Despite the vast areas occupied by deserts in the world, it is still far from the civilized development and development of the other regions, so they became semi-neglected areas that extend to the hand of urbanization only in specific places and for special purposes, due to the harsh natural conditions surrounding it and to the accuracy The ecological balance in it became the greatest enemy of human beings in the desert areas is the same person who paved the way for increased intervention in the exploitation of natural resources and increase the demand for them to drain seriously affect the impact and still on the environmental and climatic conditions and thus living for the inhabitants of these Areas. The main potential for deve

Experimental investigation of the influence of inserting the metal foam to the solar chimney to induce natural ventilation are described and analyzed in this work. To carry out the experimental test, two identical solar chimneys (without insertion of metal foam and with insertion of metal foam) are designed and placed facing south with dimensions of length× width× air gap (2 m× 1 m× 0.2 m). Four incline angles are tested (20^o,30^o,45^o,60^o) for each chimney in Baghdad climate condition (33.3^o latitude, 44.4^o longitude) on October, November, December 2018. The solar chimney performance is investigated by experimentally recording absorber pl

t-Self-Compacting Concrete (SCC) reduces environmental noise and has more workability. This research presents an investigation of the behavior of SCC under mechanical loading (impact loading). Two types of cement have been used to produce SCC mixtures, Ordinary Portland Cement (OPC) and Portland Limestone Cement (PLC), which reduces the emission of carbon dioxide during the manufacturing process. The mixes were reinforced with Carbon Fiber Reinforced Polymer (CFRP) which is usually used to improve the seismic performance of masonry walls, to replace lost steel reinforcements, or to increase column strength and ductility. Workability tests were carried out for fresh SCC. Prepared concrete slabs of 500×500×50mm were tested for lo

With growing global demand for hydrocarbons and decreasing conventional reserves, the gas industry is shifting its focus in the direction of unconventional reservoirs. Tight gas reservoirs have typically been deemed uneconomical due to their low permeability which is understood to be below 0.1mD, requiring advanced drilling techniques and stimulation to enhance hydrocarbons. However, the first step in determining the economic viability of the reservoir is to see how much gas is initially in place. Numerical simulation has been regarded across the industry as the most accurate form of gas estimation, however, is extremely costly and time consuming. The aim of this study is to provide a framework for a simple analytical method to esti

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

In present study, the technique was used, including nuclear track detector type (CR-39), for appreciative concentrations uranium and radon in soil samples from Baghdad University Campus-AL-Jadiriyah utilizing a prolonged -term with a solid-state nuclear path sensor, a technique for charged particles has been developed., the radon concentrations, effective dose rate and uranium concentrations have measured in soil samples. Eight various venues from soil Baghdad University Campus have appointed. The results indicated variant values about uranium and radon concentrations, the average value for radon gas, effective dose rate and uranium concentrations was found to be 281.59 Bq/cm3, 7.09 mSv/y and 0.01 Bq/mm-2 respectively. All results a

Experts have given much attention on the use of waste in asphalt paving because of its significance from a sustainability perspective. This paper evaluated the performance properties of asphalt concrete mixes modified with Crumb Rubber (CR) as a partial replacement for two grade sizes of fine aggregate (2.36, and 0.3 mm) at six replacement rates: 0%, 2%, 4%, 6%, 8%, and 10% by weight. Asphalt concrete mixes were prepared at their Optimum Asphalt Content (OAC) and then tested for their engineering properties. Marshall properties, fatigue, rutting, ideal CT index test, Scanning Electron Microscopy (SEM), and Energy-Dispersive X-ray (EDX) spectroscopy were deployed to examine the crystalline structure and elemental composition of the C