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Record W2014063159 · doi:10.1108/17440080580000090

Developing applications for internet telephony: A case study on the use of web services for conferencing in SIP networks

2005· article· en· W2014063159 on OpenAlexaff
May El Barachi, Roch Glitho, Rachida Dssouli

Bibliographic record

VenueInternational Journal of Web Information Systems · 2005
Typearticle
Languageen
FieldComputer Science
TopicService-Oriented Architecture and Web Services
Canadian institutionsResearch CanadaEricsson (Canada)Concordia University
Fundersnot available
KeywordsComputer scienceVoice over IPTelephonyThe InternetSIP trunkingWeb serviceTelecommunicationsWorld Wide WebWeb developmentTeleconference

Abstract

fetched live from OpenAlex

Applications offered to end‐users as value‐added services play a vital role in the success of Internet telephony service providers. Today’s standard frameworks for developing them have several shortcomings that motivate the need for novel frameworks. Web services are an emerging paradigm for program‐to‐program interactions over the Internet. This paradigm is a prime candidate for application development in Internet Telephony because it may aid in addressing the drawbacks of today’s standard frameworks. This paper presents a case study that gives insights in the suitability of Web services as a standard framework for the development of conferencing applications in Internet Telephony. The case study includes the definition and the implementation of a novel Web service for conferencing, the implementation of the conference server in a SIP environment, the development of several conferencing applications (including a game), and performance evaluation. Based on this case study, we conclude that Web services are very promising for conferencing application development in Internet Telephony, especially as the performance can be significantly improved with the emerging techniques that are briefly discussed in the paper.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.648
Threshold uncertainty score0.412

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.048
GPT teacher head0.293
Teacher spread0.245 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations9
Published2005
Admission routes1
Has abstractyes

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