Results 111 to 120 of about 7,081 (248)

Catalyst‐Specialized Chemical Language Model Based on Transformer Variational Autoencoder for Catalyst Design and Discovery

Advanced Intelligent Discovery, EarlyView.
We present CatTransVAE, a catalyst‐specialized chemical language model (CLM) built on a transformer variational autoencoder (VAE), developed through pretraining on general compounds followed by fine‐tuning on diverse catalyst databases. A template‐guided generation framework is introduced to enable controlled catalyst design under structural ...
Apakorn Kengkanna, Masahito Ohue
wiley   +1 more source

Sports Activity Recognition Using Textile‐Based Sensor Fusion and Complex‐Valued Residual Convolutional Neural Networks

Advanced Intelligent Systems, EarlyView.
Motion artifacts in electrocardiographic signals, conventionally dismissed as noise, are shown to encode discriminative activity information. A smart t‐shirt fusing textile strain sensors with textile ECG electrodes, processed through a complex‐valued residual network, recognizes 12 sport activities.
Nada Al‐azzawi, Munire Sibel Cetin, Asli Tuncay Atalay, Ozgur Atalay, Gökhan Ince   +4 more
wiley   +1 more source

Resilient Multimodal Fusion for Robust Vulnerability Exploitability Prediction Under Data Degradation

Advanced Intelligent Systems, EarlyView.
Secure Fusion‐X harmonizes unstructured NVD descriptions with structured CVSS/CWE/CPE metadata via decision‐level fusion, overcoming the fragility of traditional unimodal models. Automated assessment of software vulnerability exploitability is essential for intelligent cyber defense, yet its effectiveness is often hindered by unstable, delayed, or ...
Mona Dolati, Seyedeh Leili Mirtaheri, Reza Shahbazian, Andrea Pugliese   +3 more
wiley   +1 more source

AI‐Enabled RGB Light‐to‐Frequency Sensor for Nondestructive Salinity Stress Monitoring in Medicinal Plants

Advanced Intelligent Systems, EarlyView.
A distributed wireless sensing framework enables noninvasive monitoring of plant salinity stress through leaf reflectance measurements acquired with portable optical sensors. The collected data are processed using TinyML‐based neural network models deployed at the edge, enabling accurate, real‐time, and low‐cost classification of salinity levels, while
Ali Ahmad, Vinie Lee Silva‐Alvarado, Arman Heydari, Sandra Sendra, Jaime Lloret   +4 more
wiley   +1 more source

AI‐Powered Smart Displays and AR Glasses: Perspectives and Challenges

Advanced Intelligent Systems, EarlyView.
This perspective examines how AI is reshaping smart displays and AR glasses. The latest in image‐quality enhancement, sensor‐integrated display optimization, and physiological sensing in display systems, followed by AI‐assisted AR technologies including waveguide optimization, image compensation, foveated rendering, and multimodal sensing, is discussed.
Luke Benoit, Yizhou Qian, Yi‐Chien Chen, Ziyang Shen, Po‐Sheng Chiu, Youngeon Lee, Cheng‐Han Ke, Chih‐Lung Lin, Shin‐Tson Wu   +8 more
wiley   +1 more source

Kinematic‐Aware Diffusion Model Correction for Human Motion Generation via Pose Transfer

Advanced Intelligent Systems, EarlyView.
Overall architecture of the proposed video kinematic pose correction pipeline. The framework integrates diffusion‐based video generation, multi‐estimator skeleton extraction, temporal Kalman smoothing, biomechanical constraint enforcement, and pose‐conditioned frame regeneration via Pose‐guided Image Synthesis and Editing. This paper presents Kinematic‐
Alaa Abdullah Albaghdadi, Ahmad R. Naghsh‐Nilchi   +1 more
wiley   +1 more source

Ultrafast RF Spectrum Analyzer Assisted by Optical Short‐Time Fourier Transform

Advanced Physics Research, EarlyView.
We present Recent efforts in an ultrafast RF spectrum analyzer based on the short‐time Fourier transform (STFT) at over 10 MHz frame rate and over 40GHz bandwidth to improve performance and support applications. All these efforts could inspire more innovative applications of temporal imaging modalities in the future.
Liao Chen, Yufan Du, Rongwu Liu, Chi Zhang, Xinliang Zhang   +4 more
wiley   +1 more source

Leveraging Big Multitemporal Multisource Satellite Data and Artificial Intelligence for the Detection of Complex and Invisible Features: The Case of Extensive Irrigation Mapping

Archaeological Prospection, EarlyView.
ABSTRACT The detection of buried or obscured archaeological features remains a central challenge in landscape archaeology, particularly in the irrigated floodplains of Mesopotamia where levees and canals formed the basis of complex agrarian systems. This study presents a deep learning–based approach for the large‐scale, automated detection of ancient ...
Nazarij Buławka, Hector A. Orengo, Felipe Lumbreras Ruiz, Iban Berganzo‐Besga, Ekta Gupta   +4 more
wiley   +1 more source

Investigating Pompeii Subsoil Using Geomatics and Geophysics Merged Analyses

Archaeological Prospection, EarlyView.
ABSTRACT The archaeological site of Pompeii represents an exceptional context for the application of non‐invasive and integrated investigation methods aimed at enhancing the understanding of both exposed and buried remains. This study presents the results of multidisciplinary research conducted in the Palestra Grande site, a large and strategically ...
Valentina Santoro, Antonio Merico, Vincenzo Sapia, Gianluca Catanzariti, Valerio Materni, Giacomo Patrucco, Riccardo Olivito, Anna Anguissola, Ilaria Cangiano, Antonia Spanò   +9 more
wiley   +1 more source

An Indicator‐Based Decision Framework for Circular Bioeconomy Transition in the Steel Industry: Integrating Multiphase Learning and Cooperative Game Modelling

Business Strategy and the Environment, EarlyView.
ABSTRACT Despite growing attention to the circular bioeconomy (CBE), the steel industry currently lacks a standardised, sectoral measurement framework to facilitate a low‐carbon transition. In this study, a decision‐support framework for evaluating CBE performance in the steel industry is proposed.
Ali Zamani Babgohari, Mohammadreza Sadeghi‐Moghadam, Hannan Amoozad Mahdiraji   +2 more
wiley   +1 more source