Results 51 to 60 of about 79,617 (312)

Data‐Efficient Electromagnetic Surrogate Solver Through Dissipative Relaxation Transfer Learning

Advanced Optical Materials, EarlyView.
Dissipative relaxation transfer learning (DIRTL) enables data‐efficient training of electromagnetic surrogate solvers by pretraining data generated with artificial material loss before fine‐tuning on target lossless data. The framework suppresses resonant outlier effects during early training, allowing effective adaptation to high‐amplitude resonances ...
Sunghyun Nam, Chan Y. Park, Min Seok Jang   +2 more
wiley   +1 more source

Sharp MSE Bounds for Proximal Denoising [PDF]

Foundations of Computational Mathematics, 2015
Denoising has to do with estimating a signal $x_0$ from its noisy observations $y=x_0+z$. In this paper, we focus on the "structured denoising problem", where the signal $x_0$ possesses a certain structure and $z$ has independent normally distributed entries with mean zero and variance $σ^2$.
Oymak, Samet, Hassibi, Babak
openaire   +4 more sources

Machine Learning Enables Inverse Design of Optically Driven Microscopic Metavehicles

Advanced Optical Materials, EarlyView.
Machine‐learning‐based inverse design is used optimize “metavehicles” — flat microparticles based on metagratings that generate a strong lateral optical force from normally incident light. The optimized design exhibits a force efficiency of ∼88% and a measured propulsion speed in water much higher than previously reported, demonstrating that inverse ...
Vasilii Mylnikov, Mahdi Shanei, Mikael Käll   +2 more
wiley   +1 more source

A State‐Adaptive Koopman Control Framework for Real‐Time Deformable Tool Manipulation in Robotic Environmental Swabbing

Advanced Robotics Research, EarlyView.
This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi, Amirreza Davar, Dongyi Wang   +2 more
wiley   +1 more source

Data‐Driven Bulldozer Blade Control for Autonomous Terrain Leveling

Advanced Robotics Research, EarlyView.
A simulation‐driven framework for autonomous bulldozer leveling is presented, combining high‐fidelity terramechanics simulation with a neural‐network‐based reduced‐order model. Gradient‐based optimization enables efficient, low‐level blade control that balances leveling quality and operation time.
Harry Zhang, Ganesh Arivoli, Huzaifa Unjhawala, Luning Bakke, Radu Serban, Dan Negrut   +5 more
wiley   +1 more source

Experimenting with urban stressors: a network-based approach to systemic resilience through the URSA framework

Urban Transformations
Understanding how shocks cascade through interdependent urban systems is essential for designing effective resilience strategies. We introduce the Urban Resilience and Sustainability Alliance (URSA), a network-based framework that represents a city’s ...
Mozhgan PourmoradNasseri, Amir Albadvi, Arifusalam Shaikh, Mohsen Ghodrat, M. Kyan Bahrami   +4 more
doaj   +1 more source

Solid Harmonic Wavelet Bispectrum for Image Analysis

Advanced Science, EarlyView.
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown, Mathilda Avirett‐Mackenzie, Carolin Villforth, Georgios Exarchakis   +3 more
wiley   +1 more source

Improving the security of LSB image steganography

JOIV: International Journal on Informatics Visualization, 2019
Steganography is the technique of hiding secret data (message) within any media such as digital color image. In this paper we will merge steganography process with cryptography process in order to increase the security of the proposed method.
Jamil Al-Azzeh, Ziad Alqadi, Belal Ayyoub, Ahmad Sharadqh   +3 more
doaj   +1 more source

Cross‐Modal Denoising and Integration of Spatial Multi‐Omics Data with CANDIES

Advanced Science, EarlyView.
In this paper, we introduce CANDIES, which leverages a conditional diffusion model and contrastive learning to effectively denoise and integrate spatial multi‐omics data. We conduct extensive evaluations on diverse synthetic and real datasets, CANDIES shows superior performance on various downstream tasks, including denoising, spatial domain ...
Ye Liu, Wanpeng Zou, Yuekai Li, Jiayi Wang, Mingxuan Cai, Hongmin Cai   +5 more
wiley   +1 more source

EARTHQUAKE FREQUENCY DATA MODELING IN MENTAWAI USING FUZZY TIME SERIES LEE AND FUZZY TIME SERIES TSAUR

Barekeng
The Fuzzy Time Series (FTS) was first studied by Song and Chissom based on the theory of fuzzy sets and the concept of linguistic variables and their applications discovered by Zadeh. FTS has several models, namely FTS Lee, FTS Tsaur, and so on.
Septri Damayanti, Jose Rizal, Siska Yosmar, Nur Afandi, Vivin Acnesya   +4 more
doaj   +1 more source