A Novel Numerical Treatment of Nonlinear and Nonequilibrium Model of Gradient Elution Chromatography considering Core-Shell Particles in the Column

Ahmad, Abdulaziz Garba; Kaabar, Mohammed K. A.; Rashid, Saima; Abid, Мuhammad

doi:10.1155/2022/1619702

Cited by 2 publications

(1 citation statement)

References 31 publications

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“…This review of the literature integrates findings from several research disciplines to offer a thorough overview of decision-making [37][38][39][40] in the selection of a mobile phone. A comprehensive viewpoint can be obtained by comprehending consumer behavior, ideas surrounding technology adoption, the function of DSS, and similarities to agricultural decision-making [41][42][43]. Future studies can examine the changing dynamics of mobile phone selection and the influence of developing technologies on decision-making processes as technology develops [42][43][44][45].…”

Section: Introductionmentioning

confidence: 99%

Decision Support System for Mobile Phone Selection Utilizing Fuzzy Hypersoft Sets and Machine Learning

Hamid,

Abid

2024

JIMD

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In the dynamic landscape of mobile technology, where a myriad of options burgeons, compounded by fluctuating features, diverse price points, and a plethora of specifications, the task of selecting the optimum mobile phone becomes formidable for consumers. This complexity is further exacerbated by the intrinsic ambiguity and uncertainty characterizing consumer preferences. Addressed herein is the deployment of fuzzy hypersoft sets (FHSS) in conjunction with machine learning techniques to forge a decision support system (DSS) that refines the mobile phone selection process. The proposed framework harnesses the synergy between FHSS and machine learning to navigate the multifaceted nature of consumer choices and the attributes of the available alternatives, thereby offering a structured approach aimed at maximizing consumer satisfaction while accommodating various determinants. The integration of FHSS is pivotal in managing the inherent ambiguity and uncertainty of consumer preferences, providing a comprehensive decision-making apparatus amidst a plethora of choices. The elucidation of this study encompasses an easy-to-navigate framework, buttressed by sophisticated Python codes and algorithms, to ameliorate the selection process. This methodology engenders a personalized and engaging avenue for mobile phone selection in an ever-evolving technological epoch. The fidelity to professional terminologies and their consistent application throughout this discourse, as well as in subsequent sections of the study, underscores the meticulous approach adopted to ensure clarity and precision. This study contributes to the extant literature by offering a novel framework that melds the principles of fuzzy set (FS) theory with advanced computational techniques, thereby facilitating a nuanced decision-making process in the realm of mobile phone selection.

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Section: Introductionmentioning

confidence: 99%

Decision Support System for Mobile Phone Selection Utilizing Fuzzy Hypersoft Sets and Machine Learning

Hamid,

Abid

2024

JIMD

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Magneto Mixed Convection of Williamson Nanofluid Flow through a Double Stratified Porous Medium in Attendance of Activation Energy

Tamilzharasan¹,

Karthikeyan²,

Kaabar

et al. 2022

MCA

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This article aims to develop a mathematical simulation of the steady mixed convective Darcy–Forchheimer flow of Williamson nanofluid over a linear stretchable surface. In addition, the effects of Cattaneo–Christov heat and mass flux, Brownian motion, activation energy, and thermophoresis are also studied. The novel aspect of this study is that it incorporates thermal radiation to investigate the physical effects of thermal and solutal stratification on mixed convection flow and heat transfer. First, the profiles of velocity and energy equations were transformed toward the ordinary differential equation using the appropriate similarity transformation. Then, the system of equations was modified by first-order ODEs in MATLAB and solved using the bvp4c approach. Graphs and tables imply the impact of physical parameters on concentration, temperature, velocity, skin friction coefficient, mass, and heat transfer rate. The outcomes show that the nanofluid temperature and concentration are reduced with the more significant thermal and mass stratification parameters estimation.

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A Novel Numerical Treatment of Nonlinear and Nonequilibrium Model of Gradient Elution Chromatography considering Core-Shell Particles in the Column

Cited by 2 publications

References 31 publications

Decision Support System for Mobile Phone Selection Utilizing Fuzzy Hypersoft Sets and Machine Learning

Decision Support System for Mobile Phone Selection Utilizing Fuzzy Hypersoft Sets and Machine Learning

Magneto Mixed Convection of Williamson Nanofluid Flow through a Double Stratified Porous Medium in Attendance of Activation Energy

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