ahajournals.org

Acute Infarct Core Volume Estimation on Noncontrast Computed Tomography With a Deep Learning Algorithm

In the first phase, stroke activations with baseline NCCT and CT angiography were used to train an aICV‐NCCT. The algorithm was then internally validated using intraclass correlations and Intersection ...
IEEE

Multi-Task Deep Reinforcement Learning for Terahertz NOMA Resource Allocation With Hybrid Discrete and Continuous Actions

Abstract: Terahertz (THz) non-orthogonal multiple access (NOMA) networks have great potential for next-generation wireless communications, by providing promising ultra-high data rates and user ...
C&EN

Surrogate Based Genetic Algorithm Method for Efficient Identification of Low-Energy Peptide Structures

You are free to share (copy and redistribute) this article in any medium or format within the parameters below: Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must ...
Frontiers

Distributed Imitation-Orientated Deep Reinforcement Learning Method for Optimal PEMFC Output Voltage Control

In order to improve the stability of proton exchange membrane fuel cell (PEMFC) output voltage, a data-driven output voltage control strategy based on regulation of the duty cycle of the DC-DC ...
Frontiers

Qudits and High-Dimensional Quantum Computing

Qudit is a multi-level computational unit alternative to the conventional 2-level qubit. Compared to qubit, qudit provides a larger state space to store and process information, and thus can provide ...
IEEE

Efficient Sparse Code Multiple Access Decoder Based on Deterministic Message Passing Algorithm

Abstract: Being an effective non-orthogonal multiple access (NOMA) technique, sparse code multiple access (SCMA) is promising for future wireless communication. Compared with orthogonal techniques, ...