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Record W2392880880

Design of Data Management System for Satellite Earth Station Based on Socket

2010· article· en· W2392880880 on OpenAlexaff
Lihua Ma, Chunli Ning

Bibliographic record

VenueMicrocomputer Information · 2010
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Computational Techniques and Applications
Canadian institutionsL'Alliance Boviteq
Fundersnot available
KeywordsComputer scienceSoftwareOperating systemReliability (semiconductor)Mode (computer interface)Embedded systemReal-time computingSatellite
DOInot available

Abstract

fetched live from OpenAlex

A design method of the software framework for Data Management System (DMS) in earth station for low-rate Marine Environmental Monitoring System based CAPS was introduced and studied.The single and multi-data receiving modes of DMS were represented respectively.In comparison with the software frameworks design of client and server for DMS with the two modes,a multireceiving framework based socket technique for DMS was proposed finally.A multi -data receiving framework mode evolved from a single -receiving mode by using WinSock module in Windows environment were more efficient and reasonable,furthermore,having higher software reliability in system.The software implement designed for the earth station improved the effective utilization of server hardware,and reduced the cost in using earth ground hardware and human resource,as well as providing well technique support for the station operation and the system updating in future.

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)0.002
metaresearch head score (Gemma)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.030
GPT teacher head0.283
Teacher spread0.253 · 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
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
Published2010
Admission routes1
Has abstractyes

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