<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>UAM KoreaTech — Articles</title><description>유에이엠코리아텍의 시장 동향 리포트, 미니 논문, 사업 모델 분석, CBRN AI 전술 분석, 정책 분석, 케이스 스터디.</description><link>https://uamkt-com.vercel.app/</link><language>ko-kr</language><copyright>© 2026 유에이엠코리아텍 주식회사</copyright><item><title>Bayesian Threat Fusion: Why One Sensor Is Never Enough</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-15-en-bayesian-threat-fusion-why-one-sensor-is-never-enough/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-15-en-bayesian-threat-fusion-why-one-sensor-is-never-enough/</guid><description>How combining IMS, Raman, gamma spectroscopy, and qPCR under Bayesian inference cuts CBRN false-alarm rates and delivers sub-second threat consensus in the field.</description><pubDate>Mon, 15 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>Single-modal CBRN detectors produce unacceptable false-positive rates in complex field environments. Bayesian threat fusion across IMS, Raman spectroscopy, gamma spectroscopy, and qPCR sensors reduces false alarms by orders of magnitude while enabling sub-second consensus—the core design principle behind UAM KoreaTech&apos;s CBRN-CADS platform.</quickAnswer><category>cbrn-ai</category><category>Tokyo Subway Attack</category><category>Salisbury Novichok</category><category>CBRN-CADS</category><category>Bayesian Fusion</category><category>Multi-Modal Detection</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>Three Mile Island: What TMI-2 Teaches Modern CBRN Defense</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-15-en-three-mile-island-what-tmi-2-teaches-modern-cbrn-defense/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-15-en-three-mile-island-what-tmi-2-teaches-modern-cbrn-defense/</guid><description>The 1979 TMI-2 partial meltdown was not a technical failure alone—it was a public-trust collapse. Here is what K-defense CBRN planners must learn from it.</description><pubDate>Mon, 15 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>TMI-2&apos;s INES Level 5 partial meltdown revealed that radiological emergency response fails not when reactors crack, but when detection data and public communication are delayed or contradictory. Modern CBRN platforms must integrate real-time multi-sensor verification with transparent command-layer reporting to close the trust gap TMI-2 exposed.</quickAnswer><category>cbrn-ai</category><category>Three Mile Island</category><category>INES Level 5</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Radiological Emergency Response</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>Aquino at Pinatubo: When CBRN Crisis Forged a Negotiator</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-14-en-aquino-at-pinatubo-when-cbrn-crisis-forged-a-negotiator/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-14-en-aquino-at-pinatubo-when-cbrn-crisis-forged-a-negotiator/</guid><description>How Corazon Aquino&apos;s 1991 Pinatubo response reveals the decision architecture behind TIP-12&apos;s RESILIENT NEGOTIATOR archetype and AI-augmented CBRN command.</description><pubDate>Sun, 14 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>Corazon Aquino&apos;s management of the 1991 Pinatubo eruption and Clark Air Base radiological-chemical crisis exemplifies the TIP-12 RESILIENT NEGOTIATOR archetype: a commander who converts compound CBRN uncertainty into political leverage, achievable today through AI-driven Prompt Intelligence Quotient scoring.</quickAnswer><category>cbrn-ai</category><category>Corazon Aquino</category><category>Mount Pinatubo</category><category>TIP-12</category><category>Tactical Prompt</category><category>Radiological Response</category><category>CBRN Decision Intelligence</category><author>박무진</author></item><item><title>BLIS-D Meets KAS Part 21/23: Civil Aviation Decon Certified</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-14-en-blis-d-meets-kas-part-2123-civil-aviation-decon-certified/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-14-en-blis-d-meets-kas-part-2123-civil-aviation-decon-certified/</guid><description>How UAM KoreaTech&apos;s BLIS-D waterless decontamination system aligns with Korean Airworthiness Standards Part 21 and 23 for civil aviation deployment and NATO STANAG compliance.</description><pubDate>Sun, 14 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>BLIS-D&apos;s bleed-air dry decontamination architecture is structurally compatible with KAS Part 21/23 type certification pathways, enabling civil aviation operators to deploy NATO STANAG-compliant CBRN decon without structural aircraft modification. This unlocks a dual-use civil-military market that no certified competitor currently occupies.</quickAnswer><category>cbrn-ai</category><category>Tokyo Subway Attack</category><category>KAS Part 21</category><category>BLIS-D</category><category>CBRN-CADS</category><category>Type Certification</category><category>NATO STANAG</category><author>박무진</author></item><item><title>Drones Over the Hot Zone: Stand-off CBRN Detection Redefined</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-13-en-drones-over-the-hot-zone-stand-off-cbrn-detection-redefined/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-13-en-drones-over-the-hot-zone-stand-off-cbrn-detection-redefined/</guid><description>UAV-mounted sensor arrays are replacing human recon teams in CBRN hot zones. Explore how AI-driven stand-off detection changes the calculus of risk and response.</description><pubDate>Sat, 13 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>UAV-mounted CBRN sensor arrays can characterize a hot zone in minutes without exposing personnel to lethal agents. AI-driven platforms like CBRN-CADS, integrating IMS, Raman, and gamma sensors, deliver stand-off detection accuracy that surpasses traditional human reconnaissance teams in speed, repeatability, and survivability.</quickAnswer><category>cbrn-ai</category><category>Tokyo Subway Attack</category><category>Salisbury Novichok</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Stand-off Detection</category><category>UAV Reconnaissance</category><author>박무진</author></item><item><title>Rabin&apos;s Restraint: How a PIQ-76 Commander Redefined CBRN Crisis</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-12-en-rabins-restraint-how-a-piq-76-commander-redefined-cbrn-crisi/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-12-en-rabins-restraint-how-a-piq-76-commander-redefined-cbrn-crisi/</guid><description>How Yitzhak Rabin&apos;s disciplined non-retaliation during Iraq&apos;s 1991 SCUD campaign offers a TIP-12 decision-intelligence blueprint for modern CBRN commanders.</description><pubDate>Fri, 12 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>Rabin&apos;s PIQ-76 Restrained Commander profile during Iraq&apos;s 39-SCUD campaign shows that AI-augmented CBRN decision frameworks—like UAM KoreaTech&apos;s TIP-12—can codify strategic restraint as a measurable, replicable doctrine rather than an improvised political judgment.</quickAnswer><category>cbrn-ai</category><category>Yitzhak Rabin</category><category>Gulf War SCUD</category><category>CBRN-CADS</category><category>TIP-12</category><category>Restraint Doctrine</category><category>Decision Intelligence</category><author>박무진</author></item><item><title>STANAG 2103 Compliance: Korea&apos;s CBRN Decon Certification Roadmap</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-12-en-stanag-2103-compliance-koreas-cbrn-decon-certification-roadm/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-12-en-stanag-2103-compliance-koreas-cbrn-decon-certification-roadm/</guid><description>How Korean defense firms can navigate NATO STANAG 2103 and AAP-21 certification to achieve CBRN decontamination interoperability with allied forces by 2027.</description><pubDate>Fri, 12 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>NATO STANAG 2103 sets the binding interoperability standard for CBRN decontamination procedures across alliance forces. Korean defense manufacturers seeking NATO market access must align product performance data, documentation, and test protocols with AAP-21 ratification requirements—a process BLIS-D is actively pursuing through bleed-air dry decon validation trials.</quickAnswer><category>cbrn-ai</category><category>STANAG 2103</category><category>Operation Tomodachi</category><category>BLIS-D</category><category>CBRN-CADS</category><category>NATO Interoperability</category><category>AAP-21 Certification</category><author>박무진</author></item><item><title>Halabja 1988: When Civilians Became CBRN Targets</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-11-en-halabja-1988-when-civilians-became-cbrn-targets/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-11-en-halabja-1988-when-civilians-became-cbrn-targets/</guid><description>The 1988 Halabja chemical attack killed 5,000 civilians in hours. What does Saddam&apos;s doctrine of civil-targeting CBRN warfare mean for Korean defense and deterrence today?</description><pubDate>Thu, 11 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>Halabja proved that chemical weapons are primarily instruments of civil-population coercion, not battlefield tools. This precedent demands detection and decontamination architectures designed for unprotected civilians — exactly the capability gap BLIS-D and CBRN-CADS are engineered to close.</quickAnswer><category>cbrn-ai</category><category>Halabja</category><category>Iran-Iraq War</category><category>BLIS-D</category><category>CBRN-CADS</category><category>Civil CBRN Deterrence</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>Halabja 1988: When Civilians Became the Target of Chemical War</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-11-en-halabja-1988-when-civilians-became-the-target-of-chemical-wa/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-11-en-halabja-1988-when-civilians-became-the-target-of-chemical-wa/</guid><description>The 1988 Halabja attack killed 5,000 civilians with Sarin and Mustard gas. Here is what it teaches K-defense about civil-targeting CBRN deterrence today.</description><pubDate>Thu, 11 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>The 1988 Halabja attack proved that chemical weapons are instruments of mass civilian terror, not just battlefield tools. Modern CBRN deterrence must therefore prioritize rapid civil-environment detection and decontamination—exactly the capability gap that AI-driven multi-sensor platforms and waterless decon systems are designed to close.</quickAnswer><category>cbrn-ai</category><category>Halabja</category><category>Iran-Iraq War</category><category>BLIS-D</category><category>CBRN-CADS</category><category>Civil CBRN Deterrence</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>IMS vs Raman: Which Sensor Wins CWA Field Detection?</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-11-en-ims-vs-raman-which-sensor-wins-cwa-field-detection/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-11-en-ims-vs-raman-which-sensor-wins-cwa-field-detection/</guid><description>A rigorous comparative analysis of IMS and Raman spectroscopy for chemical warfare agent detection, and how CBRN-CADS fuses both to close the false-positive gap.</description><pubDate>Thu, 11 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>Neither IMS nor Raman alone is sufficient for reliable CWA field detection: IMS offers sub-ppb sensitivity but suffers high false-positive rates in complex environments, while Raman provides molecular specificity but struggles with fluorescence and low-vapor-pressure agents. CBRN-CADS fuses both with AI classification to deliver confirmed identification in under 90 seconds.</quickAnswer><category>cbrn-ai</category><category>IMS</category><category>Raman Spectroscopy</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Chemical Warfare Agents</category><category>Sensor Fusion</category><author>박무진</author></item><item><title>Park Chung-hee&apos;s 30-Minute OODA: The Defensive Founder of Korean CBRN Doctrine</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-10-en-park-chung-hees-30-minute-ooda-the-defensive-founder-of-kore/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-10-en-park-chung-hees-30-minute-ooda-the-defensive-founder-of-kore/</guid><description>How the 1·21 Incident of 1968 forged Korea&apos;s layered defense instinct—and why its logic lives inside UAM KoreaTech&apos;s TIP-12 Defensive Founder archetype today.</description><pubDate>Wed, 10 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>Park Chung-hee&apos;s sub-30-minute OODA response to the 1968 Blue House Raid established the Defensive Founder doctrine that underpins Korean layered-defense thinking. UAM KoreaTech&apos;s TIP-12 framework codes this archetype as PIQ 69→80, directly informing AI-augmented CBRN decision logic in the CBRN-CADS platform.</quickAnswer><category>cbrn-ai</category><category>Park Chung-hee</category><category>1·21 Incident</category><category>CBRN-CADS</category><category>TIP-12</category><category>Layered Defense Doctrine</category><category>OODA Loop</category><author>박무진</author></item><item><title>Bayesian Threat Fusion: How Multi-Sensor CBRN Networks Decide in Seconds</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-09-en-bayesian-threat-fusion-how-multi-sensor-cbrn-networks-decide/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-09-en-bayesian-threat-fusion-how-multi-sensor-cbrn-networks-decide/</guid><description>How combining IMS, Raman, gamma spectroscopy, and qPCR under Bayesian fusion logic reduces false positives and speeds confirmed CBRN threat consensus to under 90 seconds.</description><pubDate>Tue, 09 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>Bayesian threat fusion integrates IMS, Raman spectroscopy, gamma detection, and qPCR into a single probabilistic consensus engine, reducing false-positive rates by over 60% compared to single-sensor systems and enabling confirmed CBRN threat identification in under 90 seconds. UAM KoreaTech&apos;s CBRN-CADS platform operationalizes this architecture for tactical field deployment.</quickAnswer><category>cbrn-ai</category><category>Tokyo Subway Attack</category><category>Salisbury Novichok</category><category>CBRN-CADS</category><category>Bayesian Fusion</category><category>Multi-Modal Sensor</category><category>Dual-Use Detection</category><author>박무진</author></item><item><title>Tokyo 1995: What Sarin on the Subway Taught the World</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-09-en-tokyo-1995-what-sarin-on-the-subway-taught-the-world/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-09-en-tokyo-1995-what-sarin-on-the-subway-taught-the-world/</guid><description>The 1995 Tokyo subway sarin attack exposed fatal gaps in urban CBRN response. Here&apos;s what K-defense must learn 30 years later—and how to close those gaps.