The friendly-environment geophysical methods are commonly used in various engineering and near-surface environmental investigations. Electrical Resistivity Imaging technique was used to investigate the subsurface rocks, sediments properties of a proposed industrial site to characterize the lateral and vertical lithological changes. via the electrical resistivity, to give an overview about the karst, weak and robust subsoil zones. Nineteen 2D ERI profiles using Wenner array with 2 m electrode spacing have been applied to investigate the specific industry area. One of these profiles has been conducted with one-meter electrode spacing. The surveyed profiles are divided into a number of blocks, each block consists of several parallel profiles in a specific direction. The positions of Electrical Resistivity Imaging profiles in the project area have been determined according to a preliminary subject plan from the civil engineers for factory foundation constructions and proposed locations of heavy machines. The inversion results of profiles showed that areas of blocks A, B, C, and D consist mainly of clastic rocks and sediments, e.g., claystone, siltstone and sandstone. The Electrical Resistivity Imaging inversion sections of blocks A, B, C, and D do not show any indication of cavitation or weak zones of sizes more than 2.0 meters, and no signs of gypsum bodies are found in these areas in general. Gypsum bodies are probably detected at block E, the southern part of the study area. The researchers recommended to keep these rocks in block E away from the continuous running water to avoid cavitation. Furthermore, the construction of heavy machines should keep away from this part of the study area to avoid to some extent, subsoil failure and subsidence in the future. Middle and Northern parts are more consistent to the constructions and factory foundations.
This paper attempts to shed light on the most influential factors in the importance of religious buildings were destroyed because of the recent war due to the control of terrorist gangs of ISIS over the city of Mosul, and to prioritize their reconstruction and their role in reviving the historical center of Mosul.
The research’s problem emerged in the lack of knowledge about the identifying the most influential factors in the importance of religious buildings and utilizing them to prioritize their reconstruction. This study aims to analyze the factors influencing the importance of religious buildings using the Expert Choice software through the Analytic Hierarchy Process (AHP) to reach an analysis of their weights and propose p
... Show MoreThis paper is based on the Sentinel-2 satellite data: the thermal, red, and NIR bands. The Babylon city was chosen in this study for different reasons: its location in the middle of Iraq and it represents the largest capitals of the Mesopotamia civilization in the word. The Land Surface Temperature (LST) was determined using a method that incorporates remote sensing, geographic information systems, and statistics. This process has made it possible to monitor the relationship between land usage and the land surface temperature for four seasons in the year 2021. The mapswere processed and analyzed by using ArcGIS software. Five maps of the LST were constructed. Each map represents diffe
This study is conducted to investigate the validity of using different levels of Rustumiya sewage water for irrigation and their effects on corn growth and some of the chemical properties of the soil such as electrical conductivity and soil pH in extract soil paste , the micro nutrient content in soil and plant which are ( Fe , Mn , Zn , Cu , Cd , Pb ). Three levels of sewage water ( 0 , 50 , 100 )% in two stages were used ,the three levels of wastewater ( without soil fertilization ) were used in the first stage , Where 80 Kg N /D+50Kg P2O5 /D was added to the soil as fertilizer in the control (0%) treatment and 40 Kg N/D+25Kg P2O5/D were added to 50 and 100% levels in the second stage .Corn seeds were planted in 12kg plastic pots in Com
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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
... Show MoreIs in this research review of the way minimum absolute deviations values based on linear programming method to estimate the parameters of simple linear regression model and give an overview of this model. We were modeling method deviations of the absolute values proposed using a scale of dispersion and composition of a simple linear regression model based on the proposed measure. Object of the work is to find the capabilities of not affected by abnormal values by using numerical method and at the lowest possible recurrence.
The Neutron Fermi Age, t, and the neutron slowing down density, q (r, t) , have been measured for some materials such as Graphite and Iron by using gamma spectrometry system UCS-30 with NaI (Tl) detector. This technique was applied for Graphite and Iron materials by using Indium foils covered by Cadmium and the measurements done at the Indium resonance of 1.46 eV. These materials are exposed to a plane 241Am/Be neutron source with recent activity 38 mCi. The measurements of the Fermi Age were found to be t = 297 ± 21 cm2 for Graphite, t = 400 ± 28 cm2 for Iron. Neutron slowing down density was also calculated depending on the recent experimental t value and distance.
A new class of higher derivatives for harmonic univalent functions defined by a generalized fractional integral operator inside an open unit disk E is the aim of this paper.
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
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