Results 81 to 90 of about 122,069 (234)

Bayesian Optimization Guiding the Experimental Mapping of the Pareto Front of Mechanical and Flame‐Retardant Properties in Polyamide Nanocomposites

open access: yesAdvanced Intelligent Discovery, EarlyView.
Bayesian optimization enabled the design of PA56 system with just 8 wt% additives, achieving limiting oxygen index 30.5%, tensile strength 80.9 MPa, and UL‐94 V‐0 rating. Without prior knowledge, the algorithm uncovered synergistic effects between aluminum diethyl‐phosphinate and nanoclay.
Burcu Ozdemir   +4 more
wiley   +1 more source

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

open access: yesAdvanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu   +4 more
wiley   +1 more source

Advancing Efficient Error Reduction in DNA Data Storage Systems with Deep Learning‐Based Denoising Models

open access: yesAdvanced Intelligent Discovery, EarlyView.
Deep learning‐based denoising models are applied to DNA data storage systems to enhance error reduction and data fidelity. By integrating DnCNN with DNA sequence encoding methods, the study demonstrates significant improvements in image quality and correction of substitution errors, revealing a promising path toward robust and efficient DNA‐based ...
Seongjun Seo   +5 more
wiley   +1 more source

RAMS: Residual‐Based Adversarial‐Gradient Moving Sample Method for Scientific Machine Learning in Solving Partial Differential Equations

open access: yesAdvanced Intelligent Discovery, EarlyView.
We propose a residual‐based adversarial‐gradient moving sample (RAMS) method for scientific machine learning that treats samples as trainable variables and updates them to maximize the physics residual, thereby effectively concentrating samples in inadequately learned regions.
Weihang Ouyang   +4 more
wiley   +1 more source

A Multimodal Intelligent System for Human Digital Twin Simulation with Continuous Kinematic Data Tracking, Biometric Prognosis, and Cognitive State Feedback in Industrial Environments

open access: yesAdvanced Intelligent Discovery, EarlyView.
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury   +4 more
wiley   +1 more source

AS‐pHopt: An Optimal pH Prediction Model Enhanced by Active Site of Enzymes

open access: yesAdvanced Intelligent Discovery, EarlyView.
To address the low accuracy of enzyme optimal pH (pHopt) prediction, this study develops active site‐based pHopt (AS‐pHopt), a prediction model enhanced by active site information and pseudo‐label prediction. Integrating key structural and physicochemical features affecting enzyme pHopt, AS‐pHopt uses Evolutionary Scale Modeling (ESM)‐2 with active ...
Wenxiang Song   +6 more
wiley   +1 more source

Context Awareness and Human–Robot Interaction Optimization for Museum Intelligent Guide Robot

open access: yesAdvanced Intelligent Systems, EarlyView.
This study presents a context‐aware human–robot interaction framework designed for intelligent museum guide robots. The system features a three‐layer architecture—perception, understanding, and behavior execution—that enables adaptive and meaningful interactions with museum visitors.
Anna Zou, Yue Meng, Shijing Tong
wiley   +1 more source

Anatolij Nikolaevich Sherstnev (on 80th birthday anniversary)

open access: yesУчёные записки Казанского университета: Серия Физико-математические науки, 2018
The paper describes the biography and the main scientific achievements of Professor Anatolij Nikolaevich Sherstnev. The scientific interests of A.N.
A.M. Bikchentaev   +2 more
doaj  

Optisense: Computational Optimization for Strain Sensor Placement in Wearable Motion Tracking Systems

open access: yesAdvanced Intelligent Systems, EarlyView.
A computational framework for optimizing strain sensor placement in wearable motion tracking systems is presented. By combining dense strain mapping with a genetic algorithm, the method discovers counterintuitive yet highly effective configurations that reduce joint angle error by 32%.
Minu Kim   +4 more
wiley   +1 more source

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