Results 131 to 140 of about 17,106 (295)

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

Advanced Robotics Research, EarlyView.
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki, Ilche Georgievski, Marco Aiello   +2 more
wiley   +1 more source

Symbolic regression as a feature engineering method for machine and deep learning regression tasks

Machine Learning: Science and Technology
In the realm of machine and deep learning (DL) regression tasks, the role of effective feature engineering (FE) is pivotal in enhancing model performance. Traditional approaches of FE often rely on domain expertise to manually design features for machine
Assaf Shmuel, Oren Glickman, Teddy Lazebnik   +2 more
doaj   +1 more source

LLM‐Integrated Human–Robot Interaction System for Microrobots

Advanced Robotics Research, EarlyView.
This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley   +1 more source

Mesenchymal Stromal Cell‐Mediated Intercellular Communication: Mapping the Interactome for Skeletal Muscle Homeostasis and Regeneration

Advanced Science, EarlyView.
Liu et al. define a systems‐level interactome of fibroadipogenic progenitor (FAP)‐mediated signaling in skeletal muscle by integrating single‐cell transcriptomics with FAP depletion‐based perturbation analysis. Functional interrogation using a conditioned media bioassay links predicted signaling to multicellular outcomes, establishing a framework to ...
Xingyu Liu, Edgar E. Perez Carbajal, Yih‐Chii Hwang, Sahil A. Mapkar, Benjamin W. Gilman, Sarah A. Bliss, Lam B. Tran, Kalgi T. Mehta, Jacob O. Banyasz, Ming Yu, Reynold R. Liu, Matthew N. Ly, Christapher S. Morrissey, Michael N. Wosczyna   +13 more
wiley   +1 more source

Deep Learning for Symbolic Regression

, 2022
Symbolic regression is a task of finding mathematical equation based on the observed data. Historically, genetic programming was the main tool to tackle the symbolic regres- sion, however, recently, new neural network based approaches emerged.
Vastl, Martin
core  

Hijacking the Host Clock: A Nematode Effector Antagonizes Soybean Circadian Defense and Translation Control

Advanced Science, EarlyView.
Soybean employs its circadian clock, governed by GmCCA1, to rhythmically defend against soybean cyst nematodes. The pathogen retaliates by secreting the effector Hg4E02, which hijacks the clock to suppress defense and co‐opt the host's translation machinery for nutrient acquisition.
Xingwei Wang, Yufeng Xu, Yanfei Hu, Lijun Cao, Ru Jiang, Changtian Chen, Rick Masonbrink, Thomas Maier, Yuchen Tu, Yabo Shi, Enhui Liu, Lingan Kong, Chan Guo, Wei Zhao, Peng Shi, Wenzhen Du, Andrew Severin, Thomas Baum, Deliang Peng, Huan Peng, Mian Zhou, Wei Wang   +21 more
wiley   +1 more source

Computing framework for symbolic regression

U današnjem "data-driven" društvu eksponencijalni rast podataka zahtijeva učinkovite alate za analizu i interpretaciju istih. Simbolička regresija, metoda za otkrivanje matematičkih izraza koji opisuju složene uzorke podataka bez unaprijed definiranih ...
Ivančević, Josip
core   +2 more sources

Microscale Mapping of Fiber Strain and Damage in Composite Wrinkled Laminates Using Computed Tomography Assisted Wide‐Angle X‐Ray Scattering

Advanced Science, EarlyView.
This study combines full‐field tomography with diffraction mapping to quantify radial (ε002$\varepsilon _{002}$) and axial (ε100$\varepsilon _{100}$) lattice strain in wrinkled carbon‐fiber specimens for the first time. Radial microstrain gradients (−14.5 µεMPa$\varepsilon \mathrm{MPa}$−1) are found to signal damage‐prone zones ahead of failure, which ...
Hoang Minh Luong, James Trevarthen, Igor Dolbnya, Wadwan Singhapong, Nicholas Pilato, Richard Butler, Jiraphant Srisuriyachot, Alexander J. G. Lunt   +7 more
wiley   +1 more source

Iterated Agent for Symbolic Regression

CoRR
Symbolic regression (SR), the automated discovery of mathematical expressions from data, is a cornerstone of scientific inquiry. However, it is often hindered by the combinatorial explosion of the search space and a tendency to overfit. Popular methods, rooted in genetic programming, explore this space syntactically, often yielding overly complex ...
Zhuo-Yang Song, Zeyu Cai, Shutao Zhang, Jiashen Wei, Jichen Pan, Shi Qiu 0016, Qing-Hong Cao, Tie-Jiun Hou, Xiaohui Liu, Ming-xing Luo, Hua Xing Zhu   +10 more
openaire   +2 more sources

Prior Expectations Bias Confidence Judgments Through Parietal Alpha‐Band Modulation

Advanced Science, EarlyView.
ABSTRACT Humans possess the metacognitive ability to estimate the likely accuracy of their own decisions through confidence judgments. Yet, whether prior information shapes confidence and the neural mechanisms mediating such influence, remain to be determined.
Luca Tarasi, Anna Pasini, Domenico Romanazzi, Margherita Covelli, Vincenzo Romei   +4 more
wiley   +1 more source