</description><pubDate>Tue, 09 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>The 1995 Tokyo subway sarin attack revealed that first responders lacked both detection capability and decontamination speed, costing lives in the critical first 90 minutes. Modern dual-use platforms like CBRN-CADS and BLIS-D directly address these documented response gaps.</quickAnswer><category>cbrn-ai</category><category>AumShinrikyo</category><category>TokyoSubwaySarin</category><category>BLIS-D</category><category>CBRN-CADS</category><category>UrbanCBRNResponse</category><category>DualUseDefense</category><author>박무진</author></item><item><title>Aum Shinrikyo Decoded: TIP-12 Reveals Cult CBRN Command Logic</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-08-en-aum-shinrikyo-decoded-tip-12-reveals-cult-cbrn-command-logic/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-08-en-aum-shinrikyo-decoded-tip-12-reveals-cult-cbrn-command-logic/</guid><description>Using UAM KoreaTech&apos;s TIP-12 Persona framework to reverse-engineer Aum Shinrikyo&apos;s command structure and extract actionable CBRN threat-detection lessons.</description><pubDate>Mon, 08 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>TIP-12&apos;s Visionary-Aggressor-Operator typology maps directly onto Aum Shinrikyo&apos;s three-tier command structure, revealing how organizations mask CBRN intent behind doctrinal ambiguity—and how AI-augmented persona profiling can detect this pattern earlier than traditional intelligence methods.</quickAnswer><category>cbrn-ai</category><category>Aum Shinrikyo</category><category>Asahara Shoko</category><category>TIP-12</category><category>CBRN-CADS</category><category>Persona Profiling Framework</category><category>Threat Decision Intelligence</category><author>박무진</author></item><item><title>BLIS-D Meets KAS Part 21/23: Civil Aviation Decon Certified</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-08-en-blis-d-meets-kas-part-2123-civil-aviation-decon-certified/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-08-en-blis-d-meets-kas-part-2123-civil-aviation-decon-certified/</guid><description>How UAM KoreaTech&apos;s BLIS-D waterless decontamination system aligns with KAS Part 21/23 airworthiness standards for civil aviation deployment across Korea and NATO partners.</description><pubDate>Mon, 08 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>BLIS-D&apos;s bleed-air dry decontamination architecture is structurally compatible with KAS Part 21 and Part 23 airworthiness certification pathways under MOLIT oversight, enabling civil aviation deployment without structural aircraft modification. This makes BLIS-D the first Korean-origin decon system positioned for dual-use type certification across both military and civil aviation fleets.</quickAnswer><category>cbrn-ai</category><category>Tokyo Sarin Attack</category><category>Salisbury Novichok</category><category>BLIS-D</category><category>CBRN-CADS</category><category>KAS Certification</category><category>Dual-Use Aviation</category><author>박무진</author></item><item><title>Drones Over the Hot Zone: The Case for UAV-Mounted CBRN Detection</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-07-en-drones-over-the-hot-zone-the-case-for-uav-mounted-cbrn-detec/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-07-en-drones-over-the-hot-zone-the-case-for-uav-mounted-cbrn-detec/</guid><description>Why UAV-mounted sensor arrays are replacing human recon teams for hot-zone CBRN characterization—and how AI-driven stand-off detection changes battlefield calculus.</description><pubDate>Sun, 07 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>UAV-mounted CBRN sensor arrays can characterize chemical and biological hot zones from stand-off distances exceeding 500 meters, eliminating the need to expose human recon teams to lethal agent concentrations. AI-driven multi-modal sensor fusion—combining IMS, Raman, and LIDAR plume-mapping—delivers actionable threat classification in under 90 seconds.</quickAnswer><category>cbrn-ai</category><category>Halabja 1988</category><category>Tokyo Subway Attack</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Stand-off Detection</category><category>UAV Reconnaissance</category><author>박무진</author></item><item><title>TMI-2 at 45: What Radiological Crises Teach K-Defense</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-07-en-tmi-2-at-45-what-radiological-crises-teach-k-defense/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-07-en-tmi-2-at-45-what-radiological-crises-teach-k-defense/</guid><description>The 1979 Three Mile Island partial meltdown remains the definitive case study in radiological emergency response failure—and a blueprint for modern CBRN detection reform.</description><pubDate>Sun, 07 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>TMI-2&apos;s INES Level 5 partial meltdown revealed that radiological emergencies are lost not by physics alone but by sensor latency and communication collapse. Modern CBRN detection platforms that fuse real-time gamma sensing with AI-driven decision support can close the response gap that cost the NRC and the public 45 years of trust.</quickAnswer><category>cbrn-ai</category><category>Three Mile Island</category><category>INES Level 5</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Radiological Emergency Response</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>STANAG 2103 Compliance: Korea&apos;s CBRN Certification Roadmap</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-06-en-stanag-2103-compliance-koreas-cbrn-certification-roadmap/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-06-en-stanag-2103-compliance-koreas-cbrn-certification-roadmap/</guid><description>How Korean dual-use CBRN firms can navigate NATO STANAG 2103 and AAP-21 to achieve interoperability certification and access Allied procurement markets.</description><pubDate>Sat, 06 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>NATO STANAG 2103 defines decontamination procedures and reporting standards that any Allied or partner-nation CBRN system must meet. Korean firms like UAM KoreaTech can achieve compliance by aligning BLIS-D bleed-air decontamination outputs to STANAG 2103 thresholds and pursuing AAP-21 standardization agreement entry, unlocking direct NATO procurement eligibility.</quickAnswer><category>cbrn-ai</category><category>STANAG 2103</category><category>Aum Shinrikyo Tokyo Attack</category><category>BLIS-D</category><category>CBRN-CADS</category><category>NATO Interoperability</category><category>AAP-21 Certification</category><author>박무진</author></item><item><title>Sun Tzu to Hannibal: TIP-12 Commander Archetypes in CBRN Crisis</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-06-en-sun-tzu-to-hannibal-tip-12-commander-archetypes-in-cbrn-cris/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-06-en-sun-tzu-to-hannibal-tip-12-commander-archetypes-in-cbrn-cris/</guid><description>How UAM KoreaTech&apos;s TIP-12 framework maps 16 historical commander archetypes to modern CBRN crisis roles, transforming AI-augmented decision-making under chemical threat.</description><pubDate>Sat, 06 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>TIP-12&apos;s 16 commander archetypes — drawn from figures like Sun Tzu, Hannibal, and Yi Sun-sin — provide AI-augmented cognitive templates that help CBRN officers match decision style to crisis role, reducing response latency and command mismatch under chemical or biological attack.</quickAnswer><category>cbrn-ai</category><category>Sun Tzu</category><category>Hannibal Barca</category><category>TIP-12</category><category>Tactical Prompt</category><category>CBRN Decision Intelligence</category><category>Commander Archetypes</category><author>박무진</author></item><item><title>IMS vs Raman: Which Wins for CWA Field Detection in 2026?</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-05-en-ims-vs-raman-which-wins-for-cwa-field-detection-in-2026/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-05-en-ims-vs-raman-which-wins-for-cwa-field-detection-in-2026/</guid><description>A head-to-head comparison of IMS and Raman spectroscopy for chemical warfare agent detection, and why fusing both inside CBRN-CADS changes the equation.</description><pubDate>Fri, 05 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>Neither IMS nor Raman alone is sufficient for reliable CWA field detection. IMS delivers speed and sensitivity at trace concentrations; Raman provides molecular specificity and reduces false positives. Fusing both sensors under AI classification—as in CBRN-CADS—closes the gap that legacy systems like JCAD and M-22 leave open.</quickAnswer><category>cbrn-ai</category><category>IMS</category><category>Raman Spectroscopy</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Chemical Warfare Agents</category><category>Sensor Fusion</category><author>박무진</author></item><item><title>Bleed-Air Engineering: From Aircraft ECS to CBRN Decon</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-04-en-bleed-air-engineering-from-aircraft-ecs-to-cbrn-decon/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-04-en-bleed-air-engineering-from-aircraft-ecs-to-cbrn-decon/</guid><description>How aircraft environmental control system bleed-air principles transfer to chemical agent neutralization — and why BLIS-D redefines NATO-compliant decontamination.</description><pubDate>Thu, 04 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>Aircraft bleed-air technology — the pressurized, superheated air tapped from jet engine compressor stages — can be repurposed to neutralize chemical warfare agents in under 90 seconds without water. UAM KoreaTech&apos;s BLIS-D applies this ECS-derived thermodynamic principle to deliver NATO STANAG-compliant, waterless decontamination at forward operating bases.</quickAnswer><category>cbrn-ai</category><category>Bleed Air</category><category>ECS Engineering</category><category>BLIS-D</category><category>CBRN-CADS</category><category>NATO STANAG</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>PIQ: Measuring AI-Collaboration Readiness in CBRN Teams</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-04-en-piq-measuring-ai-collaboration-readiness-in-cbrn-teams/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-04-en-piq-measuring-ai-collaboration-readiness-in-cbrn-teams/</guid><description>The Prompt Intelligence Quotient (PIQ) offers CBRN operators a 5-minute self-diagnostic to measure AI-collaboration capability and close critical decision gaps.</description><pubDate>Thu, 04 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>PIQ (Prompt Intelligence Quotient) quantifies how effectively a CBRN operator can collaborate with AI systems under time pressure. Teams scoring below PIQ-60 show statistically longer triage cycles; the 5-minute diagnostic identifies skill gaps before a live incident.</quickAnswer><category>cbrn-ai</category><category>Stanford Symbolic Systems</category><category>Bhopal Disaster</category><category>PIQ</category><category>TIP-12</category><category>Prompt Engineering</category><category>Decision Intelligence</category><author>박무진</author></item><item><title>PIQ: Measuring AI-Collaboration Skill in CBRN Operators</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-04-en-piq-measuring-ai-collaboration-skill-in-cbrn-operators/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-04-en-piq-measuring-ai-collaboration-skill-in-cbrn-operators/</guid><description>The Prompt Intelligence Quotient (PIQ) offers CBRN teams a 5-minute self-diagnostic to measure AI-collaboration capability and close deadly decision gaps under chemical threat.</description><pubDate>Thu, 04 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>PIQ (Prompt Intelligence Quotient) quantifies how effectively a CBRN operator can collaborate with AI systems under time pressure. Teams scoring below the PIQ-60 threshold make agent-identification errors at 3× the rate of higher-scoring peers, making PIQ a mission-critical readiness metric alongside traditional decon and detection drills.</quickAnswer><category>cbrn-ai</category><category>Stanford Symbolic Systems</category><category>Prompt Engineering</category><category>PIQ</category><category>TIP-12</category><category>Decision Intelligence</category><category>CBRN Readiness</category><author>박무진</author></item><item><title>Bayesian Fusion: Why One CBRN Sensor Is Never Enough</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-03-en-bayesian-fusion-why-one-cbrn-sensor-is-never-enough/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-03-en-bayesian-fusion-why-one-cbrn-sensor-is-never-enough/</guid><description>How Bayesian threat fusion across IMS, Raman, gamma spectroscopy, and qPCR sensors enables sub-second CBRN consensus—and why CBRN-CADS leads the field.</description><pubDate>Wed, 03 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>Single-modality CBRN detectors produce unacceptable false-positive rates in complex threat environments. Bayesian multi-sensor fusion across IMS, Raman spectroscopy, gamma spectroscopy, and qPCR can reduce classification error by orders of magnitude, enabling sub-second actionable threat consensus in field conditions—the core design principle behind CBRN-CADS.</quickAnswer><category>cbrn-ai</category><category>Tokyo Subway Attack</category><category>Salisbury Novichok</category><category>CBRN-CADS</category><category>Bayesian Fusion</category><category>Multi-Modal Detection</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>Halabja 1988: When Civilians Became the Target of Chemical War</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-03-en-halabja-1988-when-civilians-became-the-target-of-chemical-wa/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-03-en-halabja-1988-when-civilians-became-the-target-of-chemical-wa/</guid><description>The 1988 Halabja chemical attack killed 5,000 Kurdish civilians. What does this precedent mean for modern CBRN deterrence and dual-use defense procurement?</description><pubDate>Wed, 03 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>The Halabja attack proved that chemical weapons can be deployed against civilian populations without immediate strategic cost—exposing a detection and deterrence vacuum that modern platforms like CBRN-CADS and BLIS-D are specifically engineered to close.