Results 71 to 80 of about 49,315 (263)

A Novel Flexible Kernel Density Estimator for Multimodal Probability Density Functions

open access: yesCAAI Transactions on Intelligence Technology
Estimating probability density functions (PDFs) is critical in data analysis, particularly for complex multimodal distributions. traditional kernel density estimator (KDE) methods often face challenges in accurately capturing multimodal structures due to
Jia‐Qi Chen   +5 more
doaj   +1 more source

Optimizing NiMo Electrocatalyst Coatings for Hydrogen Evolution in Alkaline Electrolysis With The Machine Learning‐Guided Autonomous Platform CatBot

open access: yesAdvanced Functional Materials, EarlyView.
This work presents a closed‐loop optimization workflow integrating CatBot, an automated synthesis and testing system, to discover NiMo hydrogen‐evolution catalysts. CatBot synthesised and evaluated 228 unique samples, identifying the best performing catalysts for transfer to nickel‐foam electrodes. The best candidate is highly active, reaching 1 Acm−2${
Paolo Vincenzo Freiesleben de Blasio   +7 more
wiley   +1 more source

Manifold learning based on kernel density estimation

open access: yesУчёные записки Казанского университета: Серия Физико-математические науки, 2018
The problem of unknown high-dimensional density estimation has been considered. It has been suggested that the support of its measure is a low-dimensional data manifold. This problem arises in many data mining tasks.
A.P. Kuleshov   +2 more
doaj  

Grayscale Photomasks Enable Noncontact Optical Patterning of Hydroxypropyl Cellulose Gels for Dynamic Art

open access: yesAdvanced Functional Materials, EarlyView.
Mask‐encoded UV exposure translates digital color information into pixel‐resolved structural‐color patterns in hydroxypropyl cellulose gels. Gaussian‐process‐guided calibration links UV processing conditions, wavelength, and mask opacity, enabling parallel fabrication of multicolor images in a single 10 s exposure.
Mengting Ye   +8 more
wiley   +1 more source

MULTILANE TRAFFIC DENSITY ESTIMATION AND TRACKING

open access: yesElectrica, 2017
As the number of vehicles in roads increases, information of traffic density becomes crucial to municipalities for making better decisions about road management and to the environment for reduced carbon emission.
Mikail YILAN, Mehmet Kemal ÖZDEMİR
doaj   +2 more sources

Asymptotics for the Transformation Kernel Density Estimator

open access: yesThe Annals of Statistics, 1995
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hossjer, Ola, Ruppert, David
openaire   +3 more sources

XTRUDE: A Process‐Informed Framework for High‐Fidelity Analysis of Hydrogel Extrusion

open access: yesAdvanced Functional Materials, EarlyView.
Extrusion performance emerges from the interplay between material properties and processing conditions. XTRUDE (eXTrusion Rheology for Understanding and Defining Extrudability) recreates the extrusion environment with in situ pressure and temperature sensing, enabling characteristic pressure signatures to quantify extrusion‐specific phenomena and ...
Farhad Sanaei   +4 more
wiley   +1 more source

Fruit Distribution Density Estimation in YOLO-Detected Strawberry Images: A Kernel Density and Nearest Neighbor Analysis Approach

open access: yesAgriculture
Precise information on strawberry fruit distribution is of significant importance for optimizing planting density and formulating harvesting strategies.
Lili Jiang   +3 more
doaj   +1 more source

Intracrystalline Void‐Mediated Toughening of Brittle Crystals in Quail Eggshells

open access: yesAdvanced Functional Materials, EarlyView.
In quail eggshells, the high density and disordered arrangement of intracrystalline voids inhibit lattice cleavage, suppress long‐range crack propagation, and promote deformation twinning and quasi‐plasticity, serving as an essential toughening motif. We show that these voids remain within a narrow subcritical size range and therefore predominantly do ...
Jingxiao Zhong   +16 more
wiley   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

open access: yesAdvanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena   +3 more
wiley   +1 more source

Home - About - Disclaimer - Privacy