Results 151 to 160 of about 36,909 (230)

A Survey for Deep Reinforcement Learning Based Network Intrusion Detection

Applied AI Letters, Volume 7, Issue 2, June 2026.
This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang, Alberto Acuto, Yihang Zhou, Dominik Wojtczak   +3 more
wiley   +1 more source

Modeling cognition through adaptive neural synchronization: a multimodal framework using EEG, fMRI, and reinforcement learning. [PDF]

Front Comput Neurosci
Hall R, Jackson M, Maleki M, Crogman HT.
europepmc   +1 more source

Spatiotemporal Encoding With Nonlinear Gradient Hardware Using Pulseq: From Principles to Practical Demonstration

Magnetic Resonance in Medicine, Volume 95, Issue 6, Page 3187-3198, June 2026.
Purpose Provide the theoretical foundation and the first practical demonstration of spatiotemporal encoding (SPEN) using additional nonlinear gradient hardware. Methods The quadratic phase profile can be generated either by a chirped‐RF pulse combined with a constant gradient or, directly, by a quadratic gradient pulse.
Andreas Holl, Frank Zijlstra, Maxim Zaitsev, Jakob Hufschmidt, Shadi Tashakori, Nils Schallner, Thomas Stieglitz, Jens Gröbner, Sebastian Littin   +8 more
wiley   +1 more source

Toward Super‐Resolution Reconstruction of Diffusion–Relaxation MRI Using Slice Excitation With Random Overlap (SERO)

Magnetic Resonance in Medicine, Volume 95, Issue 6, Page 3213-3226, June 2026.
ABSTRACT Purpose Diffusion MRI probes tissue microstructure, but low SNR and limited resolution hinder detection of features and parameter estimates. We introduce slice excitation with random overlap (SERO), which enables variable repetition times (TRs) and diffusion weighting within a single shot.
Felix Mortensen, Jakub Jurek, Jens Sjölund, Geraline Vis, Ronnie Wirestam, Malwina Molendowska, Andrzej Materka, Filip Szczepankiewicz   +7 more
wiley   +1 more source

Calibration of Low-Cost Sensors for PM₁₀ and PM_2.5 Based on Artificial Intelligence for Smart Cities. [PDF]

Sensors (Basel)
Gómez R, Rodríguez J, Ferro R.
europepmc   +1 more source

An Overview of Artificial Intelligence and Machine Learning Approaches for Building Energy Analysis, Characterization, Control, and Grid Support Services Provision

WIREs Energy and Environment, Volume 15, Issue 2, June 2026.
Artificial Intelligence and Machine Learning Approaches used in Building Energy Analysis, Control, and Provision of Grid Support Services. ABSTRACT Increasing penetrations of variable renewable energy sources like wind and solar photovoltaic (PV) systems are challenging power system stability worldwide.
Jack S. Bryant, Hangxin Li, Nawanjana Maheepala, Xiaoyu Lin, Mingkun Dai, Binglong Han, Robin Guan, Lasantha Meegahapola, Shengwei Wang, Dilan Robert, Liuping Wang, Fu Xiao   +11 more
wiley   +1 more source

Generalized FitzHugh-Nagumo equations with Caputo gH-differentiability: A novel fuzzy fractional approach to digital memristor networks. [PDF]

PLoS One
Yousuf M, Ahmad U, Muhammad G, Alsulami H.   +3 more
europepmc   +1 more source

The United States Magnetotelluric Array and the National Impedance Map

Reviews of Geophysics, Volume 64, Issue 2, June 2026.
Abstract The United States Magnetotelluric Array (USMTArray) data set, collected in the years 2006–2024, consists of more than 1,700 long‐period magnetotelluric stations covering the entirety of the contiguous United States on a quasi‐regular 70 km grid.
Anna Kelbert, Paul A. Bedrosian, Adam Schultz, Gary D. Egbert, Louise Pellerin, Jeffrey J. Love, Andrew Frassetto, Benjamin S. Murphy   +7 more
wiley   +1 more source

Sensorimotor Frequency Tagging Is Enhanced by Auditory and Audiovisual but Not Visual, Inputs During a Body-Walking Task. [PDF]

Psychophysiology
Matamala-Gomez M, Vilà-Balló A, Cucurell D, Tajadura-Jiménez A, Rodriguez-Fornells A.   +4 more
europepmc   +1 more source

Advances in Electrocardiogram‐Based Non‐Invasive Blood Glucose Monitoring Technology

Diabetes, Obesity and Metabolism, Volume 28, Issue 6, Page 4445-4463, June 2026.
ABSTRACT Blood glucose monitoring is fundamental to diabetes management, yet traditional invasive methods are limited by patient discomfort and infection risks. In recent years, electrocardiogram (ECG), a conventional tool for cardiovascular assessment, has gained attention as a prospective method for non‐invasive blood glucose monitoring.
Qi Zeng, Jiaying Ni, Ziyi Zhang, Jinghao Cai, Jingyi Lu, Jian Zhou   +5 more
wiley   +1 more source