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Estudos em transmissões multicasting de vídeo comprimido

2018· dissertation· pt· W2784607611 on OpenAlexaff
Leonardo Antônio de Andrade

Bibliographic record

Venuenot available
Typedissertation
Languagept
FieldComputer Science
TopicAlgorithms and Data Compression
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsHumanitiesPhysicsComputer scienceArt

Abstract

fetched live from OpenAlex

.\ impklnenta() de uma aplicao cliente/servidor de vdeo apresenta aspectos complexos e (ILIC exigem tratamento diferenciado, como trabalhar com arquivos que ocupam grande espao de armazenamento e fluxos de dados que necessitam de alta largura de banda para serem transmitidos. Quando o fluxo de dados compactado e a transmisso feita com tcnicas de a transmisso se torna ainda mais complexa. Um exemplo tpico a utilizao de ilColts Vl)P, ojtie podem ser perdidos e/ou chegarem ao destino desordenados, durante uma sesso ) de transmisso e recepo. Nesta dissertao so discutidas as implementaes de duas aplicaes cliente/servidor que exploram as tcnicas de ,,wi/i'a.rhuma delas possuindo suporte para 11'v4 e WFP, e a outra suporte para IPv4 ou IPv6). A problemtica do envio e recebimento de pacotes para posterior exibio do vdeo pelo cliente foi estudada e alguns testes foram feitos com os padres de compresso MJI) EG e um mtodo proposto, implementado com transformadas /'w/'e/e/.r e codificao 17W. Medidas e comparaes de desempenho foram realizadas, utilizando-se os sistemas operacionais Linux e Windows. As concluses obtidas com a metodologia aplicada a este trabalho podem contribuir para a soluo da problemtica da Iransmnisso de vdeo em ambientes Jill//%wo'i/g, especialmente para o caso de cxteflSOCS e refinamentos los nas iniplenientaes realizadas e no desenvolvimento de aplicaes que incluam OU 1 t( )5 COtlifR)liCI) tes de hardware e software, iv

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 categoriesMeta-epidemiology (narrow)
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 score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.027
GPT teacher head0.301
Teacher spread0.274 · 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.

Study designSimulation or modeling
Domainnot available
GenreMethods

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
Published2018
Admission routes1
Has abstractyes

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