American option pricing with an adaptive penalization strategy using the sparse grid combination technique combined with the Parareal-algorithm

My name is Anna Clevenhaus and I am a second year Phd-Student in the Applied Mathematics and Numerical Simulation (AMNA) group of the University of Wuppertal. My interest in numerical simulations and analysis started during my bachelor degree when I studied mathematics and chemistry. Afterwards I started with the international […]

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In new ways in the field of medical image analysis supported by artificial intelligence

For more than a decade data mining, including machine learning has been an active topic of research and teaching at the Mathematical Institute at the Eötvös Loránd University with the objective of keeping up a good balance of mathematical and engineering approach. In recent years it was a good base […]

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COVID-19 task force of mathematical modelling and epidemiological analysis in Hungary

Research on mathematical modelling of infectious diseases has been carried out at the Bolyai Institute of the University of Szeged for already 12 years. Earlier topics studied by the research group include strategies for influenza vaccination, the impact of mandatory varicella vaccination, the risk of measles outbreaks during the 2012 […]

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Analysis and extensions of Tellinen’s scalar hysteresis model

My name is Jan Kühn and I am a PhD student in the Applied Mathematics and Numerical Analysis (AMNA) working group of the University of Wuppertal. My bachelor degree was in applied science with the combination of mathematics and physics. The master degree was in mathematics with special focus on […]

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ECMI Webinar “Math for Industry 4.0 – Models, Methods and Big Data”, December 2 – 3, 2020

In a joint activity of the Special Interest Groups Mathematics for Big Data and Math for the Digital Factory of the European Consortium for Mathematics in Industry (ECMI) this workshop strives to bring together data scientists, mathematicians, and engineers from academia and industry to discuss recent developments in digital manufacturing. […]

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Markovchart: an R package for cost-optimal patient monitoring and treatment using control charts

This post is a follow-up on our previous one from 2019: In that one we discussed Markov chain-based cost-optimal control charts briefly and gave an example for their use on the data of diabetic patients. The goal of control charts (and generally of statistical process control) is to improve a […]

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PRecision crop protECtion: deep learnIng and data fuSION

Current farming practices require a uniform application of pesticides in order to protect crop plants from pest and disease. These treatments are typically repeated at regular time intervals. However, it is well known that several pests and diseases exhibit an uneven spatial distribution, with typical patch structures evolving around localized […]

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Data Assimilation by Nudging for Temperature Field in Rayleigh-Bénard Convection using active Particles

My name is Lokahith Agasthya and I am a PhD student in the Applied Mathematics and Numerical Analysis (AMNA) working group of the University of Wuppertal. Before this, I completed my Bachelors and Masters in physics from the Indian Institute of Science Education and Research, Pune, India. During my Masters, as part of my […]

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Modeling provincial Covid-19 epidemic data in Italy using an adjusted time-dependent SIRD model

The outbreak of the Covid-19 epidemics in early 2020 has caused an unprecedented effort of the scientific community to produce models that could monitor and predict the evolution of the epidemics in a reliable way, also to advice governments to take actions which could mitigate the burden of hospitals to […]

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EpideMSE – Epidemiological Modeling, Simulation and Decision Support of COVID-19

Intensice Care Bed Capacity

When the Covid19-Pandemic started in early 2020, Germany reacted with strict, acute nationwide measures that aimed at minimizing infection risk within the population. These included closing possible meeting locations such as schools, non-essential shops, playgrounds, restaurants and the like. Now that the numbers have declined, the government was and is faced with the dilemma of balancing citizens’ freedom rights against the risk of a new wave of infection. With smaller, but heterogeneously distributed outbreaks, local health authorities and politicians are now responsible for deciding on the degree of relaxation of protective measures in their administrative districts. There are currently numerous publications and pre-publications (cf. Flaxman, 2020) in which scientists analyze the current infection situation and attempt to predict the further course of the pandemic. Nevertheless, it cannot be expected that a district administrator or the head of the local health department will have the time and training to apply the study results, which were prepared for specific countries, regions or cities, to the situation in his or her district.

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