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- API data.nasa.gov | Last Updated 2020-01-29T01:42:45.000Z
We propose to develop an innovative Autonomous Flight Safety Inference Engine (AFSIE) system to autonomously and reliably terminate the flight of an errant launch vehicle. This proposed phase 1 research is innovative in that it combines proven NASA-developed AFS algorithms, real-time hazard assessment algorithms and hazard envelopes generated from Joint Advanced Range Safety System Real Time (JARSS RT) and an on-board vehicle simulator into a refined onboard software inference engine that monitors navigation states, mission flight rules and onboard anomaly instrumentation. An autonomous flight safety system must be able to reliably perform accurate and autonomous navigation so as to determine the vehicle position, velocity and attitude states in real time. Reliability requirements for AFS are high due to stringent loss-of-life constraints, often leading to redundant navigation sensors with attendant cost impacts. Our innovative solution proposes to satisfy RCC accuracy and reliability requirements by exploiting the low-cost COTS sensor and processor architectures that are currently being baselined for the Common NanoSat/Launcher Avionics Technology (CNAT) study and a Nano launch vehicle avionics design. This dual use hardware implementation will greatly reduce the recurring costs for the production of an autonomous flight safety system. This has significant implications for reducing the costs for launch vehicles, particularly Nano and Micro Satellite Launch Vehicles (NMSLV), where range safety costs currently consume a burdensome percentage of the launch cost. Under this proposed phase 1 effort, we will 1) identify the range requirements and develop a plan for range safety for approval of the system, 2) identify reliable low-cost COTS hardware that satisfies the range accuracy and reliability requirements and, 3) develop an end to end simulation to demonstrate the AFSIE Concept of Operations.
- API data.austintexas.gov | Last Updated 2015-08-17T17:23:15.000Z
Chromatograms GC2010 2013-07-11
- API data.nasa.gov | Last Updated 2020-01-29T01:51:17.000Z
<p>Near-Earth Asteroid Scout, or NEA Scout, is a 6U CubeSat developed jointly between NASA’s Marshall Space Flight Center and the Jet Propulsion Laboratory. NASA selected NEA Scout as a candidate secondary payload for Exploration Mission 1 (EM-1), the first integrated (uncrewed) flight test of the Space Launch System and Orion Crewed Spacecraft.</p><p>NEA Scout is a robotic reconnaissance mission that will be deployed to fly by and return data from an asteroid representative of NEAs that may one day be human destinations. The NEA Scout team is currently evaluating a range of targets, and is continually updating the candidate pool based on new discoveries and expected performance. While the target can change based on launch date, the current planned target is <a href="http://neo.jpl.nasa.gov/risk/1991vg.html">1991VG</a>. It will be visible for astronomical observations from Earth in the July 2017-March 2018 timeframe, which will help refine its orbit ahead of the mission. The primary instrument payload will be a visible camera with color filters to collect data regarding the mineralogical, physical, and geotechnical properties of a candidate NEA for potential future robotic and human surface missions. </p><p>Near-Earth asteroids (NEAs) are the most easily accessible bodies in the solar system, and detections of NEAs are expected to grow exponentially in the near future, offering increasing target opportunities. As NASA continues to refine its plans to possibly explore these small worlds with human explorers, initial reconnaissance with comparatively inexpensive robotic precursors is necessary. Obtaining and analyzing relevant data about these bodies via robotic precursors before committing a crew to visit a NEA will significantly minimize crew and mission risk, as well as maximize exploration return potential. </p><p>In considering targets for human asteroid missions, there are several major factors that will make a significant difference in assessment of mission risks that can be addressed by simple photo-reconnaissance of a target. One of the most important of these factors is the spin state of the asteroid: does it rotate in a slow, easily predictable way? Asteroids that rotate very rapidly or that tumble about multiple axes present significant hazards in planning and executing proximity operations− especially operations that must be carried out over extended time periods. Another consideration is the physical state of the asteroid itself: is it a coherent mass or does it consist of a gravitationally bound pile of much smaller pieces? A coherent structure is unlikely to rearrange its configuration in response to a push by an astronaut or a hardware deployment and will provide a much easier surface in which to plant anchors for astronaut mobility or to hold equipment to the surface than will a rubble pile.