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František Gašpar (FJFI)26/06/2023, 17:15
This presentation delves into the essential rules and guidelines, as outlined by norm ISO 80000 and the guidelines of CTU in Prague, for writing math text, aiming to improve the clarity, accessibility, and visual appeal of mathematical content. We will explore the fundamental principles of mathematical typography, including the appropriate usage of symbols, notation, and formatting...
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Jitka Hrabáková (FIT CTU)27/06/2023, 09:30
The contribution study the minimum distance density estimators based on Kolmogorov and Cramér -von Mises distance. Inequalities between Kolmogorov and Cramér -von Mises distances are proven to achieve $n^{-\gamma}$ consistency in (expected) L$_1$ norm of M(CM)E. Further, the generalized Cramér - von Mises distance is defined together with so called Kolmogorov - Cramér distance which includes...
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Antonie Brožová27/06/2023, 09:50
Inverse problems in imaging, like denoising, inpainting or superresolution usually require a suitable regularization of prior to achieve good reconstruction results. It was shown that untrained neural networks can replace traditional handcrafted priors and achieve superior performance. This contribution will focus on Deep Image Prior, the pioneering work utilizing untrained neural priors, its...
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Jan Thiele27/06/2023, 10:10
In this presentation, we investigate the performance enhancement of the DBSCAN algorithm through robust preprocessing techniques. We explore the impact of data whitening, geometric median, and the pursuit method for variable selection and estimation in high-dimensional models. The use of these techniques, including the estimators of scale $S_n$ and $Q_n$ introduced by Rousseeuw and Croux,...
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Kristina Jarůšková (FNSPE CTU in Prague)27/06/2023, 11:00
Detector simulations are an important component of the research in High Energy Physics. However, the current Mote Carlo-based simulation tools are computationally intensive and finding a faster alternative is necessary. This talk focuses on the current development in the domain of using deep learning models for calorimeter simulations, namely the experimentation with transformer neural networks.
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Anna Guľa Gartman27/06/2023, 11:20
The Deep Underground Neutrino Experiment (DUNE) is a long baseline neutrino oscillation experiment hosted by the Fermi National Accelerator Laboratory (Fermilab). Beyond its primary focus on advancing neutrino physics, DUNE also aspires to explore the possibility of proton decay, which holds the potential to provide evidence for grand unified theories.
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The DUNE far detector comprising four 10... -
Mrs Michaela Krbálková (Faculty of Transport Engineering, University of Pardubice; Faculty of Science, University of Hradec Králové)27/06/2023, 11:40
Studying recent empirical traffic data, we show surprising statistical anomalies in the traffic microstructure that can not be explained by current scientific approaches used in physics of traffic. We introduce the concept of Balanced Particle Systems as an effective mathematical instrument for a description of statistical properties of vehicular microstructure, quantify these anomalies...
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Tereza Siváková29/06/2023, 09:15
This presentation focuses on the specification of user's preferences in decision-making, particularly in cases where users have limited knowledge of decision-making (DM) theory and express their preferences incompletely.
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The decision-making task is solved by a fully probabilistic design (FPD), which models a closed loop between the user and the system. The FPD introduces an ideal probability... -
Mr Aleksej Gaj (Department of Mathematics, FNSPE, Czech Technical University in Prague)29/06/2023, 09:35
Contemporary decision making (DM) theory stands on classical probability. However, it has been shown that there is a variety of situations when the decision theory fails to explain some psychological and cognitive effects observed in human decision making. Other aspects not covered by the classical approach are that the results of merging information depend on the order of merging, or that the...
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Jiří Nábělek29/06/2023, 09:55
In this presentation, we will focus on mathematic approaches to optimal control systems for rolling stock. We will discuss several formulations of optimal control problems for trains and trams. We will then look into optimising the energy consumption under various constraining conditions, including the available power and force, time schedule, and speed limits. We will present the tram optimal...
