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Record W2051756223 · doi:10.1109/tmech.2014.2377116

Planar Cell Orientation Control System Using a Rotating Electric Field

2014· article· en· W2051756223 on OpenAlexaff
Chuan Jiang, James K. Mills

Bibliographic record

VenueIEEE/ASME Transactions on Mechatronics · 2014
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOrientation (vector space)Rotation (mathematics)Microscale chemistryElectric fieldComputer scienceControl systemField of viewVoltageControl theory (sociology)Computer visionArtificial intelligencePhysicsEngineeringMathematicsElectrical engineeringControl (management)Geometry

Abstract

fetched live from OpenAlex

In this paper, an automated cell orientation control system is proposed to reorient suspended cells in the plane, about a single axis of rotation. The system consists of a vision system, which images the suspended cell, a software system which estimates the cell orientation angle, and a rotating electric field, applied to rotate the suspended cell. The angular coordinate of the cell is used as a feedback in a closed-loop system to reorient the cell, rotating it to its desired angle. The closed-loop feedback system permits the suspended cell orientation to track reference input signals. A microscale device, energized with sinusoidal voltages, is used to generate a rotating electric field. This device was designed and fabricated using MEMS fabrication techniques. A vision-tracking algorithm to image and estimate cell orientation in real time was designed and implemented, based on the circular Hough transform. The cell is driven to its desired orientation angle with a PID controller using the estimated cell rotation angle as a feedback. Experiments have been carried out which demonstrate that the cell orientation control system performs well. A variety of tests have been performed, including step response and trajectory following. Cell orientation control may be used as one step in the general process of orienting cells for cell surgery.

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 score0.828
Threshold uncertainty score0.879

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 head0.007
GPT teacher head0.191
Teacher spread0.184 · 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

Citations24
Published2014
Admission routes1
Has abstractyes

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