The present study aimed to identify the extent to which the content of social and national studies courses was included in interactive thinking maps in the educational stages in the Kingdom of Saudi Arabia, and to achieve the goal of the study, the researcher used the descriptive and analytical approach, and the study tool used consisted of a content analysis card; Where it included a list of the types of thinking maps, where the study sample consisted of all social and national studies courses at the elementary and intermediate levels, and it is (12) books for the student in its first and second parts, and after verifying the validity and reliability of the tool, it was applied to the study sample, and the study reached conclusions, including: The percentage of inclusion focused Thinking maps at the school level, each of the intermediate stage in the first and second semesters (54.9%), followed by the elementary stage (45.1%). The percentage of inclusion of thinking maps at the level of classroom arrangement in the first semester of elementary school ranked first with a percentage (30.6%), and with a high degree of availability, followed by the first and second semester of intermediate school in second place with a percentage (28.9%), (26.0) %), With medium availability, then the rest of the chapters with low availability. The order of thinking maps came in first place: the tree map was ranked first, with a total inclusion percentage in the primary and middle stages (37.0%), with a high degree of availability, then the flow chart came in second place with a percentage (19.7%), with a medium degree of availability, followed by the rest of the thinking maps with a degree Low availability. The study recommended that thinking maps should be included in a balanced and in-depth manner in all social and national studies courses at the different educational stages and more broadly, to conduct similar studies on different educational stages and other decisions.
Oral swab samples were collected from 120 children (ages between one month- 10 years) who were infected with oral thrush and 30 healthy children. The percentages of isolated yeasts and Bacteria were 66.6% and 96.6% respectively. The dominate yeast and bacteria were Candida albicans and Staphylococcus aureus with of 78.7% and 34.4% respectively. Results revealed that the highest percent of infection with oral thrush disease was 32.5% in children within the age of 1-2 months.
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In this paper, the process of comparison between the tree regression model and the negative binomial regression. As these models included two types of statistical methods represented by the first type "non parameter statistic" which is the tree regression that aims to divide the data set into subgroups, and the second type is the "parameter statistic" of negative binomial regression, which is usually used when dealing with medical data, especially when dealing with large sample sizes. Comparison of these methods according to the average mean squares error (MSE) and using the simulation of the experiment and taking different sample
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In The Name of Allah Most Gracious Most Merciful
The reason for choosing this topic was:
First: It is my great love for the Prophet Muhammad, may God’s prayers and peace be upon him, his family, his companions, his followers, the followers of their followers, and the scholars after them until the Day of Judgment.
Secondly: Showing a great jurisprudential figure who has contributed by speaking about important jurisprudential issues in the life of this nation, and bringing out this immortal book to put it in the hands of scholars, so I chose a figure from the followers (may God be pleased with them all).
Third: The study of the jurisprudence of the companions
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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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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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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr
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