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Record W3194817223 · doi:10.1002/jnm.2946

QCA based cost efficient coplanar 1 × 4 <scp>RAM</scp> design with set/reset ability

2021· article· en· W3194817223 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 Numerical Modelling Electronic Networks Devices and Fields · 2021
Typearticle
Languageen
FieldComputer Science
TopicQuantum-Dot Cellular Automata
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsReset (finance)Quantum dot cellular automatonComputer scienceCellular automatonDissipationSet (abstract data type)Memory cellComputer hardwareParallel computingAlgorithmEngineeringElectrical engineeringTransistorPhysicsVoltage

Abstract

fetched live from OpenAlex

Abstract In this paper, a loop based coplanar random access memory (RAM) cell with set/reset ability using quantum‐dot cellular automata (QCA) technology is first proposed. The operation of the RAM cell is validated physically as well as by simulations using QCADesigner tool. The energy dissipation analysis of the proposed RAM cell demonstrates that the proposed design dissipates very low energy. Additionally, the fault tolerance to single cell missing and addition defects of the proposed RAM cell is also presented. Further, we designed a coplanar 1 × 4 RAM which consists of four proposed RAM cells, one 2:4 decoder and one 5‐input majority voter along with the control signals required for the proper operation of the RAM. The proposed RAM cell and 1 × 4 RAM designs achieve performance improvement of up to 88.16% and 79.28%, respectively from the existing design in terms of QCA circuit cost. These structures can therefore be used to design efficient higher order RAM structures.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.966
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.247
Teacher spread0.227 · 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