Results 141 to 150 of about 93,904 (259)

Multilevel Models for the Distribution of Hosts and Symbionts. [PDF]

PLoS One, 2016
Joseph MB, Stutz WE, Johnson PT.
europepmc   +1 more source

Non‐Destructive, Reference‐Free Quantitative Analysis of TaOx Memristive Devices Using Soft X‐Ray Radiation

Advanced Electronic Materials, EarlyView.
A non‐destructive, quantitative approach has been developed to explore the nanoscale dynamics of TaOx‐based memristive devices. The utilization of nano‐X‐ray fluorescence analysis enables the direct probing of spatially resolved elemental distributions, including those present in buried layers, that are critical for the resistive switching.
André Wählisch, Xin Zheng, Andreas Haidl, Jan Weser, Christian Stadelhoff, Marc Dummin, Leona J. Bauer, Rainer Unterumsberger, Ilia Valov, Burkhard Beckhoff   +9 more
wiley   +1 more source

Estimation of Random Coefficient Multilevel Models in the Context of Small Numbers of Level 2 Clusters. [PDF]

Educ Psychol Meas, 2019
Bolin JH, Finch WH, Stenger R.
europepmc   +1 more source

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

Evaluating two small-sample corrections for fixed-effects standard errors and inferences in multilevel models with heteroscedastic, unbalanced, clustered data. [PDF]

Behav Res Methods
Zhang Y, Lai MHC.
europepmc   +1 more source

Enabling Quantum‐Compatible Nonvolatile Memory: Cryogenic Evaluation of 1T1R HfO2‐Based RRAM From 300 to 1.5 K

Advanced Electronic Materials, EarlyView.
Resistive memory devices are explored for operation at extremely low temperatures relevant to quantum computing. The study reveals how transistor behavior strongly influences memory performance under cryogenic conditions and introduces an optimized programming strategy.
Emilio Pérez‐Bosch Quesada, Alberto Mistroni, Ruolan Jia, Keerthi Dorai Swamy Reddy, Markus Fritscher, Felix Reichmann, Oliver Skibitzki, Juan Bautista Roldán, Helena Castán, Salvador Dueñas, Christian Wenger, Eduardo Pérez   +11 more
wiley   +1 more source

SPICE‐Compatible Compact Modeling of Cuprate‐Based Memristors Across a Wide Temperature Range

Advanced Electronic Materials, EarlyView.
A physics‐guided compact model for YBCO memristors is introduced, incorporating carrier trapping, field‐induced detrapping, and a differential balance equation to describe their switching dynamics. The model is compared with experiments and implemented in LTspice, allowing realistic circuit‐level simulations.
Thomas Günkel, Aleix Barrera, Lluís Balcells, Narcís Mestres, Enrique Miranda, Anna Palau, Jordi Suñé   +6 more
wiley   +1 more source

Using 3 Health Surveys to Compare Multilevel Models for Small Area Estimation for Chronic Diseases and Health Behaviors. [PDF]

Prev Chronic Dis, 2018
Wang Y, Holt JB, Xu F, Zhang X, Dooley DP, Lu H, Croft JB.   +6 more
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

Multilevel models improve precision and speed of IC50 estimates. [PDF]

Pharmacogenomics, 2016
Vis DJ, Bombardelli L, Lightfoot H, Iorio F, Garnett MJ, Wessels LF.   +5 more
europepmc   +1 more source