In this paper, three approximate methods namely the Bernoulli, the Bernstein, and the shifted Legendre polynomials operational matrices are presented to solve two important nonlinear ordinary differential equations that appeared in engineering and applied science. The Riccati and the Darcy-Brinkman-Forchheimer moment equations are solved and the approximate solutions are obtained. The methods are summarized by converting the nonlinear differential equations into a nonlinear system of algebraic equations that is solved using Mathematica®12. The efficiency of these methods was investigated by calculating the root mean square error (RMS) and the maximum error remainder (𝑀𝐸𝑅n) and it was found that the accuracy increases with increasi

In many applications such as production, planning, the decision maker is important in optimizing an objective function that has fuzzy ratio two functions which can be handed using fuzzy fractional programming problem technique. A special class of optimization technique named fuzzy fractional programming problem is considered in this work when the coefficients of objective function are fuzzy. New ranking function is proposed and used to convert the data of the fuzzy fractional programming problem from fuzzy number to crisp number so that the shortcoming when treating the original fuzzy problem can be avoided. Here a novel ranking function approach of ordinary fuzzy numbers is adopted for ranking of triangular fuzzy numbers with simpler an

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

This work introduces a newly synthesized triazole derivative, 5-([(2-furanyl)methyl]-thiomethyl)-4-(naphtha-2-yl)-3-hydroxyl-4H-1,2,4-triazole (FTNT), as an effective corrosion inhibitor for carbon steel A106 G/B in 0.1 M HCl solution. The structure of the novel derivative was confirmed by FTIR, 1 H NMR, and 13 C NMR spectra. Potentiodynamic polarization measurements reveal that FTNT markedly suppresses corrosion, with inhibition efficiency reaching 81.6% at 600 ppm. Thermodynamic analysis indicates spontaneous, physisorption/chemisorption-augmented adsorption of FTNT on the steel surface, best described by the Freundlich isotherm. Atomic force microscopy (AFM) surface examination demonstrated that a protective FTNT coating precipitated on

Organic Permeable Base Transistors (OPBTs) reach a very high transit frequency and large on-state currents. However, for a later commercial application of this technology, a high operational stability is essential as well. Here, the stability of OPBTs during continuous cycling and during base bias stress is discussed. It is observed that the threshold voltage of these transistors shifts toward more positive base voltages if stressed by applying a constant potential to the base electrode for prolonged times. With the help of a 2D device simulation, it is proposed that the observed instabilities are due to charges that are trapped on top of an oxide layer formed around the base electrode. These charges are thermally released after rem

The research demonstrates new species of the games by applying separation axioms via  sets, where the relationships between the various species that were specified and the strategy of winning and losing to any one of the players, and their relationship with the concepts of separation axioms via  sets have been studied.