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Record W2054703316 · doi:10.1109/mownet.2013.6613805

A cloud-hosted hybrid framework for consuming Web Services on mobile devices

2013· article· en· W2054703316 on OpenAlexaff
Rahnuma Kazi, Ralph Deters

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicPeer-to-Peer Network Technologies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsComputer scienceDisseminationSynchronizingWireless networkComputer networkEvent (particle physics)Cloud computingMobile computingWorld Wide WebWirelessTelecommunicationsTransmission (telecommunications)Operating system

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.451
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.013
GPT teacher head0.261
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2013
Admission routes1
Has abstractyes

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