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Li-ion Battery Aging Datasets
This data set has been collected from a custom built battery prognostics testbed at the NASA Ames Prognostics Center of Excellence (PCoE). Li-ion batteries were run through 3... -
Discovering Anomalous Aviation Safety Events Using Scalable Data Mining Algorithms
The worldwide civilian aviation system is one of the most complex dynamical systems created. Most modern commercial aircraft have onboard flight data recorders that record... -
Distributed Anomaly Detection using 1-class SVM for Vertically Partitioned Data
There has been a tremendous increase in the volume of sensor data collected over the last decade for different monitoring tasks. For example, petabytes of earth science data are... -
Multivariate Time Series Search
Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical monitoring,... -
Damage Propagation Modeling for Aircraft Engine Run-to-Failure Simulation
This paper describes how damage propagation can be modeled within the modules of aircraft gas turbine engines. To that end, response surfaces of all sensors are generated via a... -
First International Diagnosis Competition – DXC’09
A framework to compare and evaluate diagnosis algorithms (DAs) has been created jointly by NASA Ames Research Center and PARC. In this paper, we present the first concrete... -
Project GitHub
Release of CertWare was announced 23 Mar 2012 on: code.nasa.gov The announcement points to the Certware project on NASA’s GitHub repository at: nasa.github.com/CertWare The... -
Discriminative Mixed-Membership Models
Although mixed-membership models have achieved great success in unsupervised learning, they have not been widely applied to classification problems. In this paper, we propose a... -
nu-Anomica algorithm
One-class nu-Support Vector machine (SVMs) learning technique maps the input data into a much higher dimensional space and then uses a small portion of the training data... -
Mining Distance-Based Outliers in Near Linear Time
Full title: Mining Distance-Based Outliers in Near Linear Time with Randomization and a Simple Pruning Rule Abstract: Defining outliers by their distance to neighboring examples... -
Theoretically Optimal Distributed Anomaly Detection
A novel general framework for distributed anomaly detection with theoretical performance guarantees is proposed. Our algorithmic approach combines existing anomaly detection... -
SAR Image Enhancement using Particle Filters
In this paper, we propose a novel approach to reduce the noise in Synthetic Aperture Radar (SAR) images using particle filters. Interpretation of SAR images is a difficult... -
New Approaches To Photometric Redshift Prediction
Expanding upon the work of Way & Srivastava (2006) we demonstrate how the use of training sets of comparable size continue to make Gaussian Process Regression a competitive... -
Qualitative Event-based Diagnosis with Possible Conflicts Applied to Spacecraft Power Distribution Systems
Model-based diagnosis enables efficient and safe operation of engineered systems. In this paper, we describe two algorithms based on a qualitative event-based fault isolation... -
Uncertainty Management for Diagnostics and Prognostics of Batteries using Bayesian Techniques
Uncertainty management has always been the key hurdle faced by diagnostics and prognostics algorithms. A Bayesian treatment of this problem provides an elegant and theoretically...
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