The childhood stage is considered the most important stage of all the stages through
the human being’s life. In this stage the human being will be more affected by the various
factors that surround him/her. The first five years of his/her life leave a great impact not only
on the human being personality, but also on his/her whole life. Therefore, it is worthwhile tobe concerned with and focus at the raising up and the teaching of the child during the
childhood stage.
The mission of raising up children in this era - the era of globalization and information
bursting or news flooding – has become a very difficult or even an impossible mission.
Furthermore, not only in the Arabic world, but also all over the world, this era has become a
depressing and a disappointing era to many serious parents and teachers, who seek the fact
and care about both their children’s benefit and the benefit of those who raise them up.
Children are seen to be more accepting to and more connecting with the building up of
civilization. The parent’s attentiveness and the level of their educational maturity will define
the level of family evolution and its role in affecting the child’s personality.
Eventually, all these matters go back to the shortage in the environmental attentiveness
and its relation to the health of the human beings. All these leads to the problem discussed in
this research which is the revealing of the attentiveness by the problem of technological media
poisoning of the children’s parents and their teachers.
The aim of this research is to be acquainted with:
The attentiveness of the technological media poisoning in the members of the sample.
The attentiveness of the technological media poisoning in the kindergarten teachers.
The differences in the attentiveness of the technological media poisoning.
between the kindergarten children’s parents and the children’s teacher.
This research is limited the children’s parents and teachers of the kindergartens in
Baghdad for the academic year 2012-2013.
In order to achieve the goal of this research, the researcher has performed a scale of the
attentiveness of the technological media poisoning according to the scientific steps in the
construction of the psychological scales.
To approve the truth of the scale to be introduced to a number of experts. After
straightening some of the scale items, (33) the of the scale has been approved.
Moreover, the researcher uses statistical analysis for the items by calculating the
distinctive power, which proves that all the items of the scale are distinctive and statistically
significant. The researcher tries to find out the relation between the degree of the item and the
total degree.
The validity of the scale has been approved by repeating the test. The validity factor is
(0.86), which proves that the validity factor is reliable. In the application of the Falkronbach
formula, it has been found that the validity factor is (0.93). This proves that the validity factor
is reliable.
The scale has been applied on (600) members of the sample, whichcontains randomly
chosen children’s parents and kindergarten teachers.
The result of the research are as follows:
All the members of the sample have attentiveness of the technological media poisoning.
The children’s parents have attentiveness of the technological media poisoning.
The kindergarten teachers have attentiveness of the technological media poisoning.
There are differences in attentiveness between all the members of the sample to the
benefit of the mothers side.
The researcher has introduced a number of recommendations and suggestions, which
are going to be discussed later.
The consensus algorithm is the core mechanism of blockchain and is used to ensure data consistency among blockchain nodes. The PBFT consensus algorithm is widely used in alliance chains because it is resistant to Byzantine errors. However, the present PBFT (Practical Byzantine Fault Tolerance) still has issues with master node selection that is random and complicated communication. The IBFT consensus technique, which is enhanced, is proposed in this study and is based on node trust value and BLS (Boneh-Lynn-Shacham) aggregate signature. In IBFT, multi-level indicators are used to calculate the trust value of each node, and some nodes are selected to take part in network consensus as a result of this calculation. The master node is chosen
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
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Objectives: To determine the effectiveness of the educational program on nursing staff knowledge about infection control measures at the Intensive Care Unit in Al-Diwaniya Teaching Hospital.
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First part: The demographic characteristics of the nursing staff (age, gender, level of education, years of experien
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