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Record W4415701938 · doi:10.23977/jeeem.2025.080117

An Investigation of Race Hazard Elimination in Digital Counter Circuits

2025· article· W4415701938 on OpenAlexvenueno aff

Bibliographic record

VenueJournal of Electrotechnology Electrical Engineering and Management · 2025
Typearticle
Language
FieldEngineering
TopicLow-power high-performance VLSI design
Canadian institutionsnot available
Fundersnot available
KeywordsReset (finance)Asynchronous communicationRobustness (evolution)Sequential logicAsynchronous circuitHazardFilter (signal processing)Combinational logicControl theory (sociology)

Abstract

fetched live from OpenAlex

Race hazards, which can lead to premature asynchronous resets or erroneous state transitions, occur when concurrent signals with different propagation delays arrive at the nodes of a combinational logic circuit. This paper investigates a modulo-13 counter centered on the SN74LS161N IC. A critical race hazard scenario is constructed in Multisim by intentionally introducing signal delays, and two common suppression strategies are evaluated: (1) connecting a parallel capacitor at the reset node to form an RC low-pass filter for analog pulse smoothing; and (2) using a 74ALS175M flip-flop to edge-register the outputs before the reset logic in a structured timing approach. Simulation results demonstrate that the RC filter significantly attenuates narrow pulses at low frequencies but introduces reset latency. In contrast, the registering method transforms sub-cycle instability into clean edge-sampling, trading a one-clock-cycle delay for enhanced robustness and scalability. This study provides a practical reference for the engineering implementation of race hazard elimination in counter circuits.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.506
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.003
GPT teacher head0.195
Teacher spread0.192 · 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 teacher head, not a consensus.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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