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Record W2159874547 · doi:10.1117/12.702914

Hand held analog television over WiMAX executed in SW

2007· article· en· W2159874547 on OpenAlexaff
Daniel Iancu, Hua Ye, Murugappan Senthilvelan, Vladimir Kotlyar, John Glossner, Mayan Moudgill, Sitij Agrawal, Sanjay Jinturkar, Andrei Iancu, Vaidyanathan Ramadurai, Gary Nacer, Stuart Stanley, Mihai Sima, Jarmo Takala

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicMultimedia Communication and Technology
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsComputer scienceDecodesWiMAXComputer hardwareEncoderDigital signal processingDigital signal processorSIGNAL (programming language)MPEG-2Embedded systemDecoding methodsWirelessTelecommunicationsOperating system

Abstract

fetched live from OpenAlex

This paper describes a device capable of performing the following tasks: it samples and decodes the composite video analog TV signal, it encodes the resulting RGB data into a MPEG-4 stream and sends it over a WiMAX link. On the other end of the link a similar device receives the WiMAX signal, in either TDD or FDD mode, decodes the MPEG data and displays it on the LCD display. The device can be a hand held device, such as a mobile phone or a PDA. The algorithms for the analog TV, WiMAX physical layer, WiMAX MAC and the MPEG encoder/decoder are executed entirely in software in real time, using the Sandbridge Technologies' low power SB3011 digital signal processor. The SB3011 multithreaded digital signal processor includes four DSP cores with eight threads each, and one ARM processor. The execution of the algorithms requires the entire four cores for the FDD mode. The WiMAX MAC is executed on the ARM processor.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0340.016

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 head0.016
GPT teacher head0.280
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations2
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicMultimedia Communication and TechnologyFrench-language works237,207