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At least 1,405 records · Page 78

Non-unimodal and non-concave relationships in the network Macroscopic Fundamental Diagram caused by hierarchical streets

Unimodal, concave relationships between average network productivity and accumulation or density aggregated across spatially compact regions of urban networks—so called network Macroscopic Fundamental Diagrams (MFDs)—have recently been shown to exist on homogeneous street networks. When present, MFD relationships facilitate the modeling of traffic congestion at a regional level and have led to the development of various regional traffic control strategies. However, real street networks are not homogeneous—they generally have a hierarchical structure where some streets (e.g., arterials) promote higher mobility than others (e.g., local roads). Here, this paper examines how the presence of hierarchical roadway structures may potentially cause non-unimodal patterns in a network's MFD. These are observed using three types of tools: analytical models of simple network structures, simulations of various idealized roadway networks, and empirical data. The impacts of street hierarchy depend on how vehicles use different roadway types to move within the network; i.e., their routing strategy. The findings suggest that the presence of roadway hierarchies may lead to MFDs that have non-unimodal or non-concave patterns on the free-flow branch when vehicles route themselves according to user equilibrium principles, which is closest to what would be observed in realistic situations. Such patterns are contrary to what is traditionally assumed in most MFD-based modeling frameworks. However, the unimodal and concave MFD should be expected under system optimal routing conditions that maximize network productivity for a given traffic state.

42 ENGINEERING↗

Network interface unit design options performance analysis

An analysis is presented of three design options for the Space Station Freedom (SSF) onboard Data Management System (DMS) Network Interface Unit (NIU). The NIU provides the interface from the Fiber Distributed Data Interface (FDDI) local area network (LAN) to the DMS processing elements. The FDDI LAN provides the primary means for command and control and low and medium rate telemetry data transfers on board the SSF. The results of this analysis provide the basis for the implementation of the NIU.

Miller, Frank W.↗

Ikhana: A NASA UAS Supporting Long Duration Earth Science Missions

NASA's Ikhana unmanned aerial vehicle (UAV) is a General Atomics MQ-9 Predator-B modified to support the conduct of Earth science missions for the NASA Science Mission Directorate through partnerships, other government agencies and universities. Ikhana, a Native American word meaning 'intelligence', can carry over 2000 lbs of atmospheric and remote sensing instruments in the payload bay and external pods. The aircraft is capable of mission durations in excess of 24 hours at altitudes above 40,000 ft. Redundant flight control, avionics, power, and network systems increase the system reliability and allow easier access to public airspace. The aircraft is remotely piloted from a mobile ground control station (GCS) using both C-band line-of-sight and Ku-band over-the-horizon satellite datalinks. NASA's GCS has been modified to support on-site science monitoring, or the downlink data can be networked to remote sites. All ground support systems are designed to be deployable to support global Eart science investigations. On-board support capabilities include an instrumentation system and an Airborne Research Test System (ARTS). The ARTS can host research algorithms that will autonomously command and control on-board sensors, perform sensor health monitoring, conduct data analysis, and request changes to the flight plan to maximize data collection. The ARTS also has the ability to host algorithms that will autonomously control the aircraft trajectory based on sensor needs, (e.g. precision trajectory for repeat pass interferometry) or to optimize mission objectives (e.g. search for specific atmospheric conditions). Standard on-board networks will collect science data for recording and for inclusion in the aircraft's high bandwidth downlink. The Ikhana project will complete GCS development, science support systems integration, external pod integration and flight clearance, and operations crew training in early 2007. A large-area remote sensing mission is currently scheduled for the Summer 2007.

