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jperc-1073
King Khalid University towards Strategies Compatible with Brain-Based Learning (BBL)
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The study aimed to reveal the level of knowledge and tendencies of high- study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with brain-based learning (BBL). And Then, putting a proposed concept to develop knowledge and tendencies of high-study students specializing in curriculum and teaching methods at King Khalid University towards harmonious strategies with Brain-based learning (BBL). For achieving this goal, a cognitive test and a scale of tendency were prepared to apply harmonious strategies with brain-based learning. The descriptive approach was used because it suits the goals of the study. The study sample consisted of (70) male and female students of postgraduate students (MA and Ph.D.) who are attending regularly at the Department of Curriculum and Teaching Methods for the academic year 1440/1441 AH. The study has shown a lot of results, the most important one is that the cognitive level and tendency to apply for postgraduate students (MA and Ph.D.) specializing in curriculum and teaching methods for harmonious strategies with brain-based learning principles was Average, and there are statistically significant differences at the level of significance (0.05) between the average of postgraduate students’ degrees in the cognitive level and the tendency towards applying harmonious strategies with brain-based learning which due to the difference in the academic degree, and in the light of the results of the study. A proposed concept was developed to enhance the knowledge and tendencies of postgraduate students specializing in curriculum and teaching methods at King Khalid University for the harmonious strategies with brain-based learning (BBL). The study was ended with a set of suggested recommendations that would activate the use of the harmonious strategies with brain-based learning.

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Publication Date
Thu Jul 30 2020
Journal Name
Journal Of Sustainability Science And Management
THE DIFFERENTIATION IN WORK ENRICHMENT STRATEGIES AND ORGANIZATIONAL CREATIVITY FUNCTION: A PERSPECTIVE FROM THE LEADERS OF THE MINISTRY OF OIL IN IRAQ
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Publication Date
Tue Nov 09 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Financial technology as one of the recovery strategies of the Iraqi banking sector in the post-Covid-19 stage: An exploratory study
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The research aims to employ one of the most important strategies for recovery from the crisis of the Covid-19 pandemic, which ravaged the economies of the entire world and its various sectors, including the banking sector, through financial technology that is based on digital transformation to achieve financial sustainability and the creation of innovative financial value chains in light of the decline in the banking sector as a result of The negative effects of the Covid-19 pandemic, be guided by the relevant international accounting standards to control the risks associated with financial technology. To recover from the Covid-19 crisis, the research came out with a set of recommendations, most notably financial technology from

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Publication Date
Thu Aug 01 2024
Journal Name
Advances In Science And Technology Research Journal
Power Predicting for Power Take-Off Shaft of a Disc Maize Silage Harvester Using Machine Learning
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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
اثر استخدام دورة التعلم في تحصیل طالبات مرحلة الرابع العام للمعلومات الفیزیائیة واستبقائھا
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This research aims to reveal the impact of applying a teaching course in
gaining and preserving information by female students comparing with the
traditional method, through testing the two following hypotheses:
1. There is no difference with statistical significance at the level of
significance (0.05) between the average grades achieved by the
experimental group of female students taught using a teaching course,
and the control group of female students taught using the traditional
method.
2. There is no difference with statistical significance at the level of
significance (0.05) between the average grades achieved by the
experimental group of female students taught using a teaching course,
and the contro

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Preparation-and Spectroscopic Characterization of Transition Metal Complexes with Schiff base 2-[1-(1H-indol-3-yl)ethylimino) methyl]naphthalene-1-ol
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The ligand 2-[1-(1H-indol-3-yl)ethylimino) methyl]naphthalene-1-ol, derived from 1-hydroxy-2-naphthaldehyde and 2-(1H-indol-3-yl)ethylamine, was used to produce a new sequence of metal ions complexes. Thus ligand reactions with NiCl2.6H2O, PdCl2, FeCl3.6H2O and H2PtCl6.6H2O were sequentially made to collect mono-nuclear Ni(II), Pd(II), Fe (III), and Pt(IV). (IR or FTIR), Ultraviolet Reflective (UV–visible), Mass Spectra analysis, Bohr-magnetic (B.M.), metal content, chloride content and molar conductivity have been the defining features of the composites. The Fe(III) and Pt(IV) complexes have octahedral geometries, while the Ni(II) complex has tetra

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Face Recognition and Emotion Recognition from Facial Expression Using Deep Learning Neural Network
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Abstract<p>Face recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.</p>
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Publication Date
Thu Mar 02 2023
Journal Name
Applied Sciences
Machine Learning Techniques to Detect a DDoS Attack in SDN: A Systematic Review
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The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach

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Publication Date
Thu Sep 01 2016
Journal Name
2016 8th Computer Science And Electronic Engineering (ceec)
Class-specific pre-trained sparse autoencoders for learning effective features for document classification
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Publication Date
Thu Jan 20 2022
Journal Name
Webology
Information Sources and their Role in E-learning from Iraqi College Students’ Viewpoint
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The study aims at identifying the sources of information and explaining their role in e-learning from the viewpoint of the Iraqi college students. The researchers relied on the descriptive method of the survey method to collect data and know the point of view of undergraduate students from the Department of Information in the College of Arts / Tikrit University and the Department of Quranic Studies at the College of Arts / University of Baghdad. The questionnaire was used as an instrument of the study, the research sample is (120) students; each section has (60) male and female students. The study concluded that there are many types and forms of information sources that students receive through electronic educational platforms from text con

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Geological Journal
Evaluating Machine Learning Techniques for Carbonate Formation Permeability Prediction Using Well Log Data
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Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

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