This paper presents the results of experimental investigation carried out on concrete model piles to study the behaviour of defective piles. This was achieved by employing non-destructive tests using ultrasonic waves. It was found that the reduction in pile stiffness factor is found to be about (26%) when the defect ratio increased from (5%) to (15%). The modulus of elasticity reduction factor as well as the dynamic modulus of elasticity reduction factor increase with the defect ratio

The excessive permanent deformation (rutting) in asphalt-concrete pavements resulting from frequent repetitions of heavy axle loads is studied in this paper. Rutting gradually develops with additional load applications and appears as longitudinal depressions in the wheel path. There are many causes of the rutting of asphalt roads, such as poor asphalt mixing and poor continuous aggregate gradation. All factors affecting the mixture resistance to permanent deformation must be discussed, and all must be properly considered to reduce the rutting propensity of asphalt-aggregate mixtures. In this study, several mixtures were produced with the most common techniques in rutting resistance (using the most effective additives for each mixture), and

Reflective cracking is one of the primary forms of deterioration in pavements. It is widespread when Asphalt concrete (AC) overlays are built over a rigid pavement with discontinuities on its surface. Thus, this research work aims to reduce reflection cracks in asphalt concrete overlay on the rigid pavement. Asphalt Concrete (AC) slab specimens were prepared in three thicknesses (4, 5, and 6 cm). All these specimens were by testing machine designed and manufactured at the Engineering Consulting Office of the University of Baghdad to examine for the number of cycles and loads needed to propagate the reflection cracking in the asphalt concert mixture at three temperatures (20, 30, and 30°C). It was noticed that the higher thickness A

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

Roller compacted concrete (RCC) is a concrete compacted by roller compaction. The concrete mixture in its unhardened state must support a roller while being compacted. The aim of this research work was to investigate the behavior and properties of roller compacted concrete when constructed in the laboratory using roller compactor manufactured in local market to simulate the field conditions. The roller compaction was conducts in three stages; each stage has different loading and number of passes of the roller. For the first stage, a load of (24) kg and (5) passes in each direction had been employed. For the second stage, a load of (104) kg and (10) passes in each direction were conducted. Finally, at the third stage, a load of (183) kg a

No-fines concrete is an advanced pavement material known for its strong drainage capabilities, making it a widely used rigid road surface. With growing demand for reduced cement content due to industrial advancements, researchers have explored epoxy resin as a partial or total cement replacement. This study examines the mechanical properties of no-fines concrete with varying epoxy replacement levels and applies KENSLAB analysis for pavement thickness design. Seven concrete mixes were prepared with epoxy replacing cement at 100%, 95%, 75%, 55%, 35%, and 15%. Mechanical tests, including compressive strength, flexural strength, modulus of elasticity, bulk density, water absorption, and durability (wet-dry), were conducted after 7 and 2

Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated