The study aims at explaining the extent to which the principles of educational management reform contribute to Ibn Ashour in achieving educational management reform and the extent to which the pillars of the Kingdom's Vision 2030 in the field of Education in achieving the educational management reform. The study also aims to provide a future vision of what the educational administrative reform and its results should be in the Kingdom during the next ten years. To achieve the goals of the study, the researcher followed two approaches: on the theoretical side, he relied on applying the content analysis method. As for the applied side, the researcher adopted the Delphi method by two questionnaires to ask (36) participants from the experts and specialists. The results revealed that there is a consensus between the principles of educational administrative reform in Ibn Ashour and the pillars of Saudi Arabia’s Vision 2030 by Expert view. Moreover, there is future feasibility for the educational administrative reform in accordance with the principles of the educational administrative reform at Ibn Ashour and the pillars of Saudi Arabia's vision 2030 from the expert point of view. The study recommended that Ibn Ashour's vision for educational reform be included in the frameworks and references of the vision in the field of education development, and research on the possibility of benefiting from the application of a way and procedures to achieve the future vision that Presented by the study, and its transformation from the theoretical to the practical and applied levels.
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<p>Energy and memory limitations are considerable constraints of sensor nodes in wireless sensor networks (WSNs). The limited energy supplied to network nodes causes WSNs to face crucial functional limitations. Therefore, the problem of limited energy resource on sensor nodes can only be addressed by using them efficiently. In this research work, an energy-balancing routing scheme for in-network data aggregation is presented. This scheme is referred to as Energy-aware and load-Balancing Routing scheme for Data Aggregation (hereinafter referred to as EBR-DA). The EBRDA aims to provide an energy efficient multiple-hop routing to the destination on the basis of the quality of the links between the source and destination. In
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This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used.
Experimental results shows LPG-
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The design, synthesis, and characterization of a star shaped 2,4,6-tris-(4`-carboxyphenoxy)-1,3,5-triazine liquid crystalline with columnar discotic mesophase properties establish H-bond interactions with 3,5-dialkoxypyidine were reported. The structures of the synthesized compounds were actually determined by elementary analysis, and FT-IR, ¹HNMR, ¹³CNMR, and mass spectroscopy. The mesomorphic properties of these mesogens were examined using differential scanning calorimetry (DSC) and optical polarizing microscopy (OPM). The synthesized molecules exhibited enantiotropic hexagonal columnar liquid crystal, which depends for the H- bond complex in a 1:3 ratio.
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The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com
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