Mathematics for Industrial Applications
Description
This book focuses on theories and applications of mathematics, statistics, and computing, where they intersect to address real-world problems in various industries. The papers contained within were presented at the 8th ICoMS-International Conference on Mathematics and Statistics, held in Athens, Greece, from September 24-26, 2025.
Organized annually since 2018, the ICoMS conference brings together leading researchers and practitioners from around the world to exchange knowledge and foster cross-disciplinary collaboration in both theoretical and applied fields. The core themes of the conference include, but it is not limited to, statistical inference, computational techniques, and applications involving high-dimensional data and complex datasets.
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Persons
Dário Ferreira is Assistant Professor at the University of Beira Interior, Portugal. He holds a Ph.D. in Mathematics (2006) from the University of Beira Interior, and a Master's degree in Applied Mathematics (2001) from the University of Évora, Portugal. His research interests lie in statistical inference for linear mixed models, particularly the estimation of variance components via algebraic structures and stochastic methodologies.
Dietrich von Rosen is Professor in Statistics at the Swedish University of Agricultural Sciences and Adjunct Professor at Linköping University, Sweden. Dr. Von Rosen holds a Ph.D. in Mathematical Statistics (1986) from Stockholm University. He is Editor-in-Chief of the "Journal of Multivariate Analysis" and has authored or co-authored the books "Advanced Multivariate Statistics with Matrices" (2005) and "Bilinear Regression Analysis: An Introduction" (2018), both published by Springer.
Nikolaos Limnios has been Professor (exceptional calss) at the University of Technology of Compiègne, France, since 1993. He holds a Ph.D. (1983) and a Doctorat d'Etat (1991) from the University of Technology of Compiègne. From October 2025 he is an Emeritus Professor at UTC. His research interests lie in stochastic processes (diffusion and Poisson approximation), statistical inference for stochastic processes, semi-Markov processes, and their applications in reliability, biostatistics, seismology, insurance, and finance. Dr. Limnios has participated in the editorial boards of several journals in the fields of probability and statistics and operation research. He has authored or co-authored several books, including "Semi-Markov Processes and Reliability" (Birkhäuser, 2001), "Semi-Markov Chains and Hidden Semi-Markov Models towards Applications" (Springer, 2008) and ''Discrete-time Semi-Markov Random Evolutions and Their Applications'' (Springer, 2023).
Sandra Ferreira is Assistant Professor at the University of Beira Interior, Portugal. She holds a Ph.D. in Mathematics (2006) from the University of Beira Interior and a Master's degree in Applied Mathematics (2001) from the University of Évora, Portugal. Her research interests lie in the fields of statistics and applied mathematics, particularly in statistical inference in linear models and the examination of statistical distributions.
Content
Delayed Acceptance Markov Chain Monte Carlo for Robust Bayesian Analysis.- New Chain Sampling Plans (NChSP-1) for Exponential Distribution.- Hypothesis Tests for Dierence in Zero-Truncated Poisson Parameters.- Constructing New Two-Sided Chain Sampling Plans (NTSChSP-1) using Minimum Angle Method (MAM).- Towards Drone-view Building Localization in the Wild: A Benchmark.- AI Doctor: A Friend or Foe? A Mathematical Analysis of the Impact of AI Doctors on Patients and Healthcare.- Generalization of Zeckendorf's Theorem to PLRS.- Differential Privacy Budget Allocation for Quantile Regression Analysis.- An Algebraic Approach for Computation of Invariant Manifolds in Non-Integrable Hamiltonian Systems.- Hyperbolic Cosine Function in Half-Discrete Hilbert's Inequality for Three Variables.- Mathematical Modeling-Based Analysis: Exploring the Need for Governments to Combat Illegal Wildlife Trade.- A Conceptual Framework for Artificial Intelligence Adoption in Data Architecture.