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Record W1539076612 · doi:10.1109/icsmc.2005.1571234

Dealing with High Workload in Future Naval Command and Control Systems

2006· article· en· W1539076612 on OpenAlex

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMilitary Strategy and Technology
Canadian institutionsnot available
FundersNational Research Council Canada
KeywordsWorkloadComputer scienceTask (project management)Command and controlScheduling (production processes)ArchitectureOperator (biology)Task analysisControl (management)Real-time computingDistributed computingOperating systemArtificial intelligenceEngineeringSystems engineering

Abstract

fetched live from OpenAlex

In this paper we propose a system, the distributed adaptive task management system (DATMS), which assists operators and commanders to decide what tasks to perform, when, and by whom. It ensures that an acceptable level of workload is kept while tasks are carried out properly. The four modules that form the DATMS architecture are analyzed and solutions are provided: some guidelines are described for the workload measure module; a model based on relevant task and operator's features is considered for the workload prediction module; a rule based expert system handling four workload segments and dealing with uncertainty and fuzziness is proposed for the task distribution module; and Jensen's time/ utility functions are applied in the task scheduling module. A prototype demonstrates both the system architecture and the different solutions introduced in the modules.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.240

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.001
GPT teacher head0.137
Teacher spread0.136 · 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

Quick stats

Citations2
Published2006
Admission routes1
Has abstractyes

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