Residual neural network
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Bài viết này nghiên cứu và áp dụng trí tuệ nhân tạo nơ-ron (AI) để cải thiện quá trình giám sát và chẩn đoán lỗi động cơ điện dựa trên tín hiệu độ rung. Mục tiêu của nghiên cứu là tự xây dựng một mô hình để thu thập dữ liệu mẫu từ động cơ và sử dụng 3 mạng AI khác nhau trong nghiên cứu này bao gồm YOLO (You Only Look Once), Resnet (Residual neural network) và SVM (Support Vector Machine).
9p visergeyne 18-06-2024 5 1 Download
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Predicting the residual flexural capacity of corroded reinforced concrete (RC) structures is to help civil engineers decide to repair or strengthen the structures. This study presents the application of six single algorithm-based models of artificial intelligence, such as artificial neural network (ANN), support vector machine (SVM), classification and regression trees (CART), linear regression (LR), general linear model (GENLIN), and automatic Chisquared interaction detection (CHAID) to predict the residual flexural capacity of corroded RC structures.
12p viaudi 29-08-2022 8 3 Download
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Models developed using Nanopore direct RNA sequencing data from in vitro synthetic RNA with all adenosine replaced by N6 -methyladenosine (m6 A) are likely distorted due to superimposed signals from saturated m6 A residues.
23p viarchimedes 26-01-2022 13 0 Download
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Measuring DNA replication dynamics with high throughput and single-molecule resolution is critical for understanding both the basic biology behind how cells replicate their DNA and how DNA replication can be used as a therapeutic target for diseases like cancer.
8p vilichoo2711 23-06-2021 15 1 Download
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Worldwide structural genomics projects continue to release new protein structures at an unprecedented pace, so far nearly 6000, but only about 60% of these proteins have any sort of functional annotation.
11p viwyoming2711 16-12-2020 14 1 Download
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Deep learning is one of the most powerful machine learning methods that has achieved the state-ofthe-art performance in many domains. Since deep learning was introduced to the field of bioinformatics in 2012, it has achieved success in a number of areas such as protein residue-residue contact prediction, secondary structure prediction, and fold recognition.
13p viflorida2711 30-10-2020 11 2 Download
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Ligand-binding proteins play key roles in many biological processes. Identification of protein-ligand binding residues is important in understanding the biological functions of proteins. Existing computational methods can be roughly categorized as sequence-based or 3D-structure-based methods.
12p vicoachella2711 27-10-2020 9 0 Download
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Protein ubiquitination occurs when the ubiquitin protein binds to a target protein residue of lysine (K), and it is an important regulator of many cellular functions, such as signal transduction, cell division, and immune reactions, in eukaryotes.
10p vicoachella2711 27-10-2020 12 0 Download
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Recurrent neural network(RNN) is a good way to process sequential data, but the capability of RNN to compute long sequence data is inefficient. As a variant of RNN, long short term memory(LSTM) solved the problem in some extent. Here we improved LSTM for big data application in protein-protein interaction interface residue pairs prediction based on the following two reasons.
11p vicolorado2711 23-10-2020 23 0 Download
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Despite the great advance of protein structure prediction, accurate prediction of the structures of mainly β proteins is still highly challenging, but could be assisted by the knowledge of residue-residue pairing in β strands.
12p vicolorado2711 22-10-2020 13 0 Download
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This paper presents an approach of linking finite element method with artificial neural network to predict J-Integral parameter in desirable airfoil condition. Finite Element (FE) and Artificial Neural Network (ANN) have been employed for the purpose.
8p tohitohi 19-05-2020 4 0 Download
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In this paper we address the problem of extracting features relevant for predicting protein±protein interaction sites from the three-dimensional structures of protein complexes. Our approach is based on information about evolutionary con-servation and surface disposition. We implement a neural network based system, which uses a cross validation proce-dure and allows the correct detection of 73% of the residues involved in protein interactions in a selected database comprising 226 heterodimers.
6p research12 29-04-2013 29 2 Download