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Nichita Vatamaniuc29/06/2023, 10:15
The analysis of biomedical data on musculoskeletal disorders using data provided by motion sensors. The patient's features are extracted from the signal represented as power in dB. The feature dimensionality is then reduced using Data Whitening and classified into two classes: healthy and diseased. Two different methods are used for classification: SVM and MLP.
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Mr Milan Chlada29/06/2023, 11:15
With the development of hardware capabilities in the field of acoustic emission signal measurement, the directional radiation of elastic waves from a fatigue crack-type source has been observed. The configuration of the sensors on a model pipe-type body is based on a detailed numerical analysis. It allows the confirmation of the effect of random directionality of the emission source, which has...
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Jan Zavadil29/06/2023, 11:35
This contribution deals with the recognition of acoustic emission signals for use in non-destructive defectoscopy or in machining process control. Classification can either be performed by representing signals by a convenient, lower-dimensional set of attributes or more directly, by passing them in their entirety to the classification algorithm. We focused on selecting methods and tools for...
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Zuzana Dvořáková29/06/2023, 11:55
Localization of continuous acoustic emission (generated, e.g. by leakage) is a very important problem in the field of non-destructive testing, but especially due to wave dispersion, velocity, and/or geometry changes the localization is still a challenge. An effective tool to overcome these problems is time reversal (TR) signal processing, which works very well in the case of burst acoustic...
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Jaromír Kukal (FNSPE CTU in Prague)29/06/2023, 14:00
The PDF of a positive continuous random variable $X$ can be too complex for direct evaluation e.g. when $X$ is a sum of the positive continuous random variables. But when the characteristic function $\psi(t)$ of $X$ is known, we can employ $N=2^k$ point FFT to obtain a table of PDF with equidistant spacing for the interpolation of $\mathrm{f}(x_k)$ and for $k=1,\ldots,m$. Adequate time...
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Quang Van Tran (KSI, FNSPE, CTU in Prague)29/06/2023, 14:20
We propose a multifactor asset pricing model for evaluation of excess return of ČEZ a.s. stock which is derived from the Asset pricing theory. Besides the market risk, factors, that can affect the performance of ČEZ a.s. stock, are also added. They are the price of electricity, the price of natural gas, the price of CO2 emission permits and index of industrial production. Taking into account a...
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Eliška Pečenková29/06/2023, 14:40
We study statistical modelling of clearances and critical clearances, which are the main subjects of the Gap Acceptance Theory. First, we define a mathematical model of an unsignalized T-intersection, and then we specify the problem of the partial distribution of clearances of order $k\in\mathrm{N}_0$. Assuming Generalized Inverse Gaussian (GIG) distribution of clearances and critical...
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Daniel Khol29/06/2023, 15:20
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Yana Podlesna29/06/2023, 15:40
Presented work investigates deep learning methods, focusing on Temporal Fusion Transformer (TFT), for multi-horizon forecasting of energy demand in power systems. The TFT model's performance is benchmarked against traditional machine learning models such as XGBoost and Random Forest and evaluated over 6-hour and 24-hour ahead predictions. The TFT's capacity for handling temporal dependencies...
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Daniel Khol (Department of Mathematics, FNSPE, Czech Technical University in Prague)
Graphs and Markov chains can be represented by matrixes. One of the most common representations is the Laplacian matrix. This presentation summarises the spectral clustering of undirected graphs. Then we consider a basic approach to spectral clustering of directed graphs by the symmetric graph. Then we show a new approach to the Laplacian matrix for directed graphs using incidence matrix M for...
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Martin Kunz (Department of Mathematics, FNSPE, Czech Technical University in Prague)
Structured illumination microscopy (SIM) is a powerful imaging technique that has revolutionized the field of superresolution microscopy. This talk aims to provide an overview of SIM and highlight its numerous benefits over other superresolution methods.
SIM utilizes patterned illumination to overcome the diffraction limit posed on resolution in optical microscopy, enabling the...
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