11-20 of 265 results
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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.
Findings: The proof-of-concept demonstrated the viability of the system, with the low-fidelity simulation successfully flagging key scenarios for further testing, and the high-fidelity simulation providing accurate and realistic results for the flagged scenarios. By streamlining the testing process and focusing computational resources where they are most needed, this framework offers a robust solution for improving UAV safety and reliability in increasingly complex operational environments.
Categories: Faculty-Staff
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Federal Aviation Administration - Aviation Ecosystem Cyber Security Data Science (CSDS)
PI M. Ilhan Akbas
CO-I Laxima Niure Kandel
To address these needs, the FAA NextGen Organization has established the CSDS research program with emphasis on discovery, assessment, adaptation, demonstration and transfer of cyber technology to enhance information cybersecurity for elements of the aviation ecosystem.
Establishing cyber analytical capabilities that are common between various elements of the aviation ecosystem is an essential capability that needs to be developed and matured to allow efficient and synchronized use of common data sets, analytical tools and communication backbones across the entire aviation ecosystem. To address these needs, the FAA NextGen Organization has established the CSDS research program with emphasis on discovery, assessment, adaptation, demonstration and transfer of cyber technology to enhance information cybersecurity for elements of the aviation ecosystem. The research is focused on Artificial Intelligence and Machine Learning (AI/ML) techniques to address these aviation ecosystem cybersecurity needs using customizable algorithms and tools. Our collaborators in this project include Astronautics, Collins Aerospace, GE Aerospace, Gulfstream Aerospace, Massachusetts Institute of Technology Lincoln Lab, The Boeing Company, The Port Authority of New York and New Jersey United Airlines.
Categories: Faculty-Staff
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Federal Aviation Administration (FAA): A11L.UAS.97: Propose Right-of-Way Rules for Unmanned Aircraft Systems (UAS) Operations and Safety Recommendations
PI M. Ilhan Akbas
The overall purpose of this project is to inform rulemaking and standards development regarding potential Right of Way (RoW) concepts for manned and unmanned aircraft in the low altitude environment.
The overall purpose of this project is to inform rulemaking and standards development regarding potential Right of Way (RoW) concepts for manned and unmanned aircraft in the low altitude environment.
There are various RoW standards, which apply to specific types of UAS. However, there is ambiguity for other UAS and rules have yet to be developed for interactions between two unmanned aircraft or for UAS swarms. RoW rules impact UAS Detect and Avoid (DAA) requirements and the development of industry standards. This research project explores RoW for diverse UAS operations and make safety-based recommendations for consideration by FAA and UAS standards bodies. Our collaborators in this project are University of North Dakota and University of Kansas.
Categories: Faculty-Staff
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Using Interpretable Artificial Intelligence (AI) for Validation of Autonomous Vehicle Decision Making in Simulation
PI M. Ilhan Akbas
Autonomous Vehicle Validation and Verification AV V&V testing produces multi-variate time series data as output, which is evaluated to determine testing coverage.
Autonomous Vehicle Validation and Verification AV V&V testing produces multi-variate time series data as output, which is evaluated to determine testing coverage. The recent surge in interpretable Artificial Intelligence (AI) research has resulted in Python interfaces for modern interpretable AI implementations. In this project, various modern interpretable AI implementations will be applied to AV V&V testing data to interpret parameter impact, and generate an informative report of AV V&V scenario using data generated from a traffic simulator and AV V&V test scenarios.
Categories: Faculty-Staff
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PolyVerif: Open-Source Environment for Autonomous Vehicle Validation and Verification
PI M. Ilhan Akbas
Validation and Verification (V&V) of Artificial Intelligence (AI) based cyber physical systems such as Autonomous Vehicles (AVs) is currently a vexing and unsolved problem.
Validation and Verification (V&V) of Artificial Intelligence (AI) based cyber physical systems such as Autonomous Vehicles (AVs) is currently a vexing and unsolved problem. PolyVerif is an open-source solution focused on V&V researchers with the objective of accelerating the state-of-the-art for AV V&V research. PolyVerif provides an AI design and verification framework consisting of a digital twin creation process, an open-source AV engine, access to several open-source physics-based simulators, and open-source symbolic test generation engines. PolyVerif’s objective is to arm V&V researchers with a framework which extends the state-of-the-art on any one of the many major axes of interest and use the remainder of the infrastructure to quickly demonstrate the viability of their solution.
Categories: Faculty-Staff
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TurtleTech: Sea Turtle Surveillance By Edge Computing on Unmanned Aerial Vehicles
PI M. Ilhan Akbas
To better understand the behavior of multiple sea turtle species along Florida’s Space Coast, we teamed up with Northrop Grumman and the Brevard Zoo to launch a drone-based surveillance effort.
