Results 61 to 70 of about 11,548 (247)

Physics‐Aware Machine‐Learning‐Driven Inverse Design of Broadband Ultra‐Open Acoustic Metamaterials

Advanced Science, EarlyView.
A physics‐aware machine‐learning framework enables inverse design of ultra‐open acoustic silencers by decoupling spectral and radial design spaces. The approach rapidly identifies broadband, compact, and highly ventilated architectures, while revealing hidden linear design rules that link geometry, impedance matching, and acoustic performance.
Zhiwei Yang, Mengyu Li, Xiaohang Xie, Ao Chen, Thomas G. Bifano, Xin Zhang   +5 more
wiley   +1 more source

The Relationship between Hidden Curriculum Components and Student Professional Adaptability at Tabriz University of Medical Sciences [PDF]

مجله ایرانی آموزش در علوم پزشکی, 2019
Introduction: Hidden curriculum is one of the concepts and topics discussed in the field of curriculum. It has been much considered in education research, but its impacts on the field of higher education have not been seriously taken into account ...
Davoud Tahmasebzadeh sheikhlar, Firooz Mahmoodi, Fatemeh Farajpor   +2 more
doaj  

Enhancing Electrical Impedance Based Deformation Sensing with Dielectric Current Guide

Advanced Electronic Materials, EarlyView.
This work introduces a dielectric‐based field manipulation strategy for electrical impedance tomography in soft robotics. By using silicone as a passive electric field guide, improved deformation sensing accuracy and reduced interference are achieved without embedding conductive components.
Arsen Abdulali, David Hardman, Yue Xie, Fumiya Iida   +3 more
wiley   +1 more source

Efficient In‐Hardware Matrix–Vector Multiplication and Addition Exploiting Bilinearity of Schottky Barrier Transistors Processed on Industrial FDSOI

Advanced Electronic Materials, EarlyView.
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez, Niladri Bhattacharjee, Yuxuan He, Giulio Galderisi, Brojogopal Sapui, Sara Mannaa, Ian O'Connor, Violetta Sessi, Peter Javorka, Thomas Mikolajick, Jens Trommer   +10 more
wiley   +1 more source

Curriculum Definition Revisited

Acta Medica Iranica
The definition of "curriculum" has been the subject of scholarly debate for decades. This commentary revisits one of the most widely accepted definitions of curriculum in health profession education and offers a revised definition.
Nasim Gheshlaghi Azar, Fakhrosadat Hosseini   +1 more
doaj   +1 more source

On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification

Advanced Electronic Materials, EarlyView.
ABSTRACT Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modest hardware requirements. Memristor‐based circuits are particularly promising for RC, as their intrinsic dynamics can reduce network size and parameter overhead in tasks such as time‐series ...
Rishona Daniels, Duna Wattad, Ronny Ronen, David Saad, Shahar Kvatinsky   +4 more
wiley   +1 more source

Using a Group Exercise to Teach About the Hidden Curriculum

MedEdPORTAL, 2015
Introduction Whether positive or negative, the hidden curriculum is a powerful force in residents' professional formation and one place where professionalism is learned. As opposed to the explicit didactic curriculum or the implicit bedside teaching that
Kathleen Crapanzano, Ann Schwartz, Jacob Sperber, Susan Stagno, Lannis Tynes   +4 more
doaj   +1 more source

Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization

Advanced Electronic Materials, EarlyView.
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali, David Lehninger, Florencio Sánchez, Ignasi Fina   +3 more
wiley   +1 more source

Physics‐encoded transfer learning for scale‐up modeling of CHO cell bioreactors

AIChE Journal, EarlyView.
Abstract Developing reliable predictive models for mammalian cell bioreactors, particularly Chinese hamster ovary (CHO) cultures widely used in biopharmaceutical manufacturing, remains challenging due to severe data scarcity in industrial‐scale reactors.
Muyang Li, Ming Xiao, Zhe Wu
wiley   +1 more source

The Interoperability Challenge in DFT Workflows Across Implementations

Advanced Intelligent Discovery, EarlyView.
Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen, Tushar Singh Thakur, Manuel Dillenz, Johan M. Carlsson, Celso R. C. Rêgo, Eibar Flores, Hamidreza Hajiyani, Felix Hanke, Juan María García Lastra, Wolfgang Wenzel, Nicola Marzari, Tejs Vegge, Giovanni Pizzi, Ivano E. Castelli   +13 more
wiley   +1 more source