Unsupervised Anomaly Detection for Liquid-Fueled Rocket Prop...

A Publication, MARK SCHWABACHER's Collection - 14 years, 5 months ago

Shared By: MARK SCHWABACHER

Title: Unsupervised Anomaly Detection for Liquid-Fueled Rocket Propulsion Health Monitoring. Abstract: This article describes the results of applying four unsupervised anomaly detection algorithms to data ...

Long-term prediction of nonlinear time series

A Publication, Indir Jaganjac's Collection - 14 years, 4 months ago

Shared By: Indir Jaganjac

This paper is about applying recurrent least squares support vector machines (LS-SVM) on three ESTSP08 competition datasets. Least squares support vector machines are used as ...

A Local Scalable Distributed EM Algorithm for Large P2P Networks

A Publication, Ashok Srivastava's Collection - 11 years, 2 months ago

Shared By: Ashok Srivastava

his paper describes a local and distributed expectation maximization algorithm for learning parameters of Gaussian mixture models (GMM) in large peer-to-peer (P2P) environments. The algorithm ...

Anomica: Fast Support Vector Based Novelty Detection

A Publication, Ashok Srivastava's Collection - 11 years, 2 months ago

Shared By: Ashok Srivastava

In this paper we propose ν-Anomica, a novel anomaly detection technique that can be trained on huge data sets with much reduced running time compared ...

New Approaches To Photometric Redshift Prediction

A Publication, Ashok Srivastava's Collection - 11 years, 2 months ago

Shared By: Ashok Srivastava

Expanding upon the work of Way & Srivastava (2006) we demonstrate how the use of training sets of comparable size continue to make Gaussian Process ...

Highly Scalable Matching Pursuit Signal Decomposition Algorithm

A Publication, Ashok Srivastava's Collection - 11 years, 2 months ago

Shared By: Ashok Srivastava

In this research, we propose a variant of the classical Matching Pursuit Decomposition (MPD) algorithm with significantly improved scalability and computational performance. MPD is a ...

Data Mining at NASA: From Theory to Applications

A Publication, Ashok Srivastava's Collection - 11 years, 2 months ago

Shared By: Ashok Srivastava

NASA has some of the largest and most complex data sources in the world, with data sources ranging from the earth sciences, space sciences, and ...

Classification of Damage Signatures in Composite Plates using On

A Publication, Santanu Das's Collection - 14 years, 5 months ago

Shared By: Santanu Das

Damage characterization through wave propagation and scattering is of considerable interest to many non-destructive evaluation techniques. For fiber-reinforced composites, complex waves can be generated during ...

Predicting Engine Parameters using the Optical Spectrum

A Publication, Ashok Srivastava's Collection - 11 years, 2 months ago

Shared By: Ashok Srivastava

The Optical Plume Anomaly Detection (OPAD) system is under development to predict engine anomalies and engine parameters of the Space Shuttle's Main Engine (SSME). The ...

Discovery of Recurring Anomalies in Text Reports

A Publication, Ashok Srivastava's Collection - 11 years, 2 months ago

Shared By: Ashok Srivastava

This paper describes the results of a significant research and development effort conducted at NASA Ames Research Center to develop new text mining algorithms to ...

Onboard Detection of Snow, Ice, Clouds, and Other Processes

A Publication, Ashok Srivastava's Collection - 11 years, 2 months ago

Shared By: Ashok Srivastava

The detection of clouds within a satellite image is essential for retrieving surface geophysical parameters from optical and thermal imagery. Even a small percentage of ...

Mixture Density Mercer Kernels: A Method to Learn Kernels

A Publication, Ashok Srivastava's Collection - 11 years, 2 months ago

Shared By: Ashok Srivastava

This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian ...

Characterizing Variability and Multi-Resolution Predictions

A Publication, Ashok Srivastava's Collection - 11 years, 2 months ago

Shared By: Ashok Srivastava

In previous papers, we introduced the idea of a Virtual Sensor, which is a mathematical model trained to learn the potentially nonlinear relationships between spectra ...

Ensemble Approach to Building Mercer Kernels

A Publication, Ashok Srivastava's Collection - 11 years, 2 months ago

Shared By: Ashok Srivastava

This paper presents a new methodology for automatic knowledge driven data mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive ...