A GPS-Based Wander Management System for the Elderly
Bibliographic record
Abstract
The proportion of elderly population in Taiwan has been on the rise, as ageing society becomes a major issue. According to Taiwan's Ministry of the Interior, in 2016, the average life expectancy was 76.8 years for males and 83.4 years for females, showing a gradual annual rise, which when coupled with decrease in birth rate led to continuous increase in ageing. Prolonged life has resulted in escalated incident rate; usually, in an ageing society, the two main physiological problems that the elderly face are dementia and need for other people's concern. This study employs webpage-obtained GPS (Global Positioning System) records as the main analysis method by utilizing GPS records to analyze and examine elderly behavior so as to understand the elderly's movement positioning. We can also use the GPS records to examine data and determine a movement range; further analysis allows us to categorize movements as either usual or unusual activities in order to explore user behavior. Our system analyzes early behavior to further understand the elderly's message behavior and motivation and then issue warning or response.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".