Joint Transmission Power Optimization and Connectivity Control in Asymmetric Networks
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Bibliographic record
Abstract
In this paper, the problem of transmission power optimization and connectivity control over asymmetric networks represented by weighted directed graphs (digraphs) is investigated using a centralized approach. The notion of generalized algebraic connectivity (GAC) introduced in the literature recently as a measure of connectivity in weighted digraphs is formulated as an implicit function of the network's transmission power vector. An optimization problem is then presented to minimize the total transmission power of the network while satisfying certain constraints on the GAC and transmission power. The interior point method is used to transform this constrained optimization problem into a sequential unconstrained optimization problem. Each subproblem is then solved numerically using the subgradient method with backtracking line search. Even though the GAC is a non-convex and non-differentiable continuous function of the network's transmission power vector, using the aforementioned methods the optimization problem gradually becomes convex as the number of iterations increases. Asymptotic convergence of the proposed algorithm to the global minimum of the original optimization problem is demonstrated analytically. The effectiveness of the algorithm is verified by simulations.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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