Carlos Paradis — Page 2 | Engineering Papers

NASA NTRSDate not supplied

Informing NLP Learning Tasks by Tracking User Features: An ASRS Use Case using Kaona

There has been growing interest in utilizing natural language processing (NLP) algorithms in Aviation Safety. This interest has extended to leveraging the decades of records publicly available on the Aviation Safety Reporting System (ASRS). While related literature has given more emphasis in lessons learned from the narratives, our prior work has focused on using NLP to support narrative search in the ASRS. Specifically, we evaluated if the use of alternative search mechanisms to keyword search, such as the retrieval of related narratives even without matching keywords could improve narrative discovery. A difficulty in experimenting alternative search mechanisms in any information retrieval task is the lack of ground truth. To address this limitation, we propose Kaona, a lightweight interface which enables the prototyping of alternative search retrieval tasks, by tracking user experience both explicitly (user-specified feedback), or implicitly (user navigation through interface affordances). Differently from distracting requests for feedback during user navigation, Kaona collects explicit feedback from users by mapping them to affordances which support the user workflow, while obtaining ground truth information for learning tasks.

human-computer-interaction↗

NASA NTRSDate not supplied

Kaona: Deep Searching and Curating Data from Aviation Safety Reporting Systems

Context: Several works in the literature have examined how safety narrative databases can be leveraged to share lessons learned. However, less attention has been given to augmenting existing processes for mining these safety reporting system databases. Aim: In this work, we introduce Kaona: An interface that weaves machine learning in existing aviation safety database mining activities. Method: We provide a use case of search, curation and newsletter writing to showcase how Kaona features build on existing processes and on its own to enhance information retrieval, curation and synthesis of narratives. Results: We created two instances of Kaona internally for evaluation, one using publicly available NASA’s ASRS narratives and another using publicly available C3RS narratives. Data ranged from 1998 to 2024. Conclusion: Our tool provides a new way to explore safety narratives, serving to re-imagine how text databases can benefit of novel information retrieval mechanisms in the era of large language models.

ASRS↗

NASA NTRSDate not supplied

Kaona: Deep Searching and Curating Aviation Safety Reporting Systems

Context: Several works in the literature have examined how safety narrative databases can be leveraged to share lessons learned. However, less attention has been given in augmenting existing processes of safety reporting systems. Aim: In this work, we introduce Kaona: An interface that weaves machine learning in existing aviation safety reporting systems activities. Method: We provide a use case of search, curation and newsletter writing to showcase how Kaona features build on existing processes and on its own to enhance information retrieval, curation and synthesis of narratives. Results: We created two instances of Kaona internally for evaluation, one using all public NASA's ASRS narratives and another using all public C3RS narratives. Data ranged from 1998 to 2024. Conclusion: Our tool provides a new way to explore safety narratives, serving to re-imagine how text databases can benefit of novel information retrieval mechanisms in the era of large language models.

asrs↗

NASA NTRSDate not supplied

Kaona: Deep Searching and Curating Safety Reporting Systems

Context: Several works in the literature have examined how safety narrative databases can be leveraged to share lessons learned. However, less attention has been given in augmenting existing processes of safety reporting systems. Aim: In this work, we introduce Kaona: An interface that weaves machine learning in existing aviation safety reporting systems activities. Method: We provide a use case of search, curation and newsletter writing to showcase how Kaona features build on existing processes and on its own to enhance information retrieval, curation and synthesis of narratives. Results: We created two instances of Kaona internally for evaluation, one using all public NASA's ASRS narratives and another using all public C3RS narratives. Data ranged from 1998 to 2024. Conclusion: Our tool provides a new way to explore safety narratives, serving to re-imagine how text databases can benefit of novel information retrieval mechanisms in the era of large language models.

asrs↗

NASA NTRSDate not supplied

Gap Analysis of UAS Manuals and Hazards

Emerging aviation includes the use of small Unmanned Aerial Systems (UAS) in novel operations. The manufacture and operation of these small UAS are not as regulated as today’s commercial operation, and their widespread use introduces new risks and hazards to the general public. Today, there are case-by-case approvals for sUAS operations, particularly for emergency response operations in which the potential benefits to use of sUAS is perceived to outweigh potential risks. We analyze operational approvals, procedures, and concepts of operation to identify and categorize the risks and hazards that applicants and approvers are already considering, and also identify barriers and mitigations that the operators have already put in place. This analysis may help lead to routine checklists that standardize safety analysis and lead to more routine operations.

grounded theory↗

NASA NTRSDate not supplied

State of the Art and Practice for Equity in Urban Air Mobility

Traditionally, new modes of transportation in the United States have benefited upper social classes at the expense of underrepresented and lower socioeconomic classes. Several recent studies in transportation have explored this disparity, and research has highlighted factors that contribute to transportation equity. In this effort, we will examine this previous work as it applies to the broader, current transportation system. We will use our literature search to highlight and educate the current emerging aviation stakeholders on equity strategies that are directly applicable to these novel operations. We will also use our literature research to make informed recommendations for experiments and data collection that will increase our understanding about how these new aviation concepts can be encouraged to provide equity as an emergent property.

transportation equity↗

NASA NTRSDate not supplied

Auna: A Geospatial System for Assessing Equity in Multimodal Mobility

Traditionally, new modes of transportation in the United States have benefited upper social classes at the expense of underrepresented and lower socioeconomic classes. Several recent studies in transportation have explored this disparity, and research has highlighted factors that contribute to transportation equity. In this effort, we will examine this previous work as it applies to the broader, current transportation system. Based on findings, we propose Auna, a tool to better visualize spatial data, including social injustice, ground and air mobility data.

GIS↗