121-130 of 168 results
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Comparison of Classic Guerrilla Warfare With So-Called Fourth-Generation Warfare Using Agent-Based Modeling and Simulation
PI Jerry Sink
CO-I Mark Abdollahian
Fourth-Generation Warfare (4GW) theory shares many characteristics of classical guerrilla theory (CGW) in security studies literature. Proponents claim that 4GW is a significant evolution that overturns traditional measures of military power, while critics counter that 4GW is simply CGW in an updated context. The two strategies are modeled in an agent-based simulation to evaluate similarities and differences in speed to victory and territory controlled over. Emergent behaviors are compared with historical data.
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Astroparticle Physics
PI Darrel Smith
CO-I Brennan Hughey
In the 1950's and 1960's, high-energy and cosmic-ray physics developed into two different fields of research. However, in the last twenty years they have come together in a most peculiar way. As space physicists explored the sources and mechanisms for producing cosmic rays, they also realized that it was impossible to measure the dynamics of the early universe (i.e., the first 400,000 years).
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Exotic Propulsion
PI Darrel Smith
Exotic propulsion has captured the interest of many Embry-Riddle students. As NASA plans its manned mission to Mars, we come face-to-face with a fundamental dilemma -- a round trip to Mars will take almost three years with traditional chemical rockets!
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NSF REU Site: Swarms of Unmanned Aircraft Systems in the Age of AI/Machine Learning
PI Houbing Song
CO-I Richard Stansbury
Embry-Riddle Aeronautical University establishes a new Research Experiences for Undergraduates (REU) Site to engage participants in research in drone swarms. The emerging concept of drone swarms, which is defined as the ability of drones to autonomously make decisions based on shared information, creates new opportunities with major societal implications. However, future drone swarm applications and services pose new networking challenges. A resurgence of Artificial Intelligence and machine learning research presents a tremendous opportunity for addressing these networking challenges. There is an overwhelming need to foster a robust workforce with competencies to enable future drone swarm applications and services in the age of AI/machine learning.
The project establishes a new Research Experiences for Undergraduates (REU) Site with a focus on networking research for drone swarms in the age of AI/machine learning at Embry-Riddle Aeronautical University. The goals of the REU Site are: (1) attract undergraduate students to state-of-the-art drone swarm research, especially those from underrepresented groups, and from institutions with limited opportunities; (2) develop the research capacity of participants by guiding them to perform research on drone swarms; (3) grow the participants’ technical skills to enable a wide variety of beneficial applications of drone swarms; (4) promote the participants’ integrated AI/machine learning and drone swarm competencies; and (5) prepare participants with professional skills for careers. The focus of the REU Site is on the design, analysis and evaluation of innovative computing and networking technologies for future drone swarm applications and services. To be specific, research activities will be conducted in three focus areas, notably dynamic network management, network protocol design, and operationalizing AI/machine learning for drone swarms. Each year eight undergraduate students will participate in a ten-week summer REU program to perform networking research for drone swarms under the guidance of research mentors with rich experiences in AI/machine learning and drone swarms. This REU site is expected to foster workforce knowledge and skills about developing new computing and networking technologies for future drone swarm applications and services. This site is supported by the Department of Defense ASSURE program in partnership with the NSF REU program.
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Unmanned Aircraft Systems (UAS) Application to Support Aircraft Rescue and Fire Fighting (ARFF)
PI Brent Terwilliger
CO-I David Ison
CO-I Dennis Vincenzi
CO-I
CO-I Dahai Liu
This continuing research project features refinement of UAS application methods to support of ARFF responses. Previously, modeling and simulation, in combination with UAS attribute performance models, was implemented to better understand challenges, limitations, and potential benefits of UAS support. However, based on the findings and recommendations of the original inquiry, the research will be expanded to include examination of operator knowledge, skills, and abilities (KSAs), performance rating standards, and appropriate training requirements and delivery approaches.
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A Curriculum Wide Software Development Case Study
PI Massood Towhidnejad
CO-I Thomas Hilburn
This NSF funded research develops case studies of software development for use in software engineering and computing instruction.
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121-130 of 168 results