An efficient emerging network and secured hopping scheme employed over the unsecured public channels
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With the emergence of new smart technologies, including the Internet of Things, wireless media are playing an important role to connect numerous devices to fulfill the requirements of newly developed communication systems. The massive connectivity, therefore, made the wireless spectrum too crowded and gave several challenges to resisting against potential wireless jammers. Note that, the two main challenges that have always been a part of any communication system, especially in the case of wireless communication, are information security and information jamming. Carefully considering the given challenges, this study uses a new advanced anti-jamming approach, a modulation technique based on the frequency-hopping spread spectrum, which has notably high resistance accounted against various potential jammers. The objective of this study is two-fold. First, the physical channel properties are considered, and the random bits are transmitted, employing a cryptographic secured hoping-spread pattern, having a set of carrier frequencies, known at both sides of the transmission. Second, the hashing code is computed only for the key, and transmitted along the original hopset, but with distinct frequencies set. The deployed practical anti-jamming approach, therefore, computed a high efficiency to examine the information secrecy well and primarily the connection availability even in the presence of the jammers. Moreover, this study considered and modeled a communication system and evaluated the proposed system’s performance, applying the theories of Shannon’s entropy and Wyner’s entropy (i.e. Wyner’s wiretap channel), to anticipate the system’s perfect secrecy, even in the worst case when jammer has unlimited computational capabilities.
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.
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it