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Discovery and Analysis of Rare High-Impact Failure Modes Using Adversarial RL-Informed Sampling
Adaptive learning agents have tremendous potential to handle critical tasks currently performed by humans. Unfortunately, due to their complexity, it...
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A rare failure detection model for aircraft predictive maintenance using a deep hybrid learning approach
The use of aircraft operation logs to develop a data-driven model to predict probable failures that could cause interruption poses many challenges...
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EMSNet: Extremely multi-scale network for salient object detection
In salient object detection, accurately segmenting objects across scales and refining boundaries are crucial challenges. We introduce the Multi-UNet...
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A novel deep learning approach for intelligent bearing fault diagnosis under extremely small samples
Rotor bearing health is crucial for ensuring the operational stability of rotating equipment. Deep learning-based fault diagnosis methods have...
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A review of machine learning-based failure management in optical networks
Failure management plays a significant role in optical networks. It ensures secure operation, mitigates potential risks, and executes proactive...
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Analysis of non-Markovian repairable fault trees through rare event simulation
Dynamic fault trees (DFTs) are widely adopted in industry to assess the dependability of safety-critical equipment. Since many systems are too large...
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An Empirical Study on Anomaly Detection Algorithms for Extremely Imbalanced Datasets
Anomaly detection attempts to identify abnormal events that deviate from normality. Since such events are often rare, data related to this domain is...
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Discovery of Rare Itemsets Using Hyper-Linked Data Structure: A Parallel Approach
Pattern mining has been more important in the solution of various data mining jobs over the years. The extraction of common patterns was the primary...
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Systematic Evaluation of Deep Learning Models for Log-based Failure Prediction
With the increasing complexity and scope of software systems, their dependability is crucial. The analysis of log data recorded during system...
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Siamese Networks for Unsupervised Failure Detection in Smart Industry
In industrial production systems, detecting malfunctions or unexpected behavior in devices early is crucial to avoid critical situations for both...
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Multivariate Time-Series Anomaly Detection with Temporal Self-supervision and Graphs: Application to Vehicle Failure Prediction
Failure prediction is key to ensuring the reliable operation of vehicles, especially for organizations that depend on a fleet of vehicles. However,...
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Long-Term Pipeline Failure Prediction Using Nonparametric Survival Analysis
Australian water infrastructure is more than a hundred years old, thus has begun to show its age through water main failures. Our work concerns...
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Dynamic swarm class rebalancing for the process mining of rare events
Process mining is becoming an indispensable method in workflow model reconstructions, offering insights into mission critical systems. The efficacy...
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On the Variance Reduction Methods for Estimating the Reliability of the Multi-phase Gaussian Degradation System
We consider the Gaussian multi-phase degradation model. The primary target quantity is reliability defined as the tail distribution of the system...
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An application of active learning Kriging for the failure probability and sensitivity functions of turbine disk with imprecise probability distributions
For the reliability analysis with imprecise probability distributions, the failure probability and its sensitivity are always denoted as the...
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Generative Adversarial Networks for Failure Prediction
Prognostics and Health Management (PHM) is an emerging engineering discipline which is concerned with the analysis and prediction of equipment health...
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Using Statistical Model Checking for Cybersecurity Analysis
This work discusses an approach to estimate the likelihood of occurrence and evolution in time of software security issues. First, software...
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Rare-Event Simulation for the Hitting Time of Gaussian Processes
In reliability theory and network performance analysis a relevant role is played by the time needed to reach a given threshold, known in probability...
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Semi-supervised diagnosis of wind-turbine gearbox misalignment and imbalance faults
AbstractBoth wear-induced bearing failure and misalignment of the powertrain between the rotor and the electrical generator are common failure modes...
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Analysis of Network Attacks
In this chapter, we will review a large variety of different attacks at the packet level. This is one of the most important things to remember, and...