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.
Objective(s): To assess the level of depression and anxiety among school age children with acute lymphoblastic leukemia under chemotherapy treatment and to find out the relationship between the level of depression and anxiety among the affected children and their demographic characteristics.
Methodology: A cross-sectional study was conducted on school age children both gender having acute lymphoblastic leukemia under chemotherapy treated and their age between 6 years to 12 years. The study started from the period of September, 19th 2020 to March,1st 2021. Non-probability (Purposive) sample of (114) children with acute lymphoblastic leukemia under chemotherapy was selected in attending hospital wards, outpatient and counseling clinics
Social Networking has dominated the whole world by providing a platform of information dissemination. Usually people share information without knowing its truthfulness. Nowadays Social Networks are used for gaining influence in many fields like in elections, advertisements etc. It is not surprising that social media has become a weapon for manipulating sentiments by spreading disinformation. Propaganda is one of the systematic and deliberate attempts used for influencing people for the political, religious gains. In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms. Data was collected from the news sources from July 2018-August 2018. After annota
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Television white spaces (TVWSs) refer to the unused part of the spectrum under the very high frequency (VHF) and ultra-high frequency (UHF) bands. TVWS are frequencies under licenced primary users (PUs) that are not being used and are available for secondary users (SUs). There are several ways of implementing TVWS in communications, one of which is the use of TVWS database (TVWSDB). The primary purpose of TVWSDB is to protect PUs from interference with SUs. There are several geolocation databases available for this purpose. However, it is unclear if those databases have the prediction feature that gives TVWSDB the capability of decreasing the number of inquiries from SUs. With this in mind, the authors present a reinforcement learning-ba
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Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed
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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho
... Show MoreIn this study, the effect of the combination of micro steel fibers and additives (calcium hydroxide and sodium carbonate) on the size of cracks formation and healing them were investigated. This study aims to apply the use of self-healing phenomenon to repair cracks and to enhance the service life of the concrete structures. Micro steel fibers straight type were used in this research with 0.2% and 0.4% by volume of concrete. A weight of 20 and 30 kg/m3 of Ca(OH)2 and 2 and 3 kg/m3 of Na2CO3 were used as a partial cement replacement. The results confirm that the concrete cracks were significantly self-healed up to 30 days re-curing. Cracks width up to 0.2 mm were comp
... Show MoreTransparent nano- coating was prepared by Sol-Gel method from titanium dioxide TiO2 which has the ability to self-cleaning coating used for hospitals, laboratories, and places requiring permanent sterilization. Three primary colors are selected (red, blue, and yellow) as preliminary study to the effect of these colors on the nano-coating. Three traditional oil paints color were used as base, then coated by a layer of TiO2-Sol and deposited on the paints. The optical properties of TiO2-Sol were measured; the maximum absorption wavelength at (λmax=387 nm), the refractive index (n=1.4423) and the energy band gap (Eg=3.2 eV). The structure properties found by X-ray diffraction of TiO
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
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