</quickAnswer><category>cbrn-ai</category><category>Halabja</category><category>Iran-Iraq War</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Civil Protection</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>John Major&apos;s Gulf War CBRN Calculus: The Continuity Executor at 74 IQ</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-02-en-john-majors-gulf-war-cbrn-calculus-the-continuity-executor-a/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-02-en-john-majors-gulf-war-cbrn-calculus-the-continuity-executor-a/</guid><description>How John Major&apos;s TIP-12 Continuity Executor profile shaped UK CBRN policy during Gulf War 1991 — and what that archetype reveals about AI-augmented defense decision-making today.</description><pubDate>Tue, 02 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>John Major&apos;s Continuity Executor archetype (TIP-12 PIQ 74) reveals how institutional loyalty over adaptive intelligence delayed UK CBRN readiness against Iraqi WMD in 1991. AI-augmented decision tools like UAM KoreaTech&apos;s Tactical Prompt platform now quantify these cognitive gaps before crises escalate.</quickAnswer><category>cbrn-ai</category><category>John Major</category><category>Gulf War 1991</category><category>TIP-12</category><category>Tactical Prompt</category><category>CBRN Decision Intelligence</category><category>Iraqi WMD</category><author>박무진</author></item><item><title>KAS Part 21/23: Certifying BLIS-D for Civil Aviation Decon</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-02-en-kas-part-2123-certifying-blis-d-for-civil-aviation-decon/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-02-en-kas-part-2123-certifying-blis-d-for-civil-aviation-decon/</guid><description>How Korean Airworthiness Standards Part 21 and Part 23 create the regulatory pathway for BLIS-D civil aircraft decontamination deployment. 180 chars.</description><pubDate>Tue, 02 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>BLIS-D&apos;s bleed-air dry decontamination architecture is uniquely compatible with KAS Part 21 supplemental type certification and Part 23 airworthiness standards, giving civil aviation operators a MOLIT-compliant, 90-second CBRN decon capability without structural aircraft modification.</quickAnswer><category>cbrn-ai</category><category>KAS Part 21</category><category>BLIS-D</category><category>Civil Aviation CBRN</category><category>Type Certification</category><category>NATO STANAG 4632</category><category>Dual-Use Airworthiness</category><author>박무진</author></item><item><title>Tokyo 1995: What Sarin on the Subway Still Teaches Us</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-01-en-tokyo-1995-what-sarin-on-the-subway-still-teaches-us/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-01-en-tokyo-1995-what-sarin-on-the-subway-still-teaches-us/</guid><description>Aum Shinrikyo&apos;s 1995 Tokyo sarin attack exposed critical urban CBRN response gaps. Here&apos;s what K-defense innovators must learn 30 years later.</description><pubDate>Mon, 01 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>The 1995 Tokyo subway sarin attack revealed that first responders lacked both the detection tools to identify the agent and the decontamination infrastructure to treat casualties at scale. Thirty years later, those same gaps persist in most urban CBRN response frameworks — and AI-driven detection platforms like CBRN-CADS and waterless decon systems like BLIS-D directly address them.</quickAnswer><category>cbrn-ai</category><category>Tokyo Sarin Attack</category><category>Aum Shinrikyo</category><category>BLIS-D</category><category>CBRN-CADS</category><category>Urban CBRN Response</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>UAV-Mounted CBRN Sensors: Ending the Human Recon Sacrifice</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-01-en-uav-mounted-cbrn-sensors-ending-the-human-recon-sacrifice/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-06-01-en-uav-mounted-cbrn-sensors-ending-the-human-recon-sacrifice/</guid><description>Stand-off drone detection is replacing human CBRN reconnaissance teams. Here is how UAM KoreaTech&apos;s CBRN-CADS sensor stack changes hot-zone characterization forever.</description><pubDate>Mon, 01 Jun 2026 00:00:00 GMT</pubDate><quickAnswer>UAV-mounted multi-sensor arrays combining IMS, Raman, and LiDAR can characterize CBRN hot zones at stand-off distances, eliminating the need to send human reconnaissance teams into lethal contamination. UAM KoreaTech&apos;s CBRN-CADS platform integrates AI-driven classification to deliver actionable threat identification in under 90 seconds without personnel exposure.</quickAnswer><category>cbrn-ai</category><category>Ghouta Chemical Attack</category><category>Tokyo Subway Sarin</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Stand-off Detection</category><category>Drone Reconnaissance</category><author>박무진</author></item><item><title>Aquino at Pinatubo: When Resilience Beats Raw Data in CBRN Crisis</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-31-en-aquino-at-pinatubo-when-resilience-beats-raw-data-in-cbrn-cr/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-31-en-aquino-at-pinatubo-when-resilience-beats-raw-data-in-cbrn-cr/</guid><description>How Corazon Aquino&apos;s 1991 Pinatubo response reveals why AI-augmented decision intelligence outperforms intuition alone in radiological and chemical crises.</description><pubDate>Sun, 31 May 2026 00:00:00 GMT</pubDate><quickAnswer>Corazon Aquino&apos;s handling of the 1991 Pinatubo eruption and Clark Air Base radiological concerns shows that resilient negotiators excel under uncertainty but systematically underweight technical sensor data — a gap that AI-driven platforms like CBRN-CADS and the TIP-12 framework are purpose-built to close.</quickAnswer><category>cbrn-ai</category><category>Corazon Aquino</category><category>Pinatubo 1991</category><category>CBRN-CADS</category><category>Tactical Prompt TIP-12</category><category>Radiological Response</category><category>Decision Intelligence</category><author>박무진</author></item><item><title>STANAG 2103 Compliance: Korea&apos;s CBRN Decon Certification Roadmap</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-31-en-stanag-2103-compliance-koreas-cbrn-decon-certification-roadm/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-31-en-stanag-2103-compliance-koreas-cbrn-decon-certification-roadm/</guid><description>How Korean dual-use CBRN manufacturers can navigate NATO STANAG 2103 and AAP-21 certification to achieve full alliance interoperability by 2027.</description><pubDate>Sun, 31 May 2026 00:00:00 GMT</pubDate><quickAnswer>NATO STANAG 2103 sets the interoperability baseline for CBRN decontamination equipment across alliance forces. Korean manufacturers seeking NATO market access must align product architecture—including dry decon systems like BLIS-D—with AAP-21 test protocols, DSAT validation cycles, and Lattice-compatible data interfaces before 2027 procurement windows close.</quickAnswer><category>cbrn-ai</category><category>STANAG 2103</category><category>Operation Protective Edge</category><category>BLIS-D</category><category>CBRN-CADS</category><category>NATO Interoperability</category><category>Dual-Use Certification</category><author>박무진</author></item><item><title>IMS vs Raman: Which Sensor Wins in CWA Field Detection?</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-30-en-ims-vs-raman-which-sensor-wins-in-cwa-field-detection/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-30-en-ims-vs-raman-which-sensor-wins-in-cwa-field-detection/</guid><description>A rigorous comparative analysis of IMS and Raman spectroscopy for chemical warfare agent detection, and how CBRN-CADS fuses both to close critical field gaps.</description><pubDate>Sat, 30 May 2026 00:00:00 GMT</pubDate><quickAnswer>Neither IMS nor Raman alone provides sufficient accuracy for CWA field detection—IMS excels at trace sensitivity but suffers high false-positive rates, while Raman offers molecular specificity but struggles with obscurants and dark samples. UAM KoreaTech&apos;s CBRN-CADS fuses both sensor modalities under AI classification to deliver sub-90-second confirmed identification.</quickAnswer><category>cbrn-ai</category><category>Gulf-War-JCAD</category><category>M22-ACADA</category><category>CBRN-CADS</category><category>IMS</category><category>Chemical-Warfare-Agents</category><category>Sensor-Fusion</category><author>박무진</author></item><item><title>TMI-2: What a 1979 Meltdown Still Teaches CBRN Defense</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-30-en-tmi-2-what-a-1979-meltdown-still-teaches-cbrn-defense/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-30-en-tmi-2-what-a-1979-meltdown-still-teaches-cbrn-defense/</guid><description>The 1979 Three Mile Island partial meltdown exposed radiological response gaps that persist today. Here&apos;s what K-defense must learn from INES Level 5.</description><pubDate>Sat, 30 May 2026 00:00:00 GMT</pubDate><quickAnswer>TMI-2&apos;s 1979 partial meltdown revealed that containment hardware alone cannot prevent a public-trust collapse during radiological emergencies. Modern CBRN defense must integrate real-time multi-sensor detection and rapid decontamination to fill the communication and response gaps TMI-2 exposed.</quickAnswer><category>cbrn-ai</category><category>TMI-2</category><category>Iodine-131</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Radiological Response</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>Bleed-Air Engineering: From Aircraft ECS to CBRN Decon</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-29-en-bleed-air-engineering-from-aircraft-ecs-to-cbrn-decon/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-29-en-bleed-air-engineering-from-aircraft-ecs-to-cbrn-decon/</guid><description>How aircraft environmental control system bleed-air principles enable waterless 90-second chemical agent decontamination — BLIS-D&apos;s technical foundation explained.</description><pubDate>Fri, 29 May 2026 00:00:00 GMT</pubDate><quickAnswer>Aircraft bleed-air systems compress and superheat engine bypass air to condition cabin environments; BLIS-D re-engineers that same pressure-ratio and heat-exchanger logic to drive waterless chemical agent neutralization in under 90 seconds, eliminating the water-waste and secondary contamination penalties of legacy wet decon.</quickAnswer><category>cbrn-ai</category><category>Bleed Air</category><category>Environmental Control System</category><category>BLIS-D</category><category>CBRN-CADS</category><category>NATO STANAG Compliance</category><category>Dual-Use Defense Technology</category><author>박무진</author></item><item><title>Rabin&apos;s Restraint: TIP-12 Lessons From the 1991 SCUD Crisis</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-29-en-rabins-restraint-tip-12-lessons-from-the-1991-scud-crisis/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-29-en-rabins-restraint-tip-12-lessons-from-the-1991-scud-crisis/</guid><description>How Yitzhak Rabin&apos;s TP-IQ 76 RESTRAINED COMMANDER archetype during Iraq&apos;s 39-SCUD barrage reshapes AI-driven CBRN decision intelligence for modern commanders.</description><pubDate>Fri, 29 May 2026 00:00:00 GMT</pubDate><quickAnswer>Rabin&apos;s calculated restraint during Iraq&apos;s 39-SCUD attacks on Israel in 1991 exemplifies a TP-IQ 76 RESTRAINED COMMANDER archetype — a decision pattern that UAM KoreaTech&apos;s TIP-12 framework encodes to help modern CBRN commanders suppress reactive escalation and integrate layered defenses under chemical-threat ambiguity.</quickAnswer><category>cbrn-ai</category><category>Yitzhak Rabin</category><category>SCUD Missile</category><category>TIP-12</category><category>Tactical Prompt</category><category>Restraint Doctrine</category><category>CBRN Decision Intelligence</category><author>박무진</author></item><item><title>Bayesian Threat Fusion: How Multi-Sensor CBRN Networks Achieve Sub-Second Consensus</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-28-en-bayesian-threat-fusion-how-multi-sensor-cbrn-networks-achiev/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-28-en-bayesian-threat-fusion-how-multi-sensor-cbrn-networks-achiev/</guid><description>Bayesian fusion of IMS, Raman, gamma spectroscopy, and qPCR sensors enables sub-second CBRN threat consensus — here&apos;s why it changes battlefield detection.</description><pubDate>Thu, 28 May 2026 00:00:00 GMT</pubDate><quickAnswer>Bayesian threat fusion combines probabilistic outputs from IMS, Raman spectroscopy, gamma detectors, and qPCR into a single confidence-weighted threat verdict in under one second. CBRN-CADS implements this architecture to reduce false-positive rates below 2% while maintaining detection sensitivity across chemical, biological, radiological, and nuclear threat classes simultaneously.</quickAnswer><category>cbrn-ai</category><category>Tokyo Subway Attack</category><category>Salisbury Novichok</category><category>CBRN-CADS</category><category>Bayesian Fusion</category><category>Multi-Sensor Detection</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>KAS Part 21/23 Certification: BLIS-D Enters Civil Aviation</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-27-en-kas-part-2123-certification-blis-d-enters-civil-aviation/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-27-en-kas-part-2123-certification-blis-d-enters-civil-aviation/</guid><description>How Korean Airworthiness Standards Part 21 and Part 23 create a regulatory pathway for BLIS-D dry decontamination systems on civil aircraft platforms.</description><pubDate>Wed, 27 May 2026 00:00:00 GMT</pubDate><quickAnswer>KAS Part 21 and Part 23 provide the type-certification and airworthiness approval framework that allows BLIS-D&apos;s bleed-air decontamination technology to transition from military to civil aviation platforms, opening a dual-use market validated by MOLIT oversight and NATO STANAG-compatible design standards.</quickAnswer><category>cbrn-ai</category><category>KAS Part 21</category><category>Tokyo Subway Sarin Attack</category><category>BLIS-D</category><category>CBRN-CADS</category><category>Type Certification</category><category>Dual-Use Aviation</category><author>박무진</author></item><item><title>Park Chung-hee&apos;s 30-Minute OODA and the Birth of Korean CBRN Doctrine</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-27-en-park-chung-hees-30-minute-ooda-and-the-birth-of-korean-cbrn/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-27-en-park-chung-hees-30-minute-ooda-and-the-birth-of-korean-cbrn/</guid><description>How the January 21, 1968 Blue House Raid forced Park Chung-hee to create layered homeland defense—the spiritual ancestor of Korea&apos;s modern CBRN framework.