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Record W2131021338 · doi:10.1109/ccst.1998.723779

Cost effective security system integration

2002· article· en· W2131021338 on OpenAlexaff
M. Maki, I.A. Newcomb, J.W. Robotham

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicEnergy Efficient Wireless Sensor Networks
Canadian institutionsSenstar (Canada)
Fundersnot available
KeywordsComputer scienceScalabilityInterface (matter)System integrationControl systemVariety (cybernetics)Embedded systemDistributed computingOperating systemEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

In earlier papers Senstar-Stellar outlined an integrated system of security devices that included control, communications and assessment capabilities. This paper reports on this new generation of systems, which features a cost-effective, easily scalable system platform that is applicable from small standalone security installations to larger networked systems. The main elements of this new system include: the integration of a wide variety of distributed sensor and device inputs and outputs; a redundant network with a fast and predictable response time; a multi-station operator control and display system that uses a real-time operating system and provides multiple interface device and language support; a centralized setup and maintenance system; and integrated assessment that provides sensory feedback. This paper outlines the system elements, including the new smart sensor components, illustrated by sample configurations that provide robust and economical security solutions for both small and large site applications.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.003
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.005

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 head0.015
GPT teacher head0.217
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations6
Published2002
Admission routes1
Has abstractyes

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