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Record W1982327179 · doi:10.1145/1551950.1551971

Facilitating 4G convergence using IMS

2009· article· en· W1982327179 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIPv6, Mobility, Handover, Networks, Security
Canadian institutionsQueen's University
Fundersnot available
KeywordsIP Multimedia SubsystemComputer scienceQuality of service3rd Generation Partnership Project 2Computer networkNext-generation networkConvergence (economics)Authentication (law)Service (business)WirelessTelecommunicationsComputer securityWorld Wide WebTelecommunications linkThe Internet

Abstract

fetched live from OpenAlex

In order to achieve the Fourth Generation of wireless communications (4G) goal of convergent and omnipresent communications and services, an efficient service delivery platform is necessary. The most promising services platform is the IP Multimedia Subsystem (IMS) as defined by the Third Generation Partnership Project. IMS provides a reliable and efficient architecture that supports multiple service categories while maintaining QoS and managing many aspects of the network such as authentication and accounting Utilizing IMS and enhancing its components to provide the abovementioned services can significantly help in building the envisioned ubiquitous 4G environment that consists of a standardized IMS core with extended capabilities. In this paper we describe how 4G convergence and mobility enhancement can be achieved via IMS. We also present a survey of current IMS convergence schemes for 4G.

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.

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 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: Empirical
Teacher disagreement score0.207
Threshold uncertainty score0.727

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.014
GPT teacher head0.233
Teacher spread0.219 · 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