</description><pubDate>Wed, 27 May 2026 00:00:00 GMT</pubDate><quickAnswer>Park Chung-hee&apos;s response to the 1968 Blue House Raid established Korea&apos;s first layered homeland defense doctrine, pioneering the rapid decision logic and civilian-military integration that underpins modern Korean CBRN frameworks—including AI-augmented platforms like TIP-12 and CBRN-CADS today.</quickAnswer><category>cbrn-ai</category><category>Park Chung-hee</category><category>January 21 Incident</category><category>TIP-12</category><category>CBRN-CADS</category><category>OODA Loop</category><category>Homeland Defense Doctrine</category><author>박무진</author></item><item><title>Drones vs. Scouts: Rethinking CBRN Hot-Zone Recon in 2026</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-26-en-drones-vs-scouts-rethinking-cbrn-hot-zone-recon-in-2026/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-26-en-drones-vs-scouts-rethinking-cbrn-hot-zone-recon-in-2026/</guid><description>UAV-mounted sensor arrays are replacing human scouts in CBRN hot zones. Here&apos;s why stand-off detection with AI-driven platforms changes the recon calculus entirely.</description><pubDate>Tue, 26 May 2026 00:00:00 GMT</pubDate><quickAnswer>Drone-based stand-off CBRN detection reduces operator exposure to zero while delivering richer multi-spectral data than a suited reconnaissance team. AI-fused sensor stacks on UAVs can characterize a chemical hot zone in under three minutes — a task that previously required a two-person team exposed for 15-30 minutes at lethal risk.</quickAnswer><category>cbrn-ai</category><category>Halabja 1988</category><category>Tokyo Sarin Attack</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Stand-off Detection</category><category>UAV Reconnaissance</category><author>박무진</author></item><item><title>Halabja 1988: What the Worst CWA Strike Teaches Modern Defense</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-26-en-halabja-1988-what-the-worst-cwa-strike-teaches-modern-defens/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-26-en-halabja-1988-what-the-worst-cwa-strike-teaches-modern-defens/</guid><description>The 1988 Halabja chemical attack killed 5,000 civilians. Here&apos;s what it reveals about detection gaps, deterrence failure, and dual-use CBRN strategy for today&apos;s defense market.</description><pubDate>Tue, 26 May 2026 00:00:00 GMT</pubDate><quickAnswer>Halabja 1988 proved that chemical weapons deployed against civilians produce mass casualties when detection and decontamination systems are absent. Modern dual-use CBRN platforms—combining AI-driven detection with rapid waterless decon—are the direct industrial answer to the capability gaps exposed that day.</quickAnswer><category>cbrn-ai</category><category>Halabja</category><category>Iran-Iraq War</category><category>BLIS-D</category><category>CBRN-CADS</category><category>Civil CBRN Deterrence</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>Aum Shinrikyo&apos;s Command Fracture: What TIP-12 Reveals</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-25-en-aum-shinrikyos-command-fracture-what-tip-12-reveals/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-25-en-aum-shinrikyos-command-fracture-what-tip-12-reveals/</guid><description>Reverse-engineering the Aum Shinrikyo cult command structure through UAM KoreaTech&apos;s TIP-12 Visionary-Aggressor-Operator typology and the PPF decision-intelligence framework.</description><pubDate>Mon, 25 May 2026 00:00:00 GMT</pubDate><quickAnswer>Aum Shinrikyo&apos;s 1995 Tokyo sarin attack succeeded because three distinct command archetypes — Visionary, Aggressor, and Operator — reinforced each other without institutional friction. TIP-12 persona profiling can detect such compound threat structures before operational execution.</quickAnswer><category>cbrn-ai</category><category>Aum Shinrikyo</category><category>Shoko Asahara</category><category>TIP-12</category><category>CBRN-CADS</category><category>Persona Profiling Framework</category><category>Threat Decision Intelligence</category><author>박무진</author></item><item><title>STANAG 2103 Compliance: Korea&apos;s CBRN Certification Roadmap</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-25-en-stanag-2103-compliance-koreas-cbrn-certification-roadmap/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-25-en-stanag-2103-compliance-koreas-cbrn-certification-roadmap/</guid><description>How Korean dual-use CBRN firms can navigate NATO STANAG 2103 and AAP-21 certification to achieve full alliance interoperability by 2027.</description><pubDate>Mon, 25 May 2026 00:00:00 GMT</pubDate><quickAnswer>NATO STANAG 2103 sets the decontamination interoperability standard all alliance partners must meet. Korean CBRN firms like UAM KoreaTech can achieve compliance by aligning BLIS-D&apos;s bleed-air dry-decon cycle with AAP-21 test protocols and Anduril Lattice data-exchange schemas, unlocking procurement access across 32 NATO member states.</quickAnswer><category>cbrn-ai</category><category>STANAG 2103</category><category>AAP-21</category><category>BLIS-D</category><category>CBRN-CADS</category><category>NATO Interoperability</category><category>K-Defense Certification</category><author>박무진</author></item><item><title>IMS vs Raman: Which Sensor Wins in CWA Field Detection?</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-24-en-ims-vs-raman-which-sensor-wins-in-cwa-field-detection/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-24-en-ims-vs-raman-which-sensor-wins-in-cwa-field-detection/</guid><description>A rigorous comparative analysis of IMS and Raman spectroscopy for chemical warfare agent detection, and how CBRN-CADS fuses both into one field-deployable platform.</description><pubDate>Sun, 24 May 2026 00:00:00 GMT</pubDate><quickAnswer>Neither IMS nor Raman alone is sufficient for reliable CWA field detection: IMS delivers sub-second sensitivity but suffers false positives, while Raman offers molecular specificity but fails on dark or dilute samples. UAM KoreaTech&apos;s CBRN-CADS fuses both sensors under AI classification to close this gap.</quickAnswer><category>cbrn-ai</category><category>IMS</category><category>Raman Spectroscopy</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Chemical Warfare Agents</category><category>Sensor Fusion</category><author>박무진</author></item><item><title>Tokyo 1995: What Sarin in the Subway Still Teaches Us</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-24-en-tokyo-1995-what-sarin-in-the-subway-still-teaches-us/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-24-en-tokyo-1995-what-sarin-in-the-subway-still-teaches-us/</guid><description>The 1995 Tokyo subway Sarin attack exposed catastrophic urban CBRN response gaps. Here is what K-defense innovators must learn 30 years later.</description><pubDate>Sun, 24 May 2026 00:00:00 GMT</pubDate><quickAnswer>The 1995 Tokyo subway Sarin attack revealed that urban first-responders lacked chemical agent detection, decontamination speed, and command clarity. Thirty years on, these same gaps persist globally — and AI-driven detection plus waterless decon platforms now exist to close them.</quickAnswer><category>cbrn-ai</category><category>Aum Shinrikyo</category><category>Tokyo Sarin Attack</category><category>BLIS-D</category><category>CBRN-CADS</category><category>Urban CBRN Response</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>Bleed-Air Engineering: From Aircraft ECS to CBRN Decon</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-23-en-bleed-air-engineering-from-aircraft-ecs-to-cbrn-decon/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-23-en-bleed-air-engineering-from-aircraft-ecs-to-cbrn-decon/</guid><description>How aircraft environmental control system bleed-air principles enable waterless 90-second chemical agent decontamination — and why NATO procurement should care.</description><pubDate>Sat, 23 May 2026 00:00:00 GMT</pubDate><quickAnswer>Aircraft bleed-air systems deliver high-pressure, high-temperature gas that can be re-engineered to denature chemical agents in under 90 seconds without water. UAM KoreaTech&apos;s BLIS-D exploits this thermodynamic principle to deliver NATO STANAG-compliant decontamination in austere, water-scarce environments.</quickAnswer><category>cbrn-ai</category><category>Lockheed SR-71 Bleed Air</category><category>Ypres 1915</category><category>BLIS-D</category><category>CBRN-CADS</category><category>NATO STANAG Compliance</category><category>Dual-Use Aerospace Engineering</category><author>박무진</author></item><item><title>Sun Tzu to Hannibal: TIP-12 Archetypes in CBRN Command</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-23-en-sun-tzu-to-hannibal-tip-12-archetypes-in-cbrn-command/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-23-en-sun-tzu-to-hannibal-tip-12-archetypes-in-cbrn-command/</guid><description>How UAM KoreaTech&apos;s TIP-12 framework maps 16 commander archetypes—from Sun Tzu to Hannibal—to CBRN crisis decision roles for faster, sharper responses.</description><pubDate>Sat, 23 May 2026 00:00:00 GMT</pubDate><quickAnswer>TIP-12&apos;s 16 commander archetypes translate historical decision-making patterns—Sun Tzu&apos;s deception logic, Hannibal&apos;s envelopment thinking, Yi Sun-sin&apos;s adaptive improvisation—into structured CBRN role assignments. Matching the right archetype to the right crisis function reduces decision latency and command misalignment under chemical or biological threat conditions.</quickAnswer><category>cbrn-ai</category><category>Sun Tzu</category><category>Hannibal</category><category>TIP-12</category><category>CBRN-CADS</category><category>Commander Archetypes</category><category>Decision Intelligence</category><author>박무진</author></item><item><title>Bayesian Fusion: How Multi-Sensor CBRN Networks Reach Consensus</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-22-en-bayesian-fusion-how-multi-sensor-cbrn-networks-reach-consens/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-22-en-bayesian-fusion-how-multi-sensor-cbrn-networks-reach-consens/</guid><description>How IMS, Raman, gamma spectroscopy, and qPCR combine under Bayesian fusion to deliver sub-second CBRN threat consensus in field-deployed networks.</description><pubDate>Fri, 22 May 2026 00:00:00 GMT</pubDate><quickAnswer>Bayesian threat fusion aggregates probabilistic outputs from IMS, Raman, gamma spectroscopy, and qPCR sensors into a single confidence-weighted verdict, reducing false-positive rates below 2% while achieving sub-second classification for chemical and radiological threats. UAM KoreaTech&apos;s CBRN-CADS platform operationalizes this architecture for tactical field deployment.</quickAnswer><category>cbrn-ai</category><category>Matsumoto Sarin Attack</category><category>Salisbury Novichok</category><category>CBRN-CADS</category><category>Bayesian Fusion</category><category>Multi-Modal Sensing</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>TMI-1979: What Radiological Chaos Taught Modern CBRN Defense</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-22-en-tmi-1979-what-radiological-chaos-taught-modern-cbrn-defense/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-22-en-tmi-1979-what-radiological-chaos-taught-modern-cbrn-defense/</guid><description>The 1979 Three Mile Island meltdown exposed fatal gaps in radiological detection, decon, and public trust. Here&apos;s what K-defense must learn 45 years later.</description><pubDate>Fri, 22 May 2026 00:00:00 GMT</pubDate><quickAnswer>Three Mile Island&apos;s INES Level 5 partial meltdown revealed that radiological emergencies are lost not by physics alone but by detection latency, decontamination failure, and public-trust collapse — three vulnerabilities that modern multi-sensor CBRN platforms and waterless decon systems are uniquely positioned to close.</quickAnswer><category>cbrn-ai</category><category>Three Mile Island</category><category>INES Level 5</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Radiological Emergency Response</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>KAS Part 21/23 Certification: Clearing BLIS-D for Civil Aviation</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-21-en-kas-part-2123-certification-clearing-blis-d-for-civil-aviati/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-21-en-kas-part-2123-certification-clearing-blis-d-for-civil-aviati/</guid><description>How Korean Airworthiness Standards Part 21 and Part 23 create a dual-use certification pathway for BLIS-D dry decontamination on civil aircraft platforms.</description><pubDate>Thu, 21 May 2026 00:00:00 GMT</pubDate><quickAnswer>KAS Part 21 and Part 23, administered by MOLIT, provide a type-certification pathway that enables BLIS-D&apos;s bleed-air dry decontamination system to be integrated into civil aircraft, bridging military-grade CBRN protection and FAA/EASA-equivalent airworthiness compliance for dual-use operators.</quickAnswer><category>cbrn-ai</category><category>KAS Part 21</category><category>KAS Part 23</category><category>BLIS-D</category><category>CBRN Decontamination</category><category>Dual-Use Airworthiness</category><category>NATO STANAG</category><author>박무진</author></item><item><title>PIQ: Measuring AI-Collaboration Skill in CBRN Teams</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-21-en-piq-measuring-ai-collaboration-skill-in-cbrn-teams/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-21-en-piq-measuring-ai-collaboration-skill-in-cbrn-teams/</guid><description>PIQ (Prompt Intelligence Quotient) is a 5-minute self-diagnostic that quantifies how well CBRN operators leverage AI tools under time-critical threat conditions.</description><pubDate>Thu, 21 May 2026 00:00:00 GMT</pubDate><quickAnswer>PIQ (Prompt Intelligence Quotient) measures a CBRN operator&apos;s ability to extract decision-grade intelligence from AI systems under stress. Teams scoring below 60 on the PIQ diagnostic statistically miss critical agent-identification windows. Improving PIQ by one tier reduces AI-assisted decision latency by an estimated 40%.</quickAnswer><category>cbrn-ai</category><category>PIQ</category><category>Stanford Symbolic Systems</category><category>Prompt Engineering</category><category>CBRN-CADS</category><category>Tactical Prompt</category><category>Decision Intelligence</category><author>박무진</author></item><item><title>Drones Over Hot Zones: The Case for UAV-Mounted CBRN Detection</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-20-en-drones-over-hot-zones-the-case-for-uav-mounted-cbrn-detectio/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-20-en-drones-over-hot-zones-the-case-for-uav-mounted-cbrn-detectio/</guid><description>UAV-mounted CBRN sensor arrays are replacing human recon teams in chemical hot zones. Here&apos;s why stand-off detection changes the survivability calculus.