The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The Census Bureau includes landmarks such as military installations in the MTDB for locating special features and to help enumerators during field operations. In 2012, the Census Bureau obtained the inventory and boundaries of most military installations from the U.S. Department of Defense (DOD) for Air Force, Army, Marine, and Navy installations and from the U.S. Department of Homeland Security (DHS) for Coast Guard installations. The military installation boundaries in this release represent the updates the Census Bureau made in 2012 in collaboration with DoD.

SELECTED SOCIAL CHARACTERISTICS IN THE UNITED STATES VETERAN STATUS - DP02 Universe - Civilian population 18 Year and over Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 Veteran status is used to identify people with active duty military service and service in the military Reserves and the National Guard. Veterans are men and women who have served (even for a short time), but are not currently serving, on active duty in the U.S. Army, Navy, Air Force, Marine Corps, or the Coast Guard, or who served in the U.S. Merchant Marine during World War II. People who served in the National Guard or Reserves are classified as veterans only if they were ever called or ordered to active duty, not counting the 4-6 months for initial training or yearly summer camps.

Analysis of ‘world military power 2020’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/mingookkim/world-military-power-2020 on 14 February 2022.

--- Dataset description provided by original source is as follows ---

I found this data on a site called data.world. It is a data material published as a dataset created by vizzup.

This is a data that allows you to see the world military rankings in 2020 and numerical status such as the army, navy, and air force.

In addition, some related data such as population and economy related to military power are also included.

Please refer to data analysis as a good data to compare military power.

Original Source : globalfirepower.com on 1st may 2020

--- Original source retains full ownership of the source dataset ---

This report summarizes our contaminants investigation at the abandoned Cold Bay Air Force Station (Station), located on the Izembek National Wildlife Refuge at Grant Point. Our investigation was conducted in 1988 by Wayne M. Crayton (Ecological Services Anchorage) and members of your staff. The report centers on determining what, if any, contaminants from the facility may have entered the surrounding refuge environment and is provided to assist you in managing contaminant-related issues on your refuge. Included is a summary of field activities, an interpretation of selected analytical data and recommendations to remediate any identified contaminant problems.

The Aransas-Wood Buffalo population of whooping cranes migrates through the U.S. Great Plains twice annually, moving between wintering areas along coastal Texas and summering areas in and around Wood Buffalo National Park, Canada. These birds primarily migrate within a roughly 300-km-wide corridor that spans areas in Texas, Oklahoma, Kansas, Nebraska, South Dakota, North Dakota, and northwestern Montana in the U.S. The United States Air Force operates three bases in Oklahoma within the migration corridor of the whooping crane. These data support summarizations that identify temporal patterns of potential encounters, spatial patterns of use surrounding bases and regionally, and use of airspace by flying whooping cranes.

The Departmental Results Framework (DRF) is the strategic view of Defence’s mandate, displaying its Core Responsibilities and key performance information. It represents the corporate framework used to demonstrate plans, achievements, expenditures and performance results. This helps Canadians and parliamentarians understand what we do, what we seek to achieve, and how we will determine if we have achieved it. This dataset presents DRF 6.1 entitled “Naval, Army, and Air Force Bases enable military operations and defence activities” and its indicator 6.1.1 entitled “ Percentage of single quarters accommodations that can be used”. This indicator shows the extent to which single quarters accommodations are available for use by members on Land Bases. The percentage represents the amount of single accommodations rooms available for use out of all the single accommodations.

Percentage representation of Employment Equity (EE) Designated Group Members (DGM) in the Canadian Armed Forces(CAF). Data is grouped by CAF component and Rank Category (Officer or Non-commissioned Member) as well as by Designated Environmental Percentage representation of Employment Equity (EE) Designated Group Members (DGM) in the Canadian Armed Forces(CAF). Data is grouped by CAF component and Rank Category (Officer or Non-commissioned Member) as well as by Designated Environmental Uniform (DEU). These DEUs are Sea (Royal Canadian Navy), Land (Canadian Army) and Air (Royal Canadian Air Force).

11 af -- Population by labour force status, sex and age, montly data, 1989 M 01-2019 M 04

SPEED+ is the next-generation dataset for spacecraft pose estimation with specific emphasis on the robustness of Machine Learning (ML) models across the domain gap. Similar to its predecessor, SPEED+ consists of images of the Tango spacecraft from the PRISMA mission. SPEED+ consists of three different domains of imageries from two distinct sources. The first source is the OpenGL-based Optical Stimulator camera emulator software of Stanford’s Space Rendezvous Laboratory (SLAB), which is used to create the synthetic domain comprising 59,960 synthetic images. The labeled synthetic domain is split into 80:20 train/validation sets and is intended to be the main source of training of an ML model.

The second source is the Testbed for Rendezvous and Optical Navigation (TRON) facility at SLAB, which is used to generate two simulated Hardware-In-the-Loop (HIL) domains with different sourcesof illumination: lightbox and sunlamp. Specifically, these two domains are constructed using realistic illumination conditions using lightboxes with diffuser plates for albedo simulation and a sun lamp to mimic direct high-intensity homogeneous light from the Sun.

Compared to synthetic imagery, they capture corner cases, stray lights, shadowing, and visual effects in general which are not easy to obtain through computer graphics. The lightbox and sunlamp domains are unlabeled and thus intendeded mainly for testing, representing a typical scenario in developing a spaceborne ML model in which the labeled images from the target space domain are not available prior to deployment.

SPEED+ is made publicly available to the aerospace community and beyond as part of the second international Satellite Pose Estimation Competition (SPEC2021) co-hosted by SLAB and the Advanced Concepts Team (ACT) of the European Space Agency.

