Divergence in situation awareness and workload
Mica R. Endsley1, Jordan Dixon2, Tristan Endsley2, David Jamrog2, Laura Smith-Velazquez3 and Avi Pfeffer3 Ergonomics, (13 Nov 2024) DOI: 10.1080/00140139.2024.2427859. ISSN: (Print) (Online) Journal homepage: www.tandfonline.com/journals/terg20 Situation awareness (SA) and workload have both received considerable attention over the past several decades. Little research has investigated the relationship between these two constructs however. The present study examines […]
Towards Joint Activity Design Heuristics: Essentials for Human-Machine Teaming
Dane A. Morey1, Prerana Walli1, Kenneth S. Cassidy1, Priyanka K. Tewani1, Morgan E. Reynolds1, Samantha Malone1, Mohammadreza Jalaeian1, Michael F. Rayo1, and Nicolette M. McGeorge2 Proceedings of the Human Factors and Ergonomics Society Annual Meeting, Volume 67, Issue 1, September 2023, Pages 131-136 As machines increasingly behave more like active cognitive agents than passive tools, additional heuristics for supporting joint human-machine activity […]
A Pilot Randomized Controlled Trial of Augmented Reality Just-in-Time Guidance for the Performance of Rugged Field Procedures
Laurel O’Connor, MD;1 Sepahrad Zamani, MS;1 Xinyi Ding;1 Nicolette McGeorge, PhD;2 Susan Latiff, PhD;2 Cindy Liu;2 Jorge Acevedo Herman, MD;1 Matthew LoConte, MD;1 Andrew Milsten, MD;1 Michael Weiner, MD;1 Timothy Boardman, MD;1 Martin Reznek, MD;1 Michael Hall, MD;1 John P. Broach, MD1 Cambridge University Press on behalf of World Association for Disaster and Emergency Medicine (07 May 2024) Introduction: Medical resuscitations in rugged prehospital settings […]
Digitizing Survivorship Care Plans Through the POST-Treatment Health Outcomes of Cancer Survivors (POSTHOC) Mobile App: Protocol for a Phase II Randomized Controlled Trial
Kaitlin H Chung1,2*; Shari M Youngblood1,3*, DCN, CNS, LDN; Carin L Clingan1, MS, CNS, LDN; Dana C Deighton4, BA; Virginia A Jump5,6, MSN, CRNP; Thushini Manuweera1, PhD; Nicolette M McGeorge7, PhD; Cynthia L Renn1, RN, PhD; Paula Y Rosenblatt4,5,8, MD; Aaron T Winder7, PhD; Shijun Zhu9, PhD, DrE; Ian R Kleckner1,4, MPH, PhD; Amber S […]
Assessment and Diagnosis of Vestibular Indicators of Soldiers’ Operational Readiness (ADVISOR)
Phillip C. Desrochers1, Daniel Duggan1, Howard Rafal1, Erin Williams2, Valerie Yunis2, Michael Hoffer2 Poster presented at the 15th Annual Traumatic Brain Injury Conference, Boston, MA (5-6 May 2024) Background: Over the last 20 years, mild Traumatic Brain Injury (mTBI) has become a significant health problem for both military personnel and civilians. mTBI is one of […]
AI-Driven Course of Action Generation Using Neuro-symbolic Methods
Michael Harradon, Kevin Golan, Oliver Daniels-Koch, Avi Pfeffer, and Robert Hyland Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC), Orlando, Florida (4 December 2024) Artificial intelligence (AI)–based systems show great promise for supporting complex decision-making and planning. AI systems can consider a massive option space that far exceeds current human processes. Notably, AI systems, particularly deep […]
Generative AI-Powered 3D-Content Creation for Military Training
Eduardo Barrera1, Deepak Haste2, Michael Renda2, Sudipto Ghoshal2, Jason H. Wong3 Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC), Orlando, Florida (4 December 2024) The U.S. Marine Corps (USMC) has taken the initiative of introducing interactive learning experiences at its schoolhouses as a cost-effective and timesaving means to augment classroom instructions and physical equipment-training with immersive […]
Human-AI Common Ground for Training and Operations
Spencer K. Lynn1, Susan S. Latiff1, William Norsworthy1, Jr., Mark Turner2, Peter Weyhrauch1 Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC), Orlando, Florida (4 December 2024) How do we create artificially intelligent agents capable of meaningful and trusted teaming with humans for training and operations? “Common ground” refers to congruent knowledge, beliefs, and assumptions among a […]
Integrating System Design Information Using a Self-Defining Ontology
