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Record W2250733480 · doi:10.14288/1.0052050

Incorporating affect into the design of 1-D rotary physical controls

2011· article· en· W2250733480 on OpenAlexaff
Colin Swindells

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHuman–computer interactionComputer scienceMechatronicsAffect (linguistics)Rendering (computer graphics)Process (computing)Affective computingPsychologyArtificial intelligence

Abstract

fetched live from OpenAlex

The visceral emotional reactions that users have to technologies is increasingly understood to be important in terms of safety, performance, and pleasure in its own right. This thesis systematically explores users's emotional (affect) reactions to everyday physical manual controls, in order to inform a design process that considers appropriate affective response as well as performance relationships. Design of both mechanical and emerging mechatronic physical controls are addressed. This novel design process includes parameterizing second order (inertial) dynamics using a system identification technique, and rendering models on a custom force-feedback knob. Next, this thesis explores biometric and self-reported measures of the affective responses elicited by these dynamics, and an iterative prototyping tool for rapid refinement of the "feel" of physical controls. This research impacts use of the passive physical interfaces such as mechanical knobs and sliders that are already ubiquitous in our everyday environments, as well as the active physical controls that are emerging in embedded computing environments such as cars, games, and medical devices.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.943
Threshold uncertainty score0.168

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 science0.0010.000
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 head0.035
GPT teacher head0.262
Teacher spread0.228 · 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

Citations4
Published2011
Admission routes1
Has abstractyes

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