Cobleigh, Brent R.↗

(ODIN): An Open Source, Low-Latency Data Integration & Visualization Framework for the NASA System Wide Safety Project's Disaster Response Safety Demonstration Series

The Open Data Integration Framework (ODIN) is an open source, low latency data integration and visualization framework (https://github.com/NASARace/race-odin) developed under NASA’s System WideSafety Program to demonstrate new safety capabilities designed to improve US airspace operations. Safety demonstrations are a set of increasingly complex (from public safety perspective) disaster response scenarios under which air systems must operate with increased capacity and include: 1) Wildland fire response, 2) Hurricane relief and recovery, 4) Emergency medical delivery via UAS and 4) Urban disaster relief. To accommodate disaster response, ODIN is field deployable and can scale on one or more multi-core, commodity laptops operating with full to limited or intermittent internet connectivity, conditions likely encountered during operations. ODIN runs as webserver with local, persistent data storage to serve either public or a secured, ad hoc network (e.g., an incident command post). The current released ODIN, ODIN-Fire is tailored for wildland fire management incorporating information on satellite overpasses with links to the near real-time data and imagery from the respective agencies. Included are winds data, an important variable for emergency responders and airspace operations, and high-resolution wind forecasts generated by super-computing resources and ingested into ODIN. As an open-source project, ODIN has attracted interest from multiple entities. We will show how 1) a commercial field instrument and data provider uses ODIN to help users visualize, publish and integrate their in-situ sensor network data and 2) ODIN’s capabilities to ingest, integrate and display near-real time satellite data with air traffic and a USFS winds forecast model used in fire response and post-fire assessment. Within NASA ODIN demonstrated novel, near terminal airspace safety capabilities for a project close-out event and previously it monitored the national airspace in real-time to meet an agency milestone. ODIN is presently under development for the anticipated hurricane relief and response demonstration notionally scheduled for the 2025-27 time frame and is available from NASA's github at the above link.

Aeronautics↗

Validation of POLDER/ADEOS data using a ground-based lidar network: Preliminary results for semi-transparent and cirrus clouds

At mid and tropical latitudes, cirrus clouds are present more than 50% of the time in satellites observations. Due to their large spatial and temporal coverage, and associated low temperatures, cirrus clouds have a major influence on the Earth-Ocean-Atmosphere energy balance through their effects on the incoming solar radiation and outgoing infrared radiation. At present the impact of cirrus clouds on climate is well recognized but remains to be asserted more precisely, for their optical and radiative properties are not very well known. In order to understand the effects of cirrus clouds on climate, their optical and radiative characteristics of these clouds need to be determined accurately at different scales in different locations i.e. latitude. Lidars are well suited to observe cirrus clouds, they can detect very thin and semi-transparent layers, and retrieve the clouds geometrical properties i.e. altitude and multilayers, as well as radiative properties i.e. optical depth, backscattering phase functions of ice crystals. Moreover the linear depolarization ratio can give information on the ice crystal shape. In addition, the data collected with an airborne version of POLDER (POLarization and Directionality of Earth Reflectances) instrument have shown that bidirectional polarized measurements can provide information on cirrus cloud microphysical properties (crystal shapes, preferred orientation in space). The spaceborne version of POLDER-1 has been flown on ADEOS-1 platform during 8 months (October 96 - June 97), and the next POLDER-2 instrument will be launched in 2000 on ADEOS-2. The POLDER-1 cloud inversion algorithms are currently under validation. For cirrus clouds, a validation based on comparisons between cloud properties retrieved from POLDER-1 data and cloud properties inferred from a ground-based lidar network is currently under consideration. We present the first results of the validation.

Chepfer, H.↗

Neurocomputing

The present work is intended to give technologists, research scientists, and mathematicians a graduate-level overview of the field of neurocomputing. After exploring the relationship of this field to general neuroscience, attention is given to neural network building blocks, the self-adaptation equations of learning laws, the data-transformation structures of associative networks, and the multilayer data-transformation structures of mapping networks. Also treated are the neurocomputing frontiers of spatiotemporal, stochastic, and hierarchical networks, 'neurosoftware', the creation of neural network-based computers, and neurocomputing applications in sensor processing, control, and data analysis.

