In this article we analysis the data of Iraqi children aged 0-9 months covered in Multiple Indicator Cluster Survey (MICS6-2018) to evaluate the nutritional status . Weight for-age z-score (WAZ), height-for-age z-score (HAZ) and BMI-for-age z-score were compared with the z-scores WHO standards. The overall prevalence of underweight and stunting of the children were 4 % and 11% respectively. Prevalence of overweight based on BMI-for-age for the sexes combined was 21%. Comparing the results obtained from MICS-6 with the results obtained from MICS-4, we find that there is an improvement in the nutritional status of Iraqi children concerning weight, but as for height, we find that there is an increase in the percentage of children who suffer fr

Cloud computing provides huge amount of area for storage of the data, but with an increase of number of users and size of their data, cloud storage environment faces earnest problem such as saving storage space, managing this large data, security and privacy of data. To save space in cloud storage one of the important methods is data deduplication, it is one of the compression technique that allows only one copy of the data to be saved and eliminate the extra copies. To offer security and privacy of the sensitive data while supporting the deduplication, In this work attacks that exploit the hybrid cloud deduplication have been identified, allowing an attacker to gain access to the files of other users based on very small hash signatures of

     In this article, we investigate a mathematical fractional model of tuberculosis that takes into account vaccination as a possible way to treat the disease. We use an in-host tuberculosis fractional model that shows how Macrophages and Mycobacterium tuberculosis interact to knowledge of how vaccination treatments affect macrophages that have not been infected. The existence of optimal control is proven. The Hamiltonian function and the maximum principle of the Pontryagin are used to describe the optimal control. In addition, we use the theory of optimal control to develop an algorithm that leads to choosing the best vaccination plan. The best numerical solutions have been discovered using the forward and backward fractional Euler

Wireless  lietworking is·  constantly improving,  changing  and

though  ba ic  principle  is the same.  ['nstead of  using standard  cables  to transmit information fmm one point to another (qr more), it .uses  radio signals.  This paper  presents .a case  study considedng real-time remote

cqntroJ using Wireless UDP/JP-based networks,. The aim of-this werk is to

reduce  real-time· remote control  system  based upon a simulatio.n  model,

which can operate via general communication  l"]etworks, whieh on bodies. modern wireles  tcchnolqgy.

The  first  part includes· a  brief

In this study asparaginase was extracted from fruit part of Capiscum annum then Asparaginase activity was detected and optimised. Optimum conditions for the activity of crude asparaginase were studied. Results showed maximum activity of asparaginase was achieved 140 u/ml when the enzyme was incubated with 200 mM of asparagines at 35 °C for 30 minutes in the presence of 0.05 M of potassium phosphate buffer solution at pH 8.

    The motion of fast deuterons in most dense plasma focus devices  ( DPF ) , may be characterized that it has a complex nature in its paths and this phenomena by describing a through gyrating motion with arbitrary changes in magnitude and direction .  In this research , we focused on the  understanding the theoretical concepts which  depend deeply on the experimental results to explain the deuteron motions in the pinch region , and then to use the fundamental physical formulas that are deeply related to the explanation of this motion to prepare a suitable model for calculating the vertical and radial components for deuteron velocity by improving the  Rung – Kutta  Method

         This study attempts to determine the necessary teaching competencies for teachers and the level of their importance in the development of their performance professionally and scientifically, and the progress towards a better future to achieve an effective level. Accordingly, the research community consists of the morning-preparatory schools for boys at the General Directorate of Education of Baghdad \ Rusafa². The study sample included (68) teachers constituted 88.31% of the total community of teachers. As for the research tools, the researcher adopted the descriptive method by using the observation method in which the researcher prepared a list of teaching. For verifying the re

The Aqra - Bekhme, Shiranish, Tanjero and Kolosh formations outcrop in the High Folded Zone, Northern Iraq in Erbil and Sulaymaniyah governorates. The formations have been studied at two selected geological sections (Bekhme Gorge and Zarda Bee). In this study, these formations are investigated based on both benthic and planktonic foraminifera. Depending on foraminifer’s investigation, three biozones have been recognized; two biozones are identified in the benthic foraminifera and the third one is identified in the planktonic foraminifera as follow:

1. Siderolites calcitropodes - Orbitoides apiculatus - Omphalocyclus macroporus Assemblage zone.
2. Loftusia morgani range zone.
3. Aba

The aim of the current research is to verify the effect of the cognitive modeling strategy on the achievement of the chemistry course for the students of the first intermediate grade. To achieve the objective of the research, the null hypothesis was formulated via cognitive modeling strategy. The results showed that the experimental group's students performed better than the students in the control group. In the light of the results, the researchers concluded: The impact of the cognitive modeling strategy in the achievement of students of first intermediate grade in chemistry.

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an