Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 225

The DOI matches its Crossref record.

Virtual Experiments in Metaverse and their Applications to Collaborative Projects: The framework and its significance

Open access
Suzuki, Sin-nosuke, Kanematsu, Hideyuki, Barry, Dana M., Ogawa, Nobuyuki, Yajima, Kuniaki, Nakahira, Katsuko T, Shirai, Tatsuya, Kawaguchi, Masashi, Kobayashi, Toshiro, Yoshitake, Michiko·2020·Procedia Computer Science

Abstract

This paper introduces and describes a learning system for analyzing devices in a virtual world and points out its significance for current research collaboration. Now we are in Society 5.0, so daily problems should be solved by IoT (Internet of Things) with a mutual collaboration without borders. The authors need to collaborate with each other among remote organizations and different nations. For such situations, we need to establish the learning system for analyzing devices which would lead to an actual sharing system in the future. In this paper, the proposed concept for the learning system in metaverse is explained. The significance of the system is described, too.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.procs.2020.09.249

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 225

Metadata

Authors
Suzuki, S.-N., Kanematsu, H., Barry, D. M., Ogawa, N., Yajima, K., Nakahira, K. T., Shirai, T., Kawaguchi, M., Kobayashi, T., & Yoshitake, M.
Venue
Procedia Computer Science
Publisher
Elsevier BV
Published
2020
Volume
176
Pages
2125-2132
ISSN
1877-0509 (ISSN-L)
OpenAlex
W3089889640
Cited by
225
References
0
FWCI
72.88
Type
conference paper
Language
en
Open access
diamond

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Virtual Experiments in Metaverse and their Applications to Collaborative Projects: The framework and its significance. https://app.cochat.ai/papers/10.1016/j.procs.2020.09.249
The paper
Suzuki, S.-N., Kanematsu, H., Barry, D. M., Ogawa, N., Yajima, K., Nakahira, K. T., Shirai, T., Kawaguchi, M., Kobayashi, T., & Yoshitake, M. (2020). Virtual Experiments in Metaverse and their Applications to Collaborative Projects: The framework and its significance. Procedia Computer Science. https://doi.org/10.1016/j.procs.2020.09.249

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.