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jcoeduw-107
The Separation Worry and its Correlation with Working Memory of the Primary School Pupils
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The concept of the separation worry is considered one of the common disorders in children. The causes and effects of this worry influence the child mental and cognitive ability and the child ability to communicate with others, has friendship and the ability of adaptive with the environment, peers and teachers and it also influences the child's academic and social performance.
The importance of this study is represented in handling the working memory, one of important subject in cognitive psychology. Many universal studies show that the working memory is very important in several daily functions such as continuous attention, followinstructions, implement instructions of many steps, the moment of information remembering and keep focusing.
Working memory is an important cognitive variable that is influenced in many problems and disorders the children faced. Therefore, the relationship between the separation worry and working memory should be explored.
The present study aimed to identify the separation anxiety in working memory and its relationship to the primary school pupils, For achieving these aims the researcher constructs a worry separation scale depending on Bowlby's perspective for this concept. She also adopts the working memory scale, constructed by Abd alwahed (2005), the researcher finds out the validity of both scales and the reliability of the separation worry scale and then she analyzes statistically the items of separation worry scale on sample of (400) pupils. Finally, both scales have been administered on (150) pupils from Baghdad primary schools/ Karkh and Rusafa, selected by using random stratified sampling. The results of the study show that:
1. The primary school pupils have separation worry.
2. The level of aural storing period is higher than the level of the aural capacity for the working memory and the level of visual capacity is higher than the visual storing period for the working memory of the primary school pupils.
3. There is grouping from being far from mother according to the separation worry predictions at working memory aural capacity of the primary school students.
4. There is grouping from being far from mother and physical symptoms according to the separation worry predictions the working memory aural storing period of the primary school students.
5. There is grouping from being far from mother, physical symptoms, and the child fears according to the separation worry predictions at working memory visual capacity of the primary school students.
6. There is grouping from being far from mother, physical symptoms and the child fears according to the separation worry predictions at working memory visual storing period of the primary school students.

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Publication Date
Tue Mar 14 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Genetic Diversity of Iraqi Barley Species Differing in Their Tolerance to Drought by RAPD Analysis
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The genetic diversity was studied in sixteen barley Hordeum vulgar L. species cultivated in Iraq , which are differ in their ability to drought stress tolerance by using random amplified polymorphic DNA polymerase chain reaction (RAPD - PCR ) .Barley species was evaluated to drought stress  after treatment the plant seedling at germination stages to different concentration of polyethylene glycol (PEDG6000) . The results showed that the Broaq and Arefat species have the highest tolerance to drought stress in contrast the rest of Barly species like Alkhair, Alwarkaa, Ebaa99, Shoaa, Alrafidain,Sameer Rehana 3 , forat9 , jazeral ,and ebaa7 revealed sensitivity to drought stress .      The primes which used RAPD technique

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Publication Date
Sat Apr 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Improvement of noisy images filtered by bilateral process using a multi-scale context aggregation network
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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

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Publication Date
Mon Nov 26 2018
Journal Name
Indian Journal Of Agricultural Research
Effect of seed weight on stem anatomical characters in white lupine (Lupinus albus L.) cultivars
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An anatomical study was carried out at the College of Agricultural Engineering Sciences, University of Baghdad, in 2017, on lupine crop (Lupinus albus) as a comparison guide of three seed weights of three lupine cultivars viz. ‘Giza-1’, ‘Giza-2’ and ‘Hamburg’. The nested design was used with four replications. The results showed that cultivars had a significant effect on stem anatomical traits. ‘Hamburg’ cultivar recorded the highest stem diameter, cortex thickness and xylem vascular diameter, while cultivar ‘Giza-1’ recorded the lowest values for the same traits as well as the highest collenchyma layer thickness, vascular bundle thickness, and xylem thickness. Cultivar ‘Giza-2’ recorded the lowest vascular b

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Publication Date
Fri Mar 01 2024
Journal Name
Water, Air, & Soil Pollution
Decontamination of Cobalt-Polluted Soils Using an Enhanced Electro-kinetic Method, Employing Eco-friendly Conditions
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Publication Date
Thu Oct 15 2015
Journal Name
International Journal Of Computer Applications
Experimental Investigation for Small Horizontal Portable Wind Turbine of Different Blades Profiles under Laboratory Conditions
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Experimental investigation for small horizontal portable wind turbine (SHPWT) of NACA-44, BP-44, and NACA-63, BP-63 profiles under laboratory conditions at different wind velocity range of (3.7-5.8 m/s) achieved in present work. Experimental data tabulated for 2, 3, 4, and 6- bladed rotor of both profiles within range of blade pitch angles . A mathematical model formulated and computer Code for MATLAB software developed. The least-squares regression is used to fit experimental data. As the majority of previous works have been presented for large scale wind turbines, the aims were to present the performance of (SHPWT) and also to make a comparisons between both profiles to conclude which is the best performance. The overall efficiency and el

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Publication Date
Wed Oct 31 2018
Journal Name
Heat Transfer-asian Research
Comparative study on heat transfer enhancement of nanofluids flow in ribs tube using CFD simulation
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Publication Date
Fri Jul 01 2022
Journal Name
Journal Of Oral And Maxillofacial Surgery, Medicine, And Pathology
Rhinocerebral mucormycosis: An Iraqi experience of 16 consecutive cases followed up for up ten years
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Publication Date
Thu May 23 2019
Journal Name
The International Journal Of Artificial Organs
Real-time classification of shoulder girdle motions for multifunctional prosthetic hand control: A preliminary study
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In every country in the world, there are a number of amputees who have been exposed to some accidents that led to the loss of their upper limbs. The aim of this study is to suggest a system for real-time classification of five classes of shoulder girdle motions for high-level upper limb amputees using a pattern recognition system. In the suggested system, the wavelet transform was utilized for feature extraction, and the extreme learning machine was used as a classifier. The system was tested on four intact-limbed subjects and one amputee, with eight channels involving five electromyography channels and three-axis accelerometer sensor. The study shows that the suggested pattern recognition system has the ability to classify the sho

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Tue Jan 31 2023
Journal Name
Iraqi Geological Journal
Geological Model for Jeribe/Euphrates Formation, Tertiary Reservoir in Qaiyarah Oil Field, North of Iraq
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Visualization of subsurface geology is mainly considered as the framework of the required structure to provide distribution of petrophysical properties. The geological model helps to understand the behavior of the fluid flow in the porous media that is affected by heterogeneity of the reservoir and helps in calculating the initial oil in place as well as selecting accurate new well location. In this study, a geological model is built for Qaiyarah field, tertiary reservoir, relying on well data from 48 wells, including the location of wells, formation tops and contour map. The structural model is constructed for the tertiary reservoir, which is an asymmetrical anticline consisting of two domes separated by a saddle. It is found that

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