Results 51 to 60 of about 36,988 (280)

Performance Quantile Regression and Bayesian Quantile Regression in Dealing with Non-normal Errors (Case Study on Simulated Data)

Numerical: Jurnal Matematika dan Pendidikan Matematika
This research discusses the performance of quantile regression and Bayesian quantile regression methods. Quantile regression uses parameter estimation by maximizing the value of the likelihood function, while Bayesian quantile regression uses parameter ...
Lilis Harianti Hasibuan, Ferra Yanuar, Vika Pradinda Harahap, Latifatul Qalbi   +3 more
doaj   +1 more source

An Imaging‐Guided, Patient‐Specific Guiding Aid (RWNGuide) for Safe and Reproducible Inner Ear Drug Delivery

Advanced Materials Technologies, EarlyView.
A patient‐specific, imaging‐guided aid enables precise and reproducible drug delivery to the inner ear. By guiding therapeutic agents directly to the round window niche, this approach reduces variability in drug localization, improves delivery safety, and addresses a critical bottleneck in inner ear therapy, offering a scalable strategy for precision ...
Yanjing Luo, Shanshan Jiang, Yimian Luo, Adele Moatti, Farnaz Matin‐Mann   +4 more
wiley   +1 more source

Model Evaluation for Forecasting Traffic Accident Severity in Rainy Seasons Using Machine Learning Algorithms: Seoul City Study

Applied Sciences, 2019
There have been numerous studies on traffic accidents and their severity, particularly in relation to weather conditions and road geometry. In these studies, traditional statistical methods have been employed, such as linear regression, logistic ...
Jonghak Lee, Taekwan Yoon, Sangil Kwon, Jongtae Lee   +3 more
doaj   +1 more source

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

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

Worst-case mean square error (MSE) transceiver design for imperfect estimate multi-input-multi-output communication channels

IET Communications, 2012
The authors consider the worst-case transceiver design problem under spectrum bounded channel uncertainty matrices. Their design aims to minimise the trace and the determinant of the estimate error covariance matrix, respectively. The authors relax the formulated problem into an optimisation problem with bilinear matrix inequality constraints (i.e. BMI
openaire   +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

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