Bibliographic record
Abstract
Modern sonar systems have greatly improved their sensor technology and processing techniques, but little effort has been put into display design for sonar data. The enormous amount of acoustic data presented by the traditional frequency versus time display can be overwhelming for a sonar operator to monitor and analyze. The recent emphasis placed on networked underwater warfare also requires the operator to create and maintain awareness of the overall tactical picture in order to improve overall effectiveness in communication and sharing of critical data. In addition to regular sonar tasks, sonobuoy system operators must manage the deployment of sonobuoys and ensure proper functioning of deployed sonobuoys. This thesis examines an application of the Ecological Interface Design framework in the interface design of a sonobuoy system on board a maritime patrol aircraft. Background research for this thesis includes a literature review, interviews with subject matter experts, and an analysis of the decision making process of sonar operators from an information processing perspective. A work domain analysis was carried out, which yielded a dual domain model: the domain of sonobuoy management and the domain of tactical situation awareness address the two different aspects of the operator's work. Information requirements were drawn from the two models, which provided a basis for the generation of various unique interface concepts. These concepts covered both the needs to build a good tactical picture and manage sonobuoys as physical resources. The later requirement has generally been overlooked by previous sonobuoy interface designs. A number of interface concepts were further developed into an integrated display prototype for user testing. Demos created with the same prototype were also delivered to subject matter experts for their feedback. While the evaluation means are subjective and limited in their ability to draw solid comparisons with existing sonobuoy displays, positive results from both user testing and subject matter feedback indicated that the concepts developed here are intuitive to use and effective in communicating critical data and supporting the user’s awareness of the tactical events simulated. Subject matter experts also acknowledged the potential for these concepts to be included in future research and development for sonobuoy systems. This project was funded by the Industrial Postgraduate Scholarships (IPS) from Natural Science and Engineering Research Council of Canada (NSERC) and the sponsorship of Humansystems Inc. at Guelph, Ontario.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".