An Investigation of Race Hazard Elimination in Digital Counter Circuits
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".