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Record W140974939

Developing component-based Web transaction systems with Servlet/JSP and CORBA.

2001· article· en· W140974939 on OpenAlexaffabout
Nan. Zhang

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2001
Typearticle
Languageen
FieldComputer Science
TopicService-Oriented Architecture and Web Services
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsCommon Object Request Broker ArchitectureComputer scienceComponent (thermodynamics)Database transactionDatabaseOperating systemJavaBeansWorld Wide WebJava
DOInot available

Abstract

fetched live from OpenAlex

Web has evolved from a network of basically static information display to a mechanism for interactive Web application. Currently, web creates for enhancing business processes, reducing costs and increasing profits. With component-based computing and MVC design pattern, web application could be developed easily, less expensively, deployed flexibly across platform, adapted to new technology quickly. Rapid delivery of business-critical information over the Internet and Corporate intranets requires a transaction-processing solution that integrates the functionality of multiple objects, provides these objects with access to multiple data sources, and ensures data integrity, scalability, and security across every business transaction. Moreover, certain runtime services should be developed to support Web applications. The ability to easily locate application components, access and execute them securely, and ensure their availability are critical factors to deploying Web applications in Internet, intranet, and extranet environments. To meet increasing need, we develop a viable approach for web transaction systems based on the component-based system development in this thesis work. This approach adopts the distributed, component-based development principle and is based on MVC design pattern. This approach offers the flexibility, scalability, and reliability necessary to support the constant evolution of business processes in the e-business world. And a prototype, which based on our infrastructure design, is also developed to validate the feasibility and effectiveness of the proposed approach. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2000 .Z527. Source: Masters Abstracts International, Volume: 40-03, page: 0730. Thesis (M.Sc.)--University of Windsor (Canada), 2001.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.003

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 head0.197
Teacher spread0.181 · 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 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
Published2001
Admission routes2
Has abstractyes

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