Hecht-Nielsen, Robert↗

A prototype Upper Atmospheric Research Collaboratory (UARC)

The National Collaboratory concept has great potential for enabling 'critical mass' working groups and highly interdisciplinary research projects. We report here on a new program to build a prototype collaboratory using the Sondrestrom Upper Atmospheric Research Facility in Kangerlussuaq, Greenland and a group of associated scientists. The Upper Atmospheric Research Collaboratory (UARC) is a joint venture of researchers in upper atmospheric and space science, computer science, and behavioral science to develop a testbed for collaborative remote research. We define the 'collaboratory' as an advanced information technology environment which enables teams to work together over distance and time on a wide variety of intellectual tasks. It provides: (1) human-to-human communications using shared computer tools and work spaces; (2) group access and use of a network of information, data, and knowledge sources; and (3) remote access and control of instruments for data acquisition. The UARC testbed is being implemented to support a distributed community of space scientists so that they have network access to the remote instrument facility in Kangerlussuaq and are able to interact among geographically distributed locations. The goal is to enable them to use the UARC rather than physical travel to Greenland to conduct team research campaigns. Even on short notice through the collaboratory from their home institutions, participants will be able to meet together to operate a battery of remote interactive observations and to acquire, process, and interpret the data.

Clauer, C. R.↗

Comparing Eyewitness-Derived Trajectories of Bright Meteors to Instrumentally-Observed Data

The NASA Meteoroid Environment Office (MEO) is often called upon to analyze meteors of public interest observed over the United States. Data from meteor networks are often utilized to accomplish this, as are recordings from the general public. When these methods fail, eyewitness reports are the only resource which can be leveraged. The MEO developed a tool to crudely calculate the trajectories of bright meteors from the eyewitness reports submitted to the American Meteor Society. The tool was tested on eyewitness data for 33 cases and compared to observed data from the NASA All Sky Fireball Network. The tool performed better for cases with more than 75 eyewitness reports than those with fewer than 75, by almost a factor of two across all metrics except for the end height. For these cases, the eyewitness-derived trajectory was about 50 km from the observed trajectory, the radiant was within 15deg, and the speed was within 20% of that observed on average. A description of the tool, example case studies, and general trends are described.

D E Moser↗

Robustness of the Ensemble Score Filter to the Type of Assimilated Observation Networks

Recent advances in data assimilation (DA) have focused on developing more flexible approaches that can better accommodate nonlinearities in models and observations. However, it remains unclear how the performance of these advanced methods depends on the observation network characteristics. In this study, we present initial experiments with the surface quasi‐geostrophic model, in which we compare a recently developed ensemble filter using score‐based diffusion models with the standard Local Ensemble Transform Kalman Filter (LETKF). Our results show that the analysis solutions respond differently to the number, spatial distribution, and nonlinear fraction of assimilated observations. We also find notable changes in the multiscale characteristics of the analysis errors. Given that standard DA techniques will eventually be replaced by more advanced methods, we hope this study sets the ground for future efforts to reassess the value of Earth observing systems in the context of newly emerging algorithms.

97 MATHEMATICS AND COMPUTING↗

The SONATA data format for efficient description of large-scale network models

Increasing availability of comprehensive experimental datasets and of high-performance computing resources are driving rapid growth in scale, complexity, and biological realism of computational models in neuroscience. To support construction and simulation, as well as sharing of such large-scale models, a broadly applicable, flexible, and high-performance data format is necessary. To address this need, we have developed the Scalable Open Network Architecture TemplAte (SONATA) data format. It is designed for memory and computational efficiency and works across multiple platforms. The format represents neuronal circuits and simulation inputs and outputs via standardized files and provides much flexibility for adding new conventions or extensions. SONATA is used in multiple modeling and visualization tools, and we also provide reference Application Programming Interfaces and model examples to catalyze further adoption. SONATA format is free and open for the community to use and build upon with the goal of enabling efficient model building, sharing, and reproducibility.

