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jeasiq-648
The Philosophy of Organizational Forgetting In Frame of Learning and Organizational knowledge
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current research aims to build an intellectual framework for concept of organizational forgetting, which is considered one of the most important topics in contemporary management thought, which is gain the consideration of most scholars and researchers in field of organizational behavior, which is to be a loss of intentional or unintentional knowledge of any organizational level. It turned out that just as organizations should learn and acquire knowledge, they must also forget, especially knowledge obsolete and worn out. And represented the research problem in the absence of Arab research dealing with organizational forgetting, and highlights the supporting infrastructure core, and show a close relationship with organizational learning and knowledge, and thus contributing to the embodiment of its contents in our organizations Arabic, which is the latest gap caused the omission of one of the vital topics in the field of organization theory and organizational behavior. And then rising of necessity to exploring the hidden aspects of the topic, to The review search method adopted in the methodology through the analysis of the relevant literature through three chapters, the research found a set of conclusions and recommendations that can help the Arab Director in the adoption of this concept and considered it as business philosophy in managing of his organization

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Publication Date
Wed Apr 16 2025
Journal Name
International Journal Of Engineering Pedagogy (ijep)
Utilizing Machine Learning Techniques to Predict University Students' Digital Competence
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Given the importance of possessing the digital competence (DC) required by the technological age, whether for teachers or students and even communities and governments, educational institutions in most countries have sought to benefit from modern technologies brought about by the technological revolution in developing learning and teaching and using modern technologies in providing educational services to learners. Since university students will have the doors to work opened in all fields, the research aims to know their level of DC in artificial intelligence (AI) applications and systems utilizing machine learning (ML) techniques. The descriptive approach was used, as the research community consisted of students from the University

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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials & Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Sat Nov 02 2019
Journal Name
Advances In Intelligent Systems And Computing
Modified Opposition Based Learning to Improve Harmony Search Variants Exploration
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Publication Date
Sat Jan 19 2019
Journal Name
Artificial Intelligence Review
Survey on supervised machine learning techniques for automatic text classification
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Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for</p> ... Show More
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Publication Date
Wed Dec 30 2015
Journal Name
College Of Islamic Sciences
Development and innovation in the theory of singing   In the Umayyad era
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The Umayyad era is characterized by the diversity of the subjects and their multiplicity in the literary phenomena. These phenomena are singing phenomena, although they were known in previous eras, they took a distinctive form in the era.
  In this light, the researcher tried to prove that singing theory in the Umayyad period was characterized by development and renewal. The research was entitled (evolution and renewal in the theory of singing in the Umayyad era).

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Publication Date
Mon Sep 30 2019
Journal Name
College Of Islamic Sciences
Loqmania commandments in the Koran And its impact in the refinement of the doctrine and morals emerging
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Luqman's story stated that human instinct, if I was brought up properly, reaches wisdom and inflicts the right to everything. It is to go to worship God and adhere to the satisfaction of morals and high morals that are ordered to meet among human beings in this life, because this worship educates in the soul the most beautiful morals needed by human beings of honesty, honesty and modesty, and the work of good and virtues, and distancing the soul from evil and vices.

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Publication Date
Mon May 30 2022
Journal Name
Pakistan Journal Of Medical And Health Sciences
Nurses' Knowledge Toward Continuous Positive Airway Pressure Machine at Respiratory Isolation Unit
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Background: For patients with coronavirus disease(COVID-19), continuous positive airway pressure (CPAP) has been considered as a useful treatment. The goal of CPAP therapy is to enhance oxygenation, relieve breathing muscle strain, and maybe avoid intubation. If applied in a medical ward with a multidisciplinary approach, CPAP has the potential to reduce the burden on intensive care units. Methods: Cross-sectional design was conducted in the ALSHEFAA center for crises in Baghdad. Questionnaire filled by 80 nurses who work in Respiratory Isolation Unit who had chosen by non-probability (purposive) selection collected the data. Then the researcher used an observational checklist to evaluate nurses’ practice. The data was analyzed us

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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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