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jperc-1098
The Integration of international issues in Saudi social studies and citizenship books in the light of international education principles
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The study aimed to reveal the level to which the international issues are integrated into the books of Saudi public education social studies and citizenship in the light of the principles of international education, and to know the level of continuity and integration of these issues in the books, to build a range and sequence matrix of international issues through it. The study followed the descriptive and analytical method that used the content analysis card as a tool for study when the tool achieved the necessary validity and reliability characteristics. The data of this study has been processed using the SPSS statistical program according to a set of appropriate methods of descriptive and inferential statistics.

 The results of the study have come up with a list consisting of (143) international issues, distributed in (9) fields. The results of the content analysis revealed a sharp, unbalanced, and uneven decrease in the inclusion of international issues in the books of social studies and citizenship curricula, as inclusion was limited to (29) issues, and by a rate of (20%) in all fields of study. A wide disparity emerged between the areas of international issues in the level of sequence in those books, as they ranged between (1.25% - 36.57%), with a total sequence level (30%). There was also a lack of integration between the areas of international issues in these books, with a value (42) according to the Chi-squared test, which is a statistically insignificant value at the significance level of (0.5≥a). Accordingly, a model for the range and sequence matrix of international issues is designed in these books in light of the principles of international education. Depending on the results of the study, appropriate recommendations and suggistions were submitted.

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Publication Date
Thu Jul 31 2025
Journal Name
Computers, Materials & Continua
A Secure Audio Encryption Method Using Tent-Controlled Permutation and Logistic Map-Based Key Generation
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The exponential growth of audio data shared over the internet and communication channels has raised significant concerns about the security and privacy of transmitted information. Due to high processing requirements, traditional encryption algorithms demand considerable computational effort for real-time audio encryption. To address these challenges, this paper presents a permutation for secure audio encryption using a combination of Tent and 1D logistic maps. The audio data is first shuffled using Tent map for the random permutation. The high random secret key with a length equal to the size of the audio data is then generated using a 1D logistic map. Finally, the Exclusive OR (XOR) operation is applied between the generated key and the sh

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Publication Date
Tue Sep 01 2020
Journal Name
Civil Engineering Journal
Assessment Resistance Potential to Moisture Damage and Rutting for HMA Mixtures Reinforced by Steel Fibers
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Rutting is mainly referring to pavement permanent deformation, it is a major problem for flexible pavement and it is a complicated process and highly observed along with many segments of asphalt pavement in Iraq. The occurrence of this defect is related to several variables such as elevated temperatures and high wheel loads. Studying effective methods to reduce rutting distress is of great significance for providing a safe and along-life road. The asphalt mixture used to be modified by adding different types of additives. The addition of additives typically excesses stiffness, improves temperature susceptibility, and reduces moisture sensitivity. For this work, steel fibres have been used for modifying asphalt mixture as they incorp

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Publication Date
Sat Jun 01 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Lung cancer classification using data mining and supervised learning algorithms on multi-dimensional data set
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These With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about t

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Publication Date
Sat Jun 09 2018
Journal Name
Journal Of Molecular Structurs
Mesogenic materials incorporating 4H-1,2,4-triazol-3-thiol moiety: Synthesis, characterization and liquid crystals study
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Three series of monomers, polymers and thioester cyclic compounds containing 4H-1,2,4-triazol-3-thiol moiety were synthesized and examined for their liquid crystalline properties. All monomers, polymers and thioester compounds were characterized by elemental analysis and FTIR, 1 H-NMR and mass spectroscopy. The phase transition and mesomorphic properties were investigated by polarized optical microscope (POM) and differential scanning calorimetry (DSC). The monomer with terminal phenyl substituent display dimorphism nematic and smectic A (SmA) mesophases. The corresponding polymers derived from acrylic and phenyl acrylic acid monomers show nematic mesophase. The only thioester cyclic compound derived from terephtaloyl chloride show nemati

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Publication Date
Tue Nov 19 2024
Journal Name
Discover Sustainability
Groundwater quality assessment and pollution sources identification using statistical analyses at Missan Governorate, Southeast Iraq
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The shortage in surface water quantities led to a shift in dependence on the groundwater as an alternative water source in southern parts of Iraq. The groundwater is decreasing in quantity and water quality is degrading due to different factors. Therefore, it is important to assess the groundwater quality of the Missan Governorate of the country by analyzing the physicochemical parameters and distinguishing the probable sources of contaminants in the area. The present study used water quality diagrams and statistical methods such as factor analysis and agglomerative cluster analysis to determine the sources of chemical ions in the forty-four groundwater samples collected from wells in the study area. In addition, the Water Quality Index (WQ

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Publication Date
Wed Nov 19 2025
Journal Name
Sensing And Imaging
Density Functional Theory Calculations for Graphene Oxide, and Reduced Graphene Oxide as a Humidity Sensor
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Publication Date
Wed May 10 2023
Journal Name
Biomass Conversion And Biorefinery
Lactic acid-based deep eutectic solvents and activated carbon for soap removal from crude biodiesel
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Publication Date
Tue May 23 2023
Journal Name
Journal Of Sensors
On-Board Digital Twin Based on Impedance and Model Predictive Control for Aerial Robot Grasping
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Aerial manipulation of objects has a number of advantages as it is not limited by the morphology of the terrain. One of the main problems of the aerial payload process is the lack of real-time prediction of the interaction between the gripper of the aerial robot and the payload. This paper introduces a digital twin (DT) approach based on impedance control of the aerial payload transmission process. The impedance control technique is implemented to develop the target impedance based on emerging the mass of the payload and the model of the gripper fingers. Tracking the position of the interactional point between the fingers of gripper and payload, inside the impedance control, is achieved using model predictive control (MPD) approach.

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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Publication Date
Thu Dec 21 2023
Journal Name
Mathematical Modelling Of Engineering Problems
A Numerical Investigation into Wheel-Track Profile Optimization for Minimizing Stress and Mitigating Hunting Phenomena
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