</description><pubDate>Wed, 20 May 2026 00:00:00 GMT</pubDate><quickAnswer>UAV-mounted stand-off CBRN detection eliminates the need to send human reconnaissance teams into chemically contaminated hot zones, cutting exposure risk to near zero while delivering faster, more accurate agent classification. Platforms like CBRN-CADS, when drone-integrated, combine IMS, Raman, and AI classification to characterize threats in under 90 seconds.</quickAnswer><category>cbrn-ai</category><category>Halabja Chemical Attack</category><category>Tokyo Subway Sarin</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Stand-off Detection</category><category>Dual-Use UAV</category><author>박무진</author></item><item><title>John Major&apos;s Gulf War Gamble: CBRN Continuity at 74 PIQ</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-19-en-john-majors-gulf-war-gamble-cbrn-continuity-at-74-piq/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-19-en-john-majors-gulf-war-gamble-cbrn-continuity-at-74-piq/</guid><description>How John Major&apos;s Thatcher succession shaped UK CBRN Gulf War policy — and what his TP-IQ 74 Continuity Executor profile reveals for modern AI-augmented CBRN command.</description><pubDate>Tue, 19 May 2026 00:00:00 GMT</pubDate><quickAnswer>John Major&apos;s 1991 Gulf War CBRN posture exemplifies a Continuity Executor archetype (TIP-12 TP-IQ 74): high institutional loyalty, low doctrinal innovation, and critical blind spots on Iraqi chemical agent dispersal timelines — gaps that AI-driven detection platforms like CBRN-CADS and waterless decon systems like BLIS-D are engineered to close today.</quickAnswer><category>cbrn-ai</category><category>John Major</category><category>Gulf War 1991</category><category>CBRN-CADS</category><category>TIP-12</category><category>CBRN Decision Intelligence</category><category>Iraqi WMD</category><author>박무진</author></item><item><title>STANAG 2103 Compliance: K-Defense CBRN Certification Roadmap</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-19-en-stanag-2103-compliance-k-defense-cbrn-certification-roadmap/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-19-en-stanag-2103-compliance-k-defense-cbrn-certification-roadmap/</guid><description>How Korean CBRN defense firms can navigate NATO STANAG 2103 and AAP-21 certification to achieve full alliance interoperability by 2027.</description><pubDate>Tue, 19 May 2026 00:00:00 GMT</pubDate><quickAnswer>NATO STANAG 2103 sets marking and reporting standards for CBRN-contaminated areas; Korean defense firms must align product documentation, test protocols, and data formats to AAP-21 to achieve NATO interoperability. BLIS-D&apos;s bleed-air decontamination architecture is structurally compatible with STANAG 2103 field procedures but requires formal validation through a NATO-recognized test authority.</quickAnswer><category>cbrn-ai</category><category>STANAG 2103</category><category>AAP-21</category><category>BLIS-D</category><category>CBRN-CADS</category><category>NATO Interoperability</category><category>K-Defense Certification</category><author>박무진</author></item><item><title>K-UAM v1.2 Content Reader 출시 — 인천공항 UAM 버티포트 2027-2028 카운트다운 동기화</title><link>https://uamkt-com.vercel.app/articles/uam-korea/2026-05-19-kuam-v12-launch-incheon-vertiport-countdown/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/uam-korea/2026-05-19-kuam-v12-launch-incheon-vertiport-countdown/</guid><description>UAM Korea Tech 가 K-UAM iOS 앱 v1.2 Content Reader 를 정식 출시했다. uamkt.com 콘텐츠를 native UI 로 표시하며, 인천국제공항 UAM 버티포트 2027-2028 준공 일정과 sync 된다. Hyundai Supernal S-A2 스타일 v4-D Touchdown Moment 아이콘 + FAA EB 105A 2025 호환 H+VTL 패드 마킹.</description><pubDate>Tue, 19 May 2026 00:00:00 GMT</pubDate><quickAnswer>UAM Korea Tech 의 K-UAM iOS 앱 v1.2 가 2026-05-19 정식 출시됐다. Content Reader 컨셉으로 uamkt.com 콘텐츠를 native UI 로 실시간 표시하며, 인천국제공항 UAM 버티포트 2027-2028 준공 일정과 운영적으로 sync 된다. Hyundai Supernal S-A2 스타일 v4-D Touchdown Moment 아이콘 적용. FAA EB 105A 2025 호환 H+VTL 패드 마킹.</quickAnswer><category>uam-korea</category><category>K-UAM</category><category>인천공항UAM버티포트</category><category>iOS앱</category><category>Content Reader</category><category>Hyundai Supernal</category><category>v4-D Touchdown</category><category>FAA EB 105A</category><category>K-UAM Grand Challenge</category><author>박무진</author></item><item><title>한국 2026의 14분 — V-Series로 본 NK_Hazmat_Seoul 시나리오의 78점 진입 로드맵</title><link>https://uamkt-com.vercel.app/articles/case-studies/2026-05-18-korea-2026-nk-hazmat-scenario/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/case-studies/2026-05-18-korea-2026-nk-hazmat-scenario/</guid><description>북한 도시 CBRN 가상 시나리오 NK_Hazmat_Seoul — 현재 한국 정부 TP-IQ 64점 RISING ADAPTIVE → V-Series Defense doctrine + CBRN-CADS 채택 시 78점 ADAPTIVE COMMANDER 진입. 인천국제공항 UAM 버티포트 2027-2028 통합 운영 모델.</description><pubDate>Mon, 18 May 2026 00:00:00 GMT</pubDate><quickAnswer>북한 도시 CBRN 시뮬레이션 NK_Hazmat_Seoul 가정 시나리오. 현재 한국 정부 TP-IQ는 64점 RISING ADAPTIVE — V-Series Defense doctrine + CBRN-CADS 채택 시 78점 ADAPTIVE COMMANDER 진입 가능. 이는 May 정부 81점(Salisbury 2018) 수준의 의사결정 인프라를 사전 확보한다는 의미. 인천국제공항 UAM 버티포트(2027-2028 준공)와 통합 운영 가능. 본 시나리오는 가상이며 정책 시뮬레이션 목적.</quickAnswer><category>case-studies</category><category>NK_Hazmat_Seoul</category><category>V-Series</category><category>한국CBRN2026</category><category>인천공항UAM버티포트</category><category>CBRN-CADS</category><category>BLIS-D</category><category>statesmen-series</category><author>박무진</author></item><item><title>박정희의 30분 — TP-IQ로 본 1·21 사태와 한국 CBRN doctrine 시초</title><link>https://uamkt-com.vercel.app/articles/case-studies/2026-05-18-park-chunghee-121-incident/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/case-studies/2026-05-18-park-chunghee-121-incident/</guid><description>1968-01-21 청와대 500m 침투 사건, 박정희 정부의 30분 OODA 1차 사이클은 한국 CBRN doctrine의 시초를 만들었다. TP-IQ 9축 채점 69점 DEFENSIVE FOUNDER. V-Series Defense doctrine 1968 가상 도입 시 80점 ADAPTIVE COMMANDER로 진입.</description><pubDate>Mon, 18 May 2026 00:00:00 GMT</pubDate><quickAnswer>1968-01-21 청와대 500m 지점에서 멈춰선 북한 124군 부대 31명. 박정희 정부의 30분 OODA 1차 사이클은 한국 CBRN doctrine의 시초를 만들었다. TP-IQ 9축 채점 69점 DEFENSIVE FOUNDER. V-Series Defense doctrine이 1968년에 존재했다면 점수는 80점 ADAPTIVE COMMANDER로 진입 — 한국이 May 정부 81점 수준의 의사결정 인프라를 30년 일찍 확보했을 시나리오.</quickAnswer><category>case-studies</category><category>박정희</category><category>1·21사태</category><category>김신조</category><category>한국CBRN</category><category>V-Series</category><category>TP-IQ</category><category>statesmen-series</category><author>박무진</author></item><item><title>Halabja 1988: Civil-Targeting CWA and the Deterrence Deficit</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-18-en-halabja-1988-civil-targeting-cwa-and-the-deterrence-deficit/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-18-en-halabja-1988-civil-targeting-cwa-and-the-deterrence-deficit/</guid><description>The 1988 Halabja chemical massacre exposed a fatal gap in civilian CBRN deterrence. Here is what K-defense must learn 37 years later.</description><pubDate>Mon, 18 May 2026 00:00:00 GMT</pubDate><quickAnswer>Halabja proved that civilian populations are primary CWA targets, not collateral ones. Modern deterrence requires layered detection and rapid decontamination at the civil level — exactly the capability gap BLIS-D and CBRN-CADS are designed to close.</quickAnswer><category>cbrn-ai</category><category>Halabja</category><category>Iran-Iraq War</category><category>BLIS-D</category><category>CBRN-CADS</category><category>Civil CBRN Deterrence</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>IMS vs Raman: Which Sensor Wins CWA Field Detection?</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-18-en-ims-vs-raman-which-sensor-wins-cwa-field-detection/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-18-en-ims-vs-raman-which-sensor-wins-cwa-field-detection/</guid><description>A rigorous technical comparison of IMS and Raman spectroscopy for chemical warfare agent detection, and how CBRN-CADS fuses both to close critical field gaps.</description><pubDate>Mon, 18 May 2026 00:00:00 GMT</pubDate><quickAnswer>Neither IMS nor Raman alone is sufficient for reliable CWA field detection: IMS offers sub-second sensitivity but suffers false positives, while Raman provides molecular specificity but struggles with opaque containers and fluorescence interference. UAM KoreaTech&apos;s CBRN-CADS fuses both sensors with AI classification to achieve identification confidence exceeding either technology independently.</quickAnswer><category>cbrn-ai</category><category>Matsumoto Sarin Attack</category><category>M-22 JCAD</category><category>CBRN-CADS</category><category>IMS</category><category>Sensor Fusion</category><category>Chemical Warfare Agent Detection</category><author>박무진</author></item><item><title>Aum Shinrikyo&apos;s Command Mind: TIP-12 Decodes Cult CBRN Logic</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-17-en-aum-shinrikyos-command-mind-tip-12-decodes-cult-cbrn-logic/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-17-en-aum-shinrikyos-command-mind-tip-12-decodes-cult-cbrn-logic/</guid><description>How UAM KoreaTech&apos;s TIP-12 Persona Framework reverse-engineers the Visionary-Aggressor-Operator command triad behind the 1995 Tokyo sarin attack.</description><pubDate>Sun, 17 May 2026 00:00:00 GMT</pubDate><quickAnswer>Aum Shinrikyo&apos;s CBRN capability was enabled by a three-tier command structure matching TIP-12&apos;s Visionary-Aggressor-Operator typology. Profiling adversary decision architecture — not just weapons inventories — is now the critical gap in CBRN threat intelligence.</quickAnswer><category>cbrn-ai</category><category>Aum Shinrikyo</category><category>Tokyo Sarin Attack</category><category>TIP-12</category><category>Tactical Prompt</category><category>Persona Profiling</category><category>CBRN Decision Intelligence</category><author>박무진</author></item><item><title>Bayesian Threat Fusion: How AI Unifies CBRN Sensors in &lt;1 s</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-16-en-bayesian-threat-fusion-how-ai-unifies-cbrn-sensors-in-1-s/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-16-en-bayesian-threat-fusion-how-ai-unifies-cbrn-sensors-in-1-s/</guid><description>How combining IMS, Raman spectroscopy, gamma detection, and qPCR under a Bayesian fusion engine delivers sub-second CBRN threat consensus in the field.</description><pubDate>Sat, 16 May 2026 00:00:00 GMT</pubDate><quickAnswer>Bayesian threat fusion integrates IMS, Raman spectroscopy, gamma spectroscopy, and qPCR into a single probabilistic consensus, cutting false-positive rates and delivering actionable CBRN threat classification in under one second. UAM KoreaTech&apos;s CBRN-CADS platform operationalizes this architecture for forward-deployed units.</quickAnswer><category>cbrn-ai</category><category>Salisbury Novichok</category><category>Tokyo Sarin</category><category>CBRN-CADS</category><category>Bayesian Fusion</category><category>Multi-Modal Sensor</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>Tokyo 1995: What Sarin on the Subway Taught the World</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-16-en-tokyo-1995-what-sarin-on-the-subway-taught-the-world/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-16-en-tokyo-1995-what-sarin-on-the-subway-taught-the-world/</guid><description>Aum Shinrikyo&apos;s 1995 sarin attack on Tokyo&apos;s subway exposed fatal gaps in urban CBRN response. Here&apos;s what K-defense must learn 30 years later.</description><pubDate>Sat, 16 May 2026 00:00:00 GMT</pubDate><quickAnswer>The 1995 Tokyo subway sarin attack revealed that urban CBRN response fails without rapid detection, waterless decontamination, and integrated command protocols. These three gaps remain only partially closed in 2026, and Korean dual-use technology—particularly AI-driven detection and bleed-air decon systems—offers the most operationally credible path to closing them.</quickAnswer><category>cbrn-ai</category><category>Aum Shinrikyo</category><category>Tokyo Subway Sarin</category><category>BLIS-D</category><category>CBRN-CADS</category><category>Urban CBRN Response</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>BLIS-D Airworthiness: KAS Part 21/23 and Civil Aviation Decon</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-15-en-blis-d-airworthiness-kas-part-2123-and-civil-aviation-decon/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-15-en-blis-d-airworthiness-kas-part-2123-and-civil-aviation-decon/</guid><description>How UAM KoreaTech&apos;s BLIS-D dry decontamination system navigates KAS Part 21 and Part 23 type certification for civil aviation deployment under MOLIT oversight.</description><pubDate>Fri, 15 May 2026 00:00:00 GMT</pubDate><quickAnswer>BLIS-D&apos;s bleed-air decontamination architecture is structurally compatible with KAS Part 21/23 type certification because it parasitically taps existing aircraft pneumatic systems without structural modification. MOLIT certification pathways open civil aviation markets — airports, medevac fleets, and commercial carriers — to military-grade CBRN decon capability for the first time.</quickAnswer><category>cbrn-ai</category><category>Aum Shinrikyo</category><category>Tokyo Subway Attack</category><category>BLIS-D</category><category>CBRN-CADS</category><category>KAS Certification</category><category>Dual-Use Aviation</category><author>박무진</author></item><item><title>Sun Tzu to Hannibal: Mapping 16 Commander Archetypes to CBRN Crisis Roles</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-15-en-sun-tzu-to-hannibal-mapping-16-commander-archetypes-to-cbrn/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-15-en-sun-tzu-to-hannibal-mapping-16-commander-archetypes-to-cbrn/</guid><description>How UAM KoreaTech&apos;s TIP-12 framework maps 16 historical commander archetypes to modern CBRN crisis decision roles, from detection to decontamination command.</description><pubDate>Fri, 15 May 2026 00:00:00 GMT</pubDate><quickAnswer>AI-augmented CBRN decision-making fails not from lack of sensors but from mismatched human decision styles. UAM KoreaTech&apos;s TIP-12 framework maps 16 commander archetypes—from Sun Tzu&apos;s systems thinker to Hannibal&apos;s encirclement strategist—to specific CBRN crisis roles, enabling commanders to deploy the right cognitive profile at each phase of a chemical or biological incident.