An analysis of the evolution of the South African law on the warranty against latent defects

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Electrical characterization of process- and radiation-induced defects in 4H-SiC

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A multi-variate approach to posture

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Assessing mitochondrial function, oxidative stress, and vitamin D status in dark-skinned patients with keloid disease

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Acclimation of apple peel to light and temperature and the effect thereof on red colour development and tolerance to sunburn by Barasu, Prince Dogbeda

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Diagnosis and prognosis of rolling element bearings at low speeds and varying load conditions using higher order statistics and artificial intelligence

“…Although many models have recently been applied with good generalization of results in predicting the RUL of bearings where they integrate the statistics (like the Kaplan-Meier estimator, Mahanalobis distance, principal component analysis (PCA) etc.) and artificial intelligent (AI) methods (e.g. artificial neural network (ANN), feed forward neural network (FFNN), recurrent neural network (RNN) etc.), it has been proven that using only the statistical method is not sufficient to give good predictions, but a hybrid of both methods often yield good results. exTSFRLSA is used on most occasions for tuning, adjusting parameters and for adaptation in the propagation model by comparing predicted and measured defect sizes as in, hence the instantaneous rate of defect propagation of the bearing can be captured despite defect growth behavior variation.…”
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Integration of Multi-State Systems in a series of EPQ models for deteriorating products

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Ethical dilemmas in orthognathic surgery involving minors. by Beukes, Jureenus Botha

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