Using Web Services for Bridging End-User Applications and Wireless Sensor Networks
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
Applications are the ultimate consumers of the information collected by sensors. There exist several frameworks for the interactions between end-user applications and sensors. They range from low-level APIs to databases and include Web Services. This paper is devoted to the use of Web Services for bridging end-user applications and wireless sensors networks. Its first contribution is a systematic evaluation of the current frameworks for the interactions between end-user applications and wireless sensors networks. The evaluation shows the potential of Web Services, compared to the other frameworks and motivates their usage in the case study. The second contribution is the definition of Web Services for the I-centric telecommunication services, and their implementation in a wireless sensor network that does not support Web Services. We demonstrate that Web Services are very promising as "bridges" and share the lessons we have learned.
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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) | 0.000 | 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