Experimental tests were conducted to study the behavior of skirted foundations rested on dry medium sandy soil subjected to vertical and inclined loads. To achieve this goal, a small-scale physical model was designed and performed which contained an aluminum circular footing (100 mm) in diameter and (10 mm) in thickness and skirts with different heights, local medium poorly graded dry sand is placed in a steel soil container (2 mm) thick with internal dimensions (1000 mm x 1000 mm in cross section and 800 mm in height). The main objective of this study was to evaluate the response of skirt attached to the foundation at different skirt (L/D) ratios (0.0, 0.5, 1.0 and 1.5) and is subjected to point load at different angles of inclinat

charge transfer complex formed by interaction between the p- aminodiphenylamine (PADPA) as electron donor with iodine as electron acceptor in ethanol at 250C as evidenced by color change and absorption. The spectrum obtained from complex PADPA – Iodine shows absorptions bands at 586 nm. All the variables which affected on the stability of complex were studies such as temperature, pH, time and concentration of acceptor. The linearity of the method was observed within a concentration rang (10–165) mg.L-1 and with a correlation coefficient (0.9996), while the molar absorbitivity and sandell sensitivity were (4643.32) L.mol-1.cm-1 and (0.0943) μg.cm-2, respectively. The adsorption of complex PADPA–I2 was studied using adsorbent surfaces

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

Bendable concrete, also known as Engineered Cementitious Composite (ECC) is a type of ultra-ductile cementitious composites reinforced with fibres to control the width of cracks. It has the ability to enhance concrete flexibility by withstanding strains of 3% and higher. The properties of bendable concrete mixes (compressive strength, flexural strength, and drying shrinkage) are here assessed after the incorporation of supplementary cementitious materials, silica fume, polymer fibres, and the use of ordinary Portland cement (O.P.C) and Portland limestone cement (IL). Mixes with Portland limestone cement show lower drying shrinkage and lower compressive and flexural strength than mixes with ordinary Portland cement, due to the ratio o

Conventional concretes are nearly unbendable, and just 0.1 percent of strain potential makes them incredibly brittle and stiff. This absence of bendability is a significant cause of strain failure and has been a guiding force in the production of an elegant substance, bendable concrete, also known as engineered cement composites, abbreviated as ECC. This type of concrete is capable of displaying dramatically increased flexibility. ECC is reinforced with micromechanical polymer fibers. ECC usually uses a 2 percent volume of small, disconnected fibers. Thus, bendable concrete deforms but without breaking any further than conventional concrete. This research aims to involve this type of concrete, bendable concrete, that will give solut

Conventional concretes are almost unbending, and even a small amount of strain potential leaves them brittle. This lack of bendability is a major source of strain loss, and it has been the main goal behind the development of bendable concrete, often known with engineered ce ment composites, or ECC. This form of concrete has a lot more flexibility than regular concrete. Micromechanical polymer fibers are used to strengthen ECC. In most cases, ECC uses a 2% amount of thin, separated fibers. As a result, bendable concrete deforms but unlike traditional concrete, it does not crack. This study aims to include this kind of concrete, bendable concrete, which can be used to solve concrete problems. Karasta (CK) and Tasluja (CT) Portland Lime