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Record W2025908978 · doi:10.1109/iscc.2007.4381516

A Performance Evaluation of a Hybrid Multicast Transport Protocol for a Distributed Collaborative Virtual Simulation of a Brain Tumor Tele-Surgery Class of Applications

2007· article· en· W2025908978 on OpenAlex
Azzedine Boukerche, Haifa Raja Maamar, Abu Hossain

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

VenueProceedings - IEEE Symposium on Computers and Communications/IEEE Symposium on Computers and Communications · 2007
Typearticle
Languageen
FieldDecision Sciences
TopicSimulation Techniques and Applications
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMulticastProtocol (science)Computer scienceClass (philosophy)Computer networkDistributed computingMedicineArtificial intelligence

Abstract

fetched live from OpenAlex

Haptic interfaces have been designed for brain surgery simulation may prove to be especially useful for training surgeons to conduct minimally invasive procedures and remote surgery using tele-operators. However, it well known that collaborative, haptic, audio and visual environments (C-HAVE) suffer from setbacks due to network delay, scalability, reliability and synchronization problem when the users are geographically distributed. In this paper, we focus upon a Brain Tumor Tele-Surgery application that is based on closely coupled and highly synchronized haptic tasks that require a high-level of coordination among the participants. We considered four main protocols: the synchronous collaboration transport protocol (SCTP), the selective reliable transmission protocol (SRTP), the reliable multicast transport protocol (RMTP) and the scalable reliable multicast (SRM) and presented a hybrid protocol that is able to satisfy all the CVE and C-HAVE requirements and discuss its implementation using brain tumor tele-surgery application as a case study.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.664
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.092
GPT teacher head0.392
Teacher spread0.301 · 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