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Incremental Grid Sampling Strategies in Robotics
We present algorithms for generating deterministic sample sequences using incremental grid-based sampling. Our algorithms are designed to generate...
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Support vector machine-based importance sampling for rare event estimation
Structural reliability analysis aims at computing failure probability with respect to prescribed performance function. To efficiently estimate the...
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Research on the sampling performance of a new bionic gravity sampler
Gravity sampling is of vital importance for sampling seabed sediments and understanding submarine sedimentary environments and resources. In this...
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Choice of Sampling Strategy for Flexible Pavement Distress Survey
Periodical monitoring of the condition of the pavement is performed through functional and structural evaluation. For functional evaluation of the...
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An importance sampling reliability method combining Kriging and Gaussian Mixture Model through ring subregion strategy for multiple failure modes
The limit state function for multiple failure modes has multiple failure regions, and Monte Carlo (MC) method usually requires a large amount of...
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Adaptive inter-intradomain alignment network with class-aware sampling strategy for rolling bearing fault diagnosis
Existing unsupervised domain adaptation approaches primarily focus on reducing the data distribution gap between the source and target domains, often...
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Importance Sampling in Life-Cycle Seismic Fragility and Risk Assessment of Aging Bridge Networks
Life-cycle structural reliability of deteriorating systems and multi-hazard risk assessment of aging infrastructure networks involve complex...
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Minority Representation and Relative Ranking in Sampling Attributed Networks
We explore two questions related to sampling and minorities in attributed networks with homophily. The first question is to investigate sampling...
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Application of Photoelectric Conversion Technology in Photoelectric Signal Sampling System
The objective of this study is to investigate the use of photoelectric conversion technology in the process of creating enhanced photoelectric signal...
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New bubble sampling method for reliability analysis
In recent years, the safety of engineering systems is seriously threatened by increasingly complex and uncertain engineering environment, and the...
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Conditional Variational Autoencoder-Based Sampling
Imbalanced data distribution implies an uneven distribution of class labels in data which can lead to classification bias in machine learning models....
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Proportional periodic sampling for cross-load bearing fault diagnosis
Bearing vibration data under various loads shows different distributions, which leads to the poor performance of existing deep learning methods in...
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A Bayesian sampling optimisation strategy for finite element model updating
Model Updating (MU) aims to estimate the unknown properties of a physical system of interest from experimental observations. In Finite Element (FE)...
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Image embedding and user multi-preference modeling for data collection sampling
This work proposes an end-to-end user-centric sampling method aimed at selecting the images from an image collection that are able to maximize the...
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SSGCN: a sampling sequential guided graph convolutional network
Graph convolutional networks(GCNs) have become one of the important technologies for solving graph structured data problems. GCNs utilize...
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Balanced Sampling-Based Active Learning for Object Detection
Active learning focuses on building competitive models using less data by utilizing intelligent sampling, thereby reducing the effort and cost...
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Gibbs Sampling-based Sparse Estimation Method over Underwater Acoustic Channels
The estimation of sparse underwater acoustic (UWA) channels can be regarded as an inference problem involving hidden variables within the Bayesian...
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Adaptive Informed RRT*: Asymptotically Optimal Path Planning With Elliptical Sampling Pools in Narrow Passages
The rapidly exploring random tree star (RRT*) is a conventional algorithm for path planning that aims to establish a collision-free path for robots...
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Sampling and Integral Sums
For systems ruled by differential equations, the underlying time was that Newtonian time that flows continuously and uniformly and can take values...
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Reliability acceptance sampling procedures characterized with compound class of exponential–logarithmic distribution
Reliability sampling plans are the sampling inspection procedures used in determining the disposition of the lot(s) of products when the lifetime of...
