The Study was achieved adjectives physical and chemical water wells in the district of
Samarra , where a study has 42 sample groundwater in different regions of the judiciary
randomly distributed all over the judiciary and examined in vitro.
The study showed that the quality of groundwater in the general area of study
Kipritateh punctuated Klordih water quality and other quality Bicarboonatih.
Varied the key components of groundwater in the study area in concentrations
between periods of rain and drought, especially because of the cation ion exchange processes
as well as mitigation as a result of filtering rain water and dominated the calcium ion,
followed by sodium.
As for the negative ions has dominated ion s

The Central Marshes are one of southern Iraq's most important wetlands and ecosystems. A study on evaluating soil quality and water quality in terms of chemical properties at certain sites in the southern Iraqi Central Marshes has been conducted to investigate their types and suitability for enhancing the agricultural reality of most field crops. Soil and water samples were collected from 15 sites and transferred to the laboratory. In the lab, the following parameters were determined: electrical conductivity (EC), total dissolved salts (TDS), organic materials (OM), pH, gypsum, and total sulfate content (SO₃). The tests conducted on the samples indicated that it could be said that the soil of the Central Marshes

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

Several stress-strain models were used to predict the strengths of steel fiber reinforced concrete, which are distinctive of the material. However, insufficient research has been done on the influence of hybrid fiber combinations (comprising two or more distinct fibers) on the characteristics of concrete. For this reason, the researchers conducted an experimental program to determine the stress-strain relationship of 30 concrete samples reinforced with two distinct fibers (a hybrid of polyvinyl alcohol and steel fibers), with compressive strengths ranging from 40 to 120 MPa. A total of 80% of the experimental results were used to develop a new empirical stress-strain model, which was accomplished through the application of the parti

Abstract:

              The phenomenon of financial failure is one of the phenomena that requires special attention and in-depth study due to its significant impact on various parties, whether they are internal or external and those who benefit from financial performance reports. With the increase in cases of bankruptcy and default facing companies and banks, interest has increased in understanding the reasons that led to this financial failure. This growing interest should be a reason to develop models and analytical methods that help in the early detection of this increasing phenomenon in recent year   . The research examines the use of

Expansive soil is one of the most serious problems that face engineers during the execution of any infrastructure projects. Soil stabilization using chemical admixture is one of the most traditional and widespread methods of soil improvement. Nevertheless, soil improvement on site is one of the most economical solutions for many engineering applications. Using construction and demolishing waste in soil stabilization is still under research., The aim of this study is to identify the effect of using concrete demolishing waste (CDW) in soil stabilization. Serious tests were conducted to investigate the changes in the geotechnical properties of the natural soil stabilized with CDW. From the results, it is concluded that the