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Record W2135039870 · doi:10.5539/cis.v5n6p6

A General Computational Framework and Simulations of Branching Programs of Boolean Circuits Using Higher Order Logic (HOL) Software - An Insight into ECAD Tool Design Paradigm

2012· article· en· W2135039870 on OpenAlexvenueno aff
Divyanshu Kumar, Qufu Weı

Bibliographic record

VenueComputer and Information Science · 2012
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsnot available
FundersBen-Gurion University of the NegevJiangnan University
KeywordsComputer scienceElectronicsSoftwareElectronic circuitBranching (polymer chemistry)CMOSConstruct (python library)PhotonicsSilicon photonicsAmplifierElectronic engineeringComputer architectureBandwidth (computing)Electrical engineeringTelecommunicationsOptoelectronics

Abstract

fetched live from OpenAlex

Integrated optics and Optical computing are now a mature technology offering many types of devices and manufacturing techniques. Recent breakthroughs in the ?eld of silicon photonics showed low-loss insulators, passive wave guide devices, high speed optical switches, detectors, silicon lasers, and silicon ampli?ers, optical amplifiers etc. These devices have provided the possibility to construct CMOS compatible optical circuits with low power consumption, high bandwidth and low latencies. A critical component that we intend to focus is on considering Branching Programs as CAD tools for the design of future electronics. Hence, BPs as viable means to accomplish the task of propelling the R&D of Electronics, are considered and simulated using HOL software based on boolean theory. We believe our research is one of the remarkable pioneering efforts, into the promising aspects of Branching Programs as CAD Tools.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
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 head0.035
GPT teacher head0.275
Teacher spread0.240 · 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 designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations1
Published2012
Admission routes1
Has abstractyes

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