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Record W2113082301 · doi:10.1109/ccece.2002.1012948

ACAN - Ad hoc Context Aware Network

2003· article· en· W2113082301 on OpenAlexafffund
Mohamed Khedr, A. Karmouch

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsComputer scienceContext (archaeology)Wireless ad hoc networkProtocol stackComputer networkService discoveryProvisioningService (business)Distributed computingHuman–computer interactionWireless sensor networkWirelessWorld Wide WebTelecommunicationsWeb service

Abstract

fetched live from OpenAlex

This paper presents the design and system architecture of the Ad hoc Context Aware Network (ACAN), a wireless environment with no pre-configuration and with spontaneous applications running according to the contextual situation. The ACAN is a new vision to the future of the wireless networks where it will consist of sensors that will capture the entities in the environment and the surrounding users. A context manager agent will interpret the sensor captures information and process it to a higher level context data to be used by the Ad hoc application in a way to minimize the user attention while maximizing the relevance of the information provided. ACAN targets the network layer and the application layer and introduces new mechanisms for network configuration, QoS provisioning and more dynamic adaptable and flexible applications. We explain the architectural model of the ACAN with the required goals and specification, the ACAN new protocol stack is presented and the Context Aware Service Discovery Protocol (CASDP) with its advantages over the existing service discovery protocols.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.949
Threshold uncertainty score0.498

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 science0.0010.000
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 head0.013
GPT teacher head0.226
Teacher spread0.212 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations18
Published2003
Admission routes2
Has abstractyes

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