Objectives: study the relation between the effect of time (long time duration) with high concentration of iodine
and study its effect on the activity of the thyroid gland (homonal and histological changes).
Methodology: An experimental study was done on (30) albino rats (8 weeks of age) to know the effect of high
concentration of iodine on the activity of the thyroid gland aiormonal and histological changes) related with
time. The study last for six months for the period of I/2/2007 to 31/7/2007, the experiment was carried out in the
research lab. of pathology deparment, College of Medicine, University of Baghdad.
Results: The study shows changes in homonal levels of thyroid hormones (T3 & T4) and also histological<

In this paper we show that if ? Xi is monotonically T2-space then each Xi is monotonically T2-space, too. Moreover, we show that if ? Xi is monotonically normal space then each Xi is monotonically normal space, too. Among these results we give a new proof to show that the monotonically T2-space property and monotonically normal space property are hereditary property and topologically property and give an example of T2-space but not monotonically T2-space.

Objectives: study the relation between the effect of time (long time duration) with high concentration of iodine
and study its effect on the activity of the thyroid gland (hormonal and histological changes).
Methodology: An experimental study was done on (30) albino rats (8 weeks of age) to know the effect of high
concentration of iodine on the activity of the thyroid gland (hormonal and histological changes) related with
time. The study last for six months for the period of 1/2/2007 to 31/7/2007, the experiment was carried out in the
research lab. of pathology department, College of Medicine, University of Baghdad.
Results: The study shows changes in hormonal levels of thyroid hormones (T3 & T4) and also histologic

This study aims to enhance the RC5 algorithm to improve encryption and decryption speeds in devices with limited power and memory resources. These resource-constrained applications, which range in size from wearables and smart cards to microscopic sensors, frequently function in settings where traditional cryptographic techniques because of their high computational overhead and memory requirements are impracticable. The Enhanced RC5 (ERC5) algorithm integrates the PKCS#7 padding method to effectively adapt to various data sizes. Empirical investigation reveals significant improvements in encryption speed with ERC5, ranging from 50.90% to 64.18% for audio files and 46.97% to 56.84% for image files, depending on file size. A substanti

Abstract:
the system of Administrative Control in organizations meets the need to check on the optimal use and proper resources and conservation to achieve the objectives sought by the organization, hence the system of Administrative Control  is part of the overall system in any organization that has undergone evolution always to be able to keep up with progress in the development of other sciences, and that the growth of coherence between subordinates in the organization means the ability to influence the opinions, ideas and attitudes to change it for directions the organization and its values ​​and this is reflected positively on the coherence of the organization, the researcher interest of the imp

 Abstract

In order to determine what type of photovoltaic solar module could best be used in a thermoelectric photovoltaic power generation. Changing in powers due to higher temperatures (25^oC, 35^oC, and 45^oC) have been done for three types of solar modules: monocrystalline , polycrystalline, and copper indium gallium (di) selenide (CIGS). The Prova 200 solar panel analyzer is used for the professional testing of three solar modules at different ambient temperatures; 25^oC, 35^oC, and 45^oC and solar radiation range 100-1000 W/m². Copper indium gallium (di) selenide module   has the lowest power drop (with the average percent

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no