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Record W2623509234 · doi:10.1145/3068796.3068814

Reactionless System Design through Decomposition and Integration Concept for Green Manufacturing

2017· article· en· W2623509234 on OpenAlexafffund
Dan Zhang, Bin Wei

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsControl reconfigurationInertiaComputer scienceDecompositionConstruct (python library)Linkage (software)Dynamic balanceControl engineeringPosition (finance)Mechanism (biology)Control theory (sociology)EngineeringControl (management)Mechanical engineeringEmbedded systemArtificial intelligence

Abstract

fetched live from OpenAlex

When mechanisms move, because the position of the center of mass (CoM) is changing and also the angular momentum is changing, there is vibration within the system, this can degrade the accuracy performance when the system is used in space. Dynamic balance can be applied to address the above problem. Normally, dynamic balancing is accomplished through employing counter-masses or counter-rotations approach. The potential issue is that the more weight and inertia are included inside the system, which is not cost-effective. Here the authors suggest that one can accomplish dynamic balancing condition based on employing the naturally dynamically balanced mechanisms rather than resorting to the old counterweights approaches. For instance, one can accomplish the reactionless condition based on the reconfiguration concept. One does not employ counter-mass but via reconfiguring the system by shifting the linkage, which does not make the system get to be heavy and therefore, reduce the energy costs and achieve green manufacturing. On the basis of this concept, firstly dynamically balance a single limb based on the reconfiguration technique (decomposition) and then integrate the balanced limbs to construct the entire parallel manipulator (integration); i.e. the decomposition and integration concept. Finally, with the mechanical reconfiguration, the control laws governing the operation of the mechanism also need to be changed.

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 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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.974
Threshold uncertainty score0.323

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 head0.022
GPT teacher head0.257
Teacher spread0.235 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2017
Admission routes2
Has abstractyes

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