This paper deals with prediction the effect of soil remoulding (smear) on the ultimate bearing capacity of driven piles. The proposed method based on detecting the decrease in ultimate bearing capacity of the pile shaft (excluding the share of pile tip) after sliding downward. This was done via conducting an experimental study on three installed R.C piles in a sandy clayey silt soil. The piles were installed so that a gap space is left between its tip and the base of borehole. The piles were tested for ultimate bearing capacity
according to ASTM D1143 in three stages. Between each two stages the pile was jacked inside the borehole until a sliding of about 200mm is achieved to simulate the soil remoulding due to actual pile driving. T

This paper deals with prediction the effect of soil re-moulding (smear) on the ultimate bearing capacity of driven piles. The proposed method based on detecting the decrease in ultimate bearing capacity of the pile shaft (excluding the share of pile tip) after sliding downward. This was done via conducting an experimental study on three installed R.C piles in a sandy clayey silt soil. The piles were installed so that a gap space is left between its tip and the base of borehole. The piles were tested for ultimate bearing capacity according to ASTM D1143 in three stages. Between each two stages the pile was jacked inside the borehole until a sliding of about 200mm is achieved to simulate the soil re-moulding due to actual pile driving. The re

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

Is the subject of environmental analysis of the important issues that should occupy the attention of the departments of banks in general and banks in particular, the research sample, regardless of their size and the nature of its activity, So if the current era and witnessing rapid developments and changes, making the banking environment is more complex and interconnected than ever, And it became not possible for banks to be aware and understand the external environment variables without an analysis of the various constituent elements and influential heavily in its financial and administrative,Therefore research aims to find out the relationship between the external environment and banking facilities analysis application on the Rafidain

  The construction of development is required to develop various economic sectors with the necessity to meet the various requirement of both individuals and institutions , or through the import process , which must be commensurate with the needs of the market and the economy and development. But in fact , we found that the process of import in Iraq after 2003 took a turn dangerous excesses on limits of philosophy and objectives of the import , which  reflected  the level of national production as well as the policy of dumping and given to the lack of matching a lot of goods and materials imported for Standards and Measures of quality and stands behind it causes many of them exposure to the market and weak sectors with an o

The construction of development is required to develop various economic sectors with the necessity to meet the various requirement of both individuals and institutions , or through the import process , which must be commensurate with the needs of the market and the economy and development. But in fact , we find that the process of import in Iraq after 2003 took a turn dangerous excesses on limits of philosophy and objectives of the import , which is reflected at the level of national production as well as the policy of dumping and given and the lack of matching a lot of goods and materials imported for Standards and Measures of quality and stands behind it causes many of them exposure to the market and weak sectors with an overlap betwee

Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

Both traditional and novel techniques were employed in this work for magnetic shielding evaluation to shed new light on the magnetic and aromaticity properties of benzene and 12 [n]paracyclophanes with n = 3–14. Density functional theory (DFT) with the B3LYP functional and all-electron Jorge-ATZP and x2c-TZVPPall-s basis sets was utilized for geometry optimization and magnetic shielding calculations, respectively. Additionally, the 6-311+G(d,p) basis set was incorporated for the purpose of comparing the magnetic shielding results. In addition to traditional evaluations such as NICS/NICSzz-Scan, and 2D-3D σiso(r)/σzz(r) maps, two new techniques were implemented: bendable grids (BGs) and cylindrical grids (CGs) of ghost atoms (Bqs). BGs a