The construction of the TRON testbed was partly funded by the U.S. Air Force Office of Scientific Research (AFOSR) through the Defense University Research InstrumentationProgram (DURIP) contract FA9550-18-1-0492, titled High-Fidelity Verification and Validation of Spaceborne Vision-Based Navigation. The SPEED+ dataset was created using the TRON testbed by SLAB at Stanford University. The post-processing of the raw images was reviewed by ACT to meet the quality requirement of SPEC2021.

For more details on the dataset and the competition, please visit https://kelvins.esa.int/pose-estimation-2021/

In this dataset offspring are assigned to a dam and sire using information from single nucleotide polymorphisms (SNPs) from previously published pedigree reassignments of Brown Treesnakes within the U.S. Geological Survey's Brown Treesnake study enclosure on Northwest Field of Andersen Air Force Base, Guam (Levine and Yackel Adams 2021 and Nafus 2021) to update the overall pedigree dataset for snakes (2009-2018). Genomic pedigree reconstruction can assign offspring to parents in invasive species for which mating, and reproduction are difficult to study.

The building footprints were compiled from building corners collected with GPS equipment in the summer of 2003 and then merged with older building polygon data originating from blueprints (Potable Water and Fire Protection Lines Blueprint #381/41002A sheet 2 of 11) provided by the LIBI staff and softcopy data available from the US Census Bureau. Originally the Little Bighorn Battlefield National Monument (LIBI) GIS program was created from academic research and coursework in the Department of Economics and Geography, United States Air Force Academy (USAFA). Some of the GIS data was brought up-to-date or supplemented with GPS data in 2003 collect by NPS employees. This dataset was updated in July 2009 to reflect changes made to buildings after 2003. Updates to the dataset were digitized using institutional knowledge as well as GPS points. Institutional knowledge and GPS points were provided by LIBI staff members. Digitization and editing was done by NPS Intermountain Region Geographic Resources Program staff. See attached scanned reference drawings that were used to digitize this dataset by clicking on the Metadata Properties button on Metadata toolbar then clicking the Enclosures tab and finally double-clicking the enclosed file whose content you want to see. The enclosures are saved as jpegs and should open automatically in the appropriate application.

© National Park Service, Intermountain Support Office, GIS Program & Major Chris Benson (comp.) of the US Air Force

This layer is a component of Little Bighorn Battlefield National Monument.

This map service provides layers covering a variety of different datasets and themes for the Little Bighorn Battlefield National Monument. It is meant to be consumed by internet mapping applications and for general reference. It is for internal NPS use only. Produced January, 2014.

© IMR Geographic Resources Division, Little Bighorn Battlefield National Monument

Percentage representation of Employment Equity (EE) Designated Group Members (DGM) in the Canadian Armed Forces(CAF). Data is grouped by CAF component and Rank Category (Officer or Non-commissioned Member) as well as by Designated Environmental Percentage representation of Employment Equity (EE) Designated Group Members (DGM) in the Canadian Armed Forces(CAF). Data is grouped by CAF component and Rank Category (Officer or Non-commissioned Member) as well as by Designated Environmental Uniform (DEU). These DEUs are Sea (Royal Canadian Navy), Land (Canadian Army) and Air (Royal Canadian Air Force).

*P-values based on χ square test of homogeneity for Sex, Service Branch, Housing Allowance, Occupation, and Race/Ethnicity and are based on unequal variance t-test for Age, Time in Service, and BMI. Statistical tests were not weighted for observation time.

Animals move to locate important resources such as food, water, and mates. Therefore, movement patterns can reflect temporal and spatial availability of resources as well as when, where, and how individuals access such resources. To test these relationships for a predatory reptile, we quantified the effects of prey abundance on the spatial ecology of invasive brown treesnakes (Boiga irregularis). After toxicant-mediated suppression of a brown treesnake population on Guam, we simultaneously used visual encounter surveys to estimate rodent abundance and radiotelemetry to document movement behavior of surviving snakes located in the Habitat Management Unit (HMU) in Northern Guam, Andersen Air Force Base. The impact of prey availability on snake movement is covered under these data via three data files.

The NCEP operational Global Forecast System analysis and forecast grids are on a 0.25 by 0.25 global latitude longitude grid. Grids include analysis and forecast time steps at a 3 hourly interval from 0 to 240, and a 12 hourly interval from 240 to 384. Model forecast runs occur at 00, 06, 12, and 18 UTC daily. For real-time data access please use the NCEP data server [http://www.nco.ncep.noaa.gov/pmb/products/gfs/].

Afghanistan Labour Force Participation Rate: Modeled ILO Estimate: Ratio of Female to Male data was reported at 7.305 % in 2024. This records a decrease from the previous number of 7.340 % for 2023. Afghanistan Labour Force Participation Rate: Modeled ILO Estimate: Ratio of Female to Male data is updated yearly, averaging 19.242 % from Dec 1990 (Median) to 2024, with 35 observations. The data reached an all-time high of 28.937 % in 2017 and a record low of 7.305 % in 2024. Afghanistan Labour Force Participation Rate: Modeled ILO Estimate: Ratio of Female to Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Afghanistan – Table AF.World Bank.WDI: Labour Force. Labor force participation rate is the proportion of the population ages 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period. Ratio of female to male labor force participation rate is calculated by dividing female labor force participation rate by male labor force participation rate and multiplying by 100.;World Bank, World Development Indicators database. Estimates are based on data obtained from International Labour Organization, ILOSTAT at https://ilostat.ilo.org/data/.;Weighted average;National estimates are also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.