relationship between mindfulness and self-regulated learning within specific demographic frame of an importantsocial category represented in university students where no previous researches nor theories have agreed on the nature of the relationship between those 2 variables. and no local study-as far as the researcher concerned-has tackled this vital topic within this wide and important class of the society which is the youth .
The objectives of the study is as the following:
1- Measuring mindfulness in the study in a sample and to enhance its statistical significance.
2- Measuring mindfulness according to the variables of gender (male-female) and academical disciplines (humanities-sciences) and to enhance their statistical significance.
3 - to identify the nature of the relationship between mindfulness and self-regulated learning in the study sample and to enhance its statistical significance.
The study sample is consisted of 400 male and female student selected randomly from 8 colleges in University of Baghdad,4 humanities colleges and 4 sciences colleges.and in order to achieve the objectives of the study,a measurement tool for mindfulness has been prepared in light of the measurements,literary references and previous studies that addressed this variable.and after analyzing the paragraphs using the 2 extreme groups method and the relation of the paragraph degree with the total degree of the measurement tool,all of its 25 paragraphs have been approved which scored stability factor average of (0,71) according to the split-half method and (0,82) according to Cronbach alfa method.and for the second variable,self-regulated learning,the researcher used the self-regulated learning measurement tool which was prepared by Al-Suraifi in 2008.which contains 39 paragraphs in its final form.and its stability was extracted by split-half method with average of (0,85) and Cronbach alfa method (0,93).
And heres the summary of the study outcomes :
1-the current study sample have mindfulness
2-there are no differences in mindfulness among university students in terms of the variable of gender (male-female) and academical disciplines (humanities-sciences) and the reaction between them .
3- there is a positive relationship between mindfulness and self-regulated learning in which as self-regulated learning increases,mindfulness increases within university students .
And the study concluded with a number of conclusions and recommendations and proposals.
Conservation of Concept among Children: Semantic Study
Background: Intestinal infections are frequently occur among children with cancer who receive chemotherapy. On the other hand, diarrhea is especially common and severe among cancer patients that develop neutropenia, either due to the disease itself or due to the intensive chemotherapy. There are many causes of diarrhea among those patients, but intestinal infections still an important etiology among them.
Objectives: to study the frequency of diarrhea among neutropenic children, with its infectious etiologies, especially the bacterial, fungal and parasitic causes.
Type of the study:Cross-sectional study.
Methods: the study was done in the Oncology
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KE Sharquie, GA Ibrahim, AA Noaimi, HK Hamudy, Journal of the Saudi Society of Dermatology & Dermatologic Surgery, 2011 - Cited by 16
KE Sharquie, HR Al-Hamami, IK Sharquie, AA Noaimi, HM Al-Karawy, Iraqi Postgraduate Medical Journal, 2013
This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce
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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.
 
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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
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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
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The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone
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