Development and Validation of Virtual Reality Application in Mining Education
Yutaka ITO; Masato TAKEUCHI; Shuto MIKAMI; Youhei KAWAMURA · 2020 · Journal of MMIJ
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Productivity, safety and its improvement is also an integral part of a good mining operation. In recent times, due to constraints on time and cost, it has become increasingly harder to conduct training and safety inductions at mine sites. For the purpose of overcoming these limitations, the use of virtual reality (VR) is proposed for mining education and training. VR has already been introduced in the education and training of miners overseas, and quantitative studies on the effects of using VR for miner's education and training have been made. However, Japan has only one such application
Abstract by Yutaka ITO; Masato TAKEUCHI; Shuto MIKAMI; Youhei KAWAMURA, Journal of MMIJ (2020) — licensed CC BY 4.0.
About to run something similar?
Run an AI Precheck on your own design to catch failure modes like this one before you spend the time. Your first desk check is free.
Related failures
t-Test at the Probe Level: An Alternative Method to Identify Statistically Significant Genes for Microarray Data
Negative / Null Result ReportMeteorological Causes of the Secular Variations in Observed Extreme Precipitation Events for the Conterminous United States
Negative / Null Result ReportThe Next Generation of Sepsis Clinical Trial Designs
Negative / Null Result ReportAnalysis of DNA Methylation in Young People: Limited Evidence for an Association Between Victimization Stress and Epigenetic Variation in Blood
Negative / Null Result ReportStudy preregistration: an early example and analysis.
Negative / Null Result ReportInsights Into LSTM Fully Convolutional Networks for Time Series Classification
WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: DOAJ · DOI 10.2473/journalofmmij.136.33
