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A Suggested Proposal to Activate Educational Supervision Based on Professional Learning Societies
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Professional learning societies (PLS) are a systematic method for improving teaching and learning performance through designing and building professional learning societies. This leads to overcoming a culture of isolation and fragmenting the work of educational supervisors. Many studies show that constructing and developing strong professional learning societies - focused on improving education, curriculum and evaluation will lead to increased cooperation and participation of educational supervisors and teachers, as well as increases the application of effective educational practices in the classroom.

The roles of the educational supervisor to ensure the best and optimal implementation and activation of professional learning societies are summarized as follows: spreading the culture of professional learning societies, training teachers in them, following up the application in all its stages, reviewing the interventions carried out by the school’s professional learning communities team, reviewing the results after analyzing them, and preparing improvement and improvement plans and benefit schools, and provide schools with new in professional learning communities.

Therefore, the present paper aims to highlight the importance and necessity of professional learning societies for educational supervision as an urgent necessity to develop the educational process in schools in the Sultanate of Oman, and provides a vision to activate educational supervision based on professional learning communities. The paper was launched from the global trends that call for the necessity of activating professional learning societies in the educational and supervisory process in order to develop and improve the educational process. The paper considered the principles and standards of professional learning societies. The paper adopted the case study approach to collect data and analyze it, through researchers' view and analysis of the reality and requirements of applying and activating professional learning societies between the different supervisory groups.

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Publication Date
Tue Sep 10 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
A classification model on tumor cancer disease based mutual information and firefly algorithm
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Publication Date
Thu Jan 01 2026
Journal Name
Ieee Access
SD-GPON: A Dynamic Prioritization for Efficient Traffic Management Based on Controlling DSCP
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Publication Date
Thu Jan 14 2021
Journal Name
Reviews In Inorganic Chemistry
A review on TiO<sub>2</sub>-based composites for superior photocatalytic activity
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Abstract<p>Heterogeneous photocatalysts was a promising material for removing organic pollutants. Titanium dioxide (TiO<sub>2</sub>) was a suitable photocatalyst for its cost efficiency and high stability to reduce various pollutants. Enhancing TiO<sub>2</sub> photocatalyst performance by doping with changed metals or non-metal ions and organic compounds have been reviewed. These methods could enhance photoelectrochemical activity via: (i) by a donor of electrons via electron-donor agents that would produce particular defects in TiO<sub>2</sub> structure and capture transporters of charge; (ii) by reducing recombination rate of the charge transporters and increasi</p> ... Show More
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Publication Date
Thu Jun 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A missing data imputation method based on salp swarm algorithm for diabetes disease
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Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
A Modified Symmetric Key Fully Homomorphic Encryption Scheme Based on Read-Muller Code
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Homomorphic encryption became popular and powerful cryptographic primitive for various cloud computing applications. In the recent decades several developments has been made. Few schemes based on coding theory have been proposed but none of them support unlimited operations with security.   We propose a modified Reed-Muller Code based symmetric key fully homomorphic encryption to improve its security by using message expansion technique. Message expansion with prepended random fixed length string provides one-to-many mapping between message and codeword, thus one-to many mapping between plaintext and ciphertext. The proposed scheme supports both (MOD 2) additive and multiplication operations unlimitedly.   We make an effort to prove

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Publication Date
Wed Sep 26 2018
Journal Name
Communications In Computer And Information Science
A New RGB Image Encryption Based on DNA Encoding and Multi-chaotic Maps
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Publication Date
Thu Jun 16 2022
Journal Name
Al-khwarizmi Engineering Journal
Path Planning and Obstacle Avoidance of a Mobile Robot based on GWO Algorithm
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planning is among the most significant in the field of robotics research.  As it is linked to finding a safe and efficient route in a cluttered environment for wheeled mobile robots and is considered a significant prerequisite for any such mobile robot project to be a success. This paper proposes the optimal path planning of the wheeled mobile robot with collision avoidance by using an algorithm called grey wolf optimization (GWO) as a method for finding the shortest and safe. The research goals in this study for identify the best path while taking into account the effect of the number of obstacles and design parameters on performance for the algorithm to find the best path. The simulations are run in the MATLAB environment to test the

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Publication Date
Wed Aug 28 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
A Novel Anomaly Intrusion Detection Method based on RNA Encoding and ResNet50 Model
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Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

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Publication Date
Tue Feb 01 2022
Journal Name
Civil Engineering Journal
Calibration of a New Concrete Damage Plasticity Theoretical Model Based on Experimental Parameters
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The introduction of concrete damage plasticity material models has significantly improved the accuracy with which the concrete structural elements can be predicted in terms of their structural response. Research into this method's accuracy in analyzing complex concrete forms has been limited. A damage model combined with a plasticity model, based on continuum damage mechanics, is recommended for effectively predicting and simulating concrete behaviour. The damage parameters, such as compressive and tensile damages, can be defined to simulate concrete behavior in a damaged-plasticity model accurately. This research aims to propose an analytical model for assessing concrete compressive damage based on stiffness deterioration. The prop

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Publication Date
Mon Dec 01 2014
Journal Name
2014 Ieee Symposium On Differential Evolution (sde)
Comparative analysis of a modified differential evolution algorithm based on bacterial mutation scheme
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A new modified differential evolution algorithm DE-BEA, is proposed to improve the reliability of the standard DE/current-to-rand/1/bin by implementing a new mutation scheme inspired by the bacterial evolutionary algorithm (BEA). The crossover and the selection schemes of the DE method are also modified to fit the new DE-BEA mechanism. The new scheme diversifies the population by applying to all the individuals a segment based scheme that generates multiple copies (clones) from each individual one-by-one and applies the BEA segment-wise mechanism. These new steps are embedded in the DE/current-to-rand/bin scheme. The performance of the new algorithm has been compared with several DE variants over eighteen benchmark functions including sever

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