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Survey of latest technologies on Decentralized applications using Blockchain

2022· article· en· W4221018432 on OpenAlexaff
N Sasikala, B. Meenakshi Sundaram, Sougata Biswas, A Sai Nikhil, V S Rohith

Bibliographic record

Venue2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS) · 2022
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology Applications and Security
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsBlockchainComputer scienceSoftwareScheme (mathematics)Asset (computer security)World Wide WebArchitectureSoftware engineeringComputer securityDatabaseOperating system

Abstract

fetched live from OpenAlex

In recent years, Websites and Web applications have been playing a significant role in everyday life. In the past decade, the number of websites progressed from three million to more than 1.7 billion. The majority of contributions to this number are produced by CMS (content management systems). Current content delivery and management services has many issues in securing data, and are vulnerable to cyberthreats. Hence, one of the methods to create apps transparent and flexible is by implementing Deoentralized applications (Dapps). This paper describes the major security issues of cms and propose an efficient scheme to build a cms dapp on the most familiar blockchain platform-Ethereum. The main Blockchain has 2 categories: partially DApp and fully DApp for the software architectures in DApps. The full and partial Dapps have their own advantages and disadvantages. Here in this paper, a software architecture for full and partial DApp focusing on simulating asset transactions for comparing both the DApps efficiency has been proposed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.687
Threshold uncertainty score0.862

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 communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.078
GPT teacher head0.301
Teacher spread0.223 · 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 designTheoretical or conceptual
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

Citations5
Published2022
Admission routes1
Has abstractyes

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