The purpose of this research is to identify the effect of the use of project-based learning in the development of intensive reading skills at middle school students. The experimental design was chosen from one group to suit the nature of the research and its objectives. The research group consisted of 35 students. For the purpose of the research, the following materials and tools were prepared: (List of intensive reading skills, intensive reading skills test, teacher's guide, student book). The results of the study showed that there were statistically significant differences at (0.05) in favor of the post-test performance of intensive reading skills. The statistical analysis also showed that the project-based learning approach has a high effect on the development of intensive reading skills among students in the research group. This was proved by calculating the effect size; using Eta squared (²η), where the effect size was equal to 0.94. In light of the findings of the research, he recommended a set of recommendations, including the need to review the objectives of teaching reading in the middle stage, so that these goals include intensive reading skills. As well as the need to train Arabic teachers in service on how to develop the skills of intensive reading through active learning methods, including the method of the project based on the effectiveness and activity of students.
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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Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15
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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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Objectives: The study aims at finding the effectiveness of dietary habits on urolithiatic patients at Urinary Units
in Baghdad Teaching Hospitals.
Methodology: A quantitative descriptive study was conducted to identify the effectiveness of dietary habits on
(100) of urolithiatic patients in Urinary Units at Baghdad Teaching Hospitals starting from May 2011 to Sep.
2012.Data were collected through the use of constructed check list of the questionnaire format, which
consists of two parts: - The first part: is related to the patient's demographic variables ; the second part: is
constructed to serve the purpose of the study (effectiveness of the dietary habits). The total number of items
of the questionnaire is (69) item
DBN Rashid, IMPAT: International Journal of Research in Humanities, Arts, and Literature, 2016 - Cited by 5
MM Abdulwahhab, kufa Journal for Nursing sciences, 2017 - Cited by 1
This study was conducted from February 2010 to December 2010. Water Samples were collected every two months in three stations in Baghdad city. The study involved the assessment of concentrations of some heavy metals such as: Chromium, Cadmium, Copper, Iron, Lead, Manganese, Nickel and Zinc. the values of chromium were undetected for the entire of the study, while the rest of the heavy metal were ranged between 0.001 -0.438 mg / l, ND -0.077 mg / L, ND -0.778 mg / l, 0.36 - 0.011 mg / l, 0.011-0 .08mg/ l, ND - 0.1985 mg / l, ND -0.0416 mg / l, respectively. The results showed that the concentrations of heavy metals were fluctuated during the study period, except Lead which have high concentrations and exceeded the permit limits in all statio
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