MAPPING WLAN COVERAGE AS A POTENTIAL COMPLEMENTARY SOURCE FOR GPS-BASED NAVIGATION IN INDOOR ENVIRONMENTS
Bibliographic record
Abstract
Enhanced-positioning systems are able to support the acquisition of accurate location information using wireless technology other than the Global Positioning System (GPS). These systems have the potential to supplement GPS where GPS is unreliable. In particular, enhanced-positioning systems can provide location information for navigational support and Location Based Services (LBS) indoors and in dense urban canyons and natural environments with extreme relief. The emergence of LBS and the widespread adoption of GPS-based navigation systems are largely a result of the accuracy with which GPS devices can determine location. The purpose of this study is to validate Wireless internet access points (WiFi APs) for determining location. This research follows three steps: 1.establish the accurate WiFi position for APs; 2. plot transects of signal strength for APs; and 3. interpolate a campus signal strength map from transect data for the University of Saskatchewan campus and validate that map. This is the first step towards the development of a non-GPS location system that can provide accurate location in a fashion that can be seamlessly integrated with GPS. 1.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".