In this research work, a new type of concrete based on sulfur-melamine modification was introduced, and its various properties were studied. This new type of concrete was prepared based on the sulfur-melamine modification and various ingredients. The new sulfur-melamine modifier was fabricated, and its fabrication was confirmed by IR spectroscopy and TG analysis. The surface morphology resulted from this modifier was studied by SEM and EDS analysis. The components ratios in concrete, chemical and physical characteristics resulted from sulfur-melamine modifier, chemical and corrosion resistance of concrete, stability of concrete against water adsorption, stability of concrete against freezing, physical and mechanical properties and durabi

Incremental sheet forming (ISF) process offers a high degree of flexibility in the manufacturing of different sheet parts, which makes it an ideal candidate for prototype parts as well as efficient at fabricating various customized products at low production costs compared to traditionally used processes. However, parts produced in this process exhibit notable geometrical inaccuracy and considerable thickness reduction. In this paper, the single point incremental sheet forming variant of the process has been implemented to manufacture a highly customized cranial implant starting from the computed tomography (CT) scan data of the patient's anatomy. A methodology, from the modeling to the realization of the implant, is presented and discus

The introduction of concrete damage plasticity material models has significantly improved the accuracy with which the concrete structural elements can be predicted in terms of their structural response. Research into this method's accuracy in analyzing complex concrete forms has been limited. A damage model combined with a plasticity model, based on continuum damage mechanics, is recommended for effectively predicting and simulating concrete behaviour. The damage parameters, such as compressive and tensile damages, can be defined to simulate concrete behavior in a damaged-plasticity model accurately. This research aims to propose an analytical model for assessing concrete compressive damage based on stiffness deterioration. The prop

The using of recycled aggregates from construction and demolition waste (CDW) can preserve natural aggregate resources, reduce the demand for landfill, and contribute to a sustainable built environment. Concrete demolition waste has been proven to be an excellent source of aggregates for new concrete production. At a technical, economic, and environmental level, roller compacted concrete (RCC) applications benefit various civil construction projects. Roller Compacted Concrete (RCC) is a homogenous mixture that is best described as a zero-slump concrete placed with compacting equipment, uses in storage areas, dams, and most often as a basis for rigid pavements. The mix must be sufficiently dry to support

Several stress-strain models were used to predict the strengths of steel fiber reinforced concrete, which are distinctive of the material. However, insufficient research has been done on the influence of hybrid fiber combinations (comprising two or more distinct fibers) on the characteristics of concrete. For this reason, the researchers conducted an experimental program to determine the stress-strain relationship of 30 concrete samples reinforced with two distinct fibers (a hybrid of polyvinyl alcohol and steel fibers), with compressive strengths ranging from 40 to 120 MPa. A total of 80% of the experimental results were used to develop a new empirical stress-strain model, which was accomplished through the application of the parti

In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N