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Record W2149884111

Computing Nice Sweeps for Polyhedra and Polygons

2004· article· en· W2149884111 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCanadian Conference on Computational Geometry · 2004
Typearticle
Languageen
FieldComputer Science
TopicComputational Geometry and Mesh Generation
Canadian institutionsCarleton University
Fundersnot available
KeywordsPolyhedronMonotone polygonCombinatoricsRegular polygonPolygon (computer graphics)MathematicsRectilinear polygonSimple polygonConvex polygonConvex setPolygon coveringKrein–Milman theoremConvex polytopeComputer scienceGeometryConvex optimization
DOInot available

Abstract

fetched live from OpenAlex

This paper does not deal with the sweeping paradigm itself; it deals with testing polygons and polyhedra to determine if they have a certain property. The properties that we consider are related to sweeping. We will test for a simple polygon or polyhedron if it can be swept by a line or plane such that every cross-section has a property like being convex or simply-connected. For example, to determine for a simple polygon (with interior) in the plane whether there is a sweep direction such that every cross-section is simplyconnected (a point, line segment, or empty) is the well-known question of determining whether a simple polygon is monotone in some direction. We solve two extensions of this problem in 3-space, and solve another extension in the plane. The first question we address applies to a polyhedron in 3space. We want to determine if there is a vector , such that if a sweeping plane with normal passes over , every cross-section of is convex. Toussaint [7] calls this property weakly monotonic in the convex sense. Obviously, for convex polyhedra, any vector gives only convex cross-sections during the sweep. For many nonconvex polyhedra no such vector exists. We give an time algorithm to find a vector if one exists, for a simple polyhedron with vertices. In case we allow more than one convex polygon in the cross-section, but no refle x vertices, we solve the problem in linear time. The second question deals with cross-sections of simple polyhedra that are always simply-connected. This property is called weakly monotonic [7]. Again the problem is to determine a vector , if one exists, such that any plane normal to intersects in a simple polygon. This cross-section may degenerate into a line segment, single point, or be empty. The cross-section may not become disconnected, nor may it contain a hole. We solve the problem in time. Thirdly, we consider sweeping a simple polygon with a line, but we allow the line to change its orientation. The problem is to determine if such a sweep exists that passes over the polygon , such that every cross-section is connected (generally, a single line segment). The problem is solved in quadratic time, also if we require additionally that the sweep line never goes back over any point of .

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.839
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.028
GPT teacher head0.264
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