Results 231 to 240 of about 78,438 (302)

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

The AI-POCUS Revolution is Here-Are Family Physicians and Our Health Systems Ready? [PDF]

Ann Fam Med
Szkwarko D, Elias H, Ramos M, Bergman K.
europepmc   +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

Equity-focused investment strategies to reduce maternal mortality in the Philippines: a subnational analysis using EQUIST. [PDF]

J Glob Health
Whitley K, Lebedeva P, Christie AC, Sim A, Thompson D, Hukpati S, Balaji L.   +6 more
europepmc   +1 more source

Stochastic‐MTJ Sampler Arrays for In‐Array Monte–Carlo Estimation

Advanced Electronic Materials, EarlyView.
A low‐energy‐barrier magnetic tunnel junction array is operated as a probability‐domain sampler: each cell's random switching, programmed through a shared digital‐to‐analog converter, makes the per‐column multiply–accumulate an unbiased Monte–Carlo expectation estimator that returns both a mean and a calibrated uncertainty.
Ran Zhang, Nellie Laleni, Sina Ranjbar, Andreas Tsiougkos, Nandakishor Yadav, Vasilis Pavlidis, Thomas Kämpfe   +6 more
wiley   +1 more source

Participatory budgeting with cumulative votes. [PDF]

Theory Decis
Skowron P, Slinko A, Szufa S, Talmon N.
europepmc   +1 more source

Bridging Performance and Fate: A Framework for Sustainable, Composite‐Based Flexible Electronic Systems

Advanced Electronic Materials, EarlyView.
Composite‐based flexible electronics integrate biodegradable polymers, conductive networks, and multilayer device architectures to balance electrical performance, mechanical durability, and controlled degradation. Interfacial engineering and encapsulation regulate transport stability and operational lifetime, while programmed disassembly enables ...
Sayam, Sangho Cho
wiley   +1 more source

Editorial: Employee resilience, volume II. [PDF]

Front Psychol
Martínez-González JA, Álvarez-Albelo CD, Kobylińska U, Barrientos-Báez A.   +3 more
europepmc   +1 more source

Establishment of a competence office for patient involvement (PPI Office) at a German university hospital. [PDF]

Res Involv Engagem
Thomas BC, Dominick F, Seidel-Glätzer A, Ottawa GB, Luntz SP.   +4 more
europepmc   +1 more source