To better understand the behavior of multiple sea turtle species along Florida’s Space Coast, we teamed up with Northrop Grumman and the Brevard Zoo to launch a drone-based surveillance effort. The Turtle Tech project, leveraging two different unmanned aircraft systems (UAS), aim to provide conservation insights by fine-tuning the operations and computer vision systems for identification of individual sea turtles, including their species, gender and even unique markings.
Categories: Faculty-Staff
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Novel n x n Bit-Serial Multiplier Architecture Optimized for Field Programmable Gate Arrays (FPGA)
PI Akhan Almagambetov
CO-I David Feinauer
CO-I Holly Ross
Bit-serial multipliers have a variety of applications, from the implementation of neural networks to cryptography. The advantage of a bit-serial multiplier is its relatively small footprint, when implemented on a Field Programmable Gate Array (FPGA) device. Despite their apparent advantages, however, traditional bit-serial multipliers typically require a substantial overhead, in terms of component usage, which directly translates to a large area of the chip being reserved while many of those resources are unused.
This research addresses the possibility of an efficient two's complement bit-serial multiplier (serial-serial multiplier) implementation that would minimize flip-flop and control set usage on an FPGA device, thereby potentially reducing the overall area of the circuit. Since the proposed architecture is modular, it functions as a "generic" definition that can be effortlessly implemented on an FPGA device for any number of bits.
Categories: Faculty-Staff
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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.
Analysis of collected data involved exploratory factor analysis to identify underlying factors, confirmatory factor analysis to verify significant relationships between manifest variables and latent constructs and to ensure a good-fitting measurement model, and structural equation modeling to identify significant relationships between latent constructs and achieve the best-fitting model of these relationships for the collected data. Variables were Likert-scale responses to literature-based survey items associated with organizational vision, leadership, communication, collaboration, decision-making, flexibility, accountability, resource availability, motivation, and learning. Additionally, participants were invited to provide comments related to any of the survey items to explain or add detail to their response selection. These comments were reviewed both as they related to individual survey items and for detection of underlying themes. Participants in the study comprised stakeholders associated with career education programs in the disciplines of interest, including students, parents, alumni, school / program faculty and staff, industry members, and advisory board members.
Hypothesis testing results suggested that the most important factor in predicting success for an aviation / aerospace / engineering academy or program is personal motivation related to learning. Though other underlying factors, including leadership / collaborative environment, organizational accountability, and resource availability were clearly related to perceived program success, they appeared to have indirect relationships with success. It is also important to recognize that a paired qualitative analysis of participant comments generated themes that transcended survey item topics, and the identification of these themes supported the conclusions from hypothesis testing regarding underlying factors. Personal motivation was the most commonly recurring theme in comments, supporting the hypothesis testing result indicating its predictive strength for an organization’s success.
Understanding the constructs that are most closely related to an organization’s success, as they are perceived by its stakeholders, offers current program leaders and groups interested in creating new programs evidence they can use to design the frameworks for their programs. Anticipated workforce shortages warrant study of how to increase the number of candidates not only in post-secondary academic and training programs, but to shift recruiting earlier through implementation of quality secondary-level programs that are established on a foundation of research-based strategies for success.
Categories: Graduate
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Increasing student learning and engagement using a TV series: Leadership in the Final Frontier
PI Anke Arnaud
Educators are continuously concerned with developing innovative and effective teaching methodology to increase student learning and engagement. This study is designed to assess the effectiveness of an innovative instructional methodology, using a TV series to teach and develop leadership understanding, skills and knowledge.
During a semester long class on leadership, students were taught abstract leadership concepts and theories using Episodes from the Star Trek Series. We used inductive reasoning methodology, watching an episode of Star Trek and then developing leadership theory, and deductive reasoning methodology, learning about a leadership theory and then analyzing the theory using an episode of Star Trek, to develop leadership understanding, skills and knowledge. Student journal entries, questionnaires on student engagement and learning, and end of course evaluations were used to assess the effectiveness of the teaching methodology. Results support our expectation that student learning and engagement can be enhanced using the effective application of TV episodes.Categories: Faculty-Staff
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Automated Homework System: Improving Teaching Quality by Utilizing Technology
PI Farshid Azadian
One of the essential elements in improving the students' skills and abilities and helping them to better understand the course materials is homework assignments. A well designed and purposeful homework not only enhances the student's understanding but also may provide valuable feedback to instructors.
However, the process of designing and grading homework assignments are laborious from the instructor's perspective for large classes. Moreover, similarity of the assignments for all students set the stage for potential plagiarism which when is left undetected can set an undesirable ethical precedence.
In this research, our objective is to provide an automated procedure that assists instructors to utilize homework assignments more productively and reduces the possibility of unethical practices. Our main idea is to create a tool that uses the existing teaching resources to produce individual (non-identical) homework assignments for each student, automatically grade them and provide feedback to students.Categories: Faculty-Staff
11-20 of 265 results