Results 141 to 150 of about 905,072 (286)
Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto +3 more
wiley +1 more source
Triboelectric Nanogenerators for Vehicle Energy Harvesting and Intelligent Sensing. [PDF]
Zhu C, Ren Y, Xi Z, Du H.
europepmc +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
A twin delayed deep deterministic-based control method for a full vehicle semi-active suspension system. [PDF]
Wan Y +6 more
europepmc +1 more source
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker +2 more
wiley +1 more source
Vehicle Pose Measurement with a Single Image via the Double-Dual-Ellipse Feature of Wheel Rims. [PDF]
Xu G, Wang R, Lin H.
europepmc +1 more source
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 +2 more
wiley +1 more source
Instability detection and overload controlling system: a case of public transportation. [PDF]
Kahsay BG, Nallamothu RB.
europepmc +1 more source
Ecoefficiency Analysis and Regression in Data Conversion for Spiking Neural Network Training
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 +3 more
wiley +1 more source
Longitudinal stability control system for distributed drive electric vehicles based on multi-model MPC. [PDF]
Dang M, Zhang C, Guo Z, Wang J.
europepmc +1 more source

