Day 2 :
Keynote Forum
Ramalingam Shanmugam,
Texas State University, USA
Keynote: Correlation and distance concepts together suggest impaired driving due to alcohol than marijuana is menace to road safety
Time : 09:45-10:35
Biography:
Ram Shanmugam is the Editor-in-Chief for the journals: Epidemiology & Community Medicine, Advances in Life Sciences and Health, and Global Journal of Research and Review. He is the Associate Editor of the International Journal of Research in Medical Sciences. He is the Book-Review Editor of the Journal of Statistical Computation and Simulation. He directed Statistics Consulting Center in the Mississippi State University. In 2015, he has published a textbook with the title “Statistics for Engineers and Scientists”. He served the Argonne National Lab., University of Colorado, University of South Alabama and the Indian Statistical Institute. He has published 125 research articles and is a Fellow of the International Statistical Institute. Currently, he is a Professor in the School of Health Administration, Texas State University. He is a recipient of several research awards from the Texas State University
Abstract:
Sometimes, repeated experience with accidents makes people to believe and conclude that impaired driving due to alcohol or marijuana is menace to road safety. However, policy makers on road safety require data evidence authenticated interpretations. What statistical methodologies now exist to do so to help policy makers? For this purpose, this exploratory and tutorial article is written with data analyses and interpretations of actual number of fatal accidents caused by impaired driving during 2013-2015 in USA (as reported in Arnold and Teft 2016). This research work first convinces, using regression analysis, that the driver’s age is not a significant predictor of fatal accidents. Then, in a novel manner, it mixes correlation and Mahalanobis distance concepts to create an approach to check whether impaired driving due to alcohol or marijuana is a serious menace to the road safety. In conclusion, this research work finds that just by eliminating impaired drivers due to alcohol (but not marijuana) could ensure road safety 16.02 times closer to an ideal situation of no fatal road accident
Keynote Forum
Mikhail Moshkov
King Abdullah University of Science and Technology, Saudi Arabia
Keynote: Extensions of dynamic programming for machine learning and knowledge representation
Time : 10:55-11:40
Biography:
Mikhail Moshkov is Professor in the CEMSE Division at King Abdullah University of Science and Technology, Saudi Arabia since October 1, 2008. He earned Master’s degree from Nizhni Novgorod State University, received his Doctorate from Saratov State University, and Habilitation from Moscow State University. From 1977 to 2004, he was with Nizhni Novgorod State University. Since 2003, he worked in Poland in the Institute of Computer Science, University of Silesia, and since 2006 also in the Katowice Institute of Information Technologies. His main areas of research are complexity of algorithms, combinatorial optimization, and machine learning. He is author or co-author of five research monographs published by Springer
Abstract:
We discuss so called multi-pruning which allows us to construct classifiers (decision trees) that outperform often classifiers constructed by CART. This approach is based on the construction of the set of Pareto optimal points for bi-criteria optimization problem relative to the size of decision trees and the number of misclassifications. The second topic is connected with multi-stage optimization of decision rules relative to the coverage and length. Based on this optimization procedure, we can simulate the work of greedy algorithm for the set cover problem. As a result, for many datasets from UCI ML Repository, we can construct small systems of enough accurate decision rules that cover the most part of objects (rows). The end of the presentation is devoted to the introduction to KAUST
- Bioinformatics|Biometrics Applications|Cyber security|Statistical Methods|Clinical Biostatistics|Computational Systems Biology
Location: Houston, USA
Chair
Bin Li
Takeda Pharmaceuticals International Co., USA
Co-Chair
Ajit Kumar Roy,
Central Agricultural University, India