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Record W4389565660 · doi:10.33102/iiecons.v10i1.90

DEVELOPMENT OF QUANTUM COMMUNICATIONS TECHNOLOGY (QCT) IN MALAYSIA

2023· article· en· W4389565660 on OpenAlexaboutno aff
Nurul Huda, Mustafa Mohd Hanefah, Rosnia Masruki, Nor Asiah Yaakub

Bibliographic record

VenueI-iECONS e-proceedings · 2023
Typearticle
Languageen
FieldComputer Science
TopicQuantum Computing Algorithms and Architecture
Canadian institutionsnot available
FundersUniversiti Malaysia Perlis
KeywordsContext (archaeology)Information and Communications TechnologyThe InternetVariety (cybernetics)Computer scienceChinaTelecommunicationsPolitical science

Abstract

fetched live from OpenAlex

The transfer of information from one single device to another has been more secure in recent years through to the development of quantum communication technology (QCT) in a variety of technological uses. Preparing for this new, emerging sector is important since information communication technology (ICT) in the future will certainly depend on QCT, which is built on quantum physics laws to secure the transfer of information. Future quantum technology will not only optimize computers and the internet but also change the way we communicate. This study discusses the importance and impact of QCT in the context of national security, framework, and policy. Furthermore, this paper also discusses the latest research trends of QCT in several countries including the United States, Canada, and China that Malaysia can learn from. In addition to that, this paper traces the development of QCT policy in other countries along with the existing development of security policy and framework in Malaysia. Finally, this paper discusses the importance of QCT with recommendations.

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: Other · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.262
Teacher spread0.241 · 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
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

Citations0
Published2023
Admission routes1
Has abstractyes

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