Intellifiber/sup TM/ fence sensor installation on alternative fence constructions
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".