Results 41 to 50 of about 1,649,141 (165)

AAPM Task Group No. 249.B—Essentials and guidelines for clinical medical physics residency training program

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract The establishment of guidelines and curriculum standards for medical physics residency training is a critical component of setting expectations and competencies for the profession. Since the last publication of these standards, residency training has become integrated into the eligibility criteria for most medical physics certification bodies.
Jonathon A. Nye, Joseph P. Dugas, William D. Erwin, David P. Gierga, Darryl G. Kaurin, Stephanie M. Leon, Ho‐Ling Anthony Liu, Zheng Feng Lu, Alphonso W. Magri, Lynn N. Rill, Leah K. Schubert, Beth A. Schueler, Irina Vergalasova, John Vetter, Brian D. Wichman, Amy Shu‐Jung Yu, Dandan Zheng   +16 more
wiley   +1 more source

Extensions of Dupire Formula: Stochastic Interest Rates and Stochastic Local Volatility

, 2020
We derive generalizations of Dupire formula to the cases of general stochastic drift and/or stochastic local volatility. First, we handle a case in which the drift is given as difference of two stochastic short rates. Such a setting is natural in foreign
Ogetbil, Orcan
core  

Radiomics in glioma: emerging trends and challenges

Annals of Clinical and Translational Neurology, Volume 12, Issue 3, Page 460-477, March 2025.
Abstract Radiomics is a promising neuroimaging technique for extracting and analyzing quantitative glioma features. This review discusses the application, emerging trends, and challenges associated with using radiomics in glioma. Integrating deep learning algorithms enhances various radiomics components, including image normalization, region of ...
Zihan Wang, Lei Wang, Yinyan Wang
wiley   +1 more source

CNS Mitochondria‐Derived Vesicle in Blood: Potential Biomarkers for Brain Mitochondria Dysfunction

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Mitochondrial dysfunction is a hallmark of neurodegenerative diseases like Alzheimer's (AD) and Parkinson's (PD). Our goal was to develop practical, noninvasive methods to assess mitochondrial status through the detection of mitochondria‐derived vesicles (MDVs).
Qi Liu, Wentao Chen, Yahong Wu, Zhen Guo, Jun Chen, Chen Tian, Pan Wang, Shaopeng Zeng, Bin Xu, Jing Duan, Shilong Han, Xiao Xiong, Jing Zhang   +12 more
wiley   +1 more source

Random Learning Leads to Faster Convergence in ‘Model‐Free’ ILC: With Application to MIMO Feedforward in Industrial Printing

International Journal of Adaptive Control and Signal Processing, EarlyView.
The cost as a function of the number of experiments for a non‐symmetric 21×21$$ 21\times 21 $$ system. Four approaches are shown: the proposed stochastic conjugate gradient ILC (SCGILC) method (), deterministic conjugate gradient ILC (), stochastic gradient descent ILC () and deterministic gradient descent ILC ().
Leontine Aarnoudse, Tom Oomen
wiley   +1 more source

Stochastic Constraint Programming

, 2008
To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision variables (which we can set) and stochastic variables (which follow a ...
Walsh, Toby
core   +1 more source

Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics

Advanced Engineering Materials, EarlyView.
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani, Aditi Singh, Behnam Ashrafi   +2 more
wiley   +1 more source

Smart Rubber Extrusion Line Combining Multiple Sensor Techniques for AI‐Based Process Control

Advanced Engineering Materials, Volume 27, Issue 8, April 2025.
This publication presents a digitalization approach for a laboratory rubber extrusion line, employing innovative measurement methods and artificial intelligence (AI)‐based process control. The results demonstrate that the measurement systems are capable of detecting changes in the process and extrudate quality.
Alexander Aschemann, Paul‐Felix Hagen, Simon Albers, Robin Rofallski, Sven Schwabe, Mohammed Dagher, Marco Lukas, Sebastian Leineweber, Benjamin Klie, Patrick Schneider, Hagen Bossemeyer, Lennart Hinz, Markus Kästner, Birger Reitz, Eduard Reithmeier, Thomas Luhmann, Hainer Wackerbarth, Ludger Overmeyer, Ulrich Giese   +18 more
wiley   +1 more source

Electrospinning Technology, Machine Learning, and Control Approaches: A Review

Advanced Engineering Materials, Volume 27, Issue 7, April 2025.
Electrospinning produces micro‐ and nanoscale fibers, holding great promise in biomedical engineering. Industrial adoption faces challenges in controlling fiber properties, reproducibility, and scalability. This review explores electrospinning techniques, modeling, and machine learning for process optimization.
Arya Shabani, Gorkem Anil Al, Nael Berri, Bernardo Castro‐Dominguez, Hannah S. Leese, Uriel Martinez‐Hernandez   +5 more
wiley   +1 more source

An Ontology‐Augmented Digital Twin for Fiber‐Reinforced Polymer Structures at the Example of Wind Turbine Rotor Blades

Advanced Engineering Materials, Volume 27, Issue 8, April 2025.
A methodology for establishing an ontology‐augmented structural digital twin for fiber‐reinforced polymer structures dedicated to individual lifetime prediction, in this case, a wind turbine rotor blade, is introduced. The methodology resembles the manufacturing as well as the operation of the structure.
Marc Luger, Alexander Seidel, Ursula Pähler, Sebastian Schröck, Peter Hofmann, Sebastian Kölbl, Klaus Drechsler   +6 more
wiley   +1 more source