The designer must find the optimum match between the object's technical and economic needs and the performance and production requirements of the various material options when choosing material for an engineering application. This study proposes an integrated (hybrid) strategy for selecting the optimal material for an engineering design depending on design requirements. The primary objective is to determine the best candidate material for the drone wings based on Ashby's performance indices and then rank the result using a grey relational technique with the entropy weight method. Aluminum alloys, titanium alloys, composites, and wood have been suggested as suitable materials for manufacturing drone wings. The requirement

The main objective of the central bank is to achieve price stability and target in fractionates. Therefore, the bank sought to use modern tools and policies in order to reduce the negative effects of the accumulation of foreign reserves represented by monetary sterilization, similar to developed and developing countries alike, but with different available tools that are possible and imposed by the local financial and monetary environments, such as the window for buying and selling foreign currency, open market operations and deposit facilities. And lending existing. Because any in crease in the monetary base resulting from the accumulation of foreign reserves will affect price stability directly due to the consumer nature of the

      The current study objective is to synthesize activated carbon (AC) from compressed wood using the ZnCl2 activating agent and to assess the ciprofloxacin (CIP) elimination efficiency in simulated wastewater. The produced AC was characterized using multiple techniques, including SEM, BET, FTIR, AFM, and XRD. The adsorbent demonstrates high adsorption performance, achieving 91% removal of CIP within 5 hours at an initial pollutant concentration of 100 mg/L with an AC dose of 2 g/L. Experimental data correspond to the Freundlich isotherm model (R² = 0.995) as well as the Langmuir competitive fitting (R² = 0.99), while the root mean square error (RMSE) equation best fits the Langmuir model. Moreover, the pseudo-second-order

The aim of this research to show the role of some enzymes in pathological mechanism of rheumatoid arthritis (RA) disease. Sixty patients with RA and matched number of apparently healthy volunteers were included in the study. Spectrophotometric methods were used to determine Peroxy nitrite (ONOO), Nitric oxide (NO), Nitric oxide synthase activity (NOS) cycloxygenase-2 activity (COX-2), glutathione peroxidase (GPX) activity and superoxide dismutase (SOD) activity in serum of both groups. Colorimetric assay kits were used to determine Iron. Rheumatoid factor (RF) was determined using Imuno-Latex kit. ONOO, NO levels, and NOS activity were significantly higher in the patients compared to the control group. Conversely, Iron level, SOD

A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

Grabisch and Labreuche have recently proposed a generalization of capacities, called the bi-capacities. Recently, a new approach for studying bi-capacities through introducing a notion of ternary-element sets proposed by the author. In this paper, we propose many results such as bipolar Mobius transform, importance index, and interaction index of bi-capacities based on our approach.

Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad