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Half Moon Bay Solid Waste Contribution to Greenhouse Gas Emissions column chart 2
datahub.smcgov.org | Last Updated 2019-05-10T16:59:26.000ZData by city showing solid waste contribution to greenhouse gas emissions in the County. This data is part of the Regionally Integrated Climate Action Planning Suite (RICAPS) program. Each city in San Mateo County has the opportunity to develop its own Climate Action Plan (CAP) using tools developed by C/CAG in conjunction with DNV KEMA https://www.dnvgl.com/ and Hara. http://www.verisae.com/default.aspx. This project was funded by grants from the Bay Area Air Quality Management District (BAAQMD) and Pacific Gas and Electric Company (PG&E). Climate Action Plans developed from these tools will meet BAAQMD's California Environmental Quality Act (CEQA) guidelines for a Qualified Greenhouse Gas Reduction Strategy. For more information, please see the RICAPS site: http://www.smcenergywatch.com/progress_report.html
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Low Noise Millimeter Wave LNA Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:24:11.000ZThe Phase I effort will result in a low noise MMIC G-Band amplifier the covers the entire 165 to 193GHz frequency range. The amplifier will be designed using a 50nm MHEMT that has already been developed by BAE Systems that enables the state-of-the-art performance to be achieved. The innovative amplifier design will have a gain of 20dB, a noise figure of less than 6dB(~4dB, an input output VSWR of less than 2:1. In addition, the MHEMT has the added advantage of having lower noise power stability and 1/f noise than InP devices. A balanced amplifier is the primary approach while a single ended unit will be investigated for missions that require reduced bandwidths. The MMIC amplifier will be designed to be inserted into a waveguide housing for additional and environmental testing in a Phase II program. At completion of the Phase II program, the amplifier will be capable of being space qualified for NASA missions.
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Surface Turbulent Fluxes, 1x1 deg Daily Grid, Set1 V2c
nasa-test-0.demo.socrata.com | Last Updated 2015-07-19T08:49:10.000ZThese data are the Goddard Satellite-based Surface Turbulent Fluxes Version-2c (GSSTF2c) Dataset recently produced through a MEaSUREs funded project led by Dr. Chung-Lin Shie (UMBC/GEST, NASA/GSFC), converted to HDF-EOS5 format. The stewardship of this HDF-EOS5 dataset is part of the MEaSUREs project, http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects/surface-turbulent-fluxes-esdr http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects GSSTF version 2b (Shie et al. 2010, Shie et al. 2009) generally agreed better with available ship measurements obtained from several field experiments in 1999 than GSSTF2 (Chou et al. 2003) did in all three flux components, i.e., latent heat flux [LHF], sensible heat flux [SHF], and wind stress [WST] (Shie 2010a,b). GSSTF2b was also found favorable, particularly for LHF and SHF, in an intercomparison study that accessed eleven products of ocean surface turbulent fluxes, in which GSSTF2 and GSSTF2b were also included (Brunke et al. 2011). However, a temporal trend appeared in the globally averaged LHF of GSSTF2b, particularly post year 2000. Shie (2010a,b) attributed the LHF trend to the trends originally found in the globally averaged SSM/I Tb's, i.e., Tb(19v), Tb(19h), Tb(22v) and Tb(37v), which were used to retrieve the GSSTF2b bottom-layer (the lowest atmospheric 500 meter layer) precipitable water [WB], then the surface specific humidity [Qa], and subsequently LHF. The SSM/I Tb's trends were recently found mainly due to the variations/trends of Earth incidence angle (EIA) in the SSM/I satellites (Hilburn and Shie 2011a,b). They have further developed an algorithm properly resolving the EIA problem and successfully reproducing the corrected Tb's by genuinely removing the "artifactitious" trends. An upgraded production of GSSTF2c (Shie et al. 2011) using the corrected Tb's has been completed very recently. GSSTF2c shows a significant improvement in the resultant WB, and subsequently the retrieved LHF - the temporal trends of WB and LHF are greatly reduced after the proper adjustments/treatments in the SSM/I Tb's (Shie and Hilburn 2011). In closing, we believe that the insightful "Rice Cooker Theory" by Shie (2010a,b), i.e., "To produce a good and trustworthy 'output product' (delicious 'cooked rice') depends not only on a well-functioned 'model/algorithm' ('rice cooker'), but also on a genuine and reliable 'input data' ('raw rice') with good quality" should help us better comprehend the impact of the improved Tb on the subsequently retrieved LHF of GSSTF2c. This is the Daily (24-hour) product; data are projected to equidistant Grid that covers the globe at 1x1 degree cell size, resulting in data arrays of 360x180 size. A finer resolution, 0.25 deg, of this product has been released as Version 3. The GSSTF, Version 2c, daily fluxes have first been produced for each individual available SSM/I satellite tapes (e.g., F08, F10, F11, F13, F14 and F15). Then, the Combined daily fluxes are produced by averaging (equally weighted) over available flux data/files from various satellites. These Combined daily flux data are considered as the "final" GSSTF, Version 2c, and are stored in this HDF-EOS5 collection. There are only one set of GSSTF, Version 2c, Combined data, "Set1" It contains 9 variables: "E" 'latent heat flux' (W/m**2), "STu" 'zonal wind stress' (N/m**2), "STv" 'meridional wind stress' (N/m**2), "H" 'sensible heat flux' (W/m**2), "Qair" 'surface air (~10-m) specific humidity' (g/kg), "WB" 'lowest 500-m precipitable water' (g/cm**2), "U" '10-m wind speed' (m/s), "DQ" 'sea-air humidity difference' (g/kg) "Tot_Precip_Water" 'total precipitable water' (g/cm**2) The double-quoted labels are the short names of the data fields in the HDF-EOS5 files. The "individual" daily flux data files, produced for each individual satellite, are also available in HDF-EOS5, although from differe...
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Approximate Cartesian Control for Robotic Tool Usage with Graceful Degradation Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:31:39.000ZMany of NASA's exploration scenarios include important roles for autonomous or partially autonomous robots. It is desirable for them to utilize human tools when possible, rather than needing to build custom tools for each robot. Control of robotic manipulators for tool usage generally requires a very precise Cartesian-space trajectory of the tool tip (e.g., moving a marker along the surface of a whiteboard or rotating a screwdriver about an axis). Well-known techniques exist for manipulator control in Cartesian space, most of which necessitate solving a series of Inverse Kinematics (IK) problems. Closed-form IK solvers work well for 7-degree-of-freedom (DOF) arms with rigid tool attachments, but cannot handle non-rigid tools that slip in the robot's hands. Numerical IK approaches are more generic and can handle non-rigid links to tools, but can be slow to converge. More importantly, if any joints fail or become limited in their range of motion, the robot arm essentially becomes 6-DOF or lower. IK solvers often fail in these lower DOF spaces because the configuration space becomes non-continuous and full of "holes". As a result, a 7-DOF robotic arm in space might be rendered largely useless if a single joint fails or even loses mobility until it can be serviced. TRACLabs proposes to investigate an alternative approach to traditional Cartesian control approaches, which rely on complex IK solvers that go from Cartesian space backwards to joint space. We propose to leverage cheap memory and modern processing speeds to instead perform simple computations that go from joint space forwards to Cartesian space. Such techniques should overcome common changes to a manipulation chain caused by tool slippage or the grasping of a new tool and to overcome uncommon changes to a chain caused by joint failures, reduced joint mobility, changes in joint geometry or range of motion, or added joints.
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Software for Application of HHT Technologies to Time Series Analysis Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:27:16.000ZThe proposed innovation is a robust and user-friendly software environment where NASA researchers can customize the latest HHT technologies for the LISA (and LIGO) application. The proposed technology will include the latest discoveries and inventions not available in the state-of-the-art. Its taxonomy includes gravitational sensors and sources, expert systems, portable data analysis tools, software development environments, and software tools for distributed analysis and simulation. The disturbance caused by the passage of a gravitational wave is expected to be very small and will be measured with laser interferometry. The Hilbert-HuangTransform (HHT)and related analysis technologies developed since the original concept has been used successfully in other applications to extract non-linear and transient signal comonents of very small magnitude with respect to the measured signal. The proposed research and development team has participated in the latest cycle of technology development related to the HHT at the theoretical, implementation, and application levels. Not only will the creation of the proposed software contribute to the data analysis of the gravitational wave signals in the laser interferometry measurements (for both LIGO and LISA data), but also in other applications within and outside NASA's mission.
