Results 51 to 60 of about 34,789 (293)
Double attention recurrent convolution neural network for answer selection [PDF]
Royal Society Open Science, 2020 Answer selection is one of the key steps in many question answering (QA) applications. In this paper, a new deep model with two kinds of attention is proposed for answer selection: the double attention recurrent convolution neural network (DARCNN). Double attention means self-attention and cross-attention. The design inspiration of this model came from
Ganchao Bao +3 more
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Advanced Functional Materials, EarlyView.Tin hexathiophosphate memristors leverage intrinsic nanopores together with a guided filament formation strategy to regulate titanium ion motion and switching behavior. The devices support reliable nonvolatile memory and reconfigurable logic‐in‐memory, demonstrating 14 Boolean logic functions in a single cell.
Thaw Tint Te Tun +7 more
wiley +1 more source
Prediction of 8-state protein secondary structures by a novel deep learning architecture
BMC Bioinformatics, 2018 Background Protein secondary structure can be regarded as an information bridge that links the primary sequence and tertiary structure. Accurate 8-state secondary structure prediction can significantly give more precise and high resolution on structure ...
Buzhong Zhang, Jinyan Li, Qiang Lü
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Sentiment Classification Via Recurrent Convolutional Neural Networks
DEStech Transactions on Computer Science and Engineering, 2017 The state-of-the-art methods used for sentiment classification are primarily based on statistical machine learning, and their performance strongly depends on the quality of the extracted features. The extracted features are often derived from the output of pre-existing natural language processing (NLP) systems, which leads to the propagation of errors ...
CHANGSHUN DU, LEI HUANG
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Recurrent convolutional neural networks for poet identification
Digital Scholarship in the Humanities, 2020 Abstract Deep neural networks have been widely used in various language processing tasks. Recurrent neural networks (RNNs) and convolutional neural networks (CNN) are two common types of neural networks that have a successful history in capturing temporal and spatial features of texts.
Momtazi, Saeedeh, Salami, Dariush
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Amyloidogenic Peptide Fragments Designed From Bacterial Collagen‐like Proteins Form Hydrogel
Advanced Functional Materials, EarlyView.This study identified amyloidogenic sequence motifs in bacterial collagen‐like proteins and exploited these to design peptides that self‐assemble into β‐sheet fibers and form hydrogels. One hydrogel supported healthy fibroblast growth, showing promise for biocompatible materials. Our work demonstrates that bacterial sequences can be harnessed to create
Vamika Sagar +5 more
wiley +1 more source
Sensors, 2023 The measurement and analysis of vital signs are a subject of significant research interest, particularly for monitoring the driver’s physiological state, which is of crucial importance for road safety.
Amal El Abbaoui +2 more
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A Short-Term Wind Power Forecasting Model Based on 3D Convolutional Neural Network–Gated Recurrent Unit [PDF]
, 2023 Xiaoshuang Huang +4 more
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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
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Atomic Layer Deposition in Transistors and Monolithic 3D Integration
Advanced Functional Materials, EarlyView.Transistors are fundamental building blocks of modern electronics. This review summarizes recent progress in atomic layer deposition (ALD) for the synthesis of two‐dimensional (2D) metal oxides and transition‐metal dichalcogenides (TMDCs), with particular emphasis on their enabling role in monolithic three‐dimensional (M3D) integration for next ...
Yue Liu +5 more
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