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9 FEBRUARY 2021DIGEST
U.S. Department of Defense (DoD) Uses 3-D Printing to Create N95 Respirators
In response to the COVID-19 pandemic, the U.S. Army Medical Materiel Development Activity’s (USAMMDA's) Warfighter Expeditionary Medicine and Treatment Project Management Office (WEMT PMO), as part of the U.S. Army Medical Research and Development Command’s Additive Manufacturing Working Group, has played an integral role in the ramped-up effort to produce N95 respirators for healthcare and frontline workers across the nation.
As stated on the Food and Drug Administration’s website, an N95 respirator is “a respiratory protective device designed to achieve a very close facial fit and very efficient filtration of airborne particles.” Compared to a surgical mask, which is loose fitting, the edges of the N95 mask are designed to form a very tight seal around the individual’s nose and mouth, providing the highest levels of protection against infection from COVID-19.
Air Force Maj. Daniel Williams serves as product manager of the WEMT PMO’s N95 respirator efforts at USAMMDA. These include coordinating programmatic and regulatory support, leveraging existing government resources, and developing synergies within the Defense Department’s organic industrial base to successfully generate N95 respirator... Read More
NOTABLE TECHNICAL INQUIRY
What group 1 and 2 unmanned aircraft systems (UASs) are marketed and/or designed for weapons deployment?
DSIAC was tasked with determining different methods that have been employed to weaponize group 1 and 2 UASs. Through open-source news articles and publications, DSIAC compiled various methods of mounting guns, launchers, and munitions to drones, as well as different efforts to advance loitering munition technologies. While some of the... Read More
Source: JBSA
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9 FEBRUARY 2021 – THE LATEST FROM THE DEFENSE SYSTEMS INFORMATION ANALYSIS CENTER
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DSIAC JOURNAL SUMMER 2020
• Investigating Surface Structures for Infrared Signature Management
• Systems Engineering of Autonomy: Frameworks for MUM-T Architecture
• Passive Coherent Location Radar – The Silent Threat
• Detection and Classification of Small UAS for Threat Neutralization
• Predicting Hydrodynamic Ram Damage in Bonded Composite Tanks Using Progressive Damage Failure
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Daunting Challenge of Drone Defense
I have worked with AFRL on deep learning for autonomy and automatic target recognition since my graduation from Ohio State University in 2018. I lead contractor research efforts on adversarial signals, robustness, and data efficiency. I also conduct research into new forms of neural architectures, which I will continue when I enter the Civilian Academic
Christopher Menart, Research Computer Scientist, U.S. Air Force Research Lab (AFRL)
• Characterization of Composite Spaced Armor Performance
HIGHLIGHT
“Introduction to Brawler” 2021 Training Course
March 16, 2021 - March 19, 2021 Lexington, MD
Brawler is a U.S. government-owned, comprehensive simulation tool which provides a detailed representation of air-to-air combat engagements involving multiple flights of aircraft in the visual- and beyond-visual-range arenas. Because of the importance of cooperative tactics and critical role of human factors (such as surprise, confusion, situation awareness, and the ability to innovate tactical responses in unexpected situations), special emphasis has been placed on simulating these command and control aspects of the engagement process. Brawler is the standard for high-fidelity, air-to-air engagement modeling within the Air Force, Navy, airframe manufacturing, and avionics communities.
This course is designed for individuals who may be involved in studies that use Brawler, including any analysts and engineers who may be running the tool, generating input data, and/or analyzing results. The course includes instruction and hands-on... Read More
Source: U.S. Marine Corps
Development Program to pursue a Ph.D. in the spring of 2021. My goal is deep-learning systems capable of incremental, general-purpose learning from many sources of information, suitable for the open-ended and evolving domains in which we expect to deploy machine learning in the future.
9 FEBRUARY 2021DIGEST
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Advanced Drone Technology (Source: JBSA, https://www.jbsa.mil/News/Photos/igphoto/2001681871/).
POSTED: OCTOBER 14, 2020 | COMPLETED: JUNE 18, 2020
What group 1 and 2 unmanned aircraft sysems (UASs) are marketed and/ordesigned for weapons deployment?DSIAC was tasked with determining diferent methods that have been employed to weaponize group 1 and 2 UASs. Throughopen-source news articles and publications, DSIAC compiled various methods of mounting guns, launchers, and munitionsto drones, as well as diferent eforts to advance loitering munition technologies. While some of the technologies were eitherdeveloped or funded by the U.S. military, many of the technologies and modifcations came from either nations or nonsateactors actively engaged in modern warfare tactics overseas. The evolving, small UAS technologies are used for precisionsrike, ground support, surveillance, and counter-UAS missions. A brief summary of recent modifcations and platforms isexamined in this report.
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Weaponizing Unmanned Aircraft Sysems(UAS)
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