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Record W2104956368 · doi:10.1109/ccece.2003.1226150

A framework of a Web-based distributed control system

2004· article· en· W2104956368 on OpenAlexafffund
L. Chen, Armin Eberlein

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicReal-Time Systems Scheduling
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceCommon Object Request Broker ArchitectureIntranetDistributed computingDistributed objectScheduling (production processes)Distributed design patternsDistributed control systemThe InternetOperating systemEmbedded systemControl (management)Distributed algorithm

Abstract

fetched live from OpenAlex

This paper describes a framework of a Web-based distributed control system (WBDCS) and the design and implementation of its software using a multitier client/server architecture and distributed object technology. The main issues addressed in this paper are the infrastructure of the system, the functionality of the components, and the real-time scheduling behavior of the application. CORBA is adopted to facilitate the communication between distributed objects across the Internet/intranet. Connectivity and controllability of on-line devices and their interaction with users are described. Because of the importance of timeliness in real-time systems, emphasis is put on time and event scheduling in the system. WBDCS features downloadable graphical user interfaces that display real-time status and process data of remote devices, allow an authorized user to access process variables and modify device configurations remotely. Built-in JNI ensures that customized control applications can be integrated into the distributed system. The programmable and reconfigurable framework of the system provides a flexible mechanism for constructing distributed real-time applications.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0050.002
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.003

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.

Opus teacher head0.009
GPT teacher head0.230
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2004
Admission routes2
Has abstractyes

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