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Record W1554145794 · doi:10.1109/ccst.2004.1405385

Intellifiber/sup TM/ fence sensor installation on alternative fence constructions

2005· article· en· W1554145794 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
TopicGeophysical Methods and Applications
Canadian institutionsSenstar (Canada)
Fundersnot available
KeywordsFence (mathematics)Computer scienceMicrophonicsTelecommunicationsEngineeringElectrical engineeringStructural engineering

Abstract

fetched live from OpenAlex

Perimeter intrusion detection systems using linear acoustic sensing cable are now widely used. Steel chain-link is one of the most common and inexpensive fence barrier materials, so is usually the medium on which these "microphonic" fence detection systems are mounted. In earlier papers we addressed a new sensor product, IntelliFIBER/spl trade/, which uses fiber-optic detection cables and described its performance when installed on such a barrier type. We reported how this fiber sensor has a variety of cable and other options that allow it to be adapted to the specific site need. However, we note that different countries or types of sites may have predominantly other fence constructions than chain-link, to meet their specific appearance or threat level needs for a delay or sensing barrier. Hence it is useful to indicate specifically how this new sensor can be installed and function for applications on those barrier types. For example in many countries there are what are termed "ornamental iron" or ornamental metal fences, consisting of angular or tubular rails and posts. We find that these are used extensively in VIP residences and industrial site headquarters, due to their attractive appearance. There are also a variant of these fences termed "palisade" fences that generally consist of vertical or arched rolled steel pales. One finds that these fences are used extensively in the UK in applications from tube stations to industrial campuses. Another fence construction consists of expanded metal panels, again used most extensively in European industrial sites but also in North America. With new terrorist threats of attack such fences may also have special constructions or modifications for high security, such as embedded vehicle anti-ram cables, or spiked toppings, which in turn require special sensor considerations. When deploying IntelliFIBER, as well as the fence type there are also specific mounting considerations for the sensor cable. For example it must be simply and economically mounted so as not to be easily damaged, and must not detract from the fence aesthetics. This paper considers the method of application of fiber optic sensors to these alternative barrier types. It describes deployment steps from mounting, to calibration for different types of threats, to recording of performance. Actual test data from installations including our Sensor Integrated Test Environment (SITE) are reported, along with comparison data from chain-link fences in the same environment.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.730

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)0.0000.001

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 head0.019
GPT teacher head0.262
Teacher spread0.244 · 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

Quick stats

Citations1
Published2005
Admission routes1
Has abstractyes

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