Digital Commons Network^™

Anomaly Detection On Small Wind Turbine Blades Using Deep Learning Algorithms, Bridger Altice, Edwin Nazario, Mason Davis, Mohammad Shekaramiz, Todd K. Moon, Mohammad A. S. Masoum

Electrical and Computer Engineering Faculty Publications

Wind turbine blade maintenance is expensive, dangerous, time-consuming, and prone to misdiagnosis. A potential solution to aid preventative maintenance is using deep learning and drones for inspection and early fault detection. In this research, five base deep learning architectures are investigated for anomaly detection on wind turbine blades, including Xception, Resnet-50, AlexNet, and VGG-19, along with a custom convolutional neural network. For further analysis, transfer learning approaches were also proposed and developed, utilizing these architectures as the feature extraction layers. In order to investigate model performance, a new dataset containing 6000 RGB images was created, making use of indoor and …

Tess As A Low-Surface-Brightness Observatory: Cutouts From Wide-Area Coadded Images, G. Bruce Berriman, John C. Good, Benne Holwerda

Faculty Scholarship

We present a mosaic of those co-added Full Frame Images acquired by the TESS satellite that had been released in 2020 April. The mosaic shows substantial stray light over the sky. Yet over spatial scales of a few degrees, the background appears uniform. This result indicates that TESS has considerable potential as a Low Surface Brightness Observatory. The co-added images are freely available as a High Level Science Product (HLSP) at MAST and accessible through a Jupyter Notebook.

Performance Evaluation Of Uavsar And Simulated Nisar Data For Crop/Noncrop Classification Over Stoneville, Ms, Simon Kraatz, S. Rose, M. H. Cosh, N. Torbick, X. Huang, P. Siquiera

Electrical and Computer Engineering Faculty Publication Series

Synthetic Aperture Radar (SAR) data are well-suited for change detection over agricultural fields, owing to high spatiotemporal resolution and sensitivity to soil and vegetation. The goal of this work is to evaluate the science algorithm for the NASA ISRO SAR (NISAR) Cropland Area product using data collected by NASA's airborne Uninhabited Aerial Vehicle SAR (UAVSAR) platform and the simulated NISAR data derived from it. This study uses mode 129, which is to be used for global-scale mapping. The mode consists of an upper (129A) and lower band (129B), respectively having bandwidths of 20 and 5 MHz. This work uses 129A …

Machine Learning Pipeline For Exoplanet Classification, George Clayton Sturrock, Brychan Manry, Sohail Rafiqi

SMU Data Science Review

Planet identification has typically been a tasked performed exclusively by teams of astronomers and astrophysicists using methods and tools accessible only to those with years of academic education and training. NASA’s Exoplanet Exploration program has introduced modern satellites capable of capturing a vast array of data regarding celestial objects of interest to assist with researching these objects. The availability of satellite data has opened up the task of planet identification to individuals capable of writing and interpreting machine learning models. In this study, several classification models and datasets are utilized to assign a probability of an observation being an exoplanet. …

Applications Of Nasa Earth Observations For Monitoring Forest Loss In The Madre De Dios Region Of Peru, Andrea Nicolau, Kelsey Herndon, Africa Flores, Robert Griffin

Von Braun Symposium Student Posters

No abstract provided.

The Encyclopedia Of Neutrosophic Researchers - Vol. 2, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

This is the second volume of the Encyclopedia of Neutrosophic Researchers, edited from materials offered by the authors who responded to my invitation. The introduction contains a short history of neutrosophics, together with links to the main papers and books. The authors who have published neutrosophic papers, books, or defended neutrosophic master theses or PhD dissertations and are not included in the two ENR volumes, are kindly invited to send their self-presentations or their CVs, a photo, and a list of neutrosophic publications to smarand@unm.edu and neutrosophy@laposte.net to be part of a third volume.

Florentin Smarandache

Data Mining By Grid Computing In The Search For Extrasolar Planets, Oisin Creaner [Thesis]

Doctoral

A system is presented here to provide improved precision in ensemble differential photometry. This is achieved by using the power of grid computing to analyse astronomical catalogues. This produces new catalogues of optimised pointings for each star, which maximise the number and quality of reference stars available. Astronomical phenomena such as exoplanet transits and small-scale structure within quasars may be observed by means of millimagnitude photometric variability on the timescale of minutes to hours. Because of atmospheric distortion, ground-based observations of these phenomena require the use of differential photometry whereby the target is compared with one or more reference stars. …

Building A Scalable Global Data Processing Pipeline For Large Astronomical Photometric Datasets, Paul Doyle

Other

Astronomical photometry is the science of measuring the flux of a celestial object. Since its introduction, the CCD has been the principle method of measuring flux to calculate the apparent magnitude of an object. Each CCD image taken must go through a process of cleaning and calibration prior to its use. As the number of research telescopes increases the overall computing resources required for image processing also increases. Existing processing techniques are primarily sequential in nature, requiring increasingly powerful servers, faster disks and faster networks to process data. Existing High Performance Computing solutions involving high capacity data centres are complex …

The Einstein@Home Search For Radio Pulsars And Psr J2007+2722 Discovery, B. Allen, B. Knispel, J. M. Cordes, J. S. Deneva, J. W.T. Hessels, D. Anderson, C. Aulbert, O. Bock, A. Brazier, S. Chatterjee, P. B. Demorest, H. B. Eggenstein, H. Fehrmann, E. V. Gotthelf, D. Hammer, V. M. Kaspi, M. Kramer, A. G. Lyne, B. Machenschalk, M. A. Mclaughlin, C. Messenger, H. J. Pletsch, S. M. Ransom, I. H. Stairs, B. W. Stappers, N. D.R. Bhat, S. Bogdanov, F. Camilo, D. J. Champion, F. Crawford

Physics and Astronomy Faculty Publications and Presentations

Einstein@Home aggregates the computer power of hundreds of thousands of volunteers from 193 countries, to search for new neutron stars using data from electromagnetic and gravitational-wave detectors. This paper presents a detailed description of the search for new radio pulsars using Pulsar ALFA survey data from the Arecibo Observatory. The enormous computing power allows this search to cover a new region of parameter space; it can detect pulsars in binary systems with orbital periods as short as 11 minutes. We also describe the first Einstein@Home discovery, the 40.8 Hz isolated pulsar PSR J2007+2722, and provide a full timing model. PSR …

2013 Annual Meeting Program

Journal of the South Carolina Academy of Science

No abstract provided.

The Physical Conditions Within Dense Cold Clouds In Cooling Flows - Ii, Gary J. Ferland, A. C. Fabian, R. M. Johnstone

Physics and Astronomy Faculty Publications

This is a progress report on our numerical simulations of conditions in the cold cores of cooling flow condensations. The physical conditions in any non-equilibrium plasma are the result of a host of microphysical processes, many involving reactions that are research areas in themselves. We review the dominant physical processes in our previously published simulations, to clarify those issues that have caused confusion in the literature. We show that conditions in the core of an X-ray-illuminated cloud are very different from those found in molecular clouds, largely because carbon remains substantially atomic and provides powerful cooling through its far infrared …