Results 91 to 100 of about 49,758 (267)

A Language‐Guided Multimodal Foundation Model for Zero‐Shot and Multi‐Task Brain Signal Analysis

Advanced Intelligent Systems, EarlyView.
METIS aligns brain signals with natural‐language instructions to enable zero‐shot and multi‐task brain signal analysis. Pretrained on over 70 000 h of EEG and iEEG recordings, it generalizes across sleep stage classification, epilepsy detection, and neurological disorder diagnosis, providing a scalable foundation model for clinically meaningful brain ...
Mingzhi Chen, Yiyu Gui, Guibo Luo, Yuchao Yang   +3 more
wiley   +1 more source

Ecoefficiency Analysis and Regression in Data Conversion for Spiking Neural Network Training

Advanced Intelligent Systems, EarlyView.
The environmental footprint of spiking neural networks is quantified during dataset encoding and training for autonomous driving regression across three benchmarks. Temporal depth emerges as the dominant driver of energy consumption and CO2 emissions, while the accuracy–energy trade‐off proves dataset‐dependent. On conventional hardware, spiking models
Fernando S. Martínez, Raúl Parada, Jordi Casas‐Roma, Laia Subirats   +3 more
wiley   +1 more source

Investigations on drone-mounted active noise control

Acta Acustica
Although drones have many potential applications including parcel delivery and surveillance, their deployment in urban areas is limited by their noise levels.
Steiner Jonas, Hilgemann Florian, Jax Peter   +2 more
doaj   +1 more source

Benchmarking Data‐Driven Control of Octopus‐Inspired Soft Arms in Underwater Environment

Advanced Intelligent Systems, EarlyView.
Underwater soft robots present safe, compliant interaction, yet reproducible control remains scarce. This work presents an open benchmark for octopus‐inspired arms: a smooth, velocity‐diverse data‐collection scheme produces a compact dataset to train a vanilla policy.
Muhammad Sunny Nazeer, Yasmin Tauqeer Ansari, Emanuele Solfiti, Baljinder Singh Bal, Matteo Lo Preti, Barbara Mazzolai, Cecilia Laschi   +6 more
wiley   +1 more source

Forecasting Solar Energy Generation and Household Energy Usage for Efficient Utilisation

Energies
In this study, a prototype was developed for the effective utilisation of a domestic solar power plant. The basic idea is to switch on certain electrical appliances when the surplus of generated energy is predicted one hour in advance, for example ...
Aistis Raudys, Julius Gaidukevičius
doaj   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source

Output quality improvement for single‐phase inverter in V2G system

IET Power Electronics
In vehicle‐to‐grid (V2G) applications, a voltage source inverter (VSI) directly connects to a residential load or grid for DC/AC conversion and power flow control.
Yipei Wang, Ancheng Liu, A‐Rim Kwak, Sung‐Jun Park   +3 more
doaj   +1 more source

A Hybrid Magnetic Actuation System for Single‐Input Multistates Stabilization: Application to pH‐Responsive Drug Delivery

Advanced Intelligent Systems, EarlyView.
This study presents an integrated proof‐of‐concept robotic platform for targeted delivery applications. A hybrid magnetic actuation system achieves single‐input (z) multistate stabilization (x, y, ϕ, and θ) for precise capsule transport with submillimeter positioning accuracy.
Sejun Park, Hanbi Park, Suho Lee, Bohyeon Kim, Jiseong Ryu, ChangKyu Yoon, Donghoon Son   +6 more
wiley   +1 more source

Vector‐Based SparseGPT: A Vector‐Based Sparsity Method for Large Language Model

Advanced Intelligent Systems, EarlyView.
Conventional pruning such as SparseGPT produces harmful accumulated errors through step‐by‐step weight editing. V‐SparseGPT prunes and updates target weights simultaneously to curb these errors for N:M structured sparsity. Block‐sparsity and layer‐parallel sparsity greatly boost pruning efficiency.
Junfei He, Mingxi Tan, Junchao Dong, Pengfei Ying   +3 more
wiley   +1 more source

Residual Strength Prediction of Chemically Reactive Two‐Phase Nanofluid Flow in a Bingham–Papanastasiou Rheological Theory Using a Morlet‐Based Wavelet Neural Network Approach

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT The behavior of nanofluid flow involving a zero‐mass flux condition has received considerable interest because of a realistic scenario. In reality, this condition confines the optimistic accumulation or disappearance of nanoparticles past a sheet, constructing a more physically realistic demonstration through several applications, such as heat
Umair Khan, Hamza Rauf, Aurang Zaib, J. K. Madhukesh   +3 more
wiley   +1 more source