ON THE COGNITIVE FOUNDATION AND ABSTRACT MEANS OF ENGINEERING DESIGNS
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
Formal inference processes in all kinds of engineering designs are based on the cognitive process and means of abstraction. This paper presents a formal treatment of system design. It first discusses the differences of system designs in abstract and concrete systems. A hierarchical abstraction model of system descriptivity (HAMSD) is developed that explains the abstract levels of entities and artifacts in both the concrete world and the abstract world. The HAMSD model classifies the design of a system at five levels known as the levels of (1) analogue objects, (2) diagrams, (3) natural languages, (4) professional notations, and (5) mathematics from the bottom up. According to the HAMSD model, an architectural, functional, or behavioral design of a system should adopt a higher-level abstract means to describe the system at a given abstract level, in order to obtain more powerful descriptivity and higher accuracy. Therefore, a mechanical system may be designed by using diagrams; while an information or software system can not be precisely described by diagrams. The reason is that the former is at an abstract level lower than the descriptive means of diagrams, but not so is the latter. Applications of the above findings in dealing with complicated problems in large-scale software system designs are discussed in the context of software engineering. Real-time process algebra (RTPA) is adopted as a highly abstract means in case studies on formal methodologies of software system design and modeling for software objects and design patterns.
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 | 0.001 | 0.001 |
| 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 | 0.000 | 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