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Federal
Classification of Mars Terrain Using Multiple Data Sources
National Aeronautics and Space Administration —
Classification of Mars Terrain Using Multiple Data Sources Alan Kraut1, David Wettergreen1 ABSTRACT. Images of Mars are being collected faster than they can be... -
Federal
KEYWORD SEARCH IN TEXT CUBE: FINDING TOP-K RELEVANT CELLS
National Aeronautics and Space Administration —
KEYWORD SEARCH IN TEXT CUBE: FINDING TOP-K RELEVANT CELLS BOLIN DING, YINTAO YU, BO ZHAO, CINDY XIDE LIN, JIAWEI HAN, AND CHENGXIANG ZHAI Abstract. We study the... -
Federal
Classification
National Aeronautics and Space Administration —
A supervised learning task involves constructing a mapping from an input data space (normally described by several features) to an output space. A set of training... -
Federal
ADAPTIVE FAULT DETECTION ON LIQUID PROPULSION SYSTEMS WITH VIRTUAL SENSORS: ALGORITHMS AND ARCHITECTURES
National Aeronautics and Space Administration —
Prior to the launch of STS-119 NASA had completed a study of an issue in the flow control valve (FCV) in the Main Propulsion System of the Space Shuttle using an... -
Federal
Distributed Anomaly Detection using 1-class SVM for Vertically Partitioned Data
National Aeronautics and Space Administration —
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... -
Federal
Sparse Solutions for Single Class SVMs: A Bi-Criterion Approach
National Aeronautics and Space Administration —
In this paper we propose an innovative learning algorithm - a variation of One-class Support Vector Machines (SVMs) learning algorithm to produce sparser solutions... -
Federal
Unsupervised Anomaly Detection for Liquid-Fueled Rocket Prop...
National Aeronautics and Space Administration —
Title: Unsupervised Anomaly Detection for Liquid-Fueled Rocket Propulsion Health Monitoring. Abstract: This article describes the results of applying four... -
Federal
Optimal Alarm Systems
National Aeronautics and Space Administration —
An optimal alarm system is simply an optimal level-crossing predictor that can be designed to elicit the fewest false alarms for a fixed detection probability. It... -
Federal
nu-Anomica algorithm
National Aeronautics and Space Administration —
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... -
Federal
A Modeling Framework for Prognostic Decision Making and its Application to UAV Mission Planning
National Aeronautics and Space Administration —
The goal of prognostic decision making (PDM) is to utilize information on anticipated system health changes in selecting future actions. One of the key challenges in... -
Federal
Pseudo-Label Generation for Multi-Label Text Classification
National Aeronautics and Space Administration —
With the advent and expansion of social networking, the amount of generated text data has seen a sharp increase. In order to handle such a huge volume of text data,... -
Federal
MULTI-LABEL ASRS DATASET CLASSIFICATION USING SEMI-SUPERVISED SUBSPACE CLUSTERING
National Aeronautics and Space Administration —
MULTI-LABEL ASRS DATASET CLASSIFICATION USING SEMI-SUPERVISED SUBSPACE CLUSTERING MOHAMMAD SALIM AHMED, LATIFUR KHAN, NIKUNJ OZA, AND MANDAVA RAJESWARI Abstract.... -
Federal
Communication Optimizations for a Wireless Distributed Prognostic Framework
National Aeronautics and Space Administration —
Distributed architecture for prognostics is an essential step in prognostic research in order to enable feasible real-time system health management. Communication... -
Federal
Fault Adaptive Control of Overactuated Systems Using Prognostic Estimation
National Aeronautics and Space Administration —
Most fault adaptive control research addresses the preservation of system stability or functionality in the presence of a specific failure (fault). This paper... -
Federal
Comparative Analysis of Data-Driven Anomaly Detection Methods
National Aeronautics and Space Administration —
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... -
Federal
USAGE OF DISSIMILARITY MEASURES AND MULTIDIMENSIONAL SCALING FOR LARGE SCALE SOLAR DATA ANALYSIS
National Aeronautics and Space Administration —
USAGE OF DISSIMILARITY MEASURES AND MULTIDIMENSIONAL SCALING FOR LARGE SCALE SOLAR DATA ANALYSIS Juan M Banda, Rafal Anrgyk ABSTRACT: This work describes the... -
Federal
Friedl presentation at CIDU
National Aeronautics and Space Administration —
The land remote sensing community has a long history of using supervised and unsupervised methods to help interpret and analyze remote sensing data sets. Until... -
Federal
PROBABILITY CALIBRATION BY THE MINIMUM AND MAXIMUM PROBABILITY SCORES IN ONE-CLASS BAYES LEARNING FOR ANOMALY DETECTION
National Aeronautics and Space Administration —
PROBABILITY CALIBRATION BY THE MINIMUM AND MAXIMUM PROBABILITY SCORES IN ONE-CLASS BAYES LEARNING FOR ANOMALY DETECTION GUICHONG LI, NATHALIE JAPKOWICZ, IAN HOFFMAN,... -
Federal
Deterministic Compilation of Temporal Safety Properties in Explicit State Model Checking
National Aeronautics and Space Administration —
The translation of temporal logic specifications constitutes an essen- tial step in model checking and a major influence on the efficiency of formal verification via... -
Federal
ν-Anomica: A Fast Support Vector based Novelty Detection Technique
National Aeronautics and Space Administration —
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 to the benchmark...