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Abstract

The historical datasets at operating mine sites are usually large. Directly applying large datasets to build prediction models may lead to inaccurate results. To overcome the real-world challenges, this study aimed to handle these large datasets using Gaussian mixture modelling (GMM) for developing a novel and accurate prediction model of truck productivity. A large dataset of truck haulage collected at operating mine sites was clustered by GMM into three latent classes before the prediction model was built. The labels of these latent classes generated a latent variable. Two multiple linear regression (MLR) models were then constructed, including the ordinary-MLR (O-MLR) and the hybrid GMM-MLR models. The GMM-MLR model incorporated the observed input variables and a latent variable in the form of interaction terms. The O-MLR model was the baseline model and did not involve the latent variable. The GMM-MLR model performed considerably better than the O-MLR model in predicting truck productivity. The interaction terms quantitatively measured the differences in how the observed input variables affected truck productivity in three classes (high, medium, and low truck productivity). The haul distance was the most crucial input variable in the GMM-MLR model. This study provides new insights into handling massive amounts of data in truck haulage datasets and a more accurate prediction model for truck productivity.
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Authors and Affiliations

Chengkai Fan
1
ORCID: ORCID
Na Zhang
2
ORCID: ORCID
Bei Jiang
2
ORCID: ORCID
Wei Victor Liu
2
ORCID: ORCID

  1. University of Alberta , Edmonton, Department of Civil and Environmental Engineering, Alberta T6G 2E3, Canada
  2. University of Alberta , Department of Mathematical and Statistical Sciences, Edmonton, Alberta T6G 2G1, Canada
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Abstract

The article is an attempted analysis of the literary genre of fable as a case study of a selection of fables by Lyudmila Petrushevskaya. In particular, the analysis focuses on the fable cycles: The New Adventures of Helen the Beautiful, Adventures of Barbie and Wild Animal Fables. The perspective adopted in the article focuses mainly on the axiological aspect of the fables and the reconstruction of their moral message. The moral sense in Petrushevskaya’s fables is veiled under their overt sense. Even the overt sense is hidden deeply under the multiple levels of “intertextual irony” (Eco). The analysis also explores the links between Petrushevskaya’s works, folk magical fairy tales and the prototypical genre of the classical Russian fable. The innovative fables created by Petrushevskaya de-conventionalize the classical schemata of the genre, and as such they constitute an ironic, mocking and sometimes a bitter commentary on the contemporary world. The fables exhibit a high degree of “poetics of everyday life” – a merger of popular and high culture. They both recreate and at the same time mock the schemata and rituals of pop culture, also displaying noticeable feminist tones. In their poetics, the fables employ cyclic and serial arrangement, and are completed with “words of wisdom” that are far from naïve moral judgements.

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Authors and Affiliations

Anna Woźniak

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