Additive Manufacturing of Neuromorphic Systems
The crossover of additive Manufacturing (AM) and neuromorphic engineering promises a new paradigm in the fabrication of intelligent hardware—one that is sustainable, scalable, cost‐efficient, and customizable. The AM‐printed neuromorphic hardware (electronics and mechanical systems) is examined, and we discussed the technological integration.
Jiongyi Yan +3 more
wiley +1 more source
A framework for processing large-scale health data in medical higher-order correlation mining by quantum computing in smart healthcare. [PDF]
Mei P, Zhang F.
europepmc +1 more source
Coupling Enhanced Diffractive Deep Neural Network with Structural Nonlinearity
Here, structural nonlinearity is introduced into diffractive deep neural networks (D2NNs) by incorporating encoding‐free data repetition layers, enabling high‐order optical nonlinearity while reducing the system complexity. Additionally, to enhance the design accuracy of D2NNs, a graph neural network is developed to characterize the coupling effects ...
Ouling Wu +5 more
wiley +1 more source
A Hybrid Scale-Up and Scale-Out Approach for Performance and Energy Efficiency Optimization in Systolic Array Accelerators. [PDF]
Sun H, Shen J, Zhang C, Liu H.
europepmc +1 more source
Dynamic Estimation of Task Level Parallelism with Operating System Support
Luong Dinh Hung, Shuichi Sakai
openalex +2 more sources
SARS‐CoV‐2 Antibody Levels and Infections in Multiple Vaccinated Employees Over Time
ABSTRACT This prospective cohort study aimed to monitor the humoral immune response to SARS‐CoV‐2 proteins over 3 years in relation to repeated vaccination or infection. Quantitative immunoassays traceable to international IgG units were used to measure and compare IgG levels against Wuhan type and Omicron spike‐S1 and nucleocapsid proteins over 3 ...
Ingrid Sander +11 more
wiley +1 more source
Strategies to Improve the Robustness and Generalizability of Deep Learning Segmentation and Classification in Neuroimaging. [PDF]
Tran AT, Zeevi T, Payabvash S.
europepmc +1 more source
Design of proteins by parallel tempering in the sequence space
Abstract Computational design of new proteins is often performed by optimizing the amino acid sequence. This sequence is characterized by an energy (lower energy means better propensity to form the desired 3D structure) that is sampled and minimized. Here, we use the parallel tempering algorithm to accelerate this task.
Preet Kalani, Vojtěch Spiwok
wiley +1 more source
An opponent striatal circuit for distributional reinforcement learning. [PDF]
Lowet AS +5 more
europepmc +1 more source