</p><p>The full success criteria entails flying by a near Earth asteroid and acquire images sufficient to determine the target volume, shape model, Asteroid spectral type and meteorite analogs, rotational properties (pole position, rotation period), orbit, debris/dust field in local environment, and regolith characteristics.</p><p>Meeting this requirement addresses the need to fill Strategic Knowledge Gaps (SKG’s) related to asteroids as a precursor to subsequent safe and successful human missions. The data obtained will also support the advancement of science interests in asteroids.</p>
- API data.nasa.gov | Last Updated 2019-12-13T00:26:52.000Z
The Shuttle Solar Backscatter Ultraviolet (SSBUV) level-2 irradiance data are available for eight space shuttle missions flown between 1989 and 1996. SSBUV, a successor to the SBUV flown on the Nimbus-7 satellite, is nearly identical to the SBUV/2 instruments flown on the NOAA polar orbiting satellites. Data are available in an ASCII text format. UV irradiance data are available for the following days from the eight missions: Flight #1: 1989 October 19, 20, 21 Flight #2: 1990 October 7, 8, 9 Flight #3: 1991 August 3, 4, 5, 6 Flight #4: 1992 March 29, 30 Flight #5: 1993 April 9, 11, 13, 15, 16 Flight #6: 1994 March 14, 15, 17 Flight #7: 1994 November 5, 7, 10, 13 Flight #8: 1996 January 12, 16, 18 The Shuttle SBUV (SSBUV) instrument measured solar spectral UV irradiance during the maximum and declining phase of solar cycle 22. The SSBUV data accurately represent the absolute solar UV irradiance between 200-405 nm, and also show the long-term variations during eight flights between October 1989 and January 1996. These data have been used to correct long-term sensitivity changes in the NOAA-11 SBUV/2 data, which provide a near-daily record of solar UV variations over the 170-400 nm region between December 1988 and October 1994. These data demonstrate the evolution of short-term solar UV activity during solar cycle 22.
- API data.texas.gov | Last Updated 2020-06-26T23:52:01.000Z
Child Protective Investigations (CPI) conducts either a traditional investigation or Alternative Response (AR). Traditional investigations and Alternative Response require caseworkers to assess safety and take needed actions to protect a child while assessing any risk of abuse or neglect in the foreseeable future. AR cases present a less adversarial more collaborative approach to working with families by allowing for family engagement along with other community supports to ensure child safety. AR differs from traditional investigations in that AR cases are Priority 2 cases involving victims who are age 6 or older, there is no substantiation of allegations, no entry of perpetrators into the Central Registry (a repository for reports of child abuse and neglect), and there is a heightened focus on guiding the family to plan for safety in a way that works for them and therefore sustains the safety. Alternative response is timely if the first face-to-face meeting with the family and children in the household occurs within five days of an AR stage being opened and will involve working with the family to conduct safety and family assessments. . AR cases can remain open for up to 60 days with a one-time 20-day extension, if appropriate. Should CPI staff identify services to improve general family functioning and overall protective actions within the standard AR case time frame, the caseworker will provide support in linking the family to existing resources within the community. A description of Alternative Response and how it differs from a traditional investigation and priority response times are in the glossary. Alterative Response has been fully implemented in Regions 1, 2, 3, 4, 5, 6B, 7, 8, 9, 10 and 11. Implementation of AR in Region 6A is in the planning stages. Full state implementation is anticipated in 2020. Region 6A is Harris County and Region 6B is Region 6 excluding Harris County.
- API www.dallasopendata.com | Last Updated 2020-03-16T22:52:36.000Z
There are over 400 service requests types that are reported in the 311 system that affect the quality of life of our citizens, neighborhoods, and communities. The most popular service requests include but are not limited to animal services requests, high weeds, junk motor vehicles, and a number of other code compliance-related issues. Requests that deal with streets and mobility such as street and pot hole repair are also very common. 311 also receives requests to address environmental issues such as water conservation and air quality complaints. This dataset represents all Service Requests for the fiscal year time period of October 1, 2018 to September 30, 2019.
