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Record W1584414627 · doi:10.5772/17524

Smart Synergistic Security Sensory Network for Harsh Environments: Net4S

2011· book-chapter· en· W1584414627 on OpenAlexaff
Igor Peshko

Bibliographic record

VenueInTech eBooks · 2011
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicRadioactive contamination and transfer
Canadian institutionsWilfrid Laurier UniversityUniversity of Toronto
Fundersnot available
KeywordsComputer securityComputer science

Abstract

fetched live from OpenAlex

This chapter discusses the basic requirements for the design and algorithms of operation of a multi-parametric, synergistic sensory network -Smart Synergistic Security Sensory Network or Net4S -specially adapted for operation at nuclear power plants or other potentially dangerous sites. This network contains sensors of different types and is capable of analyzing the dynamics of environmental processes and predicting the most probable events. The discussion includes analysis of: 1) the technical aspects of operability of the sensors, optical and electrical telecommunication channels, and computers in the presence of ionizing radiation; 2) the influence of environmental parameters on the sensors' accuracy and network operability; and 3) the development of simulators capable of advising safe solutions based on the analysis of the data acquired by the Net4S. Such a real-time operating network should monitor: (1) environmental and atmospheric conditions -chemical, biological, radiological, explosive, and weather hazards; (2) climate/man-induced catastrophes; (3) contamination of water, soil, food chains, and public health care delivery; and (4) large public/industrial/government/military areas. Military personnel, police officers, firefighters, miners, rescue teams, and nuclear power plant personnel may use the mobile terminals (man-operated vehicles or unmanned robots) as separate multi-sensor units for local and remote monitoring. Among different types of sensors, only optical laser sensors can respond immediately and remotely. Such sensors can simultaneously monitor several gases, vapours, and ions with the help of single tunable laser; however, the use of several lasers operating at different, well separated wavelengths, dramatically improves accuracy and reliability, and increases the number of monitored substances. The Net4S, monitoring a number of parameters inside and outside a Nuclear Power Plant (NPP), can serve as the security, safety, and controlling system of the NPP. Besides the technical issues, the chapter also discusses the social aspects of the Nuclear Power Plants' design, construction, and exploitation. Some power consumption-free technologies that significantly improve the reliability of the Nuclear Power Plant are discussed.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.843
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.022
GPT teacher head0.214
Teacher spread0.193 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations3
Published2011
Admission routes1
Has abstractyes

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