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Record W2151634152 · doi:10.1109/wescan.1993.270518

Real-time dynamic arithmetic coding for low bit-rate channels

2002· article· en· W2151634152 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAlgorithms and Data Compression
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsHuffman codingArithmetic codingComputer scienceArithmeticVariable-length codeData compressionContext-adaptive binary arithmetic codingCoding (social sciences)AlgorithmDecoding methodsMathematicsStatistics

Abstract

fetched live from OpenAlex

The authors present an implementation and thereby demonstrate the capability of real-time and dynamic arithmetic coding in low-bit-rate serial communications channels. Data files from disk and text entered from the keyboard were compressed in real time using dynamic arithmetic coding. Each character in the source stream was compressed and an arithmetic code stream formed. The code stream was transmitted through an RS-232 channel at bit rates up to 19.2 kb/s. The effective transmission rate, kappa , is greater than the actual transmission rate, where kappa is equivalent to the achieved compression ratio for these low bit rates. Arithmetic coding achieves, on average, a reduction of 15% for binary files, 45% for text files, and up to 90% for special files such as bit maps. For each of these files arithmetic coding achieved better compression ratios than traditional entropy coding techniques, such as Huffman and Shannon-Fano. A software implementation on a 386 IBM compatible computer is described.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.991
Threshold uncertainty score0.485

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 communication0.0000.001
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 head0.018
GPT teacher head0.243
Teacher spread0.225 · 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

Quick stats

Citations5
Published2002
Admission routes1
Has abstractyes

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