Interface Management for Telecommunication System Design through OPM and DSM-based Approaches
Bibliographic record
Abstract
Telecommunication systems require precise interface management and analysis as interactions play a key role in realizing the core functionality of such systems. This paper models and analyzes the interface relationships of different components of an industrial Reconfigurable Transmitarray Antenna system through Design Structure Matrix (DSM), which is a universal tool for precise interface management in various engineering disciplines. The novelty lies in the introduction of new types of interface relationships for telecommunication systems such as Radio Frequency, Electrical, Analog, and Digital, in an extension of typical interaction definitions in complex systems (Spatial, Structural, Energy, Material, and Informational). The approach presented in this paper aims to utilize and enhance systems engineering methods such as Object-Process Methodology (OPM) and DSM. While these tools have not been widely used to represent the nature of telecommunication systems, we demonstrate their potential to improve interface management process. The study of such a system led us to focus more attention on the signal flow as an interaction type. This type of focus is certainly less obvious in mechanical systems.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Systems-engineering interface management for a telecom antenna system.
This applies systems-engineering tools to telecommunications design rather than studying research practice.
Systems-engineering interface management for a telecom antenna product, not research methods.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".