Results 111 to 120 of about 404,815 (264)
High‐Performance Bio‐Glue From the Berries of a Parasitic Plant
Advanced Materials, EarlyView.We report a fully bio‐based adhesive derived primarily from a (poly)saccharide extract obtained from the berries of the hemi‐parasitic plant mistletoe (Viscum album), supplemented with tannic and malic acid without any further chemical functionalization.
Ufuk Gürer +8 more
wiley +1 more source
Modeling Site Specific Heterogeneity in an On-Site Stratified Random Sample of Recreational Demand [PDF]
Using estimation of demand for the George Washington/Jefferson National Forest as a case study, it is shown that in a stratified/clustered on-site sample, latent heterogeneity needs to be accounted for twice: first to account for dispersion in the data ...
Bergstrom, John C., Sardana, Kavita
core +1 more source
Improving Random Forests [PDF]
, 2004 Random forests are one of the most successful ensemble methods which exhibits performance on the level of boosting and support vector machines. The method is fast, robust to noise, does not overfit and offers possibilities for explanation and visualization of its output.
openaire +1 more source
A Hybrid Computational Framework for PCF‐based SPR Sensor With Machine Learning and xAI
Advanced Materials Interfaces, EarlyView.A photonic crystal fiber‐based surface plasmon resonance (SPR) sensor integrating rectangular air holes along with conventional circular air holes achieves exceptional wavelength sensitivity of 15,000 nm/RIU across a broad refractive index range of 1.31–1.39. Integrated machine learning with explainable AI (xAI) models achieves high prediction accuracy
Mahabur Rahman Fahim +3 more
wiley +1 more source
Estimating Forest Aboveground Biomass Using a Combination of Geographical Random Forest and Empirical Bayesian Kriging Models [PDF]
Accurately estimating forest aboveground biomass (AGB) is imperative for comprehending carbon cycling, calculating carbon budgets, and formulating sustainable forest management plans.
Jiahua Zhang +3 more
core +1 more source
On the asymptotics of random forests
Journal of Multivariate Analysis, 2016 The last decade has witnessed a growing interest in random forest models which are recognized to exhibit good practical performance, especially in high-dimensional settings. On the theoretical side, however, their predictive power remains largely unexplained, thereby creating a gap between theory and practice. The aim of this paper is twofold. Firstly,
openaire +2 more sources
Material Before Morphology: Substrate‐Dependent Mechanical Tuning of Radular Teeth
Advanced Materials Interfaces, EarlyView.Substrate‐dependent material tuning in Clausilia radular teeth. Closely related taxa retain a conserved gross tooth morphology, but differ in elemental composition and mechanical properties according to feeding substrate. Rock‐associated taxa show increased Ca–Si enrichment and higher stiffness and hardness, especially in the central radular region ...
Ida Lilienthal +3 more
wiley +1 more source
Recent Advances of Slip Sensors for Smart Robotics
Advanced Materials Technologies, EarlyView.This review summarizes recent progress in robotic slip sensors across mechanical, electrical, thermal, optical, magnetic, and acoustic mechanisms, offering a comprehensive reference for the selection of slip sensors in robotic applications. In addition, current challenges and emerging trends are identified to advance the development of robust, adaptive,
Xingyu Zhang +8 more
wiley +1 more source
Advanced Materials Technologies, EarlyView.Aerosol Jet Printing (AJP) has emerged as a versatile additive manufacturing technique for high‐resolution, conformal, and multi‐material printing. This review highlights advances in printable materials, substrate compatibility, post‐processing, characterization, and process innovations, while critically discussing current challenges and future ...
Chandrachur Chatterjee +2 more
wiley +1 more source
Advanced Robotics Research, EarlyView.Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar +8 more
wiley +1 more source