Despite recent attempts to improve safety in the construction sector, this sector is considered dangerous and unsafe. Iraq is one of the emerging nations that suffers from a lack of construction safety management. In 2018, the construction sector in Iraq was responsible for 38% of all industrial accidents. Creating a safety program minimizes this problem by making safety an intrinsic part of construction projects. As a result, this article aims to identify the crucial safety factors that affect the safety performance in Iraqi construction projects. After conducting a critical literature review of the related literature, a list of 35 sub-factors classified into nine categories of main factors was chosen to rank each facto

In this paper, we propose an approach to estimate the induced potential, which is generated by swift heavy ions traversing a ZnO thin film, via an energy loss function (ELF). This induced potential is related to the projectile charge density, ρq(k) and is described by the extended Drude dielectric function. At zero momentum transfer, the resulting ELF exhibits good agreement with the previously reported results. The ELF, obtained by the extended Drude model, displays a realistic behavior over the Bethe ridge. It is observed that the induced potential relies on the heavy ion velocity and charge state q. Further, the numerical results show that the induced potential for neutral H, as projectile, dominates when the heavy ion velocity is less

The article includes the concept of aesthetics through what has been dealt with in the literature by philosophers and researchers who have addressed this concept in an attempt to derive indicators of aesthetics. The article adopted a descriptive and analytical methodology by reviewing recent literature on the concept of aesthetics and its relation to urban planning and design issues. Many subjective and objective aesthetics indicators have been identified, some of which are classified under real aesthetics, and some under fake aesthetics. The indicators were applied to the Kufa Mosque complex and Sahla Mosque complex as a comparative case study. It was found that the indicators of real aesthetics have a higher weight in determining

In the case where a shallow foundation does not satisfy with design requirements alone, the addition of a pile may be suitable to improve the performance of the foundation design. The lack of in-situ data and the complexity of the issues caused by lagging in the research area of pile foundations are notable. In this study, different types of piles were used under the same geometric conditions to determine the load-settlement relationships with various sandy soil relative densities. The ultimate pile capacity for each selected pile is obtained from a modified California Bearing Ratio (CBR) machine to be suitable for axial pile loading. Based on the results, the values of Qu for close-ended square pile were increased by 15

Recent reports of new pollution issues brought on by the presence of medications in the aquatic environment have sparked a great deal of interest in studies aiming at analyzing and mitigating the associated environmental risks, as well as the extent of this contamination. The main sources of pharmaceutical contaminants in natural lakes and rivers include clinic sewage, pharmaceutical production wastewater, and sewage from residences that have been contaminated by drug users' excretions. In evaluating the health of rivers, pharmaceutical pollutants have been identified as one of the emerging pollutants. The previous studies showed that the contaminants in pharmaceuticals that are widely used are non-steroidal anti-inflammatory drugs, ant

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an