In this paper, a fast lossless image compression method is introduced for compressing medical images, it is based on splitting the image blocks according to its nature along with using the polynomial approximation to decompose image signal followed by applying run length coding on the residue part of the image, which represents the error caused by applying polynomial approximation. Then, Huffman coding is applied as a last stage to encode the polynomial coefficients and run length coding. The test results indicate that the suggested method can lead to promising performance.

The study's objective is to find out the difference between the scholar of the research sample in awareness Green nanotechnology on the scaleas a whole and in each of its fields. The research depended of (136) specimen mem and women scholars of the fourth stage scholars / Department of Chemistry at the College of Education for Pure Sciences / Ibn Al-Haytham in Iraq for (2022-2023 AD) for the morning and evening studies, (65%) of the scientific community, It was picked at random with relation to the research instrument. it was a measure of awareness of green nanotechnology of (40) items, distributed in three areas (cognitive, skillful, emotional), and its validity and reliability were verified. Data analysis was completed for utilizing the s

The research risk of flooding on six water basins located in the eastern part of the western plateau, reached total area of the basin (22,998.9 km 2), has reached all the Basin area (basin to time 7056.1 km2 basin by 3585 km 2, Bath Alheiazi 6404 km 2, Abu beasts 544.1 km2 basin Abu Shannan 144.6 km 2, Bath Valley Faraj 5265.1 km 2), where it was specifically spatial degree of this risk by studying some of the hydrological basin transactions directly related to operations spate runoff study area and the occurrence of flood risks on the surface of ponds.

In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and

Background: Diabetes mellitus consists of a group of diseases characterized by abnormally high blood glucose levels. Glycated haemoglobin (HbA1c) is a form of haemoglobin used to identify the average concentration of plasma glucose over prolonged periods of time. It is formed in a non-enzymatic pathway by normal exposure of hemoglobin to high levels of plasma glucose, The main alterations observed in the saliva of Type 1 diabetic patients are hyposalivation and alteration in its composition, particularly those related to the levels of glucose. The aim of the present study was to assess the effect of Glycated haemoglobin level on the level of salivary glucose which may have an effect on oral health condition. Materials and methods