59 BASIC BIOLOGICAL SCIENCES↗

Wavelength division multiplexing for future Space Station data systems

A future Space Station will require information network architectures and technologies that are evolvable, adaptive, high performing, and self-correcting and repairing. One of the conceptual network configurations involves fiber optic data buses with Wavelength Division Multiplexing (WDM). Discussion of this network concept, components being developed and results on a four-channel WDM star bus will be presented.

Hendricks, H. D.↗

Respirable particulate monitoring with remote sensors. (Public health ecology: Air pollution)

The feasibility of monitoring atmospheric aerosols in the respirable range from air or space platforms was studied. Secondary reflectance targets were located in the industrial area and near Galveston Bay. Multichannel remote sensor data were utilized to calculate the aerosol extinction coefficient and thus determine the aerosol size distribution. Houston Texas air sampling network high volume data were utilized to generate computer isopleth maps of suspended particulates and to establish the mass loading of the atmosphere. In addition, a five channel nephelometer and a multistage particulate air sampler were used to collect data. The extinction coefficient determined from remote sensor data proved more representative of wide areal phenomena than that calculated from on site measurements. It was also demonstrated that a significant reduction in the standard deviation of the extinction coefficient could be achieved by reducing the bandwidths used in remote sensor.

Severs, R. K.↗

Numerical aerodynamic simulation facility preliminary study, volume 2 and appendices

Data to support results obtained in technology assessment studies are presented. Objectives, starting points, and future study tasks are outlined. Key design issues discussed in appendices include: data allocation, transposition network design, fault tolerance and trustworthiness, logic design, processing element of existing components, number of processors, the host system, alternate data base memory designs, number representation, fast div 521 instruction, architectures, and lockstep array versus synchronizable array machine comparison.

Source record↗

Description and Status of the DC Lightning Mapping Array

The DC Lightning Mapping Array (DC LMA) centered on the Washington, DC metro region has been in operation since 2006. During that time the DC LMA has provided real time data to regional National Weather Service (NSF) Sterling, VA forecast office for operations support and the NOAA Meteorological Development Laboratory (MDL) for new product development and assessment. Data from this network (as well as other from other LMA systems) are now being used to create proxy Geostationary Lightning Mapper (GLM) data sets for GOES-R risk reduction and algorithm development activities. In addition, since spring 2009 data are provided to the Storm Prediction Center in support of Hazardous Weather Testbed and GOES-R Proving Ground activities during the Spring Program. Description, status and plans will be discussed.

Blakeslee, Richard↗

History and Status of ALSEP and the Apollo Lunar Data Project

A suite of automated scientific instruments (the Apollo Lunar Surface Experiment Package, or ALSEP) was installed at each of the landing sites of Apollo 12, 14, 15, 16, and 17 from 1969 to 1972. They operated from deployment until decommissioning on 30 September 1977. These data were continuously transmitted to Earth and saved on the Range Tapes, which were recorded at the Manned Space Flight Network stations. These data were also broken out by experiment and sent to the experiment Principal Investigators on what were called the P.I. Tapes. Starting in April 1973 the Range Tape data were stored in digital format on 7-track magnetic tapes, the ARCSAV Tapes. In February 1976, the handling of the Range Tapes was transferred to UT Galveston. They produced 9-track tapes referred to as the Work Tapes. Following the Apollo program the Range and ARCSAV tapes, which were never archived, were lost. The Work Tapes were archived at the National Space Science Data Center (NSSDC). Some investigators archived their individual experiment data with NSSDC as well, but much of the data had minimal documentation, were not in digital form, or were stored in difficult to translate formats. Data from many experiments were never delivered to the NSSDC. The Lunar Data Project was started to address the problem of both missing and not readily usable data. Our effort has resulted in recovery of some of the ARCSAV tapes, recovery and digitization of a large volume of Apollo scientific and technical documentation, and restoration of many ALSEP and other Apollo data collections. Restoration involves deciphering formats, assembling necessary ancillary data (metadata), and packaging data in digital format to be archived with the Planetary Data System (PDS). Recovery of the data from the ARCSAV tapes involved having the tapes read on special equipment and extracting the individual experiment data out of the integrated data stream. We will report on the history and status of the various recovery efforts.