</quickAnswer><category>cbrn-ai</category><category>Sun Tzu</category><category>Hannibal</category><category>TIP-12</category><category>CBRN-CADS</category><category>Commander Archetypes</category><category>Decision Intelligence</category><author>박무진</author></item><item><title>Drones Over the Hot Zone: Stand-off CBRN Detection Reframed</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-14-en-drones-over-the-hot-zone-stand-off-cbrn-detection-reframed/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-14-en-drones-over-the-hot-zone-stand-off-cbrn-detection-reframed/</guid><description>UAV-mounted sensor arrays are replacing human recon teams in CBRN hot zones. Here is why stand-off detection changes every calculus in CBRN defense procurement.</description><pubDate>Thu, 14 May 2026 00:00:00 GMT</pubDate><quickAnswer>UAV-mounted multi-sensor arrays can characterize a CBRN hot zone from stand-off distances without exposing personnel to lethal contamination. UAM KoreaTech&apos;s CBRN-CADS platform integrates IMS, Raman, gamma, and AI classification onto drone-deployable form factors, cutting characterization time from hours to minutes while keeping operators outside the hazard perimeter.</quickAnswer><category>cbrn-ai</category><category>Tokyo Subway Attack</category><category>Salisbury Novichok</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Stand-off Detection</category><category>UAV Reconnaissance</category><author>박무진</author></item><item><title>TMI-1979: What Radiological Trust Collapse Teaches K-Defense</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-14-en-tmi-1979-what-radiological-trust-collapse-teaches-k-defense/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-14-en-tmi-1979-what-radiological-trust-collapse-teaches-k-defense/</guid><description>The 1979 Three Mile Island meltdown exposed fatal gaps in radiological detection, public communication, and decontamination doctrine—lessons Korea&apos;s dual-use defense sector must internalize now.</description><pubDate>Thu, 14 May 2026 00:00:00 GMT</pubDate><quickAnswer>TMI-2&apos;s INES Level 5 meltdown revealed that radiological emergencies are lost not by radiation alone but by detection latency and public-trust collapse. Korea&apos;s dual-use CBRN sector must embed real-time multi-sensor detection and transparent AI-driven communication into its next-generation response architecture.</quickAnswer><category>cbrn-ai</category><category>Three Mile Island</category><category>Iodine-131</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Radiological Emergency Response</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>PIQ: Measuring AI-Collaboration Readiness in CBRN Teams</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-13-en-piq-measuring-ai-collaboration-readiness-in-cbrn-teams/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-13-en-piq-measuring-ai-collaboration-readiness-in-cbrn-teams/</guid><description>The Prompt Intelligence Quotient (PIQ) gives CBRN operators a 5-minute self-diagnostic to measure AI-collaboration capability and close the human-machine decision gap.</description><pubDate>Wed, 13 May 2026 00:00:00 GMT</pubDate><quickAnswer>PIQ (Prompt Intelligence Quotient) is a structured self-assessment that measures how effectively CBRN operators collaborate with AI systems under time pressure. Teams scoring below the operational threshold misframe AI queries during crises, degrading detection and triage speed. A 5-minute PIQ diagnostic identifies that gap before it becomes a casualty.</quickAnswer><category>cbrn-ai</category><category>Stanford Symbolic Systems</category><category>Prompt Engineering</category><category>PIQ</category><category>TIP-12</category><category>Decision Intelligence</category><category>CBRN AI Readiness</category><author>박무진</author></item><item><title>STANAG 2103 Compliance: Korea&apos;s CBRN Certification Roadmap</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-13-en-stanag-2103-compliance-koreas-cbrn-certification-roadmap/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-13-en-stanag-2103-compliance-koreas-cbrn-certification-roadmap/</guid><description>How Korean dual-use CBRN firms can navigate NATO STANAG 2103 and AAP-21 certification to achieve full alliance interoperability by 2027.</description><pubDate>Wed, 13 May 2026 00:00:00 GMT</pubDate><quickAnswer>NATO STANAG 2103 defines standardized CBRN decontamination procedures that all alliance members must meet. Korean defense firms like UAM KoreaTech can achieve compliance by mapping BLIS-D&apos;s bleed-air dry decontamination outputs against STANAG 2103 and AAP-21 certification criteria, unlocking direct procurement eligibility across 32 NATO member states.</quickAnswer><category>cbrn-ai</category><category>STANAG 2103</category><category>AAP-21</category><category>BLIS-D</category><category>CBRN-CADS</category><category>NATO Interoperability</category><category>K-Defense Certification</category><author>박무진</author></item><item><title>Amerithrax at 25: The Stand-Off Detection Gap We Never Closed</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-12-en-amerithrax-at-25-the-stand-off-detection-gap-we-never-closed/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-12-en-amerithrax-at-25-the-stand-off-detection-gap-we-never-closed/</guid><description>The 2001 anthrax letter attacks killed 5, paralyzed the USPS, and exposed a critical gap in biological stand-off detection that persists today. Here is what changed—and what hasn&apos;t.</description><pubDate>Tue, 12 May 2026 00:00:00 GMT</pubDate><quickAnswer>The 2001 Amerithrax attacks revealed that no reliable stand-off biological detection capability existed—and that gap remains largely unresolved. AI-fused multi-sensor platforms integrating IMS, Raman spectroscopy, and qPCR now offer the first credible path to sub-minute Bacillus anthracis identification before a letter is opened or a package is handled.</quickAnswer><category>cbrn-ai</category><category>Amerithrax</category><category>Bacillus anthracis</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Stand-Off Bio Detection</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>IMS vs Raman: Which Sensor Wins in CWA Field Detection?</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-12-en-ims-vs-raman-which-sensor-wins-in-cwa-field-detection/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-12-en-ims-vs-raman-which-sensor-wins-in-cwa-field-detection/</guid><description>A rigorous comparison of IMS and Raman spectroscopy for chemical warfare agent detection—physics, false-alarm rates, and how CBRN-CADS fuses both for battlefield-grade accuracy.</description><pubDate>Tue, 12 May 2026 00:00:00 GMT</pubDate><quickAnswer>Neither IMS nor Raman alone is sufficient for reliable CWA field detection: IMS offers sub-second sensitivity but suffers high false-alarm rates in humid or contaminated environments, while Raman provides confirmatory molecular fingerprinting but struggles with fluorescence interference and low-concentration agents. UAM KoreaTech&apos;s CBRN-CADS fuses both sensors under AI classification to deliver confirmed detection in under 60 seconds.</quickAnswer><category>cbrn-ai</category><category>IMS</category><category>Raman Spectroscopy</category><category>CBRN-CADS</category><category>JCAD</category><category>Chemical Warfare Agents</category><category>Sensor Fusion</category><author>박무진</author></item><item><title>Aum Shinrikyo&apos;s Command DNA: TIP-12 Decodes Cult CBRN Threat</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-11-en-aum-shinrikyos-command-dna-tip-12-decodes-cult-cbrn-threat/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-11-en-aum-shinrikyos-command-dna-tip-12-decodes-cult-cbrn-threat/</guid><description>How UAM KoreaTech&apos;s TIP-12 Persona Profiling Framework reverse-engineers Aum Shinrikyo&apos;s Visionary-Aggressor-Operator command structure to sharpen modern CBRN threat anticipation.</description><pubDate>Mon, 11 May 2026 00:00:00 GMT</pubDate><quickAnswer>Aum Shinrikyo&apos;s 1995 sarin attack succeeded partly because analysts lacked a structured commander-typology framework. TIP-12&apos;s Visionary-Aggressor-Operator model, applied retroactively, reveals predictable decision nodes that modern AI-augmented CBRN intelligence can exploit before an attack executes.</quickAnswer><category>cbrn-ai</category><category>Aum Shinrikyo</category><category>Shoko Asahara</category><category>TIP-12</category><category>CBRN-CADS</category><category>Persona Profiling Framework</category><category>AI Decision Intelligence</category><author>박무진</author></item><item><title>Bleed-Air Engineering: From Aircraft ECS to CBRN Decon</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-11-en-bleed-air-engineering-from-aircraft-ecs-to-cbrn-decon/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-11-en-bleed-air-engineering-from-aircraft-ecs-to-cbrn-decon/</guid><description>How aircraft environmental control system bleed-air principles transfer to chemical agent neutralization — and why BLIS-D represents the next leap in dry decon.</description><pubDate>Mon, 11 May 2026 00:00:00 GMT</pubDate><quickAnswer>Aircraft bleed-air systems compress and condition high-enthalpy air for cabin environments; BLIS-D repurposes these same thermodynamic principles—pressure ratio, heat exchange, and controlled flow—to neutralize chemical and biological agents on personnel and equipment in under 90 seconds without water.</quickAnswer><category>cbrn-ai</category><category>Bleed Air</category><category>Environmental Control System</category><category>BLIS-D</category><category>CBRN-CADS</category><category>NATO STANAG</category><category>Dry Decontamination</category><author>박무진</author></item><item><title>Bayesian Fusion: How Multi-Sensor CBRN Networks Reach Sub-Second Consensus</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-10-en-bayesian-fusion-how-multi-sensor-cbrn-networks-reach-sub-sec/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-10-en-bayesian-fusion-how-multi-sensor-cbrn-networks-reach-sub-sec/</guid><description>How IMS, Raman, gamma spectroscopy, and qPCR sensors fused via Bayesian inference eliminate false positives in real CBRN threat detection.</description><pubDate>Sun, 10 May 2026 00:00:00 GMT</pubDate><quickAnswer>Bayesian threat fusion combines IMS, Raman spectroscopy, gamma detection, and qPCR into a single probabilistic consensus that reduces CBRN false-positive rates below 0.3% while cutting time-to-decision under 90 seconds. UAM KoreaTech&apos;s CBRN-CADS implements this architecture in a field-deployable unit.</quickAnswer><category>cbrn-ai</category><category>Tokyo Sarin Attack</category><category>Salisbury Novichok</category><category>CBRN-CADS</category><category>Bayesian Fusion</category><category>Multi-Modal Detection</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>Halabja 1988: When Civilians Became the Target of Chemical War</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-10-en-halabja-1988-when-civilians-became-the-target-of-chemical-wa/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-10-en-halabja-1988-when-civilians-became-the-target-of-chemical-wa/</guid><description>The 1988 Halabja chemical attack killed 5,000+ civilians. What it reveals about civil-targeting CBRN deterrence and Korea&apos;s dual-use defense imperative.</description><pubDate>Sun, 10 May 2026 00:00:00 GMT</pubDate><quickAnswer>Halabja proved that chemical weapons are most lethally deployed against unprotected civilians, not soldiers. Effective CBRN deterrence therefore demands civil-facing detection and decontamination capabilities — precisely the gap UAM KoreaTech&apos;s BLIS-D and CBRN-CADS are engineered to close.</quickAnswer><category>cbrn-ai</category><category>Halabja</category><category>Iran-Iraq War</category><category>BLIS-D</category><category>CBRN-CADS</category><category>Civil CBRN Deterrence</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>KAS Part 21/23 Certification: BLIS-D Enters Civil Aviation</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-09-en-kas-part-2123-certification-blis-d-enters-civil-aviation/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-09-en-kas-part-2123-certification-blis-d-enters-civil-aviation/</guid><description>How Korean Airworthiness Standards Part 21 and Part 23 unlock BLIS-D dry decontamination for civil aircraft, airports, and dual-use NATO deployment.</description><pubDate>Sat, 09 May 2026 00:00:00 GMT</pubDate><quickAnswer>KAS Part 21 and Part 23 type-certification pathways, administered by MOLIT&apos;s KDCA, are the regulatory gateway for deploying BLIS-D dry decontamination technology on civil Korean aircraft. Achieving these approvals validates bleed-air decon hardware for both domestic civil aviation and NATO-aligned dual-use operations.</quickAnswer><category>cbrn-ai</category><category>Tokyo Subway Sarin Attack</category><category>Bhopal Gas Tragedy</category><category>BLIS-D</category><category>CBRN-CADS</category><category>KAS Type Certification</category><category>NATO STANAG 4101</category><author>박무진</author></item><item><title>Sun Tzu to Hannibal: TIP-12 Archetypes in CBRN Command</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-09-en-sun-tzu-to-hannibal-tip-12-archetypes-in-cbrn-command/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-09-en-sun-tzu-to-hannibal-tip-12-archetypes-in-cbrn-command/</guid><description>How UAM KoreaTech&apos;s TIP-12 framework maps 16 commander archetypes—from Sun Tzu to Hannibal—to CBRN crisis decision roles, enabling AI-augmented command.</description><pubDate>Sat, 09 May 2026 00:00:00 GMT</pubDate><quickAnswer>TIP-12&apos;s 16 commander archetypes translate historical command styles—Sun Tzu&apos;s indirection, Hannibal&apos;s encirclement, Yi Sun-sin&apos;s asymmetric resilience—into structured CBRN decision profiles, allowing AI systems to flag cognitive blind spots and optimize crisis role assignment before the first agent is detected.</quickAnswer><category>cbrn-ai</category><category>Sun Tzu</category><category>Hannibal Barca</category><category>TIP-12</category><category>CBRN-CADS</category><category>Decision Intelligence</category><category>Commander Archetypes</category><author>박무진</author></item><item><title>Drone-Based Stand-off CBRN Detection: UAVs vs. Human Recon</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-08-en-drone-based-stand-off-cbrn-detection-uavs-vs-human-recon/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-08-en-drone-based-stand-off-cbrn-detection-uavs-vs-human-recon/</guid><description>UAV-mounted sensor arrays are redefining hot-zone characterization. Discover how stand-off CBRN detection outperforms human recon teams in speed, accuracy, and survivability.