Mathematical and Statistical Applications in Life Sciences and Engineering

Mathematical and Statistical Applications in Life Sciences and Engineering

Hardcover(1st ed. 2017)

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Product Details

ISBN-13: 9789811053696
Publisher: Springer Singapore
Publication date: 12/07/2017
Edition description: 1st ed. 2017
Pages: 372
Product dimensions: 6.10(w) x 9.25(h) x (d)

About the Author

AVISHEK ADHIKARI, M.Sc. (Gold Medalist), PhD from the Indian Statistical Institute, assistant professor at the Dept of Pure Mathematics, University of Calcutta, and foundersecretary of the IMBIC, India is a recipient of the President of India Medal and Young Scientist Award. He was a post-doctoral fellow at INRIA-Rocquencourt, France and a visiting scientist at Linkoping University, Sweden. He visited, on invitation, many institutions in India, Japan, Sweden, France, England, Switzerland and South Korea. His main interests are in cryptology, combinatorics, and algebra and its applications. He has published four textbooks on mathematics including Basic Modern Algebra with Applications (Springer) and edited one research monograph. He has published numerous papers in respected international journals, conference proceedings and contributed volumes. He is on the editorial board of several journals.

MAHIMA RANJAN ADHIKARI, PhD, founder president of the Institute IMBIC, India and former professor of Pure Mathematics at the University of Calcutta, is a recipient of the Gold medal. He has published several research papersand eight textbooks including Basic Modern Algebra with Applications and Basic Algebraic Topology and its Applications (both with Springer). He was elected president of the Mathematical Science Section (including Statistics) of the 95th Indian Science Congress, 2008. He has successfully guided several PhD students in 9 different areas of mathematics. He has visited several institutions in India, USA, UK, China, Japan, France, Greece, Sweden, Switzerland, Italy and many other countries on invitation.

YOGENDRA PRASAD CHAUBEY, PhD, is professor of Statistics at the Department of Mathematics and Statistics at Concordia University, Montreal, Canada. His research interests include sampling, linear models, distribution theory and nonparametric smoothing. His current research, funded by the Natural Sciences and Engineering Research Council of Canada’s discovery grant program, is focused on the nonparametric functional estimation. He has served on the editorial board of several statistical journals and is an elected member of the International Statistical Institute. He has edited three research monographs and published over 130 research articles in several international statistical journals, conference proceedings and book chapters.



Table of Contents

​Chapter 1.Perfectly Reliable and Secure Message Transmission.- Chapter 2.Hole: An Emerging Character in the Story of Radio k-Coloring Problem.- Chapter 3.Robust Control of Stochastic Structures using Minimum Norm Quadratic Partial Eigenvalue Assignment Technique.- Chapter 4. Single-time and multi-time Hamilton-Jacobi theory based on higher-orderLagrangians.- Chapter 5.On Wavelet Based Methods for Noise Reduction of cDNA Microarray Images.- Chapter 6.A Transformation for the Analysis of Unimodal Hazard Rate Lifetimes Data.- Chapter 7.The Power M-Gaussian Distribution: an R-Symmetric Analog of the Exponential-Power Distribution.- Chapter 8.Stochastic Volatility Models (SV) in the Analysis of Drought Periods.- Chapter 9.Nonparametric Estimation of Mean Residual Life Function Using Scale Mixtures.- Chapter 10.Something Borrowed, Something New: Precise Prediction of Outcomes from Diverse Genomic Profiles.- Chapter 11.Bivariate Frailty Model and Association Measure.- Chapter 12.On Bayesian Inference of P<(Y < X) for Weibull Distribution.- Chapter 13.Air pollution effects on clinical visits in small areas of Taiwan: a review of Bayesian spatio-temporal analyses.- Chapter 14.On Competing Risks With Masked Failures.- Chapter 15.Environmental applications based on Birnbaum-Saunders models.- Chapter 16.Response-Dependent Sampling and Observation of Life History Processes.- Chapter 17.Exact likelihood-based point and interval estimation for lifetime characteristics of Laplace distribution based on a time-constrained life-testing experiment.

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