Application of Hasse Diagrams for Counting Topologies on Finite Sets Technical Report No. 14
Diagram method for counting topologies on finite sets
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Diagram method for counting topologies on finite sets
Cyclotomic numbers of order 18 with applications to difference sets
Closure and convexity of attainable control sets in finite and infinite dimensions, noting Liapunov theorem
Geophysics research has been faced with a growing need for automated techniques with which to process large quantities of data. A successful tool must meet a number of requirements: it should be consistent, require minimal parameter tuning, and produce scientifically meaningful results in reasonable time. We introduce a hidden Markov model (HMM)-based method for analysis of geophysical data sets that attempts to address these issues.
We propose a summary product that describes data belonging to each one degree grid cell by a set of multivariate representatives and weights and errors associated with them.
This talk discusses a method for creating low-volume versions of massive geophysical data sets that approximately retain high-resolution data structure.
This paper describes a method for summaraizing data in a way that approximately preserves high-resolution data structure while reducing data volume and maintaining global integrity of very large, remote sensing data sets. The method is under development for one of Terra's instruments, the Multi-angle Imaging SpectroRadiometer (MISR).
The NASA Airspace Technology Demonstration 2 Phase 1 and 2 Field Evaluations have successfully demonstrated new technologies developed to manage the Integrated Arrival, Departure, and Surface traffic flows at a single airport. The Phase 3 Field Evaluation extends the capabilities to a Metroplex environment where multiple airports are interacting and sharing resources along the terminal boundary. This paper describes the scheduling algorithm enabling the coordinated scheduling and describes the interaction between airports within the Metroplex and the terminal boundary. We describe the metrics developed to inform flight operators about reroute opportunities and discuss the potential benefits to the rerouted flight and the system-wide aggregate benefits of a single reroute. We believe that the capabilities developed and the lessons learned during the Phase 3 Field Evaluation will set up the National Airspace System for future success.
This paper describes NASA’s Airspace Technology Demonstration 2 (ATD-2) Phase 3 prototype capability that is being tested in the North Texas region through summer 2021. For the first time, a shared Decision Support Tool (DST) provides opportunities for participating Flight Operators (FOs) and Air Traffic Controllers (ATCs) to coordinate using a Trajectory Option Set (TOS). When the metroplex airspace is impacted by demand/capacity imbalances, TOS enables departure flights to be rerouted to alternative departure routes with less surface delay.
This video recorded presentation is about the NASA’s Airspace Technology Demonstration 2 (ATD-2) Phase 3 prototype capability that is being tested in the North Texas region through summer 2021. For the first time, a shared Decision Support Tool (DST) provides opportunities for participating Flight Operators (FOs) and Air Traffic Controllers (ATCs) to coordinate using a Trajectory Option Set (TOS). When the metroplex airspace is impacted by demand/capacity imbalances, TOS enables departure flights to be rerouted to alternative departure routes with less surface delay.
This paper presents results of NASA’s Airspace Technology Demonstration 2 Phase 3 Trajectory Option Set reroute capability designed to resolve a demand capacity imbalance along the terminal airspace boundary. We focus on Candidate flights generated during the Stormy 2020 Shadow Evaluation which was the result of using the system to passively collect predictions for each flight at the OUT event. Benefit metrics associated with the predictions are defined for the individual rerouted flight and also the system-wide savings. Candidate flights are grouped into three distinct use cases and the benefit mechanism is explained for each use case along with illustrative data. Analysis of the different use cases shed light on the underlying causes of the reroute opportunities. Lessons learned from the Stormy 2020 Shadow Evaluation including the importance of reroutes during recovery from Severe Weather Avoidance Programs and also reroutes in the absence of terminal airspace constraints will be incorporated into the Phase 3 Field Evaluation in 2021 to maximize reroute opportunities.
A concept that enables advanced airborne reroute operations is proposed, built on NextGen capabilities called Airborne Reroute (ABRR) and Trajectory Option Set (TOS). The concept introduces new third-party services / tools for the airline dispatchers to generate airline-preferred trajectories in response to convective weather events. The airborne TOS routes are sent to the traffic flow managers, who can evaluate the feasibility of the trajectory options with the help of their own third-party services / tools which have been built for this concept. A virtual demonstration study was conducted to elicit feedback from air traffic and airline subject-matter-experts. The feedback was generally positive, both in the benefits of the concept and the feasibility / need for the new tools to enable the concept but their feedback was mixed on the feasibility of the new tools to be third-party services instead of being integrated into their core tools. Nevertheless, this concept explores and demonstrates an evolutionary pathway toward a service-oriented future that shifts the responsibilities and the capabilities of air traffic operations from the air traffic service providers to the airline industry and third-party vendors.
