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Nanofluidics have better thermal properties than regular fluids, which makes them useful for heat transfer applications. This research investigated the complex dynamics of confined magnetic forces that influence the rotation of nanostructures and vortex formation in a tri-hybrid nanofluid (Ag, Al2O3, TiO2) flow regime. The study shows that the magnetic field can change the flow and heat transfer of nanofluidic, depending on its direction and strength. The study also provides insights into the complex physics of nanofluid flow and heat transfer, which can help design devices that use nanofluids more efficiently for cooling electronics, harvesting solar energy, and generating power from fuel cells. We used a single-phase model to model the nanofluids while the governing partial differential equations were solved numerically. An alternating-direction implicit approach has been employed to analyze the impact of confined magnetic fields on the nanofluid flow and thermal properties. Unlike previous studies that assumed uniform magnetic fields, we introduced multiple confined magnetic fields in the form of horizontal and vertical strips. Using our custom MATLAB codes, we systematically examined various parameters, including the magnetic field strength, number of strips and their position, and nanoparticle volume fraction, to assess their effects on nanofluid flow and thermal characteristics. Our findings revealed that the confined Lorentz force induced the spinning of tri-hybrid nanoparticles, resulting in a complicated vortex structure within the flow regime. In the absence of a magnetic field, a single symmetric vortex can be seen in the flow field. However, the introduction of magnetic sources stretches this vortex until it splits into two smaller, weaker vortices in the lower cavity, rotating clockwise or counterclockwise. Furthermore, the magnetic field strength significantly reduces both skin friction and the Nusselt number, while Reynolds numbers mainly affect the Nusselt number.

Supplier selection as a multiattribute decision-making (MADM) problem has various inherent uncertainties due to a number of symmetrical variables. In order to handle such information-based uncertainties, rational models like intuitionistic fuzzy sets have already been introduced in the literature. However, a picture fuzzy set (PiFS) with four dimensions of positive, neutral, negative, and rejection is better at capturing and interpreting such kinds of ambiguous information. Additionally, fuzzy parameterization (FPara) is helpful for evaluating the degree of uncertainty in the parameters. This study aims to develop a fuzzy parameterized picture fuzzy soft set (FpPiFSS) by integrating the ideas of PiFS and FPara. This integration is more adaptable and practical since it helps decision makers manage approximation depending on their objectivity and parameterization uncertainty. With the assistance of instructive examples, some of the set-theoretic operations are examined. A decision support framework is constructed using matrix manipulation, preferential weighting, fuzzy parameterized grades based on Pythagorean means, and the approximations of decision makers. This framework proposes a reliable algorithm to evaluate four timber suppliers (initially scrutinized by perusal process) based on eight categorical parameters for real estate projects. In order to accomplish suppliers evaluation, crucial validation outcomes are taken into account, including delivery level, purchase cost, capacity, product quality, lead time, green degree, location, and flexibility. To assess the advantages, dependability, and flexibility of the recommended strategy, comparisons in terms of computation and structure are provided. Consequently, the results are found to be reliable, analog, and consistent despite the use of fuzzy parameterization and picture fuzzy setting. [ABSTRACT FROM AUTHOR]

In this work, an artificial neural network based on the Cuckoo search algorithm (CS-ANN) is implemented for squeezing flow problems. Three problems are considered: the squeezing flow, the MHD squeezing flow, and the flow of the third-grade fluid past a moving belt. First, the approximation for the said nonlinear differential equations is explained and the proposed problems are transformed into the L 2 norms of minimization problems. Then, a well-known Cuckoo search algorithm is used to minimize the norms of each problem to get the best set of weights for artificial neural networks. The outcome of the proposed method is displayed through graphs. Two cases for each problem are discussed consisting of the solution, error, weights, and fitness function, respectively. The numerical results for the state variables are displayed in Tables. The error analysis in each case proves the accuracy of our implemented technique. The results are validated through graphs by comparing CS-ANN results with the gradient descent method. [ABSTRACT FROM AUTHOR]

Human activity recognition (HAR) is the process of interpreting human activities with the help of electronic devices such as computer and machine version technology. Humans can be explained or clarified as gestures, behavior, and activities that are recorded by sensors. In this manuscript, we concentrate on studying the problem of HAR; for this, we use the proposed theory of Aczel and Alsina, such as Aczel–Alsina (AA) norms, and the derived theory of Choquet, such as the Choquet integral in the presence of Atanassov interval-valued intuitionistic fuzzy (AIVIF) set theory for evaluating the novel concept of AIVIF Choquet integral AA averaging (AIVIFC-IAAA), AIVIF Choquet integral AA ordered averaging (AIVIFC-IAAOA), AIVIF Choquet integral AA hybrid averaging (AIVIFC-IAAHA), AIVIF Choquet integral AA geometric (AIVIFC-IAAG), AIVIF Choquet integral AA ordered geometric (AIVIFC-IAAOG), and AIVIF Choquet integral AA hybrid geometric (AIVIFC-IAAHG) operators. Many essential characteristics of the presented techniques are shown, and we also identify their properties with some results. Additionally, we take advantage of the above techniques to produce a technique to evaluate the HAR multiattribute decision-making complications. We derive a functional model for HAR problems to justify the evaluated approaches and to demonstrate their supremacy and practicality. Finally, we conduct a comparison between the proposed and prevailing techniques for the legitimacy of the invented methodologies. [ABSTRACT FROM AUTHOR]