In this experimental study, the use of stone powder as a stabilizer to the clayey soil studied. Tests of Atterberg limits, compaction, fall cone (FCT), Laboratory vane shear (LVT), and expansion index (EI) were carried out on soil-stone powder mixtures with fixed ratios of stone powder (0%, 5%, 10%, 15%, and 20%) by the dry weight. Results indicated that the undrained shear strength obtained from FCT and LVT increased at all the admixture ratios, and the expansion index reduced with the increase of the stone powder.

The existing investigation explains the consequence of irradiation of violet laser on the structure properties of MawsoniteCu₆Fe₂SnS₈ [CFTS] thin films. The film was equipped by the utilization of semi-computerized spray pyrolysis technique (SCSPT), it is the first time that this technique is used in the preparation and irradiation using a laser. when the received films were processed by continuous red laser (700 nm) with power (>1000mW) for different laser irradiation time using different number of times a laser scan (0, 6, 9, 12, 15 and 18 times) with total irradiation time (0,30,45,60,75,90 min) respectively at room temperature.. The XRD diffraction gave polycrysta

Attention has recently been given to finding alternative and sustainable raw material sources for wood and metal adhesives, such as polyvinyl alcohol (PVA), corn starch (CS), arabic gum (AG), and dextrins (D). Modifying polymer dispersion using unique substances, such as modifying reactive elastomer liquid (EL) using PVA, CS, AG, or D results in sufficiently moisture-resistant adhesive joins. In the present study, the physical characteristics of EL/blended with the natural polymers PVA, CS, AG, and D, based on high-density fiberboard (HDF) wood and aluminum (Al) adhesives and coatings, were investigated and compared to those of pure EL. The EL was blended with PVA, CS, AG, or D at a ratio of 60/40 (w/w) to form EL/blends. The che

The importance of this topic may not be overlooked by many of the specialists, because it is one the sciences of the Arabic language, but it is an important method in the field of influencing the recipient and his aesthetic ability to create influential images as well.
The talking about Semantic (Badi'iyah)is as old as the Arabic age, so it may be talking about it not the new thing because the people who specialized have preceded us and exhausted all the talk .

Oilwell cementing operations are crucial for drilling and completion, preserving the well's productive life. However, weak and permeable formations pose a high risk of cement slurry loss, leading to failure. Lightweight cement, like foamed cement, is used to avoid these difficulties. This study is focused on creating a range of foamed slurry densities and examining the effect of gas concentration on their rheological properties. The foaming agent and foam stabilizer are tested, and the optimal concentration is determined to be 2% and 0.12%, respectively, by the weight of the cement.

Furthermore, the construction of samples of foam cement with different densities (0.8, 1.0, 1.2, 1.4, and 1.6) g/cc is performed to f

         International companies are striving to reduce their costs and increase their profits, and these trends have produced many methods and techniques to achieve these goals. these methods is heuristic and the other Optimization.. The research includes an attempt to adapt some of these techniques in the Iraqi companies, and these techniques are to determine the optimal lot size using the algorithms Wagner-Whitin under the theory of constraints. The research adopted the case study methodology to objectively identify the problem of research, namely determining lot size optimal for each of the products of electronic measurement laboratory in Diyala and in light of the bottlenecks in w

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob