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Mindfulness and Its Relation to Self Regulated Learning Among University Students
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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.

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Publication Date
Thu Jun 01 2023
Journal Name
Ifip Advances In Information And Communication Technology
Rapid Thrombogenesis Prediction in Covid-19 Patients Using Machine Learning
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Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Machine Learning Prediction of Brain Stroke at an Early Stage
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     The healthcare sector has traditionally been an early adopter of technological progress, gaining significant advantages, particularly in machine learning applications such as disease prediction. One of the most important diseases is stroke. Early detection of a brain stroke is exceptionally critical to saving human lives. A brain stroke is a condition that happens when the blood flow to the brain is disturbed or reduced, leading brain cells to die and resulting in impairment or death. Furthermore, the World Health Organization (WHO) classifies brain stroke as the world's second-deadliest disease. Brain stroke is still an essential factor in the healthcare sector. Controlling the risk of a brain stroke is important for the surviv

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Publication Date
Sat Jan 19 2019
Journal Name
Artificial Intelligence Review
Survey on supervised machine learning techniques for automatic text classification
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Publication Date
Sun Apr 29 2018
Journal Name
Iraqi Journal Of Science
Intelligent Age Estimation From Facial Images Using Machine Learning Techniques
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     Lately, a growing interest has been emerging in age estimation from face images because of the wide range of potential implementations in law enforcement, security control, and human computer interactions. Nevertheless, in spite of the advances in age estimation, it is still a challenging issue. This is due to the fact that face aging process is not only set by distinct elements, such as genetic factors, but by extrinsic factors, such as lifestyle, expressions, and environment as well. This paper applied machine learning technique to intelligent age estimation from facial images using J48 classifier on FG_NET dataset. The proposed work consists of three phases; the first phase is image preprocessing which include

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
Heart Disease Classification–Based on the Best Machine Learning Model
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    In recent years, predicting heart disease has become one of the most demanding tasks in medicine. In modern times, one person dies from heart disease every minute. Within the field of healthcare, data science is critical for analyzing large amounts of data. Because predicting heart disease is such a difficult task, it is necessary to automate the process in order to prevent the dangers connected with it and to assist health professionals in accurately and rapidly diagnosing heart disease. In this article, an efficient machine learning-based diagnosis system has been developed for the diagnosis of heart disease. The system is designed using machine learning classifiers such as Support Vector Machine (SVM), Nave Bayes (NB), and K-Ne

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Publication Date
Sun Jan 01 2023
Journal Name
المجلة السياسية والدولية
الديمقراطية في الفكر الاسلامي المعاصر وعلاقتها بنظرية الشورى
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الديمقراطية في الفكر الاسلامي المعاصر وعلاقتها بنظرية الشورى

Publication Date
Mon Jan 01 2007
Journal Name
Journal Of Educational And Psychological Researches
الضغــــوط المهنية وعلاقتها بالتوافق المهني لــدى أســــاتذة الجـــــامعـــة
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تكمن المشكلة  في ان معظم العاملين في عصرنا الحالي يواجهون انواعا متعددة من الضغوط اثناء العمل، ولهذا يعد اتجاه العامل نحو دوره في العمل عنصر مهم في زيادة الاداء الوظيفي وتحقيق التوافق النفسي السوي للعامل داخل عمله.

ان هناك ضغوط في بيئة العمل قد تسبب الشعور بالتوتر وتكمن خطورة الضغوط في الاصابة بالاحتراق النفسي والتي تتمثل في حالات التشاؤم واللامبالاة وعدم دقة الاداء وسوء التوافق العام

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Publication Date
Sun Jan 04 2004
Journal Name
Al-academy
البنية الشكلية لتصاميم الحقائب الجلدية وعلاقتها بجذب المستهلك
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البنية الشكلية لتصاميم الحقائب الجلدية وعلاقتها بجذب المستهلك

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Publication Date
Sun Jun 06 2010
Journal Name
Baghdad Science Journal
Algebraic Coincidence Periods Of Self – Maps Of A Rational Exterior Space Of Rank 2
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Let f and g be a self – maps of a rational exterior space . A natural number m is called a minimal coincidence period of maps f and g if f^m and g^m have a coincidence point which is not coincidence by any earlier iterates. This paper presents a complete description of the set of algebraic coincidence periods for self - maps of a rational exterior space which has rank 2 .

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Publication Date
Sun Feb 10 2019
Journal Name
Iraqi Journal Of Physics
Nuclear structure study of some tin isotopes using the self-consistent mean field method
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Hartree-Fock calculations for even-even Tin isotopes using
Skyrme density dependent effective nucleon-nucleon interaction are
discussed systematically. Skyrme interaction and the general formula
for the mean energy of a spherical nucleus are described. The charge
and matter densities with their corresponding rms radii and the
nuclear skin for Sn isotopes are studied and compared with the
experimental data. The potential energy curves obtained with
inclusion of the pairing force between the like nucleons in Hartree-
Fock-Bogoliubov approach are also discussed.

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