Displaying 181-192 of 284 Results

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NSF-CNS: REU Site: Swarms of Unmanned Aircraft Systems in the Age of AI/Machine Learning

  • PI Richard Stansbury

    CO-I Thomas Yang

  • Embry-Riddle Aeronautical University establishes a new Research Experiences for Undergraduates (REU) Site to engage participants in research in drone swarms. Drone swarms create new opportunities with major societal implications.
NSF-DMS: Collaborative Research: Data-driven Realization of State-space Dynamical Systems via Low-complexity Algorithms

  • PI Sirani Mututhanthrige Perera

  • This project will utilize data-driven methods and analyze state-space dynamical systems to predict and understand future states, surpassing classical techniques. The project will also utilize state-of-the-art machine learning (ML) algorithms to efficiently analyze and predict information within data matrices and tensor computations with low-complexity algorithms.
NSF-DUE: Distributed Learning for Undergraduate Programs in Data Science at Diverse Universities

  • PI Hong Liu

    CO-I Sirani Mututhanthrige Perera

    CO-I Ming Wang

    CO-I Michael Wolyniak

    CO-I Sheldon Liang

  • This project aims to serve the national interest by improving undergraduate education in data science. This project will develop and deliver ten Data Sciences (DS) courses to students from a consortium of eleven diverse universities by using a flexible distributed learning (DL) platform.
NSF-ECCS: Collaborative Research: SWIFT: AI-based Sensing for Improved Resiliency via Spectral Adaptation with Lifelong Learning

  • PI Sirani Mututhanthrige Perera

  • This SWIFT project will demonstrate a system for spectral situational awareness through radio frequency (RF) machine learning (ML). The key objective is to obtain actionable spectrum intelligence in the sub-6 GHz legacy bands through a real-time understanding of waveform shapes, spectral content, and modulation schemes.
NSF-ECCS: Collaborative Research: Wideband Multi-Beam Antenna Arrays: Low-Complexity Algorithms and Analog-CMOS Implementations

  • PI Sirani Mututhanthrige Perera

    PI Arjuna Habarakada Madanayake

  • Explosion of millimeter-wave (mm-wave) bandwidth opens up applications in 5G wireless systems spanning communications, localization, imaging, and radar. This project addresses challenges in mathematics, engineering, and science in developing efficient wideband beamformers based on sparse factorizations of the matrix called-delay Vandermonde matrices (DVM). The proposed highly integrated approach is attractive for mobile applications including 5G smart devices, the internet of things, mobile robotics, unmanned aerial vehicles, and other emerging applications focused on mm-waves.

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Oil for Terrorism: Examining the Effectiveness of Western Intervention in ISIS’s Oil Smuggling

  • CO-I Rae Heuer

    CO-I Elisabeth Murray

  • The Terrorist organization ISIS has been identified as a violent, radical group that poses a threat to both the regional and international arena. By gathering both primary and secondary research data from foreign and domestic sources, this project investigates whether ending ISIS’s oil smuggling would decrease ISIS’s strength, power, and influence as a terrorist organization.
On the climatology, multiscale dynamics, and predictability of convective snow bursts in the northern United States

  • PI Shawn Milrad

  • The goal is to broadly address non-lake effect snow squalls (hereafter referred to as “snow bursts”), defined as short-duration (< 6 h) mesoscale phenomena that can have substantial impacts on aviation and human interests during the cool season.
On the synoptic-dynamic characteristics of extreme precipitation events: Understanding and quantifying the role of anticyclones

  • PI Shawn Milrad

  • This work represents an initial step towards further understanding and quantification of the importance of anticyclones, including their role in air mass modification (i.e., the transport of warm, moist air).
Open-Source Validation and Verification Framework for AI-Controlled Aerial Vehicles

  • PI M. Ilhan Akbas

  • The goal of this project is to develop a simulation framework to streamline the testing and validation of AI-controlled aerial vehicles. The Artificial Intelligence (AI) design and verification flow consists of the digital environment creation process, an open-source AI-controlled autopilot, access to multiple open-source simulators, symbolic test generation engine, example test scenarios, and native design-for-experiment layer for each of the major subsystem of an AI-controlled aerial vehicle.
Optimizing Countermeasures for Spaceflight-Induced Deconditioning

  • PI Christine Walck

  • This research focuses on understanding space deconditioning and developing comprehensive systems to mitigate the adverse physiological effects of microgravity on astronauts.
Organizational Design of Secondary Aviation/Aerospace/Engineering Career Education Programs

  • PI Susan Archer

    CO-I David Esser

  • Modern nations operate within a global economy, relying heavily on the aviation industry for efficient and effective transportation of passengers and goods. The Boeing 2018 Pilot and Technical Outlook Report indicated that over the next 20 years, the aviation industry will need almost two and a half million new aircrew and maintenance employees to meet anticipated global demand. The industry will also need engineers, aviation managers, and workers in other aviation and aerospace disciplines. Aviation and aerospace jobs require solid backgrounds in mathematics, science, and technology; the development of pre-college aviation / aerospace / engineering career education programs would presumably enhance student preparation in these areas and increase the workforce pipeline for the industry. The goal of this study was to identify and evaluate the underlying organizational factors of successful secondary aviation / aerospace / engineering career education programs, through application of measures traditionally associated with organizational theory.

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Pilot Acceptance of Personal, Wearable Fatigue Monitoring Technology: An Application of the Extended Technology Acceptance Model

  • PI Rachelle Strong

    CO-I Dahai Liu

  • The research problem of pilot fatigue has been referenced as a causal factor for aircraft accidents in many United States National Transportation and Safety Board (NTSB) accident reports; however, the United States Code of Federal Regulations 14 CFR Part 117, Flight and Duty Limitations and Rest Requirements for Flight Crew Members, does not provide a tangible means of measuring fatigue for aircraft crew members. This problem is relevant to the airline industry and the travelling public because pilot fatigue is preventable as a causal factor in aviation accidents, and pilots need an accurate way to measure it. Adoption of a technology-based solution has been recommended by the NTSB.