Results 101 to 110 of about 212,585 (307)

Water‐Assisted Exfoliation of HfO2‐Based Membrane for Flexible Robust Ferroelectric Synaptic Transistors

open access: yesAdvanced Science, EarlyView.
A flexible freestanding HfO2‐based ferroelectric membrane is achieved via a water‐assisted exfoliation technique using a Sr4Al2O₇ sacrificial layer. The BaTiO3/Hf0.5Zr0.5O2/BaTiO3 heterostructure maintains robust ferroelectricity and exhibits reliable synaptic plasticity.
Han Zhang   +13 more
wiley   +1 more source

Application of Deep Learning Algorithm for Web Shell Detection in Web Application Security System

open access: yesJurnal Sisfokom
A web shell is a script executed on a web server, often used by hackers to gain control over an infected server. Detecting web shells is challenging due to their complex behavior patterns. This research focuses on using a deep learning approach to detect
Rezky Yuranda, Edi Surya Negara
doaj   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

open access: yesAdvanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho   +6 more
wiley   +1 more source

Which Method Best Predicts Postoperative Complications: Deep Learning, Machine Learning, or Conventional Logistic Regression?

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
Deep learning has shown promise in predicting postoperative complications, particularly when using image or time‐series data. However, on tabular clinical data such as the NCD, it often underperforms compared to conventional machine learning. Integrating multimodal data may enhance predictive accuracy and interpretability in surgical care.
Ryosuke Fukuyo   +4 more
wiley   +1 more source

Collaboration Development through Interactive Learning between Human and Robot [PDF]

open access: yes, 2003
In this paper, we investigated interactive learning between human subjects and robot experimentally, and its essential characteristics are examined using the dynamical systems approach.
Masago, Noritaka   +3 more
core  

A Solution for Exosome‐Based Analysis: Surface‐Enhanced Raman Spectroscopy and Artificial Intelligence

open access: yesAdvanced Intelligent Discovery, EarlyView.
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz   +2 more
wiley   +1 more source

Toward Environmentally Friendly Hydrogel‐Based Flexible Intelligent Sensor Systems

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review summarizes environmentally and biologically friendly hydrogel‐based flexible sensor systems focusing on physical, chemical, and physiological sensors. Furthermore, device concepts moving forward for the practical application are discussed about wireless integration, the interface between hydrogel and dry electronics, automatic data analysis
Sudipta Kumar Sarkar, Kuniharu Takei
wiley   +1 more source

W-RNN: News text classification based on a Weighted RNN

open access: yes, 2019
7 pages, 10 ...
Wang, Dan, Gong, Jibing, Song, Yaxi
openaire   +2 more sources

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

open access: yesAdvanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour   +5 more
wiley   +1 more source

Neutrosophy-Driven Deep Learning for Predicting Student Performance [PDF]

open access: yesNeutrosophic Sets and Systems
This paper proposes a hybrid architecture using several deep learning models in the neutrosophy environment for predicting student learning outcomes. The proposed framework proceeds on deep neural network models with the neutrosophy encoder/decoder.
N.T.K Son, N.T. Thong, N.H. Quynh
doaj   +1 more source

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