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At least 1,189 records · Page 66

Constrained spectral clustering under a local proximity structure assumption

This work focuses on incorporating pairwise constraints into a spectral clustering algorithm. A new constrained spectral clustering method is proposed, as well as an active constraint acquisition technique and a heuristic for parameter selection. We demonstrate that our constrained spectral clustering method, CSC, works well when the data exhibits what we term local proximity structure.

domain knowledge↗

Medium power amplifiers covering 90 - 130 GHz for telescope local oscillators

This paper describes a set of power amplifier (PA) modules containing InP High Electron Mobility Transistor (HEMT) Monolithic Millimeter-wave Integrated Circuit (MMIC) chips. The chips were designed and optimized for local oscillator sources in the 90-130 GHz band for the Atacama Large Millimeter Array telescope. The modules feature 20-45 mW of output power, to date the highest power from solid state HEMT MMIC modules above 110 GHz.

coplanar waveguides↗

Spatial Growth Modeling and High Resolution Remote Sensing Data Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world s population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include business as usual and smart growth scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS lkm land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Quattrochi, Dale A.↗

Desert Research and Technology Studies (RATS) Local and Remote Test Sites

Desert RATS (Research and Technology Studies) is a combined group of inter-NASA center scientists and engineers, collaborating with representatives of industry and academia, for the purpose of conducting remote field exercises. These exercises provide the capability to validate experimental hardware and software, to evaluate and develop mission operational techniques, and to identify and establish technical requirements applicable for future planetary exploration. D-RATS completed its ninth year of field testing in September 2006. Dry run test activities prior to testing at designated remote field site locations are initially conducted at the Johnson Space Center (JSC) Remote Field Demonstration Test Site. This is a multi-acre external test site located at JSC and has detailed representative terrain features simulating both Lunar and Mars surface characteristics. The majority of the remote field tests have been subsequently conducted in various high desert areas adjacent to Flagstaff, Arizona. Both the local JSC and remote field test sites have terrain conditions that are representative of both the Moon and Mars, such as strewn rock and volcanic ash fields, meteorite crater ejecta blankets, rolling plains, hills, gullies, slopes, and outcrops. Flagstaff is the preferred remote test site location for many reasons. First, there are nine potential test sites with representative terrain features within a 75-mile radius. Second, Flagstaff is the location of the United States Geologic Survey (USGS)/Astrogeology Branch, which historically supported Apollo astronaut geologic training and currently supports and provides host accommodations to the D-RATS team. Finally, in considering the importance of logistics in regard to providing the necessary level of support capabilities, the Flagstaff area provides substantial logistics support and lodging accommodations to take care of team members during long hours of field operations.

Janoiko, Barbara↗

Remote Versus Local Forcing of Chlorophyll Variability in the South Atlantic Bight

This TM documents results of analyses addressing the local versus remote forcing of chlorophyll variability on the shelf and slope regions of the South Atlantic Bight (SAB) based on satellite-derived products and a limited amount of in situ data. This study is part of a larger multi-disciplinary, multi-institutional effort to study the Eastern U.S. Continental Shelf carbon budget (U.S. Eastern Continental Shelf Carbon Budget: Modeling, Data Assimilation, and Analysis, U.S. ECoS), a project funded by the NASA Earth System Enterprise Interdisciplinary Science Program that started in the summer of 2004.

Signorini, Sergio R.↗

What can be Learned from X-ray Spectroscopy Concerning Hot Gas in Local Bubble and Charge Exchange Processes?

What can be learned from x-ray spectroscopy in observing hot gas in local bubble and charge exchange processes depends on spectral resolution, instrumental grasp, instrumental energy band, signal-to-nose, field of view, angular resolution and observatory location. Early attempts at x-ray spectroscopy include ROSAT; more recently, astronomers have used diffuse x-ray spectrometers, XMM Newton, sounding rocket calorimeters, and Suzaku. Future observations are expected with calorimeters on the Spectrum Roentgen Gamma mission, and the Solar Wind Charge Exchange (SWCX). The Geospheric SWCX may provide remote sensing of the solar wind and magnetosheath and remote observations of solar CMEs moving outward from the sun.