</description><pubDate>Fri, 08 May 2026 00:00:00 GMT</pubDate><quickAnswer>UAV-mounted stand-off CBRN sensor arrays can characterize a chemical or biological hot zone in minutes without exposing personnel, reducing casualty risk by an order of magnitude compared to human reconnaissance teams. UAM KoreaTech&apos;s CBRN-CADS platform integrates IMS, Raman, gamma, and qPCR sensors into a deployable multi-rotor payload that provides AI-classified threat data in near-real-time.</quickAnswer><category>cbrn-ai</category><category>Halabja Chemical Attack</category><category>Tokyo Subway Sarin</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Stand-off Detection</category><category>UAV Reconnaissance</category><author>박무진</author></item><item><title>Tokyo 1995: What Sarin on the Subway Still Teaches Us</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-08-en-tokyo-1995-what-sarin-on-the-subway-still-teaches-us/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-08-en-tokyo-1995-what-sarin-on-the-subway-still-teaches-us/</guid><description>Aum Shinrikyo&apos;s Tokyo subway sarin attack exposed fatal gaps in urban CBRN response. Here is what K-defense must learn 30 years later.</description><pubDate>Fri, 08 May 2026 00:00:00 GMT</pubDate><quickAnswer>The 1995 Tokyo subway sarin attack killed 13 and injured 5,500 because responders lacked rapid agent identification and waterless decontamination. Thirty years on, those exact capability gaps—sub-90-second detection and non-water-dependent decon—remain unsolved in most urban transit systems, including Seoul&apos;s.</quickAnswer><category>cbrn-ai</category><category>Aum Shinrikyo</category><category>Tokyo Sarin Attack</category><category>BLIS-D</category><category>CBRN-CADS</category><category>Urban CBRN Response</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>NATO STANAG 2103: Korea&apos;s CBRN Certification Roadmap</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-07-en-nato-stanag-2103-koreas-cbrn-certification-roadmap/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-07-en-nato-stanag-2103-koreas-cbrn-certification-roadmap/</guid><description>How Korean dual-use CBRN firms can achieve NATO STANAG 2103 compliance, unlock AAP-21 certification, and integrate with Anduril Lattice for allied interoperability.</description><pubDate>Thu, 07 May 2026 00:00:00 GMT</pubDate><quickAnswer>NATO STANAG 2103 sets the baseline decontamination doctrine for allied forces; Korean CBRN firms that map their products to AAP-21 test protocols and Lattice data standards can access a $6B+ NATO decon market while closing a critical readiness gap that legacy wet-chemistry systems cannot fill in 90 seconds or less.</quickAnswer><category>cbrn-ai</category><category>STANAG 2103</category><category>AAP-21</category><category>BLIS-D</category><category>CBRN-CADS</category><category>NATO Interoperability</category><category>K-Defense Certification</category><author>박무진</author></item><item><title>PIQ: The 5-Minute Test That Reveals Your AI Readiness</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-07-en-piq-the-5-minute-test-that-reveals-your-ai-readiness/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-07-en-piq-the-5-minute-test-that-reveals-your-ai-readiness/</guid><description>PIQ (Prompt Intelligence Quotient) measures how effectively CBRN operators collaborate with AI systems. A 5-minute self-diagnostic for defense teams.</description><pubDate>Thu, 07 May 2026 00:00:00 GMT</pubDate><quickAnswer>PIQ (Prompt Intelligence Quotient) quantifies a CBRN operator&apos;s ability to extract accurate, actionable intelligence from AI systems under stress. Teams scoring below 60/100 on the 5-minute diagnostic demonstrate statistically higher rates of AI misinterpretation during live CBRN response scenarios, representing a critical readiness gap.</quickAnswer><category>cbrn-ai</category><category>PIQ</category><category>Stanford Symbolic Systems</category><category>TIP-12</category><category>CBRN-CADS</category><category>Prompt Engineering</category><category>Decision Intelligence</category><author>박무진</author></item><item><title>IMS vs Raman for CWA Field Detection: What the Data Shows</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-06-en-ims-vs-raman-for-cwa-field-detection-what-the-data-shows/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-06-en-ims-vs-raman-for-cwa-field-detection-what-the-data-shows/</guid><description>A rigorous comparative analysis of IMS and Raman spectroscopy for chemical warfare agent detection in mobile CBRN scenarios, and how sensor fusion closes the gap.</description><pubDate>Wed, 06 May 2026 00:00:00 GMT</pubDate><quickAnswer>Neither IMS nor Raman alone meets the full operational requirement for CWA field detection: IMS delivers sub-ppb sensitivity but generates false positives in complex matrices, while Raman provides molecular confirmation but struggles with dark or dilute samples. Fusing both sensors under AI arbitration—as in CBRN-CADS—is the operationally validated path forward.</quickAnswer><category>cbrn-ai</category><category>Ghouta 2013</category><category>JCAD M-22</category><category>CBRN-CADS</category><category>IMS</category><category>Raman Spectroscopy</category><category>Sensor Fusion</category><author>박무진</author></item><item><title>Three Mile Island&apos;s Real Lesson: Trust Fails Before Reactors Do</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-06-en-three-mile-islands-real-lesson-trust-fails-before-reactors-d/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-06-en-three-mile-islands-real-lesson-trust-fails-before-reactors-d/</guid><description>The 1979 TMI-2 partial meltdown was not primarily a reactor failure—it was a radiological communication collapse. K-defense can learn from both.</description><pubDate>Wed, 06 May 2026 00:00:00 GMT</pubDate><quickAnswer>TMI-2&apos;s INES Level 5 incident demonstrated that radiological emergency response fails first at the information layer, not the containment layer. Modern dual-use CBRN platforms must integrate real-time multi-sensor detection with decision-support AI to prevent the trust collapse that amplified TMI-2&apos;s consequences far beyond the physical release.</quickAnswer><category>cbrn-ai</category><category>Three Mile Island</category><category>Iodine-131</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Radiological Emergency Response</category><category>Public Trust Collapse</category><author>박무진</author></item><item><title>Aum Shinrikyo&apos;s Command Structure Through the TIP-12 Lens</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-05-en-aum-shinrikyos-command-structure-through-the-tip-12-lens/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-05-en-aum-shinrikyos-command-structure-through-the-tip-12-lens/</guid><description>How UAM KoreaTech&apos;s TIP-12 Persona framework reverse-engineers Aum Shinrikyo&apos;s cult command structure to sharpen AI-augmented CBRN threat assessment.</description><pubDate>Tue, 05 May 2026 00:00:00 GMT</pubDate><quickAnswer>Aum Shinrikyo&apos;s attack chain was enabled by a three-layer Visionary-Aggressor-Operator command typology that conventional threat models missed. UAM KoreaTech&apos;s TIP-12 framework reconstructs that decision architecture to help CBRN planners anticipate non-state chemical weapons deployment before the next attack cycle.</quickAnswer><category>cbrn-ai</category><category>Aum Shinrikyo</category><category>Asahara Shoko</category><category>TIP-12</category><category>CBRN-CADS</category><category>Persona Profiling Framework</category><category>AI Decision Intelligence</category><author>박무진</author></item><item><title>Bleed-Air Engineering: From Aircraft ECS to CBRN Decon</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-05-en-bleed-air-engineering-from-aircraft-ecs-to-cbrn-decon/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-05-en-bleed-air-engineering-from-aircraft-ecs-to-cbrn-decon/</guid><description>How aircraft environmental control system bleed-air principles enable waterless 90-second chemical decontamination — and why NATO CBRN forces should care.</description><pubDate>Tue, 05 May 2026 00:00:00 GMT</pubDate><quickAnswer>Aircraft bleed-air systems extract high-pressure, high-temperature air from engine compressor stages to power environmental control systems. UAM KoreaTech&apos;s BLIS-D repurposes these same thermodynamic principles — controlled pressure ratios and heat-exchanger cascades — to neutralize chemical agents in under 90 seconds without water, meeting NATO STANAG decontamination benchmarks.</quickAnswer><category>cbrn-ai</category><category>Bleed Air</category><category>ECS Engineering</category><category>BLIS-D</category><category>CBRN-CADS</category><category>NATO STANAG</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>Amerithrax 2001: Why Stand-Off Bio-Detection Still Fails</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-04-en-amerithrax-2001-why-stand-off-bio-detection-still-fails/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-04-en-amerithrax-2001-why-stand-off-bio-detection-still-fails/</guid><description>The 2001 anthrax letters killed 5 and exposed a critical detection gap. Learn how AI-driven platforms like CBRN-CADS are closing that gap 25 years later.</description><pubDate>Mon, 04 May 2026 00:00:00 GMT</pubDate><quickAnswer>The 2001 Amerithrax attacks revealed that no fielded stand-off system could detect aerosolized Bacillus anthracis before casualties occurred. A generation later, multi-sensor AI platforms integrating IMS, Raman spectroscopy, and qPCR are the first technologies capable of closing that detection-to-decision gap below the 90-second clinical threshold.</quickAnswer><category>cbrn-ai</category><category>Amerithrax</category><category>Bacillus anthracis</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Stand-Off Bio-Detection</category><category>Dual-Use Defense</category><author>박무진</author></item><item><title>Bayesian Threat Fusion: How Multi-Sensor CBRN Networks Decide</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-04-en-bayesian-threat-fusion-how-multi-sensor-cbrn-networks-decide/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-04-en-bayesian-threat-fusion-how-multi-sensor-cbrn-networks-decide/</guid><description>How combining IMS, Raman, gamma spectroscopy, and qPCR under Bayesian fusion enables sub-second CBRN threat consensus in contested field environments.</description><pubDate>Mon, 04 May 2026 00:00:00 GMT</pubDate><quickAnswer>Bayesian threat fusion integrates IMS, Raman spectroscopy, gamma detection, and qPCR sensor outputs into a single probabilistic consensus, reducing false-positive rates below 2% while achieving sub-second chemical and radiological threat classification. UAM KoreaTech&apos;s CBRN-CADS platform operationalizes this multi-modal architecture for tactical field deployment.</quickAnswer><category>cbrn-ai</category><category>Aum Shinrikyo</category><category>Tokyo Subway Attack</category><category>CBRN-CADS</category><category>Bayesian Fusion</category><category>Multi-Modal Sensor</category><category>Gamma Spectroscopy</category><author>박무진</author></item><item><title>KAS Part 21/23 Certification: BLIS-D&apos;s Path to Civil Aviation</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-03-en-kas-part-2123-certification-blis-ds-path-to-civil-aviation/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-03-en-kas-part-2123-certification-blis-ds-path-to-civil-aviation/</guid><description>How Korean Airworthiness Standards Part 21 and Part 23 create a regulatory pathway for BLIS-D dry decontamination systems in civil aircraft and dual-use platforms.</description><pubDate>Sun, 03 May 2026 00:00:00 GMT</pubDate><quickAnswer>KAS Part 21 and Part 23, administered by MOLIT, provide the type-certification framework enabling BLIS-D&apos;s bleed-air dry decontamination technology to be integrated into civil aircraft as qualified airborne equipment—bridging NATO STANAG 4632 compliance with commercial aviation safety standards.</quickAnswer><category>cbrn-ai</category><category>KAS Part 21</category><category>Type Certification</category><category>BLIS-D</category><category>CBRN-CADS</category><category>NATO STANAG</category><category>Dual-Use Aviation</category><author>박무진</author></item><item><title>Sun Tzu to Hannibal: 16 Commander Archetypes for CBRN Crisis Roles</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-03-en-sun-tzu-to-hannibal-16-commander-archetypes-for-cbrn-crisis/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-03-en-sun-tzu-to-hannibal-16-commander-archetypes-for-cbrn-crisis/</guid><description>UAM KoreaTech&apos;s TIP-12 framework maps 16 historical commander archetypes to CBRN crisis decision roles, enabling AI-augmented personnel assignment and command resilience.</description><pubDate>Sun, 03 May 2026 00:00:00 GMT</pubDate><quickAnswer>TIP-12&apos;s 16 commander archetypes—drawn from Sun Tzu, Hannibal, Yi Sun-sin, and others—provide a structured Persona Profiling Framework that matches individual decision styles to specific CBRN crisis roles, reducing command failure risk and improving AI-augmented staff assignments under chemical, biological, radiological, and nuclear threat conditions.</quickAnswer><category>cbrn-ai</category><category>Sun Tzu</category><category>Hannibal Barca</category><category>TIP-12</category><category>CBRN-CADS</category><category>Persona Profiling Framework</category><category>Decision Intelligence</category><author>박무진</author></item><item><title>Sun Tzu to Hannibal: 16 Commander Archetypes in CBRN Crisis</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-03-en-sun-tzu-to-hannibal-16-commander-archetypes-in-cbrn-crisis/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-03-en-sun-tzu-to-hannibal-16-commander-archetypes-in-cbrn-crisis/</guid><description>How UAM KoreaTech&apos;s TIP-12 framework maps 16 historical commander archetypes to modern CBRN crisis roles, accelerating decisions under chemical and biological threat.</description><pubDate>Sun, 03 May 2026 00:00:00 GMT</pubDate><quickAnswer>UAM KoreaTech&apos;s TIP-12 framework maps 16 commander archetypes—from Sun Tzu&apos;s systemic thinker to Hannibal&apos;s encirclement specialist—onto CBRN crisis roles, enabling AI-augmented decision profiling that reduces command latency by matching cognitive style to threat type before contamination spreads.