- API data.nasa.gov | Last Updated 2020-01-29T04:28:14.000Z
One cannot build a system-level Prognosis and Health Management (PHM) solution by cobbling together a bunch of existing prognostic techniques; it will have a very high rate of false-positive indications. On the other hand, if a system-level health management solution could identify the individual degradations and indictors associated with those degradations, and thereby decouple the problem into smaller pieces, the existing prognostic techniques could still be used to predict time to failure, and could therefore drive an effective Condition Based Maintenance and Decision Support System (CBM+). Qualtech Systems, Inc. (QSI) and Vanderbilt University team seeks to develop a system-level diagnostic and prognostic process and a "sense and respond capability" which first uses error codes and discrete sensor values to correctly diagnose the system health including degradations and failures of sensors and components, and then invoke appropriate prognostic routines for assessment of remaining life and capability. Thus, QSI's Testability Engineering And Maintenance System (TEAMS) real-time reasoner will enable the use of many existing prognostics techniques in the broader context by decomposing the complex system into local datasets of degradations and associated sensor data sets, thereby limiting the problem-space for the prognostic techniques to their limited design scope. Indeed, it is well established in the contexts of parameter estimation and model-based fault identification (i.e., fault isolation and severity estimation) that feature selection and diagnosis, respectively, followed by parameter estimation provides major improvements in estimation performance (measured in terms of computational time as well as the standard deviations of the estimated parameters) when compared to full parameter estimation which provides biased estimates for all the parameters.
Child and Adult Care Food Programs (CACFP) – Emergency Shelters – Meal Reimbursement – Program Year 2016-2017data.texas.gov | Last Updated 2020-06-26T23:49:41.000Z
<b>About the Agency</b><br> The Texas Department of Agriculture administers 12 U.S. Department of Agriculture nutrition programs in Texas including the National School Lunch and School Breakfast Programs and the Child and Adult Care Food Program (CACFP). TDA’s Food and Nutrition division provides technical assistance and training resources to partners operating the programs and oversees the USDA reimbursements they receive to cover part of the cost associated with serving food in their facilities. By working to ensure these partners serve nutritious meals and snacks, the division adheres to its mission — <i>Feeding the Hungry and Promoting Healthy Lifestyles.</i><p> <i><b>For more information on these programs, please visit our <a href=http://www.SquareMeals.org target="_blank">website</a>.</b></i><p> <b>About the Dataset</b><br> This data set contains claims information for <b> meal reimbursement for CACFP sites participating as emergency shelters for program year 2016-2017.</b> The CACFP program year begins October 1 and ends September 30. <p> <b>This dataset only includes claims submitted by CACFP sites operating as emergency shelters.</b> Sites can participate in multiple CACFP sub-programs. For reimbursement data on CACFP participants operating as Day Care Homes, Adult Day Care Centers, Child Care Centers, At-Risk Child Care Centers, Head Start Centers, or centers providing care for students outside school hours, please refer to the corresponding “Child and Adult Care Food Programs (CACFP) – Meal Reimbursement” dataset for that sub-program available on the State of Texas Open Data Portal. <p> <b>About Dataset Updates</b><br> TDA aims to post new program year data by December 15 of the active program year. <b>Participants have 60 days to file monthly reimbursement claims.</b> Dataset updates will occur monthly until 90 days after the close of the program year. After 90 days from the close of the program year, the dataset will be updated at six months and one year from the close of program year before becoming archived. Archived datasets will remain published but will not be updated. Any data posted during the active program year is subject to change.
- API stat.montgomerycountymd.gov | Last Updated 2016-08-23T23:37:37.000Z
PYDI Indicator - SPM Youth Crimes By Time2
- API www.datahub.va.gov | Last Updated 2020-05-15T22:13:11.000Z
<p>This is a monthly report that the VA Office of Information Technology provides to congress about data incidents that took place during the month (May 2014). The report contains details about and total numbers of mis-handling incidents; mis-mailed incidents; mis-mailed CMOP incidents; IT equipment inventory incidents; missing stolen PC incidents; missing/stolen laptop incident; lost blackberry incidents; and lost non-blackberry mobile devices (tablets, iPhones, androids, etc.) incidents.</p>