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Record W2028323256 · doi:10.5539/cis.v3n2p180

Study on the Software Collaboration Framework Based on Internetware

2010· article· en· W2028323256 on OpenAlexvenueno aff
Hebiao Yang, Kai Chen

Bibliographic record

VenueComputer and Information Science · 2010
Typearticle
Languageen
FieldComputer Science
TopicMobile Agent-Based Network Management
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceSoftwareXMLSoftware engineeringPetri netProcess (computing)The InternetAsynchronous communicationDistributed computingWorld Wide WebProgramming language

Abstract

fetched live from OpenAlex

With the popularization of the new computation environment, internet, traditional software form has gradually not adapted the development and application under the internet environment. So a new generation software form with many characteristics such as independence, collaboration, response, evolution and multi-object, internetware is proposed. Its establishment depends on the effective collaboration among various distributed and asynchronous autonomous software entities in the opening environment. In the collaboration process, one important problem is how to effectively plan and adjust the topology structure among software entities to realize users’ demand in the dynamic environment. Aiming at this problem, several aspects including the organization and the assembling of the software entity and the evolvement of the topology are studied in this article, and concrete works include giving an internetware collaboration framework and flow model based on the Petri net and the mobile Agent technology, where the integrated model of internetware entities based on the Petri net reflects the ordered organization of the internetware entities in the problem space, and proving the support mechanism for the dynamically assembling among software entities based on the assembling model with the XML format, and using the influencing factors and the dynamic operation rules to describe several basic system evolvement activities.

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 categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.909
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
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 head0.012
GPT teacher head0.254
Teacher spread0.242 · 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
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

Citations0
Published2010
Admission routes1
Has abstractyes

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