Abstract

 This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine

A series of coumarin derivatives linked to amino acid ester side chains were synthesized and evaluated of their antibacterial and antifungal activity. The coumarin derivatives was alkylated by the ethyl bromoacetate and then using potassium carbonate to get alkylated hymecromone. Conventional solution method for amide bond formation was used as a coupling method between the carboxy-protected amino acids with acetic acid side chain of coumarin derivatives. The DCC/ HOBt coupling reagents were used for peptide bond formation. The proposed analogues were successfully synthesized and their structural formulas were consistent with the proposed struct

An experimental investigation has been made to study the influence of using v-corrugated aluminum fin on heat transfer coefficient and heat dissipation in a heat sink. The geometry of fin is changed to investigate their performance. 27 circular perforations with 1 cm diameter were made. The holes designed into two ways, inline arrangement and staggered in the corrugated edges arrangement. The experiments were done in enclosure space under natural convection. Three different voltages supplied to the heat sink to study their effects on the fins performance. All the studied cases are compared with v-corrugated smooth solid fin. Each experiment was repeated two times to reduce the error and the data recorded after reaching t

Mechanical and thermal properties of composites, consisted of unsaturated polyester resin, reinforced by different kinds of natural materials (Orange peels and Date seeds) and industrial materials (carbon and silica) with particle size 98 µm were studied. Various weight ratios, 5, 10, and 15 wt. % of natural and industrial materials have been infused into polyester. Tensile, three-point bending and thermal conductivity tests were conducted for the unfilled polyester, natural and industrial composite to identify the weight ratio effect on the properties of materials. The results indicated that when the weight ratio for polyester with date seeds increased from 10% to 15%, the maximum Young’s modulus decreased by 54%. When the weight rat

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

This study aimed to fabricate a curcumin@platinum nanohybrid (CUR@Pt NPs) through a green tea–based synthesis method and to evaluate its various functions, including antioxidant, burn-healing, and selective anticancer activities against PANC-1 pancreatic cancer cells. Green tea polyphenols served as natural reducing and stabilizing agents, facilitating an eco-friendly, single-step manufacturing process. Physicochemical characterization confirmed successful nanohybrid formation: a CUR@Pt band appeared at 457 nm in the UV–Vis spectrum, XRD displayed crystalline platinum peaks at 2θ = 46.9°, and 67.0°, matching the (200), and (220) planes, respectively, and TEM images showed well-dispersed spherical nanoparticles with an average siz