Results 91 to 100 of about 4,036,534 (282)

Physical Origin of Temperature Induced Activation Energy Switching in Electrically Conductive Cement

open access: yesAdvanced Science, EarlyView.
The temperature‐induced Arrhenius activation energy switching phenomenon of electrical conduction in electrically conductive cement originates from structural degradation within the biphasic ionic‐electronic conduction architecture and shows percolation‐governed characteristics: pore network opening dominates the low‐percolation regime with downward ...
Jiacheng Zhang   +7 more
wiley   +1 more source

Approximate inference of the bandwidth in multivariate kernel density estimation [PDF]

open access: yes, 2011
Kernel density estimation is a popular and widely used non-parametric method for data-driven density estimation. Its appeal lies in its simplicity and ease of implementation, as well as its strong asymptotic results regarding its convergence to the true ...
Sanguinetti, G.   +3 more
core   +1 more source

Mr BMT Achieves Systemic Macrophage Replacement With Preservation of Tissue Homeostasis

open access: yesAdvanced Science, EarlyView.
Microglia replacement by bone marrow transplantation (Mr BMT) enables systemic replacement of tissue‐resident macrophages. Despite persistent macrophage and tissue remodeling across multiple organs, core biological functions and innate immune responses remain preserved, supporting long‐term maintenance of organismal homeostasis and the therapeutic ...
Yufei Xu   +17 more
wiley   +1 more source

Crowd Density Estimation Using Enhanced Multi-Column Convolutional Neural Network and Adaptive Collation

open access: yesIEEE Access
Accurate crowd density estimation is essential for public safety operations, urban and transportation design and multiple intelligent systems. The research presents an improved Multi-Column Convolutional Neural Network (MC-CNN) structure to predict crowd
Azamat Serek   +4 more
doaj   +1 more source

An Improved Convolutional Neural Network on Crowd Density Estimation

open access: yesITM Web of Conferences, 2016
In this paper, a new method is proposed for crowd density estimation. An improved convolutional neural network is combined with traditional texture feature.
Pan Shao-Yun, Guo Jie, Huang Zheng
doaj   +1 more source

Harnessing Phase Separation for the Development of High‐Performance Hydrogels

open access: yesAdvanced Science, EarlyView.
ABSTRACT Hydrogels are indispensable for the development of next‐generation bioelectronics, soft robotics, and biomedical devices, where their mechanical properties determine performance and reliability. Among strategies to enhance hydrogel mechanics, phase separation enables controlled heterogeneity resulting in gel networks that are reinforced by ...
Yue Shao   +3 more
wiley   +1 more source

Physics‐Informed Machine Learning for Sustainable Alloy Design: Toward a Recyclable Unified Q&P Steel

open access: yesAdvanced Science, EarlyView.
A physics‐informed property‐bridging framework links high‐throughput hardness screening to tensile performance in quenching and partitioning steels. By transferring metallurgically guided representations across properties, a single alloy composition is designed to achieve multiple strength grades through heat‐treatment tuning alone, offering a ...
Xiaolu Wei   +7 more
wiley   +1 more source

Feature Descriptor for Crowd Density Estimation

open access: yes, 2019
Crowd density estimation is an important task for crowd monitoring. Many efforts have been done to automate the process of estimating crowd density from images and videos. Despite series of efforts, it remains a challenging task. In this paper, we proposes a new texture feature-based approach for the estimation of crowd density based on Completed Local
Muhammad Bilal, Adwan Alanazi
openaire   +2 more sources

Crowd density estimation using deep learning for Hajj pilgrimage video analytics. [PDF]

open access: yesF1000Res, 2021
Bhuiyan MR   +6 more
europepmc   +1 more source

Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review

open access: yesAdvanced Science, EarlyView.
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh   +8 more
wiley   +1 more source

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