User Centered, Application Independent Visualization of National Airspace Data

This paper describes an application independent software tool, IV4D, built to visualize animated and still 3D National Airspace System (NAS) data specifically for aeronautics engineers who research aggregate, as well as single, flight efficiencies and behavior. IV4D was origin ally developed in a joint effort between the National Aeronautics and Space Administration (NASA) and the Air Force Research Laboratory (A FRL) to support the visualization of air traffic data from the Airspa ce Concept Evaluation System (ACES) simulation program. The three mai n challenges tackled by IV4D developers were: 1) determining how to d istill multiple NASA data formats into a few minimal dataset types; 2 ) creating an environment, consisting of a user interface, heuristic algorithms, and retained metadata, that facilitates easy setup and fa st visualization; and 3) maximizing the user?s ability to utilize the extended range of visualization available with AFRL?s existing 3D te chnologies. IV4D is currently being used by air traffic management re searchers at NASA?s Ames and Langley Research Centers to support data visualizations

Novel audio lures to improve interaction and encounter rates of possums (Trichosurus vulpecula) with control methods in New Zealand

The brushtail possum (Trichosurus vulpecula), a marsupial native to Australia, was widely introduced in both the North and South Islands of New Zealand between 1890 and 1930 to support the fur industry that was booming in Australia at the time. Possums were one of the many mammalian species that humans introduced when they discovered and settled in New Zealand. Before the settlement of humans in New Zealand, there were no terrestrial mammals; therefore, the local species evolved in the absence of mammalian predators. This resulted in native species populations falling at alarming rates and possibly facing extinction due to numerous predators and species that had not been intended to coexist alongside one another. The government's initiative to reduce New Zealand's predators (possums, rats, and stoats) by 2050 has significantly expanded efforts to eliminate these pest mammals in recent years. Managing these pest mammal populations is crucial to protect the native bird, reptile, and invertebrate species. In New Zealand, predator control has been practiced for a long time, but what started with simple trapping has since developed into a thriving industry full of expertise to boost the efficiency of trapping and toxins, including species-specific attractants. The number of traps and bait stations needed to be set up and the associated labour and expense would be significantly reduced if animals could be reliably drawn from a distance to a bait station or trap. Any sound played to encourage or discourage interaction with a control tool/area is known as an audio lure. This research aims to identify if audio lures can significantly increase possum encounter and interaction rates of control devices and establish an audio lure tool that is durable, easy to use, and cost-effective for the wider public to use. Preliminary captive trials found that an aggressive possum sound is significantly more attractive to possums than an alarmed possum sound, a beeping sound, or a control (no sound). Preliminary field trials have found that the audio lure being developed performs similarly to an already established audio lure included as part of the Cacophony Project Thermal Camera. The price point of the audio lure being developed is around $250 (NZD) and should last 30 days in the field. At the conference, I will present the final captive trial results and more field trial research. The field trial research will investigate encounter and interaction rates of possums feeding in live-capture traps with and without audio lures. I will also, report the final audio lure costings and field life before servicing is required

The Stellar Halos of Massive Elliptical Galaxies II: Detailed Abundance Ratios at Large Radius

We study the radial dependence in stellar populations of 33 nearby early-type galaxies with central stellar velocity dispersions sigma* > 150 km/s. We measure stellar population properties in composite spectra, and use ratios of these composites to highlight the largest spectral changes as a function of radius. Based on stellar population modeling, the typical star at 2 R_e is old (~10 Gyr), relatively metal poor ([Fe/H] -0.5), and alpha-enhanced ([Mg/Fe]~0.3). The stars were made rapidly at z~1.5-2 in shallow potential wells. Declining radial gradients in [C/Fe], which follow [Fe/H], also arise from rapid star formation timescales due to declining carbon yields from low-metallicity massive stars. In contrast, [N/Fe] remains high at large radius. Stars at large radius have different abundance ratio patterns from stars in the center of any present-day galaxy, but are similar to Milky Way thick disk stars. Our observations are thus consistent with a picture in which the stellar outskirts are built up through minor mergers with disky galaxies whose star formation is truncated early (z~1.5-2).Comment: ApJ in press, 12 pages, 6 figure

Low-Power Boards Enabling ML-Based Approaches to FDIR in Space-Based Applications

Modern satellite complexity is increasing, thus requiring bespoke and expensive on-board solutions to provide a Failure Detection, Isolation and Recovery (FDIR) function. Although FDIR is vital in ensuring the safety, autonomy, and availability of satellite systems in flight, there is a clear need in the space industry for a more adaptable, scalable, and cost-effective solution. This paper explores the current state of the art for Machine Learning error detection and prognostic algorithms utilized by both the space sector and the commercial sector. Although work has previously been done in the commercial sector on error detection and prognostics, most commercial applications are not nearly as limited by the power, mass, and radiation tolerance constraints as for operation in a space environment. Therefore, this paper also discusses several Commercial Off-The-Shelf (COTS) multi-core micro-processors, small-footprint boards that will be explored as possible testbeds for future integration into a satellite in-orbit demonstrator

