Dynamic modelling and parameter identification stand at the forefront of advancing robotics, enabling the precise simulation and control of robotic systems in increasingly complex real-world ...

Researchers demonstrate how mathematical modeling combined with dynamic biomarkers can be used to characterize metastatic disease and identify appropriate therapeutic approaches to improve patient ...

Many personal transportation-related decisions—such as vehicle purchases—are influenced by life events, like the birth of a child or a change in employment. Modeling tools that reflect how life ...

The proposed intelligent analysis method bridges high-fidelity modeling and computational efficiency. It uses an iterative algorithm to identify optimal mode shapes ...

Researchers from Jordan’s Al al-Bayt University have created comprehensive theoretical dynamic modeling to analyze the performance of building integrated photovoltaic thermal (BIPV/T) systems. The ...

Implementing Cancer Registry Data With the PCORnet Common Data Model: The Greater Plains Collaborative Experience Current image-based long-term risk prediction models do not fully use previous ...

Researchers at the Department of Energy’s Oak Ridge National Laboratory (ORNL) have developed a dynamic modeling method that uses machine learning to provide accurate simulations of grid behavior and ...

Unfortunately, this book can't be printed from the OpenBook. If you need to print pages from this book, we recommend downloading it as a PDF. Visit NAP.edu/10766 to get more information about this ...

Vapor compression cycles are predominantly used in air-conditioning, heat pump and refrigeration equipment. A good understanding of transient behaviors of vapor compression systems is critical to ...