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Record W2917110949 · doi:10.1177/1550147719829960

Case studies of communications systems during harsh environments: A review of approaches, weaknesses, and limitations to improve quality of service

2019· review· en· W2917110949 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

VenueInternational Journal of Distributed Sensor Networks · 2019
Typereview
Languageen
FieldEngineering
TopicSmart Grid Security and Resilience
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsComputer scienceRisk analysis (engineering)Strengths and weaknessesCommunications systemQuality (philosophy)Service (business)Computer securityQuality of serviceTelecommunicationsBusiness

Abstract

fetched live from OpenAlex

The failure of communications systems may cause catastrophic damage to human life and economic activities as people are unable to communicate with each other in a timely manner and with a convenient quality of service. Therefore, the exchange of information is more than necessary for people in their everyday life or during harsh environments to prevent the death and injury of thousands of individuals. The study of communications systems behavior in harsh environments helps to design or select more resilient technologies that are capable of operating in challenging conditions. This article reviews existing approaches, major causes of failure, and weaknesses of communications systems during extreme events. First, we highlight the importance of communications systems, and then we examine related works, how communication may fail, and the effect of this failure on human life in general and during extreme events response. Furthermore, we study and analyze how communications are used during various stages of extreme events, and we identify the main weaknesses and limitations that communications systems may suffer based on many case studies. To conclude, we identify and discuss relevant attributes, requirements, and recommendations for communications systems to perform with a suitable quality of service during harsh environments and to reduce risks of communication failure in challenging conditions.

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)0.001
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: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.336
Threshold uncertainty score0.848

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.166
GPT teacher head0.351
Teacher spread0.185 · 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