Snowden, Steve↗

Differential temperature stress measurement employing array sensor with local offset

The instrument has a focal plane array of infrared sensors of the integrating type such as a multiplexed device in which a charge is built up on a capacitor which is proportional to the total number of photons which that sensor is exposed to between read-out cycles. The infrared sensors of the array are manufactured as part of an overall array which is part of a micro-electronic device. The sensor achieves greater sensitivity by applying a local offset to the output of each sensor before it is converted into a digital word. The offset which is applied to each sensor will typically be the sensor's average value so that the digital signal which is periodically read from each sensor of the array corresponds to the portion of the signal which is varying in time. With proper synchronization between the cyclical loading of the test object and the frame rate of the infrared array the output of the A/D converted signal will correspond to the stress field induced temperature variations. A digital lock-in operation may be performed on the output of each sensor in the array. This results in a test instrument which can rapidly form a precise image of the thermoelastic stresses in an object.

Lesniak, Jon R.↗

System and method for object localization

A computer-assisted method for localizing a rack, including sensing an image of the rack, detecting line segments in the sensed image, recognizing a candidate arrangement of line segments in the sensed image indicative of a predetermined feature of the rack, generating a matrix of correspondence between the candidate arrangement of line segments and an expected position and orientation of the predetermined feature of the rack, and estimating a position and orientation of the rack based on the matrix of correspondence.

Kelly, Alonzo J.↗

Remotely actuated localized pressure and heat apparatus and method of use

Apparatus and method for the use of a remotely actuated localized pressure and heat apparatus for the consolidation and curing of fiber elements in, structures. The apparatus includes members for clamping the desired portion of the fiber elements to be joined, pressure members and/or heat members. The method is directed to the application and use of the apparatus.

Merret, John B.↗

MISR Level 1B1 Local Mode Radiance Data (MIB1LM_V1)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. In addition to the Level 1B1 radiometric product for MISR's Global Mode imagery, there is a separate Level 1B1 product for each high-resolution Local Mode scene. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m for red band only; Longitude_Resolution=275 m for red band only; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=about 15 orbits/day].

NEAR IR IMAGERY↗

MISR Level 1B2 Local Mode Ellipsoid Radiance Data (MB2LME_V2)

In addition to the Level 1B2 Global Mode imagery, MISR can be configured to disable the on-board data averaging and provide high resolution images in all 36 channels for selected targets and observation times. This capability is referred to as Local Mode (LM). [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m x 360 km (cross-track); Longitude_Resolution=275 m x 300 km (along-track)].

AM-1↗

MISR Level 1B2 Local Mode Terrain Radiance Data (MB2LMT_V2)

In addition to the Level 1B2 Global Mode imagery, MISR can be configured to disable the on-board data averaging and provide high resolution images in all 36 channels for selected targets and observation times. This capability is referred to as Local Mode (LM). [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m x 360 km (cross-track); Longitude_Resolution=275 m x 300 km (along-track)].

RADIANCE↗

MISR Level 1B1 Local Mode Radiance Data (MIB1LM_V2)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. In addition to the Level 1B1 radiometric product for MISR's Global Mode imagery, there is a separate Level 1B1 product for each high-resolution Local Mode scene. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m for red band only; Longitude_Resolution=275 m for red band only; Temporal_Resolution=about 15 orbits/day].

AM-1↗

Long Term Mean Local Time of the Ascending Node Prediction

Significant error has been observed in the long term prediction of the Mean Local Time of the Ascending Node on the Aqua spacecraft. This error of approximately 90 seconds over a two year prediction is a complication in planning and timing of maneuvers for all members of the Earth Observing System Afternoon Constellation, which use Aqua's MLTAN as the reference for their inclination maneuvers. It was determined that the source of the prediction error was the lack of a solid Earth tide model in the operational force models. The Love Model of the solid Earth tide potential was used to derive analytic corrections to the inclination and right ascension of the ascending node of Aqua's Sun-synchronous orbit. Additionally, it was determined that the resonance between the Sun and orbit plane of the Sun-synchronous orbit is the primary driver of this error. The analytic corrections have been added to the operational force models for the Aqua spacecraft reducing the two-year 90-second error to less than 7 seconds.

McKinley, David P.↗