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ICI - Accommodation and Food Services Garbage Composition - Proper Disposal Location
data.calgary.ca | Last Updated 2023-02-01T15:39:37.000ZThis chart shows weight per cent composition grouped by proper disposal location. This dataset is for garbage bin waste from the Industrial, Commercial, and Institutional (ICI) sector. The North American Industry Classification System (NAICS) is used to categorize ICI businesses and organizations into sub-sectors for ease of data collection and reporting. The NAICS sub-sectors included in this study are: Accommodation and Food Services (NAICS code 72), Retail Trade (44-45), Manufacturing (31-33), Health Care and Social Assistance (62), and Public Administration (91). All businesses and organizations included in the study were customers of The City’s Commercial Collections service, except for one privately-serviced customer in the Accommodation and Food Services sub-sector that was added to provide better sector representation. A total of 115 samples are included in the dataset: 30 in Accommodation and Food Services, 35 in Retail Trade, 17 in Manufacturing, 25 in Health Care and Social Assistance, and 8 in Public Administration. The weight per cent for each sub-sector is the pooled average of samples collected in the four seasons of 2019. Waste Composition studies are periodically conducted by Waste and Recycling Services to help assess the performance of diversion and education programs and inform improvements and new program design.
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ICI - Retail Garbage Composition - Proper Disposal Location
data.calgary.ca | Last Updated 2023-02-01T15:39:39.000ZThis chart shows weight per cent composition grouped by proper disposal location. This dataset is for garbage bin waste from the Industrial, Commercial, and Institutional (ICI) sector. The North American Industry Classification System (NAICS) is used to categorize ICI businesses and organizations into sub-sectors for ease of data collection and reporting. The NAICS sub-sectors included in this study are: Accommodation and Food Services (NAICS code 72), Retail Trade (44-45), Manufacturing (31-33), Health Care and Social Assistance (62), and Public Administration (91). All businesses and organizations included in the study were customers of The City’s Commercial Collections service, except for one privately-serviced customer in the Accommodation and Food Services sub-sector that was added to provide better sector representation. A total of 115 samples are included in the dataset: 30 in Accommodation and Food Services, 35 in Retail Trade, 17 in Manufacturing, 25 in Health Care and Social Assistance, and 8 in Public Administration. The weight per cent for each sub-sector is the pooled average of samples collected in the four seasons of 2019. Waste Composition studies are periodically conducted by Waste and Recycling Services to help assess the performance of diversion and education programs and inform improvements and new program design.
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PHOENIX MARS ROBOTIC ARM CAMERA 5 XYZ OPS V1.0
data.nasa.gov | Last Updated 2023-01-26T20:09:16.000ZThe Robotic Arm Camera (RAC) experiment on the Mars Phoenix Lander consists of one instrument component plus command electronics. This RAC Imaging Operations RDR data set contains xyz data from the Robotic Arm Camera (RAC).
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Sanitary Sewer Spills - Strategic KPI
sharefulton.fultoncountyga.gov | Last Updated 2023-01-30T16:55:22.000ZThis measure tracks the number of sanitary sewer overflows reported by Fulton County. This measure currently applies only to the sanitary sewer system operated by Fulton County and does not include the City of Atlanta sewer system. A sanitary sewer overflow is a condition in which untreated sewage is released into the environment. Most overflows in the Fulton County system in recent years have been caused by blockages from debris or grease with roots often being a contributing or primary factor. Other causes have included physical failure of the sewer line and mechanical failure of pumps.
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2014-2015 Arts Survey Data
data.cityofnewyork.us | Last Updated 2022-05-09T22:23:30.000ZThe Annual Arts in Schools Report includes data about arts teachers, arts budgeting, space for the arts, partnerships with arts and cultural organizations and parent involvement for elementary, middle and high schools. These reports help school administrators, parents, and students understand how their schools are progressing towards offering universal arts education to all students.