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Formation Engineering and Pedagogy of E-Learning in Light of Corona Pandemic
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Publication Date
Mon Jan 28 2019
Journal Name
Iraqi Journal Of Science
Building a 3D Petrophysical Model for Mishrif Formation in Nasiriyah Oil Field, Southern Iraq
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A 3D geological model for Mishrif Reservoir in Nasiriyah oil field had been invented "designed" "built". Twenty Five wells namely have been selected lying in Nasiriyah  Governorate in order to build Structural and petrophysical (porosity and water saturation) models represented by a 3D static geological model in three directions .Structural model showed that Nasiriyah oil field represents anticlinal fold its length about 30 km and the width about 10  km, its axis extends toward NW–SE  with structural closure about 65 km . After making zones for Mishrif reservoir, which was divided into 5 zones i.e. (MA zone, UmB 1zone,MmB1 zone ,L.mB1 zone and mB2zone) .Layers were built for each zone depending on petrophysical propertie

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Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
The Compatibility between leadership of empowerment and organizational learning abilities and their reflection on knowledge capital Applied research at Wasit University
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The current research aims at: - Identifying the role played by the leadership in empowerment and organizational learning abilities and their reflection on the knowledge capital, and the extent to which these concepts can be applied effectively at Wasit University. The problem of research .... In a series of questions: The most important is that the dimensions leadership empowerment and distance learning organizational capacity correlation relationship and impact and significant statistical significance with the capital knowledge.

     To understand the nature of the relationship and the impact between the variables, leadership was adopted by empowerment as the fir

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Publication Date
Tue Mar 14 2023
Journal Name
Iraqi Journal Of Science
The Biological Effect of Rosmarinus officinelis L. Essential Oil on Biofilm Formation and Some Fimbrial Genes (fimH-1 and mrkD) of Klebseilla pneumoniae
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Klebseilla pneumoniae possesses many virulence factors and survival strategies to persist and overcome host defenses; one of these strategies is biofilm formation. Therefore, the aims of this study was to determine the antibacterial and antibiofilm effect of Rosmarinus officinelis L. essential oil (EO) and its effect on the genes encoding of fimbrial adhesions. The antimicrobial activity was investigated by MIC. The ability to form biofilm as well as inhibition of initial cell attachment and biofilm formation was performed. PCR was carried out to detect fimH-1 and mrkD genes of type 1 and type 3 fimbrial adhesions at different time of incubation. The study revealed that MIC value of EO was 104 μg/ml on 24 (83%) of isolates, 93% of them

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Publication Date
Mon Jun 28 2021
Journal Name
Journal Of The College Of Education For Women
Teaching Arabic to Non-Native Speakers between Communication and Pragmatics:Qualitative Approach in Light of the Common European Framework of Reference for Teaching Foreign Languages: هداية تاج الأصفياء حسن البصري
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This research is qualitative in nature. It aims to investigate descriptively, analytically, and comparatively the modern AK model represented by the Sudan Open University Series, and the European framework, the common reference for Teaching Foreign Languages, to uncover what was achieved in them in terms of communication and language use. Accordingly, an integrated, multi-media approach has been adopted to enable the production and reception activities, and the spread of Arabic in vast areas of the world. Such a spread helps Arabic language to be in a hegemonic position with the other living languages. The study is based on getting benefit from human experiences and joint work in the field of teaching Arabic to non-Arabic speakers to mee

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Publication Date
Sun Jun 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Zinc Element Traces to Inhibit Scale Formation on Cooling Tower and Air Cooler Systems
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Calcium carbonate is predominantly present in aqueous systems, which is
commonly used in industrial processes. It has inverse solubility characteristics
resulting in the deposition of scale on heat transfer surface. This paper focuses on
developing methods for inhibition of calcium carbonate scale formation in cooling
tower and air cooler system where scaling can cause serious problems, ZnCl 2 and ZnI
2 has been investigated as scale inhibitor on AISI 316 and 304. ZnCl 2 were more
effective than ZnI 2 in both systems, and AISI 316 show more receptivity to the
chlorides salt compared to AISI 304. The inhibitors were more effective in cooling
tower than air cooler system. AISI 316 show more constant inhibition effic

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Publication Date
Fri Dec 08 2023
Journal Name
Iraqi Journal Of Science
AL-Dibdiba Formation Basin Hydrological Aspects Extraction Using GIS techniques and Quantitative Morphometric Analysis
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The drainage basin's hydrological aspect studying is considered to be important issue because of their influence (especially in arid to semi-arid regions) on the water management projects, agricultural management projects, and grazing ones. The importance of this study is coming from the fact that AL-Dibdiba formation basin climate is arid to semi-arid and there are human activities (habitation and agricultural) in the east part of it, so the water resources management is needed for this basin. The morphometric analysis illustrates the hydrological aspects in a quantitative form; the problem is the use of the traditional schemes in the calculation processes (such as the topographic map and the planmeter), which coast time and money and a

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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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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Publication Date
Fri Jul 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on distributed denial of service attack detection using deep learning: A review
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Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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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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Scopus (3)
Crossref (2)
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Publication Date
Fri Mar 10 2023
Journal Name
Mathematics
Hamilton–Jacobi Inequality Adaptive Robust Learning Tracking Controller of Wearable Robotic Knee System
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A Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton

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Scopus (5)
Crossref (4)
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