Predicting Engine Parameters using the Optical Spectrum

A Publication, Ashok Srivastava's Collection - 10 years, 4 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 - 10 years, 4 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 - 10 years, 4 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 - 10 years, 4 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 - 10 years, 4 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 - 10 years, 4 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 ...

Stable and Efficient Gaussian Process Calculations

A Publication, Ashok Srivastava's Collection - 10 years, 4 months ago

Shared By: Ashok Srivastava

The use of Gaussian processes can be an effective approach to prediction in a supervised learning environment. For large data sets, the standard Gaussian process ...

Comparison of Unsupervised Anomaly Detection Methods

A Publication, Ashok Srivastava's Collection - 10 years, 4 months ago

Shared By: Ashok Srivastava

Several different unsupervised anomaly detection algorithms have been applied to Space Shuttle Main Engine (SSME) data to serve the purpose of developing a comprehensive suite ...

Comparative Analysis of Data-Driven Anomaly Detection Methods

A Publication, Ashok Srivastava's Collection - 10 years, 4 months ago

Shared By: Ashok Srivastava

This paper provides a review of three different advanced machine learning algorithms for anomaly detection in continuous data streams from a ground-test firing of a ...

Novel Methods for Predicting Photometric Redshifts

A Publication, Ashok Srivastava's Collection - 10 years, 4 months ago

Shared By: Ashok Srivastava

We calculate photometric redshifts from the Sloan Digital Sky Survey Main Galaxy Sample, The Galaxy Evolution Explorer All Sky Survey, and The Two Micron All ...

Algorithms for Spectral Decomposition with Applications

A Publication, Ashok Srivastava's Collection - 10 years, 4 months ago

Shared By: Ashok Srivastava

The analysis of spectral signals for features that represent physical phenomenon is ubiquitous in the science and engineering communities. There are two main approaches that ...

Detection and Prognostics on Low Dimensional Systems

A Publication, Ashok Srivastava's Collection - 10 years, 4 months ago

Shared By: Ashok Srivastava

This paper describes the application of known and novel prognostic algorithms on systems that can be described by low dimensional, potentially nonlinear dynamics. The methods ...

Anomaly Detection and Diagnosis Algorithms for Discrete Symbols

A Publication, Ashok Srivastava's Collection - 10 years, 4 months ago

Shared By: Ashok Srivastava

We present a set of novel algorithms which we call sequenceMiner that detect and characterize anomalies in large sets of high-dimensional symbol sequences that arise ...

Discovering System Health Anomalies using Data Mining Techniques

A Publication, Ashok Srivastava's Collection - 10 years, 4 months ago

Shared By: Ashok Srivastava

We discuss a statistical framework that underlies envelope detection schemes as well as dynamical models based on Hidden Markov Models (HMM) that can encompass both ...