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Record W2382278237

A new 3D Gaussian beams launching and predicting model in complex metropolis environment

2014· article· en· W2382278237 on OpenAlexaboutno aff
Tang Ya-pin

Bibliographic record

VenueChinese Journal of Radio Science · 2014
Typearticle
Languageen
FieldEngineering
TopicOptical Systems and Laser Technology
Canadian institutionsnot available
Fundersnot available
KeywordsDiffractionSuperposition principleRay tracing (physics)Beam tracingGaussian beamGaussianOpticsReflection (computer programming)Beam (structure)TracingGeometrical opticsDistributed ray tracingTransverse planeHeuristicM squaredBeam diameterPhysicsMathematicsComputer scienceMathematical analysisMathematical optimizationEngineeringQuantum mechanics
DOInot available

Abstract

fetched live from OpenAlex

The traditional Gaussian beam tracing and predicting model doesn't take a special treatment of diffraction effects,which are accounted for by superposition of transformed beam fields.A new 3D Gaussian beam-tracing and predicting model in complex metropolis environment is proposed.The beam tracing algorithm is based on geometrical optics and the uniform geometrical theory of diffraction.Diffraction effects are evaluated by using complex ray formulas and a new heuristic uniform diffraction coefficient for nonperfectly conducting wedges.The effects of propagation distance and order of reflection on predicting precision and complexity are also analyzed.The simulation results show that the precision of our new method is 0.02 to 2.2dB higher than old Gaussian beam-tracing method and meanwhile the calculation efficiency is decreased by 7.5 to 10 percent in Ottawa.And it is found that 12 is a good value for the order of reflection considering reflection loss and beam transverse extension.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.295

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.006
GPT teacher head0.211
Teacher spread0.205 · 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 designSimulation or modeling
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
Published2014
Admission routes1
Has abstractyes

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