Zobrazeno 1 - 10
of 2 349
pro vyhledávání: '"HD2321-4730.9"'
Autor:
Matei Hanu, Jürgen Hesser, Guido Kanschat, Javier Moviglia, Claudia Schillings, Jan Stallkamp
Publikováno v:
Journal of Mathematics in Industry, Vol 14, Iss 1, Pp 1-21 (2024)
Abstract This paper addresses the challenging task of guide wire navigation in cardiovascular interventions, focusing on the parameter estimation of a guide wire system using Ensemble Kalman Inversion (EKI) with a subsampling technique. The EKI uses
Externí odkaz:
https://doaj.org/article/933a9c3b47484a72b54c0a264250143e
Autor:
Bernadett Stadler, Roberto Biasi, Mauro Manetti, Andreas Obereder, Ronny Ramlau, Matteo Tintori
Publikováno v:
Journal of Mathematics in Industry, Vol 14, Iss 1, Pp 1-23 (2024)
Abstract In the design process of large adaptive mirrors numerical simulations represent the first step to evaluate the system design compliance in terms of performance, stability and robustness. For the next generation of Extremely Large Telescopes
Externí odkaz:
https://doaj.org/article/745e3cabd476421ab4f9ae09fdf9729f
Publikováno v:
Journal of Mathematics in Industry, Vol 14, Iss 1, Pp 1-22 (2024)
Abstract In this paper we propose an algorithm for testing whether the independent observations come from finite-variance distribution. The preliminary knowledge about the data properties may be crucial for its further analysis and selection of the a
Externí odkaz:
https://doaj.org/article/7092ed9c1ddb4821871d2f4fc02990f0
Publikováno v:
Journal of Mathematics in Industry, Vol 14, Iss 1, Pp 1-20 (2024)
Abstract In this work we focus on the development of a numerical algorithm for the inverse elastography problem. The goal is to perform an efficient material parameter identification knowing the elastic displacement field induced by a mechanical load
Externí odkaz:
https://doaj.org/article/eda79448eb3b4319922ee82c7225e7be
Autor:
Natascha Jeziorski, Claudia Redenbach
Publikováno v:
Journal of Mathematics in Industry, Vol 14, Iss 1, Pp 1-26 (2024)
Abstract Training defect detection algorithms for visual surface inspection systems requires a large and representative set of training data. Often there is not enough real data available which additionally cannot cover the variety of possible defect
Externí odkaz:
https://doaj.org/article/1d63fa5da74842179e971b0daf22cd1d
Publikováno v:
Journal of Mathematics in Industry, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract The molecular movement in single particle tracking (SPT) experiments shows a crucial role of diffusion in many biological processes such as signaling, cellular organization, transport mechanisms, and more. The SPT analysis detects not only c
Externí odkaz:
https://doaj.org/article/750f261e91cc44e189b5ed3f31650727
Autor:
Stephan Scholz, Lothar Berger
Publikováno v:
Journal of Mathematics in Industry, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract The chain rule is a standard tool in differential calculus to find derivatives of composite functions. Faà di Bruno’s formula is a generalization of the chain rule and states a method to find high-order derivatives. In this contribution,
Externí odkaz:
https://doaj.org/article/ef5bfa16dd004a9491cf9811928228f4
Publikováno v:
Journal of Mathematics in Industry, Vol 14, Iss 1, Pp 1-17 (2024)
Abstract In this paper we build a methodology for pricing of insurance-linked securities which are tied to multiple natural catastrophe perils. As a representative example, we construct a multi-peril catastrophe (CAT) bond which can be linked to the
Externí odkaz:
https://doaj.org/article/72970eb412054884ac88b9651104a667
Publikováno v:
Journal of Mathematics in Industry, Vol 14, Iss 1, Pp 1-18 (2024)
Abstract Functional data analysis is typically performed in two steps: first, functionally representing discrete observations, and then applying functional methods to the so-represented data. The initial choice of a functional representation may have
Externí odkaz:
https://doaj.org/article/a59cda2f2f1c4f38a0891cb249df8e81
Autor:
Richard Kwame Ansah, Alex Akwasi Opoku, Kassim Tawiah, Richard Kena Boadi, Bridget Nana-Ama Gana, Sampson Tackie, Maud Avevor Ayornu, Stephen Manu Ampofo Mills
Publikováno v:
Journal of Mathematics in Industry, Vol 14, Iss 1, Pp 1-17 (2024)
Abstract This paper employs a statistical mechanical model as a framework to investigate how socioeconomic factors of individuals such as gender and place of residence influence their decision when deciding between comprehensive and third-party motor
Externí odkaz:
https://doaj.org/article/b7aea9d9fb1b415593869dc7f110672c