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.
Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the
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Automated clinical decision support system (CDSS) acts as new paradigm in medical services today. CDSSs are utilized to increment specialists (doctors) in their perplexing decision-making. Along these lines, a reasonable decision support system is built up dependent on doctors' knowledge and data mining derivation framework so as to help with the interest the board in the medical care gracefully to control the Corona Virus Disease (COVID-19) virus pandemic and, generally, to determine the class of infection and to provide a suitable protocol treatment depending on the symptoms of patient. Firstly, it needs to determine the three early symptoms of COVID-19 pandemic criteria (fever, tiredness, dry cough and breat
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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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This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.
The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20
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In the theoretical part, removal of direct yellow 8 (DY8) from water solution was accomplished using Bentonite Clay as an adsorbent. Under batch adsorption, the adsorption was observed as a function of contact time, adsorbent dosage, pH, and temperature. The equilibrium data were fitted with the Langmuir and Freundlich adsorption models, and the linear regression coefficient R2 was used to determine the best fitting isotherm model. thermodynamic parameters of the ongoing adsorption mechanism, such as Gibb's free energy, enthalpy, and entropy, have also been measured. The batch method was also used for the kinetic calculations, and the day's adsorption assumes first-order rate kinetics. The kinetic studies also show that the intrapar
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IR, MIR, UV – Visible spectra have been studied for Cobalt chloride molecule (CoCl2. 6H2O) compound, In wide range spectra (40000 – 410) cm-1 specially MIR range. Assignment were achieved for the fundamental vibrational bands of (CoCl2 . 6H2O ) to symmetry stretching ?1 (?^+) Anti – symmetry stretching ?3(?^+), these bands are non-degenerate , and the bending band is ?2(?) is doubly degenerate thought they have activity in IR and Raman , which explain the weakness in symmetry of this molecule, the fundamental bands for the molecule are centered at the following wave numbers (615, 685, 795, 1115, 1340, 1375, 1616.35, 2091, 2386, 2410, 3364) cm-1 which are corresponding to wave lengths (16260, 14598, 12578, 8968, 7462, 7272, 6186,
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