Intelligent Monitoring and Control of Industrial Processes Through the Internet
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
This paper presents a framework for developing a universal network infrastructure that would allow web-based monitoring and control of industrial processes, research facilities, and academic experiments. Internet technology is used here for its versatility, wide availability, and relative low cost. The main element of the infrastructure is a web-server, which connects to multiple control-servers, which in turn are connected to various processing modules within a local industrial facility, Since the web-server is the system centerpiece, which provides smooth information flow, a robust, intelligent, and autonomous scheduling scheme is required. Once such infrastructure is established, remote users in an academic or research environment, or in an industrial environment will be able to carry out a variety of tasks including experiments, monitoring and supervision, process scheduling and reconfiguration, using a web-browser. The flexibility and modularity of the developed networked infrastructure provide the rationale for implementing a multi-level hierarchical monitoring and control structure for a process. The usefulness of such a hierarchical structure is demonstrated through an application example on an industrial fish processing machine, which incorporates intelligent adaptive control.
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 | 0.000 | 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