Personal and service mobility in ubiquitous computing environments: Research Articles
Bibliographic record
Abstract
Ubiquitous computing environment is defined by the shift of computing technology from the desktop to the background. One of its most notable attributes is its potential to extend the scope of service and personal mobility. This paper describes an agent-based architecture that brings personal and service mobility to the ubiquitous computing environment. A software agent, running on a portable device carried by the user, leverages the existing service discovery protocols to learn about all services available in the vicinity of the user. Short-range wireless technology such as Bluetooth can be used to build a personal area network connecting only devices that are close enough to the user. Acting on behalf of the user and based on a number of aspects, the software agent runs a quality of service (QoS) negotiation and selection algorithm to select the most appropriate available service(s) to be used for a given communication session. The software agent selects as well the configuration parameters for each service. The proposed architecture supports also service hand-off to recompense for service volatility during user movement. Copyright © 2004 John Wiley & Sons, Ltd.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".