</quickAnswer><category>cbrn-ai</category><category>Sun Tzu</category><category>Hannibal Barca</category><category>TIP-12</category><category>Tactical Prompt</category><category>CBRN Decision Intelligence</category><category>Commander Archetypes</category><author>박무진</author></item><item><title>Sun Tzu to Hannibal: 16 Commander Archetypes in CBRN Crisis Roles</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-03-en-sun-tzu-to-hannibal-16-commander-archetypes-in-cbrn-crisis-r/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-03-en-sun-tzu-to-hannibal-16-commander-archetypes-in-cbrn-crisis-r/</guid><description>How UAM KoreaTech&apos;s TIP-12 framework maps 16 historical commander archetypes to modern CBRN decision roles, from detection through decontamination.</description><pubDate>Sun, 03 May 2026 00:00:00 GMT</pubDate><quickAnswer>TIP-12&apos;s 16 commander archetypes—drawn from figures like Sun Tzu, Hannibal, and Yi Sun-sin—map directly to distinct CBRN crisis roles, enabling commanders to recognize their cognitive defaults, compensate for blind spots, and allocate decision authority more effectively under chemical or biological threat conditions.</quickAnswer><category>cbrn-ai</category><category>Sun Tzu</category><category>Hannibal Barca</category><category>TIP-12</category><category>Tactical Prompt</category><category>CBRN Decision Intelligence</category><category>Commander Archetypes</category><author>박무진</author></item><item><title>Sun Tzu to Hannibal: Mapping 16 Commander Archetypes to CBRN Roles</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-03-en-sun-tzu-to-hannibal-mapping-16-commander-archetypes-to-cbrn/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-03-en-sun-tzu-to-hannibal-mapping-16-commander-archetypes-to-cbrn/</guid><description>UAM KoreaTech&apos;s TIP-12 framework maps 16 historical commander archetypes to CBRN crisis roles, enabling AI-augmented decision intelligence for modern defense teams.</description><pubDate>Sun, 03 May 2026 00:00:00 GMT</pubDate><quickAnswer>UAM KoreaTech&apos;s TIP-12 framework identifies 16 commander archetypes—drawn from figures like Sun Tzu, Hannibal, and Yi Sun-sin—and maps each to specific CBRN crisis roles, enabling commanders and AI systems to align decision styles with operational demands before a chemical or biological incident escalates.</quickAnswer><category>cbrn-ai</category><category>Sun Tzu</category><category>Hannibal Barca</category><category>TIP-12</category><category>CBRN-CADS</category><category>Commander Archetypes</category><category>Decision Intelligence</category><author>박무진</author></item><item><title>Sun Tzu to Hannibal: TIP-12 Archetypes in CBRN Command</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-03-en-sun-tzu-to-hannibal-tip-12-archetypes-in-cbrn-command/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-03-en-sun-tzu-to-hannibal-tip-12-archetypes-in-cbrn-command/</guid><description>How UAM KoreaTech&apos;s TIP-12 framework maps 16 commander archetypes—from Sun Tzu to Hannibal—to real CBRN crisis decision roles, improving response speed and outcome.</description><pubDate>Sun, 03 May 2026 00:00:00 GMT</pubDate><quickAnswer>TIP-12&apos;s 16 commander archetypes translate historical battlefield psychology—Sun Tzu&apos;s systemic calculation, Hannibal&apos;s envelopment instinct, Yi Sun-sin&apos;s adaptive resilience—into structured CBRN decision roles, reducing cognitive mismatch between commander profile and crisis type. Assigning the right archetype to the right CBRN function measurably accelerates triage, containment, and escalation decisions.</quickAnswer><category>cbrn-ai</category><category>Sun Tzu</category><category>Hannibal Barca</category><category>TIP-12</category><category>CBRN-CADS</category><category>Commander Archetypes</category><category>Decision Intelligence</category><author>박무진</author></item><item><title>Sun Tzu to Hannibal: TIP-12 Archetypes in CBRN Crisis Command</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-03-en-sun-tzu-to-hannibal-tip-12-archetypes-in-cbrn-crisis-command/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-05-03-en-sun-tzu-to-hannibal-tip-12-archetypes-in-cbrn-crisis-command/</guid><description>How UAM KoreaTech&apos;s TIP-12 framework maps 16 commander archetypes—from Sun Tzu to Hannibal—to CBRN crisis decision roles, improving response under uncertainty.</description><pubDate>Sun, 03 May 2026 00:00:00 GMT</pubDate><quickAnswer>TIP-12 maps 16 historically grounded commander archetypes to specific CBRN crisis roles, enabling AI-augmented decision support that matches cognitive style to operational demand. Commanders who understand their own archetype—and those of adversaries—make faster, less error-prone decisions in chemical, biological, radiological, and nuclear incidents.</quickAnswer><category>cbrn-ai</category><category>Sun Tzu</category><category>Hannibal Barca</category><category>TIP-12</category><category>CBRN-CADS</category><category>Decision Intelligence</category><category>Commander Archetypes</category><author>박무진</author></item><item><title>4분의 외교 — 솔즈베리 노비촉 2018이 K-방산에 던지는 V-Series Defense 선택</title><link>https://uamkt-com.vercel.app/articles/case-studies/2026-04-30-salisbury-novichok-vseries-defense/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/case-studies/2026-04-30-salisbury-novichok-vseries-defense/</guid><description>Novichok 2018 솔즈베리 사건의 96시간 외교 의사결정과 V-Series Defense 독트린 — BLIS-D 8-Layer Patent + Dual-Pressure Chamber로 메우는 K-방산 격차</description><pubDate>Thu, 30 Apr 2026 00:00:00 GMT</pubDate><quickAnswer>Novichok 2018 솔즈베리 사건은 영국이 96시간 안에 28개국 동맹 외교 추방을 동원한 4분의 외교 사건이며, 한국이 동일 위협에 직면할 경우 V-Series Defense 독트린(BLIS-D 8-Layer Patent + Dual-Pressure Chamber + DDC 블록체인 + Lattice Tasks API)이 11개월·11M GBP 봉쇄를 11일·1.2M GBP로 압축할 수 있는 K-방산 우위 모듈입니다.</quickAnswer><category>case-studies</category><category>Novichok 2018</category><category>4MinuteDiplomacy</category><category>V-Series Defense</category><category>BLIS-D</category><category>Salisbury</category><category>CBRN-CADS</category><category>K-Defense</category><author>박무진</author></item><item><title>5분 안의 의사결정 — 1995 도쿄 사린 사건이 K-방산 30년에 남긴 숙제</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-04-29-tokyo-sarin-1995-k-defense-30-year-gap/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-04-29-tokyo-sarin-1995-k-defense-30-year-gap/</guid><description>1995 도쿄 사린 사건은 5,500명 부상의 의사결정 격차를 드러냈다. 30년 후 K-방산이 답해야 할 질문, CBRN-CADS·BLIS-D 통합 doctrine. (v2 — L 등급 보강 2026-05-01)</description><pubDate>Wed, 29 Apr 2026 00:00:00 GMT</pubDate><quickAnswer>1995-03-20 도쿄 지하철 사린 사건은 일본 정부의 4시간 46분 진단 지연이 5,500명의 부상을 만든 사례입니다. 같은 K-방산이 30년 후에도 동일 격차를 유지하고 있다면 — 서울 인구밀도(~16,000명/km²) 환경에서 산술적으로 6,800~8,200명 부상자가 예상됩니다. UAM KoreaTech의 CBRN-CADS·BLIS-D 통합 doctrine은 4시간 46분을 45분으로 압축 가능한 단일 시스템 답안입니다.</quickAnswer><category>cbrn-ai</category><category>Sarin1995</category><category>5MinuteDecision</category><category>DryDecontamination</category><category>CBRNCADS</category><category>UAMKoreaTech</category><category>DefenseTech2026</category><category>K-Defense</category><author>박무진</author></item><item><title>Salisbury 2018의 한 방울 — NATO의 CBRN 빈자리를 한국 스타트업이 채우는 법</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-04-27-salisbury-novichok-nato-gap-korea-blis-d/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-04-27-salisbury-novichok-nato-gap-korea-blis-d/</guid><description>Novichok이 영국 도시 한복판에서 노출시킨 NATO의 화생방 대응 한계 — UAM KoreaTech의 BLIS-D 무수분 제독 시스템이 왜 글로벌 솔루션이 될 수 있는가에 대한 dual-use 시장 분석.</description><pubDate>Mon, 27 Apr 2026 00:00:00 GMT</pubDate><quickAnswer>2018년 영국 Salisbury에서 한 방울의 노비촉(Novichok)이 4개월간 도시를 봉쇄했고, 1명이 사망했으며, 청소 비용은 수천만 파운드에 달했습니다. NATO의 30시간 wet decontamination 표준은 도시 환경에서 작동하지 않았습니다. UAM KoreaTech의 BLIS-D는 같은 위협을 90초 안에 무수분으로 처리하는 dual-use 솔루션으로, NATO의 CBRN 빈자리를 한국발 기술로 채울 수 있는 글로벌 시장 기회를 의미합니다.</quickAnswer><category>cbrn-ai</category><category>CBRN-CADS</category><category>BLIS-D</category><category>Novichok</category><category>NATO</category><category>Dual-Use</category><category>Salisbury</category><category>Decontamination</category><author>박무진</author></item><item><title>국내 최초 UAM 버드스트라이크 솔루션의 5가지 차별점</title><link>https://uamkt-com.vercel.app/articles/case-studies/2026-04-26-uam-birdstrike-5-differentiators/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/case-studies/2026-04-26-uam-birdstrike-5-differentiators/</guid><description>AVIX-AI 폐루프 OS · Anduril Lattice gap-filling · BSM 2.0 4 모듈 — 한국 최초 UAM 버티포트 적용 사례를 5가지 차별 요소로 분해 분석</description><pubDate>Sun, 26 Apr 2026 00:00:00 GMT</pubDate><quickAnswer>UAM KoreaTech은 국내 최초로 UAM 버티포트 특화 조류충돌 솔루션을 운영하는 기업이며, (1) 버티포트 특화 폐루프 OS, (2) Anduril Lattice gap-filling 19/19 PoC, (3) BSM 2.0 5단 폐루프 아키텍처, (4) AI 4 모듈 통합, (5) Dual-Use 적용성의 5가지 축에서 기존 시장 대비 구조적 우위를 확보하고 있습니다.</quickAnswer><category>case-studies</category><category>UAM</category><category>Bird Strike</category><category>AVIX-AI</category><category>BSM 2.0</category><category>Anduril Lattice</category><category>Vertiport</category><author>박무진</author></item><item><title>Korean CBRN AI Market 2026: A Strategic Outlook</title><link>https://uamkt-com.vercel.app/articles/market-trends/2026-04-cbrn-ai-korean-perspective/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/market-trends/2026-04-cbrn-ai-korean-perspective/</guid><description>유에이엠코리아텍이 분석한 2026년 한국 CBRN AI 시장 동향과 5년 전망</description><pubDate>Sat, 25 Apr 2026 00:00:00 GMT</pubDate><quickAnswer>The Korean CBRN AI market is at an inflection point in 2026. UAM KoreaTech is the only domestic vendor with a military-grade decision support AI (CBRN-CADS), backed by NATO Lattice integration and 17 IP assets including 4 granted patents. Government R&amp;D investment in CBRN/UAM convergence is projected to grow 35–45% YoY through 2028, driven by ROK-US combined operations modernization and the Mobility Innovation Fund.</quickAnswer><category>market-trends</category><category>CBRN</category><category>Defense AI</category><category>Korea</category><category>Market Analysis</category><category>JWARN</category><author>박무진</author></item><item><title>DoD CBRN RFI 2026 정합성 분석: UAM KoreaTech의 응답 전략</title><link>https://uamkt-com.vercel.app/articles/policy/2026-04-dod-rfi-2026-analysis/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/policy/2026-04-dod-rfi-2026-analysis/</guid><description>미 국방부 2026년 CBRN RFI(Request for Information)의 핵심 요구사항 분해와 CBRN-CADS 적합성 매핑</description><pubDate>Fri, 24 Apr 2026 00:00:00 GMT</pubDate><quickAnswer>미 DoD가 2026년 2월 발행한 CBRN RFI는 (1) 자율 의사결정, (2) NATO STANAG 2103 호환, (3) GPS-거부 환경 대응, (4) MUM-T 통합의 4대 요구를 명시했습니다. UAM KoreaTech의 CBRN-CADS는 4개 요구를 모두 직접 충족하며, 특히 KR 10-2026-0055778 특허로 GPS-거부 MUM-T 의사결정 영역에서 차별화됩니다. RFI 응답 마감은 2026-Q3로 예정되어 있습니다.</quickAnswer><category>policy</category><category>DoD</category><category>RFI</category><category>CBRN</category><category>정책 분석</category><category>FMS</category><author>박무진</author></item><item><title>CBRN-CADS Business Model Canvas: Lean BD Scenario for 2026–2028</title><link>https://uamkt-com.vercel.app/articles/business-models/2026-04-cbrn-cads-business-canvas/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/business-models/2026-04-cbrn-cads-business-canvas/</guid><description>CBRN-CADS 제품의 9-블록 비즈니스 모델 캔버스 + 3가지 시장 진입 시나리오 비교</description><pubDate>Thu, 23 Apr 2026 00:00:00 GMT</pubDate><quickAnswer>CBRN-CADS의 사업 모델은 (1) 정부 직접 조달, (2) 대기업 OEM 번들, (3) NATO/EDF 국제 협력 3가지 채널로 구성됩니다. 핵심 가치 제안은 &apos;한국 유일의 NATO JWARN 등가물 + 33x OODA 단축&apos;이며, 핵심 자원은 17건 IP 포트폴리오와 박무진 대표의 도메인 전문성입니다. 2026~2028 3년 사이 KRW 12~18B 누적 매출을 목표합니다.</quickAnswer><category>business-models</category><category>BMC</category><category>CBRN-CADS</category><category>Lean Canvas</category><category>방산 BD</category><category>수출</category><author>박무진</author></item><item><title>Active Resilience Deterrence: A Tactical Doctrine for CBRN AI Decision Support</title><link>https://uamkt-com.vercel.app/articles/papers/2026-04-active-resilience-deterrence/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/papers/2026-04-active-resilience-deterrence/</guid><description>수동적 방어를 넘어선 능동 회복탄력성 억제(ARD) 독트린의 이론적 정의와 CBRN-CADS 적용 사례</description><pubDate>Wed, 22 Apr 2026 00:00:00 GMT</pubDate><quickAnswer>Active Resilience Deterrence (ARD) is a tactical doctrine that reframes CBRN response from passive damage limitation to active denial of adversary objectives. By compressing the decide-act phase of the OODA Loop through AI decision support, ARD restores the offensive optionality that conventional CBRN doctrine concedes. UAM KoreaTech&apos;s CBRN-CADS implements ARD at the battalion level with documented 33x OODA compression.</quickAnswer><category>papers</category><category>Doctrine</category><category>CBRN</category><category>OODA</category><category>Decision Support</category><category>Resilience</category><author>박무진</author></item><item><title>What is JWARN? — NATO 화생방 경보 체계와 한국형 등가물(CBRN-CADS) 비교</title><link>https://uamkt-com.vercel.app/articles/cbrn-ai/2026-04-what-is-jwarn/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/cbrn-ai/2026-04-what-is-jwarn/</guid><description>JWARN(Joint Warning and Reporting Network)의 정의, NATO 회원국 운영 사례, 그리고 CBRN-CADS와의 기능 매핑</description><pubDate>Tue, 21 Apr 2026 00:00:00 GMT</pubDate><quickAnswer>JWARN(Joint Warning and Reporting Network)은 NATO 회원국이 공유하는 표준 화생방 경보·보고 체계로, STANAG 2103/2150 위에 구축됩니다. CBRN 사건 탐지 시 자동 경보·예측·전파를 수행합니다. 한국형 등가물은 UAM KoreaTech의 CBRN-CADS이며, JWARN의 핵심 5대 기능(탐지·분류·예측·경보·전파)을 100% 호환 구현하면서 OODA Loop를 33배 단축합니다.</quickAnswer><category>cbrn-ai</category><category>JWARN</category><category>STANAG 2103</category><category>CBRN-CADS</category><category>NATO</category><category>화생방 경보</category><author>박무진</author></item><item><title>Anduril Lattice 19/19 통합 실증 보고서: 인천테크노파크 공고 제2026-177호</title><link>https://uamkt-com.vercel.app/articles/case-studies/2026-04-lattice-19-19-integration/</link><guid isPermaLink="true">https://uamkt-com.vercel.app/articles/case-studies/2026-04-lattice-19-19-integration/</guid><description>UAM KoreaTech가 2026년 4월 20일 달성한 Anduril Lattice SDK 19/19 HTTP 200 실증의 기술 보고서</description><pubDate>Mon, 20 Apr 2026 00:00:00 GMT</pubDate><quickAnswer>UAM KoreaTech는 2026-04-20 인천테크노파크 공고 제2026-177호 실증에서 Anduril Lattice SDK 대상 19개 엔티티(정적 6 + 동적 13)를 모두 HTTP 200으로 게시하는 데 성공했습니다. 이는 한국 기업 최초의 NATO 표준 군용 데이터 플랫폼 통합 검증으로, STANAG 2103 호환과 CBRN-CADS의 NATO 상호운용성을 동시에 입증합니다. 5대 API 필드 규칙(disposition·template·environment·GEO·publisher)이 회귀 테스트 기준선으로 확정되었습니다.</quickAnswer><category>case-studies</category><category>Anduril</category><category>Lattice</category><category>통합 실증</category><category>STANAG 2103</category><category>Case Study</category><author>박무진</author></item></channel></rss>