Results 161 to 170 of about 10,615 (256)

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Autonomous AI‐Driven Design for Skin Product Formulations

Advanced Intelligent Discovery, EarlyView.
This review presents a comprehensive closed‐loop framework for autonomous skin product formulation design. By integrating artificial intelligence‐driven experiment selection with automated multi‐tiered assays, the approach shifts development from trial‐and‐error to intelligent optimisation.
Yu Zhang, Yongrui Xiao, Chunlin Chen, Dimitrios Tsaoulidis, Kai Yang, Tao Chen   +5 more
wiley   +1 more source

Computation Offloading Strategy Based on Multi-Agent Reinforcement Learning in Vehicular Edge Computing Networks. [PDF]

Sensors (Basel)
Liu Y, Sun Q, Liu Z.
europepmc   +1 more source

Enhancing Sensitivity across Scales with Highly Sensitive Hall Effect‐Based Auxetic Tactile Sensors

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Herein, a tactile sensor based on hall‐effect sensors with an auxetic structure, called Hall effect‐based auxetic tactile sensor (HEATS), is proposed. The change in magnetism resulting from the deformation of the auxetic structure is utilized for sensing.
Youngheon Yun, Dongchan Lee, Soyeon Lee, Salvador Pané, Josep Puigmartí‐Luis, Sungwoo Chun, Bumjin Jang   +6 more
wiley   +1 more source

Adaptive traffic signal control using deep reinforcement learning: Toward smarter and safer urban mobility. [PDF]

PLoS One
Alanazi F, Armghan A, Tanveer M, Yousef A.   +3 more
europepmc   +1 more source

Extending Battery Usage Time of a Heavy‐Duty Mecanum‐Wheeled Autonomous Electric Vehicle Used in Iron–Steel Industry by Considering Wheel Slippage

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
It is a fact that slippage causes tracking errors in both longitudinal and lateral directions which results to have less travel distance in tracking a reference trajectory. Less travel distance means having energy loss of the battery and carrying loads less than planned.
Gokhan Bayar, Goktug Hambarci, Ali Sezai Demirel   +2 more
wiley   +1 more source

Edge Driven Trust Aware Threat Detection for IoT Enabled Intelligent Transportation Systems. [PDF]

Sensors (Basel)
Alshudukhi KS, Humayun M, Alsalem AO, Khan MF, Haseeb K.   +4 more
europepmc   +1 more source

A Compact, High‐Performance, and Deformation‐Resilient Trielectrode Electrostatic Soft Pump for Soft Robotics

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Existing soft pumps often require tradeoffs between performance and compatibility with soft robotic systems. The proposed trielectrode electrostatic soft pump addresses these limitations through an innovative driving mechanism. Its design, which includes a trielectrode configuration and the use of compliant materials, improves operational efficiency ...
Yangqiao Lin, Xiaoli Yang, Tao Jin, Jieyu Wang, Sicheng Yi, Yue Wang, Songyi Zhong, Tao Yue, Quan Zhang, Yingzhong Tian, Long Li   +10 more
wiley   +1 more source

A study on in-depth accident investigation of intelligent connected vehicles based on reverse scenario construction. [PDF]

Sci Rep
Zhang S, Li X, Zha Z, Xiong H, Wu C, Li P, Kang Z.   +6 more
europepmc   +1 more source

Robust Reinforcement Learning Control Framework for a Quadrotor Unmanned Aerial Vehicle Using Critic Neural Network

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Quadrotor unmanned aerial vehicle control is critical to maintain flight safety and efficiency, especially when facing external disturbances and model uncertainties. This article presents a robust reinforcement learning control scheme to deal with these challenges.
Yu Cai, Yefeng Yang, Tao Huang, Boyang Li   +3 more
wiley   +1 more source