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Identification of Spatial Fault Patterns in Semiconductor Wafers recent views
Abstract The semiconductor industry is constantly searching for new ways to increase the rate of both process development and yield learning. As more data is being collected and... -
SAR Image Enhancement using Particle Filters recent views
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... -
Unsupervised Anomaly Detection for Liquid-Fueled Rocket Prop... recent views
Title: Unsupervised Anomaly Detection for Liquid-Fueled Rocket Propulsion Health Monitoring. Abstract: This article describes the results of applying four unsupervised anomaly... -
Classification recent views
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 examples---... -
ASE SIM Workshop WEBCAST Link & Presentation Slides recent views
Link to Aeroservoelasticity Simulation Workshop WEBCAST -
Analysis of Virtual Sensors for Predicting Aircraft Fuel Consumption recent views
Previous research described the use of machine learning algorithms to predict aircraft fuel consumption. This technique, known as Virtual Sensors, models fuel consumption as a... -
Pseudo-Label Generation for Multi-Label Text Classification recent views
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, new and... -
Anomaly Detection in a Fleet of Systems recent views
A fleet is a group of systems (e.g., cars, aircraft) that are designed and manufactured the same way and are intended to be used the same way. For example, a fleet of delivery... -
A Survey of Artificial Intelligence for Prognostics recent views
Integrated Systems Health Management includes as key elements fault detection, fault diagnostics, and failure prognostics. Whereas fault detection and diagnostics have been the... -
Estimation of Faults in DC Electrical Power System recent views
This paper demonstrates a novel optimizationbased approach to estimating fault states in a DC power system. The model includes faults changing the circuit topology along with... -
Data Mining in Systems Health Management recent views
This chapter presents theoretical and practical aspects associated to the implementation of a combined model-based/data-driven approach for failure prognostics based on particle... -
Automated Discovery of Flight Track Anomalies recent views
As new technologies are developed to handle the complexities of the Next Generation Air Transportation System (NextGen), it is increasingly important to address both current and... -
Diagnosing Faults in Electrical Power Systems of Spacecraft and Aircraft recent views
Electrical power systems play a critical role in spacecraft and aircraft, and they exhibit a rich variety of failure modes. This paper discusses electrical power system fault... -
The Case for Software Health Management recent views
Software Health Management (SWHM) is a new field that is concerned with the development of tools and technologies to enable automated detection, diagnosis, prediction, and... -
A Model-based Avionic Prognostic Reasoner (MAPR) recent views
The Model-based Avionic Prognostic Reasoner (MAPR) presented in this paper is an innovative solution for non-intrusively monitoring the state of health (SoH) and predicting the... -
Fleet Level Anomaly Detection of Aviation Safety Data recent views
For the purposes of this paper, the National Airspace System (NAS) encompasses the operations of all aircraft which are subject to air traffic control procedures. The NAS is a... -
DATA MINING THE GALAXY ZOO MERGERS recent views
DATA MINING THE GALAXY ZOO MERGERS STEVEN BAEHR, ARUN VEDACHALAM, KIRK BORNE, AND DANIEL SPONSELLER Abstract. Collisions between pairs of galaxies usually end in the coalescence... -
Comparative Analysis of Data-Driven Anomaly Detection Methods recent views
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 subscale... -
Improving Computational Efficiency of Prediction in Model-based Prognostics Using the Unscented Transform recent views
Model-based prognostics captures system knowledge in the form of physics-based models of components, and how they fail, in order to obtain accurate predictions of end of life...