Abstract:
The aim of the present research is to evaluate the child’s nutritional
method (2-5 years old) which is based on his resistance of the food highly rich
with nutritional elements and his acceptance of the food of a low nutritional
value in addition to his having forbidden food with other mates and making
use of all mates when having food, in establishing the sound social values and
affection since child hood. The required statistical equation have been used
by the researcher namely (Z test).
The sample of the present study consists of (26) children who were selected
intentionally and randomly from the kindergartens of Al-Bayaa region and the
college of Education for women. The questionnaires were distributed among
the samples mother. After sorting the answers, it was noticed that the foods
refused by the child included : milk, eggs, meat, fish, rice, potatoes, soup,
bread, eggplants, green pepper, cucumber, tomatoes, banana and orange.
The reasons behind the children’s refusal mediated between the highest
percentage (100%) for the children who had no desire and the lowest
percentage (20%) for fear of the shape of food as a fish for not having such
types of food by the cartoon films, while the other percentages (30-80%)
oscillated for the food taste, lack of appetite, inability to crew, food smell,
creating accuses, the child’s health but when the child was brought together
with his mates, he was able to have the same rejected food in a high degree.
The results of the study concluded that the increase of the child’s acceptance
of the food leads to some positive indicators among which achieving the
sound social, educational and nutritional aims especially under the
circumstances our country lives in and this is the first step towards
establishing the national values for the children of the neighborhood and the
kinder gather friends away from any wrong concept that might dissociate
them.
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A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.
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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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