Results 51 to 60 of about 288,791 (262)

Multi‐Scale Interface Engineering of MXenes for Multifunctional Sensory Systems

Advanced Functional Materials, EarlyView.
MXenes, as two‐dimensional transition metal carbides and nitrides, demonstrate remarkable capabilities for multifunctional sensing applications. This review systematically examines multi‐scale interface engineering approaches that enhance sensing performance, enable diverse detection functionalities, and improve system‐level compatibility in MXene ...
Jiaying Liao, Sin‐Yi Pang, Jianhua Hao
wiley   +1 more source

Attention-Based SeriesNet: An Attention-Based Hybrid Neural Network Model for Conditional Time Series Forecasting

Information, 2020
Traditional time series forecasting techniques can not extract good enough sequence data features, and their accuracies are limited. The deep learning structure SeriesNet is an advanced method, which adopts hybrid neural networks, including dilated ...
Yepeng Cheng, Zuren Liu, Yasuhiko Morimoto   +2 more
doaj   +1 more source

Deep Neural Network Architectures for Modulation Classification

, 2018
In this work, we investigate the value of employing deep learning for the task of wireless signal modulation recognition. Recently in [1], a framework has been introduced by generating a dataset using GNU radio that mimics the imperfections in a real ...
Gamal, Aly El, Liu, Xiaoyu, Yang, Diyu
core   +1 more source

Computational Modeling Meets 3D Bioprinting: Emerging Synergies in Cardiovascular Disease Modeling

Advanced Healthcare Materials, EarlyView.
Emerging advances in three‐dimensional bioprinting and computational modeling are reshaping cardiovascular (CV) research by enabling more realistic, patient‐specific tissue platforms. This review surveys cutting‐edge approaches that merge biomimetic CV constructs with computational simulations to overcome the limitations of traditional models, improve ...
Tanmay Mukherjee, Mehdi Salar Amoli, Sarah Rezapourdamanab, Lama Rita El Shammas, Martin L. Tomov, Emilio A. Mendiola, Vahid Serpooshan, Reza Avazmohammadi   +7 more
wiley   +1 more source

A Method Based on GA-CNN-LSTM for Daily Tourist Flow Prediction at Scenic Spots

Entropy, 2020
Accurate tourist flow prediction is key to ensuring the normal operation of popular scenic spots. However, one single model cannot effectively grasp the characteristics of the data and make accurate predictions because of the strong nonlinear ...
Wenxing Lu, Haidong Rui, Changyong Liang, Li Jiang, Shuping Zhao, Keqing Li   +5 more
doaj   +1 more source

Effective Use of Word Order for Text Categorization with Convolutional Neural Networks

, 2015
Convolutional neural network (CNN) is a neural network that can make use of the internal structure of data such as the 2D structure of image data. This paper studies CNN on text categorization to exploit the 1D structure (namely, word order) of text data
Johnson, Rie, Zhang, Tong
core   +1 more source

In Vivo Skin 3‐D Surface Reconstruction and Wrinkle Depth Estimation Using Handheld High Resolution Tactile Sensing

Advanced Healthcare Materials, EarlyView.
A compact handheld GelSight probe reconstructs in vivo 3‐D skin topography with micron‐level precision using a custom elastic gel and a learning‐based surface normal to height map pipeline. The device quantifies wrinkle depth across various body locations and detects changes in wrinkle depth following moisturizer application.
Akhil Padmanabha, Arpit Agarwal, Catherine Li, Austin Williams, Dinesh K. Patel, Sankalp Chopkar, Achu Wilson, Ahmet Ozkan, Wenzhen Yuan, Sonal Choudhary, Arash Mostaghimi, Zackory Erickson, Carmel Majidi   +12 more
wiley   +1 more source

RUL prediction of lithium ion battery based on CEEMDAN-CNN BiLSTM model

Energy Reports, 2023
With the wide application of lithium ion batteries, the importance of life prediction is also highlighted. The prediction of the remaining life of lithium ion battery is an important part of its health management, and accurate prediction can improve the ...
Xifeng Guo, Kaize Wang, Shu Yao, Guojiang Fu, Yi Ning   +4 more
doaj   +1 more source

CNN-MGP: Convolutional Neural Networks for Metagenomics Gene Prediction [PDF]

Interdisciplinary Sciences: Computational Life Sciences, 2018
Accurate gene prediction in metagenomics fragments is a computationally challenging task due to the short-read length, incomplete, and fragmented nature of the data. Most gene-prediction programs are based on extracting a large number of features and then applying statistical approaches or supervised classification approaches to predict genes.
Amani Al-Ajlan, Achraf El Allali
openaire   +2 more sources

Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing

Advanced Materials, EarlyView.
This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long, Huanyu Zhou, Jaewan Ko, Hongwei Tan, Jaemin Lim, Yanfei Zhao, Daehan Kang, Eojin Yoon, Gyeong‐Tak Go, Somin Kim, Seung‐Woo Lee, Chan‐Yul Park, Hyojun Choi, Hyeran Kim, Hyung Joong Yun, Sung Hyuk Park, Kwan Sik Park, Jeong Woo Park, Mungeun Kim, Yong Soo Cho, Ho Won Jang, Wenqiang Yang, Min Hyuk Park, Wan Ki Bae, Sebastiaan van Dijken, Joona Bang, Tae‐Woo Lee   +26 more
wiley   +1 more source