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Record W2172070569 · doi:10.1109/igarss.1997.615891

Using JPEG data compression for remote moving window display

2002· article· en· W2172070569 on OpenAlexaffabout
Peter Shu‐Wai Leung, Michael Adair, J. Lam

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsComputer scienceRemote sensingReal-time computingSatelliteJPEGData compressionData transmissionTelecommunications linkComputer hardwareTelecommunicationsComputer visionEngineeringGeography

Abstract

fetched live from OpenAlex

CCRS operates two remote sensing data satellite receiving ground stations (one in Prince Albert, Saskatchewan and the other in Cantley, Quebec), capable of receiving RADARSAT data, which are geographically distant from the RADARSAT mission control and data processing centres. In order to provide sensor data quickly and downlink quality assessment to the mission control centre and for other time-critical monitoring applications (quality assurance, ice monitoring, etc.), CCRS has developed two FastScan systems with industry. Each Fastscan is capable of processing the RADARSAT downlinked data into imagery and generates a moving window display (MWD) in real-time. The MWD imagery is also JPEG compressed into digital browse imagery which is suitable for electronic transmission to a remote site immediately following downlink reception. At the remote site, these JPEG files will then be re-assembled back and displayed on a MWD station as a complete swath, simulating a near real-time reduced resolution MWD. This paper describes the hardware and software development of the remote MWD station and its data communication link to the two satellite ground stations.

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)0.000
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: none
Teacher disagreement score0.882
Threshold uncertainty score0.445

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 science0.0020.001
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 head0.202
GPT teacher head0.335
Teacher spread0.132 · 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
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
Published2002
Admission routes2
Has abstractyes

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