Versatile Modeling Platform for Multilevel Hybrid Modeling of Physiological Systems

Silica -magnetic inorganic hybrid nanomaterials as versatile sensing platform

Several hybrid sensing materials, which are organized by interaction of organic molecules onto inorganic supports, have been developed as a novel and hopeful class of hybrid sensing probes. The hybrid silica-magnetic based sensors provide perfect properties for production of various devices in sensing technology. The hybridization of silica and magnetic NPs as biocompatible, biodegradable and s...

SECURING INTERPRETABILITY OF FUZZY MODELS FOR MODELING NONLINEAR MIMO SYSTEMS USING A HYBRID OF EVOLUTIONARY ALGORITHMS

In this study, a Multi-Objective Genetic Algorithm (MOGA) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear Multi-input Multi-output (MIMO) systems. In the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. Furthermore, se- curing low-level and high-level ...

Modeling of Hybrid Systems

Nano-gels: A versatile nano -carrier platform for drug delivery systems: A mini review

Nowadays the application of nanotechnology in different biomedical fields such as drug delivery is increasing due to its unique advantages. With this in mind, it is widely believed that nanogels as the nanometer-sized networked polymeric particles have a considerable impact on drug delivery systems as biocompatible nanocarriers due to their unique characteristics such as high loading capacity, ...

Mathematical Modeling of Physiological Systems

Although mathematical modeling has a long and very rich tradition in physiology, the recent explosion of biological, biomedical, and clinical data from the cellular level all the way to the organismic level promises to require a renewed emphasis on computational physiology, to enable integration and analysis of vast amounts of life-science data. In this introductory chapter, we touch upon four ...