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Shubhanku Kochar, M. Phil. , Ph. D. CandidateDyslexia: A Critical Study of Language Deficiency in Children and Adolescents . Vaishali Narbheram Punjani, M. A. , M. Phil. B. Ed.


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In this study, vehicular wheel and transition ground speeds were obtained using DTGs, one of the broadly penetrated connected devices in Korea, to calculate wheel slip and acceleration data. After identifying strong relationships between the slip and the acceleration data on dry surfaces, three approaches, including regression analysis, SVM, and deep learning models, were applied to categorize the pavement states slippery or non slippery. As a result, SVM models resulted in reasonably good performances with an average accuracy of 96. 5%, although the deep learning model showed the best performance for one of the three analysis groups that has the largest sample size. A follow up experiment is scheduled in wintertime in 2021 to further investigate that the approach of this study can be applied for data from trucks and buses that carry several kinds of LBS devices for fleet management. In addition, deep learning algorithms need to be further investigated with more data in groups 2 and 3 in Table 2 to find out if the performance of group 1 can be applied to other groups with sufficient data.



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