This presentation discusses what Trajectory Options Set (TOS) are and how they are used in the ATD-2 Multi-Airport field demonstration in the North Texas area. The use cases and benefits of this technology are summarized.
The maximal independent set (MIS) graph problem arises in many applications such as computer vision, information theory, molecular biology, and process scheduling. The growing scale of graph data suggests the use of distributed memory hardware as a cost-effective approach to providing necessary compute and memory resources. Existing distributed memory parallel MIS algorithms rely on synchronous communication and use techniques such as subgraph computations. In this paper, we present an asynchronous distributed-memory parallel graph algorithm that relies on a virtual directed acyclic graph (DAG) that is created during the algorithm execution. We introduce two additional algorithms that save computations by ordering generated work. The first algorithm applies ordering globally to reduce computations, and the second algorithm applies ordering locally at the level of threads to minimize the synchronization overhead. We use two different implementations of Luby’s algorithm variants as baseline to compare the performance of the presented algorithms: (1) vertex-centric Luby A and Luby B implementations, and (2) the CombBLAS linear-algebra Luby A implementation. Results show that proposed algorithms outperform both implementations of Luby algorithms, especially in distributed execution. Furthermore, we show that for low-diameter graphs the algorithm that applies global ordering scales better than other algorithms and for high diameter graphs the original asynchronous algorithm and thread-level ordering algorithm show better performance.
Instructions on how to go about setting the BIOS on a SPARCS CPU used in an ATU or Pod.
This presentation applies open set recognition to classify unknown waveforms, enabling systems to not only identify known types but also reliably detect when waveforms fall outside the training distribution. This approach enhances robustness by avoiding forced misclassification of novel or anomalous signals.
When characterizing subsurface properties is crucial for reliable and cost-effective groundwater supply management and contaminant remediation. With recent advances in sensor technology, large volumes of hydro-geophysical and geochemical data can be obtained to achieve high-resolution images of subsurface properties. However, characterization with such a large amount of information requires prohibitive computational costs associated with “big data” processing and numerous large-scale numerical simulations. To tackle such difficulties, the Principal Component Geostatistical Approach (PCGA) has been proposed as a “Jacobian-free” inversion method that requires much smaller forward simulation runs for each iteration than the number of unknown parameters and measurements needed in the traditional inversion methods. PCGA can be conveniently linked to any multi-physics simulation software with independent parallel executions. In our paper, we extend PCGA to handle a large number of measurements (e.g. 106 or more) by constructing a fast preconditioner whose computational cost scales linearly with the data size. For illustration, we characterize the heterogeneous hydraulic conductivity (K) distribution in a laboratory-scale 3-D sand box using about 6 million transient tracer concentration measurements obtained using magnetic resonance imaging. Since each individual observation has little information on the K distribution, the data was compressed by the zero-th temporal moment of breakthrough curves, which is equivalent to the mean travel time under the experimental setting. Moreover, only about 2,000 forward simulations in total were required to obtain the best estimate with corresponding estimation uncertainty, and the estimated K field captured key patterns of the original packing design, showing the efficiency and effectiveness of the proposed method. This article is protected by copyright. All rights reserved.
Fluidization behavior of biomass and glass beads binary mixtures in a bubbling fluidized bed was experimentally investigated. Mixtures containing different mass fraction of Loblolly Pine white wood and glass beads were fluidized at different fluidization velocities. The particle properties were characterized in a QICPIC that uses a dynamic image processing method to measure both particle size and sphericity. The minimum fluidization velocity was determined using the pressure drop method. An image processing method was developed to capture the dynamic expanded bed height at a very high frequency. The effect of biomass mass fraction and inlet gas velocity on mixing and segregation behavior was studied and analyzed through pressure drop measurements. Pressure drop fluctuations and expanded bed height fluctuations via fast Fourier transform were analyzed and compared. Here, the complete and accurate experimental data reported in this study could provide a benchmark data set for various computational fluid dynamics models validation, calibration, and identification.