Objective: The study aimed to screen the prepubertal children for idiopathic scoliosis at earlier stages, and find
out the relationship between idiopathic scoliosis and demographic data such as age, sex, body mass index,
heavy backpacks, and heart & lung diseases.
Methodology: A descriptive study was conducted on screening program for prepubertal children in primary
schools at Baghdad city, starting from 24th of February to the end of October 2010. Non- probability
(purposive) sample of 510 prepubertal children were chosen from primary schools of both sides of Al-Karkh
and Al-Russafa sectors. Data was collected through a specially constructed questionnaire format include (24)
items multiple choice questions, and researcher observation. The validity of the questionnaire was determined
through a panel of experts related to the field of the study, and the reliability through a pilot study. The data
were analyzed through the application of descriptive statistical analysis frequency, & percentages, and
inferential statistical analysis, chi-square, are used.
Results: The study results revealed that most of the prepubertal children have idiopathic scoliosis, two third of
the sample (88.4%) were at age 10-12 years and mostly boys. There is highly significant association with (low
Body Mass Index & carry of the school backpack) but no significant association with the age, gender, and lung
& heart diseases. There is highly significant association between prepubertal children's idiopathic scoliosis signs
& the researcher observation for the prepubertal body feature, and Adam's Bending Forward Test which
revealed highly significant association with their idiopathic scoliosis. The results of the study reflect that the
majority of prepubertal children's idiopathic scoliosis deformities have significant association at early detection
than the other spinal deformities (kyphosis & kyphoscoliosis).
Recommendation: The researchers recommended that Ministry Of Health should activate the screening program
of scoliosis within school health service programs, and Ministry of Education should be involved their teachers in
the screening & training program.
Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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... Show MoreKarst aquifers in semi-arid regions are vital yet exceptionally vulnerable lifelines. This study investigates how tectonic, geomorphological, and climatic factors control the dynamics of karst springs in the El Menzel Causse (Middle Atlas, Morocco). Using an integrated approach that combines field investigations, remote sensing, and quantitative hydro-climatic analysis, we identify the mechanisms driving the system’s severe decline. Results indicated that the structural architecture of the major fault systems in the North Middle Atlas Fault (NMAF) and the Median Middle Atlas Fault (MMAF), governs the spatial distribution of more than 50 springs, which occur preferentially within highly permeable fault damage zones. However, the aquifer is
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