Bibliographic record
Abstract
With today's system-on-chip (SOC) technology, we are able to design larger and more complicated application-specific integrated circuits (ASICs) and field programmable gate array (FPGA) in shorter time period. The key point of the success of SOC technology is the reuse of intellectual property (IP) cores. Consequently the copyright protection for these IP cores becomes the major concern for the development pace of SOC technology. Watermarking technology has been proved to be an effective way of copyright protection. In this thesis, the author presents two new watermarking algorithms respectively at algorithm level and FPGA layout level. The simulations and implementation results show that the new proposals have much less design and hardware implementation overheads, lower watermark embedding and extraction cost, as well as higher security strength, compared to the previously proposed methods.Dept. of Electrical and Computer Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2004 .D39. Source: Masters Abstracts International, Volume: 43-03, page: 0929. Advisers: H. K. Kwan; H. Wu. Thesis (M.A.Sc.)--University of Windsor (Canada), 2004.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".