Developing Machine Learning Models for Space Based Edge AI Platforms

On September 3rd 2020, one of the first small satellites equipped with Edge AI hardware was launched. The inclusion of a UB0100 board on PhiSat-1 enabled the use of deep neural networks to provide real-time image analysis on-board an Earth Observation satellite. The primary benefit of this was a 90% reduction in downlink data as the system only transmitted non-cloudy, and thus usable, data. PhiSat-1 and missions like it have started the revolution of satellite-based machine learning, leading ESA and other space agencies to further explore the in-situ deployment of machine-learning models. Other applications that can benefit from on-board space-based machine learning capabilities range from anomaly detection and prognostics to feature recognition and object detection. This paper focuses on the application of anomaly detection models on space-ready Edge AI hardware to detect and classify anomalous behaviour in telemetry data. The ability to accurately detect anomalies onboard satellite systems has the potential to both increase system lifetimes and reduce satellite operator workloads. The limitations of Edge AI boards and the space environment put restrictions on the models that can be used. Limited power and potential single event upsets constrain the complexity of the models that can be deployed. Therefore, this paper is targeted at models that will run efficiently within these constraints. We describe an experiment that evaluates the suitability of different anomaly detection approaches (multi-layer-perceptrons, auto-encoders, etc.) for space applications. These approaches are compared both in terms of their performance in the anomaly detection tasks and how well they run on “space ready” low-power hardware. We focus on the Intel Myriad chipset, the basis of the UB0100, which hosted the machine learning image analysis model on PhiSat-1. Our evaluations use both the MIMII machine audio dataset, a well-regarded anomaly detection dataset that is a good proxy for telemetry data, and a dataset generated using anonymized NASA mission telemetry data. The findings show how well basic models work when presented with anomalous satellite telemetry

MECHANISMS FOR ADDRESSING THIRD-PARTY IMPACTS RESULTING FROM VOLUNTARY WATER TRANSFERS

This research uses laboratory experiments to test alternative water market institutions designed to protect third-party interests. The institutions tested include taxing mechanisms that raise revenue to compensate affected third-parties, and a free market in which third-parties actively participate. We also discuss the likely implications of a command-and-control approach in which there are fixed limits on the volume of water that may be exported from a region. The results indicate that there are some important trade-offs in selecting a policy option. Although theoretically optimal, active third-party participation in the market is likely to result in free-riding that may erode some or all of the efficiency gains, and may introduce volatility into the market. Fixed limits on water exports are likely to result in a more stable market, but the constraints on exports will result in lower levels of social welfare. Taxing transfers and compensating third-parties offers a promising balance of efficiency, equity and market stability.Resource /Energy Economics and Policy,

Interdisciplinary Environmental Education Program for Teachers

Environmental education offers a unique opportunity for innovative teaching because no one is around to say, But, I always did it this way. Thus new environmental programs do not have to overcome the educational inertia of tradition which has stopped many new instructional movements dead in their tracks

Sharing as Risk Pooling in a Social Dilemma Experiment

In rural economies with missing or incomplete markets, idiosyncratic risk is frequently pooled through informal networks. Idiosyncratic shocks, however, are not limited to private goods but can also restrict an individual from partaking in or benefiting from a collective activity. In these situations, a group must decide whether to provide insurance to the affected member. In this paper, we describe results of a laboratory experiment designed to test whether a simple sharing institution can sustain risk pooling in a social dilemma with idiosyncratic risk. We test whether risk can be pooled without a commitment device and, separately, whether effective risk pooling induces greater cooperation in the social dilemma. We find that even in the absence of a commitment device or reputational considerations, subjects voluntarily pool risk thereby reducing variance in individual earnings. In spite of effective risk pooling, however, cooperation in the social dilemma is unaffected

Corrosion of Civil War Era Sub Marine Explorer—Part 1

The Sub Marine Explorer is one of five submersibles (submarines) constructed prior to 1870 that have survived either in museums or as in situ archaeological sites around the world. Since 1869, the wreck of Explorer has emerged at low tide on the beach of Isla San Telmo, Archipiélago de las Perlas, Panama, located ~75 km southwest of Panama City in the Bay of Panama. In 2001, James Delgado visited the site. Locals described the wreck as a World War II-era Japanese midget submarine. Delgado consulted with Richard Wills, an expert on American Civil War submarines, and confirmed that the well-preserved wreck was the Sub Marine Explorer from the Civil War period

The effect of forced vergence on heart rate

The effect of forced vergence on heart rat