Work Tapes↗

Deep neural network uncertainty quantification for LArTPC reconstruction

We evaluate uncertainty quantification (UQ) methods for deep learning applied to liquid argon time projection chamber (LArTPC) physics analysis tasks. As deep learning applications enter widespread usage among physics data analysis, neural networks with reliable estimates of prediction uncertainty and robust performance against overconfidence and out-of-distribution (OOD) samples are critical for their full deployment in analyzing experimental data. While numerous UQ methods have been tested on simple datasets, performance evaluations for more complex tasks and datasets are scarce. Here we assess the application of selected deep learning UQ methods on the task of particle classification using the PiLArNet monte carlo 3D LArTPC point cloud dataset. We observe that UQ methods not only allow for better rejection of prediction mistakes and OOD detection, but also generally achieve higher overall accuracy across different task settings. We assess the precision of uncertainty quantification using different evaluation metrics, such as distributional separation of prediction entropy across correctly and incorrectly identified samples, receiver operating characteristic curves (ROCs), and expected calibration error from observed empirical accuracy. We conclude that ensembling methods can obtain well calibrated classification probabilities and generally perform better than other existing methods in deep learning UQ literature.

47 OTHER INSTRUMENTATION↗

Navigation Architecture for a Space Mobile Network

The Tracking and Data Relay Satellite System (TDRSS) Augmentation Service for Satellites (TASS) is a proposed beacon service to provide a global, space based GPS augmentation service based on the NASA Global Differential GPS (GDGPS) System. The TASS signal will be tied to the GPS time system and usable as an additional ranging and Doppler radiometric source. Additionally, it will provide data vital to autonomous navigation in the near Earth regime, including space weather information, TDRS ephemerides, Earth Orientation Parameters (EOP), and forward commanding capability. TASS benefits include enhancing situational awareness, enabling increased autonomy, and providing near real-time command access for user platforms. As NASA Headquarters' Space Communication and Navigation Office (SCaN) begins to move away from a centralized network architecture and towards a Space Mobile Network (SMN) that allows for user initiated services, autonomous navigation will be a key part of such a system. This paper explores how a TASS beacon service enables the Space Mobile Networking paradigm, what a typical user platform would require, and provides an in-depth analysis of several navigation scenarios and operations concepts. This paper provides an overview of the TASS beacon and its role within the SMN and user community. Supporting navigation analysis is presented for two user mission scenarios: an Earth observing spacecraft in low earth orbit (LEO), and a highly elliptical spacecraft in a lunar resonance orbit. These diverse flight scenarios indicate the breadth of applicability of the TASS beacon for upcoming users within the current network architecture and in the SMN.

Data Relay↗

Business is Beaming

Terabeam has developed a Fiberless Optical(TM) Network that transmits broadband data from office buildings to the nation's wide-area networks (WANs), without digging up the streets. A key component of Terabeam's Fiberless Network is Large Aperture Holographic Optic technology, developed by Ralcon Development Lab, of Paradise, Utah. Ralcon developed the Holographic Optical Element (HOE) technology with assistance from a NASA Goddard Space Flight Center Small Business Innovation Research (SBIR) contract. Terabeam further developed the HOE technology and incorporated it into its Fiberless Optical Network-sending an immeasurable amount of information soaring overhead. Terabeam developed its Fiberless Optical Network using a proprietary HOE to transmit data. The unit is mounted near an office window and has the ability to beam safe, low-power, invisible data through the air at gigabits-per-second speeds to anywhere in the service area. Gigabits-per-second speeds are thousands of times faster than the speeds of current broadband transmissions. This allows businesses to connect to local-area networks (LANs) as well as WANs, in a quick and affordable manner.

Source record↗