Stephen Hookway, William Norsworthy, Jr. Paper presented at the 23rd International Semantic Web Conference, Baltimore, MD (November 2024) Engineers use a variety of software tools to support system design and development. These tools help engineers encode and reason about complex requirements and designs, but they also create data silos of information related to the components […]
Sparking System Change with System Dynamics
David Koelle (Charles River Analytics), Stephanie Losi (21 Labs, Inc.) SXSW 2024, Austin, TX (March 2024) The 1972 Limits to Growth study predicted a climate change trajectory that looks accurate all these decades later. The study used system dynamics, a modeling approach that aims to find leverage points: places where a small change can cause big […]
Swarms: Current Research and Future Applications
David Koelle (Charles River Analytics), Nora Ayanian (Brown University), Giovanni Beltrame (Ecole Polytechnique De Montreal), Amir Rahmani (NASA Jet Propulsion Laboratory) SXSW 2024, Austin, TX (March 2024) Collections of robots working together to achieve tasks–swarm systems–are an exciting and intriguing means to solve problems in novel ways. Swarms provide solutions to challenges in agriculture, search […]
Using a Mechanical Whale to Test Automatic Whale Blow Detection with Applications to Offshore Wind Development
R. S. Eaton; J. C. Prisco; J. J. Everson; J. E. Riedel; Y. M. Randall Paper presented at the 2024 Offshore Technology Conference, Houston, Texas (May 2024) Marine mammals have the potential to be harassed by exposure to loud sounds caused by survey or construction activity and even killed by collisions with fast moving vessels. […]
Challenges and Progress in Predictive Maintenance of Long-Endurance & Long-Range Uncrewed Platforms
Kenneth Lu, Sanja Cvijic, Arjuna Balasuriya AUVSI XPONENTIAL 2024, San Diego, CA (April 2024) Today’s uncrewed platforms are typically operated by humans using remote control to guide every detailed aspect of a mission. However, as missions become more complex, there are many scenarios (particularly in the marine and ground domains) in which operators are unable […]
Collaborative Autonomy Meets the Real World
David Koelle AUVSI XPONENTIAL 2024, San Diego, CO (April 2024) The physical world is being increasingly served by autonomy, including self-driving taxi cabs, autonomous mining vehicles, and robots in warehouses and hospitals. While this is certainly a significant step in technical advancement, these robots and vehicles all operate independently. The ability for robots to work […]
A Joint, Adaptive, Robust Visualization and Interaction System for AI-Enabled, Symbiotic Cyber-Physical System Design
Ryan Kilgore, David Koelle, Matthew Miller, Amanda Warren, Gabrielle Loeff and Nicholas Alico Proceedings of the 26th International Conference on Human-Computer Interaction (HCII 2024), Washington, DC (July 2024). A cyber-physical system (CPS) is a collection of physical and computer components that are integrated with each other to operate a process safely and efficiently. Artificial intelligence […]
Enabling Human-centered Machine Translation Using Concept-based Large Language Model Prompting and Translation Memory
Dr. Ming Qian Proceedings of the 26th International Conference on Human-Computer Interaction (HCII 2024), Washington, DC (July 2024). This study evaluates a novel human-machine collaborative machine translation workflow, enhanced by Large Language Model features, including pre-editing instructions, interactive concept-based post-editing, and the archiving of concepts in post-editing and translation memories. By implementing GPT-4 prompts for […]
Hybrid-AI Approach to Health Monitoring of Vehicle Control System
Kenneth Lu1, Margarita Hiett1, Ernest Vincent Cross1, Michael Reposa1, Aaron Kain2, Erik Davis2 Proceedings of The 70th Annual Reliability & Maintainability Symposium (RAMS®) (January 2024) Advances in Artificial Intelligence and Machine Learning AI/ML have demonstrated enormous potential in improving and optimizing condition-based maintenance processes. In this paper, we present novel research that leverages the power […]