The childhood of the important stages in which the adopted child's personality, mental and physical, motor and configure , as well as gain experience , it is the basis on which the future life of the child , studies have unanimously competent in the fields of childhood verily the first five years of a child of the most important stages of life and the most fertile life . Because the stage Childhood its an active role as the foundation upon which to build human personality , it was necessary to create all leads to raise the level of intelligence of children , because intelligence is the first element in the organization of thinking makes the child able to do the activities characterized by mental qualities .
Indicated most of the scientists, there is a mental and intellectual series deals with a number of intelligences , including musical intelligence , that music intelligence is thefoundation upon which to build the artistry capacity , because it is inspired by a sense of the individual environmental beauty, taste of nature and you pay to become more understanding to the content of the aesthetic elements of the environment , also, the family that develop musical intelligence of her child , help to gain a lot of different values and principles , including: respect for his homeland, and to respect the rights of others and the rights of the community in which he lives , working on widening the intellectual, linguistic, emotional and imaginary field when, for example, learned how to coordinate his voice to learn a particular skill or experience, and thus grow human being sound and integrated.
Given the importance of music in a child intelligence kindergarten , and the lack of studies on this topic , the researcher sought to measure the musical intelligence of kindergarten children By building a test of intelligence musician at the age of (5-6) years based on the theory (Wing) musical intelligence, researcher chose Kindergarten (AL- Slam) of the Directorate of Baghdad / Karkh second in the AL-Alam area , and that the number of its children (187) boys and girls .
In order to test the application for adoption , researcher Extracted transactions discrimination and difficulty of the paragraphs of the test , validity to the test as a whole transactions ,and its fields, the test includes the three areas, it is as follows: (Music cognition), which consists of (30) items , (musical taste), which consists of (3) items , and finally (Music Performance), which consists of (8) items , bringing the number of items of the test as a whole (41) items.
After the test application on the research sample consisting of (187 ) children, the data were analyzed Which Obtained by researcher Children of answers on the test , and introduced the statistical system (SPSS) , results of the study revealed that the kindergarten children were suffering from the weakness of their intelligence in music, compared with the average premise, researcher This result was interpreted according to the theory (Wing) that the by relying in the search , that the cause of the weakness of children in kindergarten musical intelligence goes back to different musical productions on the three areas identified by (Wing) to his test.
The researcher also provided after receiving a Search some of the recommendations and suggestions which it considered useful to researchers and the concerned authorities in this issue result.
African countries are among the countries in the world that suffer from the phenomenon of child recruitment in wars and conflicts. There are many reasons behind it, including the nature of the human formation of children, the societal violence to which they are exposed, lack of access to education, economic hardships, as well as the role of African wars and conflicts and other reasons that compelled children to join armed groups and participate in military operations. The recruitment of children is divided into two types, compulsory and voluntary, and this leads to many humanitarian and security repercussions that are not limited to a specific period of time but extend to subsequent generations, and due to its seriousness, t
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Background: Cerebral palsy is non-progressive disorder of posture or movement due to a lesion of the developing brain. It is the commonest physical disability in childhood. Objective: To study the clinical, neurological abnormalities, prevalence of convulsion (epilepsy) & to asses the value of CT scans of brain in patients with cerebral palsy.
40 blood sample were taken from children infected with kala-azar at age less than ten years, who were admitted to El-Eskan child hospital, and central health laboratory in Baghdad. At the same time 15 sample collected from healthy child for comparing. During research estimated immunoglobulins level ( IgG, IgM, IgA) and (IFAT) IFAT test recorded a higher indicate antibodies level witch was synergistic with infected severity, the stander level of antibodies arrange between 1/16, 1/32 and 1/64 that means it graduate from the lowest one 1/16 into the highest one 1/64 within groups. During infectious the IgG ,IgM level recorded the higher level (2012.9 mg/dl) and (154.3 mg/dl) compared to the control group (874.3 mg/dl),
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Objective(s): To assess the behavior that impedes the eating of children with autism spectrum disorders in Baghdad city, and find out the relationships between the behaviors that impede eating of autistic children and their demographic characteristics.
Methodology: The study started from the period of 16th September 2019 to the 16th of March 2020. A non-probability (purposive) sample of 80 children with autism spectrum disorders was selected. The questionnaire was designed and composed of two parts: the first part includes the autistic children demographic data, the second part includes scales of behavior that impede eating followed by parents towards autistic child. The reliability of the questionnaire was determined through a pilot
Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
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This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima
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Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le
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This study aims to demonstrate the role of artificial intelligence and metaverse techniques, mainly logistical Regression, in reducing earnings management in Iraqi private banks. Synthetic intelligence approaches have shown the capability to detect irregularities in financial statements and mitigate the practice of earnings management. In contrast, many privately owned banks in Iraq historically relied on manual processes involving pen and paper for recording and posting financial information in their accounting records. However, the banking sector in Iraq has undergone technological advancements, leading to the Automation of most banking operations. Conventional audit techniques have become outdated due to factors such as the accuracy of d
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