A cloud-hosted hybrid framework for consuming Web Services on mobile devices
Bibliographic record
Abstract
As wireless network is becoming an standard access media in consuming Web Services for today's mobile devices such as smartphones and tablets, it is worth investigating the challenges involved in such network. Consuming Web Services over unreliable wireless network often faces the challenges of propagating data in real-time and synchronizing them across the framework. To overcome these challenges, there is an acute need for a distributed information framework that can disseminate events in real-time over wireless network. In this paper, we propose a hybrid of REST-based and publish/subscribe event based framework to provide reliable event dissemination in mobile environment. Our cloud hosted persistent WS service channels ensures a guaranteed delivery of event messages and the adopted durable subscription mechanism assists in synchronizing event messages in the face of disconnectivity in wireless network. A prototypical implementation of the framework has been conducted for disseminating healthcare information from our developed electronic pain diary application named PIn GO. The preliminary performance evaluations show that our proposed framework is feasible and reliable for mobile devices for disseminating information over wireless network.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".