Reconfigurable platform for 3D-panoramic telepresence system for mobile applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The concept of telepresence allows human beings to interact with hazardous environments and situations without facing any actual risks. Examples include the nuclear industry, outer space and underwater operations, mining, bomb disposal and firefighting. Recent progress in digital system technology, especially in technology of reconfigurable logic devices (e.g. FPGA), allows the effective implementation of advanced embedded systems characterized by high-performance data processing and high-bandwidth communication. However, most of the existing telepresence systems do not benefit from these advancements. Therefore, the goal of this work was to develop a concept and architecture of the platform for the 3D-Panoramic Telepresence System for mobile robotic applications based on reconfigurable logic devices. During the development process, two versions of the system were implemented. The first system focused on feasibility testing of major components of the proposed architecture. Based on the experimental results obtained on the first prototype of the system and their analyses, a set of recommendations were derived for an updated version of the system. These recommendations were incorporated into the implementation of the second and final version of the system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it