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Comparison of the performance of some r- (k,d) class estimators with the (PCTP) estimator that used in estimating the general linear regression model in the presence of autocorrelation and multicollinearity problems at the same time "
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In the analysis of multiple linear regression, the problem of multicollinearity and auto-correlation drew the attention of many researchers, and given the appearance of these two problems together and their bad effect on the estimation, some of the researchers found new methods to address these two problems together at the same time. In this research a comparison for the performance of the Principal Components Two Parameter estimator (PCTP) and The (r-k) class estimator and the r-(k,d) class estimator by conducting a simulation study and through the results and under the mean square error (MSE) criterion to find the best way to address the two problems together. The results showed that the r-(k,d) class estimator is the best estimator.

 

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Publication Date
Mon Jul 01 2013
Journal Name
Journal Of Engineering
Water Hammer Arresters; Review Studies and Practical Experiments for Alternatives
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The current research deals with practical studies that explain to the Iraqi consumer multiple instances about the phenomenon of water hammer which occur in the water pipeline operating with pressure. It concern a practical study of the characteristics of this phenomenon and economically harmful to the consumer the same time. Multiple pipe fittings are used aimed to reduce this phenomenon and its work as alternatives to the manufactured arresters that used to avoid water hammer in the sanitary installations, while the consumer did not have any knowledge as to the non-traded for many reasons, including the water pressure decreases in the networks and the use of consumer pumps to draw water directly from the network. Study found a numbe

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Publication Date
Wed Jul 02 2014
Journal Name
Journal Of The Faculty Of Medicine
Unintended durotomy during degenerative lumbar Spine surgery (Incidence and management
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AW Tarik, AW Ali T, A Salah, Journal of faculity of medicine Baghdad university, 2014 - Cited by 3

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Publication Date
Thu Dec 15 2016
Journal Name
Research Journal Of Applied Sciences, Engineering And Technology
Building Words Dictionary List Using Symbol Enumeration and Hashing Methodology
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Publication Date
Tue Dec 28 2021
Journal Name
2021 2nd Information Technology To Enhance E-learning And Other Application (it-ela)
Pedestrian and Objects Detection by Using Learning Complexity-Aware Cascades
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Publication Date
Wed Jul 16 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Periodontal health and salivary Interleukin -6 among preterm postpartum women
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Background: Hormonal changes during pregnancy have been suggested to predispose women to gingivitis. Furthermore, advance periodontal infection in pregnant women may pose a threat to the placenta and uterus and may increase the like hood of preterm delivery. The aim of this study was to investigate the effect of salivary interleukin -6 (IL-6) level and periodontal health among preterm postpartum women. Materials and Methods: Salivary samples were taken from 33 preterm postpartum women (study group) and 33 full term postpartum women (control group). The supernatant salivary samples were assayed using atomic absorption spectrophotometer. Plaque, calculus and gingival indices were used for recording the oral hygiene and gingivitis also probing

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Publication Date
Wed Jan 01 2020
Journal Name
International Conference Of Numerical Analysis And Applied Mathematics Icnaam 2019
Isolation and characterization study towards microbial improved oil recovery applications
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Publication Date
Tue Jan 07 2020
Journal Name
International Journal Of Research In Pharmaceutical Sciences
Fifth stage pharmacy students’ knowledge and perceptions about generic medicines
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The aim of the current study was to evaluate the knowledge and perception of the fifth stage pharmacy students (college of pharmacy/ University of Baghdad /Iraq) regarding generic medicines. This study is a cross-sectional study carried in a college of pharmacy /University of Baghdad during the period from (November 2018- March 2019). The number of students included in the current study was 168 undergraduate stager pharmacists. A questionnaire was used to collect data of the study. Nearly 86% of the students said that they had heard of generic and brand medicines, and pharmacy was the main source of knowledge regarding generic medicines (66.7%).  About (33.3%) of the respondents agreed that generic medicines are bioequivalent to br

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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Publication Date
Wed Dec 30 2015
Journal Name
College Of Islamic Sciences
Al-Hafizh Abdan al-Ahwazi, 306 And his modern efforts
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Abadan, one of the modernists, is the critics, whose words depend on the wound, the modification and the ills of the hadeeth.
He lived Abadan, age in the request to talk and take the elders, and Awali, and attribution, which affected him by taking, and update about (300) Sheikh or more.
Abadan also excelled in the novel and its origins, which made students talk to him, and ask for the novel, with his hardness and hardship. As we will see in the folds of the search

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Publication Date
Thu Mar 13 2025
Journal Name
Academia Open
Deep Learning and Fusion Techniques for High-Precision Image Matting:
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General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

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