RISC-V Based Processor Architecture for an Embedded Visible Light Spectrophotometer
Bibliographic record
Abstract
The miniaturization of sensing systems often requires embedding an electronic subsystem for local or edge computing, or to interface with the sensor for pre-processing operations. The sensing part of the work presented in this paper is an optoelectronic system that measures neurotransmitters concentration based on visible spectroscopy and that is currently implemented with an external processor in a computer. This paper presents a System on a Chip (SoC) design based on the RISC-V processor and the required peripheral interfaces to replace the current system. The new design is first simulated and then implemented on Cyclone IV and Xilinx ZCU102 FPGAs to explore the usability and advantages of the approach. Both architectures were similar in terms of memory and register use, but the ZCU102-based system used 18016 logic elements, while the Cyclone IV-based one used much less, 13468 logic elements. We also observed a significant difference in frequency of operation, with Cyclone IV was running at 27.84 MHz and ZCU102 at 125 MHz clock speeds.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".