Bibliographic record
Abstract
In this paper, we present a security data communication solution to resolve the problem of getting information in a secure way from the remote site in which no computer network is available. For this purpose, a programmed TI (Texas Instrument) product DSP (digital signal processor) TMS320LF2407 EVM is used to develop a compact DSP based device to acquire and store the information at the remote site, and be accessed via PTSN (public telephone switched network) though the serial communication interface module. Data integrity and data authentication are two important issues for secure data transmission. In this paper, two approaches are proposed to improve the security on both issues. First, a new algorithm is developed and implemented to produce a verification message for data authentication. This verification message is encrypted with an one way hash function based on the symmetric block cipher and suited for the 16-bit fix point DSP architecture. Also, this verification message will be changed for each data transmission in order to protect the eavesdroppers stealing this authentication information. Second, beside all the important data are encrypted with block cipher algorithm (Rijndael in this project), message authentication codes (MAC) approach is applied for both data transmission and the synchronous changing of the user information (e.g. user password, security key) at both sites (receiver and sender). In addition, some other functionary modules such as data format setting, timer of auto-connection and multimodem access are also implemented.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.009 |
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".