This paper describes experiments on phonetic speech segmentation of audiobooks by using LSTM neural networks. The segmentation procedure includes an iterative adaptation of an initial speaker-independent model. The experimental data involves 5 audiobooks recorded by various renowned Czech speakers. Ab...

This paper deals with identification of noise covariance matrices of a dynamic system described by a linear discrete-in-time time-invariant stochastic state-space model. In particular, the parametric identifiability of the correlations methods is analysed and explicit relations for determination of a&...

Diabetes is a widespread civilization disease. When developing a new treatment method, in-silico benefits the development process by reducing the need for in-vivo subjects. In-silico evaluation requires a reliable metabolic model, often created as a multi-compartmental model. A common approach to...

Novel concepts like digital twins and X-in-the-Loop (XIL) simulations are being adopted in many new application areas by all entities in supply chains, including enterprises of all sizes as well as research institutes. However, they are not sufficiently addressed during control education...

A steam turbine is a complex device that is part of a turbogenerator. Detailed knowledge of the entire system and its parts is essential to ensure the stability of the machine. One of the most researched sources of forces acting on the rotor is the labyrinth seal.&#x...

In this paper we present a system for word-level sign language recognition based on the Transformer model. We aim at a solution with low computational cost, since we see great potential in the usage of such recognition system on hand-held devices. We base the recognition ...

Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, the difficulty of identifying plants, animals and fungi is hindering the aggregation&#...

The main goal of the third year of the SnakeCLEF challenge was to provide an evaluation platform that helps track the performance of AI-driven methods for snake species recognition systems on a global scale and allows direct comparison with human experts. We ran two challenges...

The main goal of the new LifeCLEF challenge, FungiCLEF 2022: Fungi Recognition as an Open Set Classification Problem, was to provide an evaluation ground for end-to-end fungi species recognition in an open class set scenario. An AI-based fungi species recognition system deployed in ...

This paper presents a novel method for turbinegenerator rotor torsional vibration monitoring. Torsional vibrations can be evaluated from an accurate knowledge of the angular velocity of the rotor. The input information for calculating the angular velocity is the data measured by an incr...

The complexity of state-of-the-art Deep Neural Network (DNN) architectures exacerbates the search for safety relevant metrics and methods that could be used for functional safety assessments. In this article, we investigate Neurons' Criticality (the ability to affect the decision process) for...

The paper describes the simulation environment for the autonomous battery management system for drones called Droneport. First, the problem of battery management is briefly described, and specific experimental and commercial solutions are listed. Then the concept of the proposed Droneport system&...

This article deals with the BTT method of blade vibration measurement used for condition monitoring of variable pitch axial fan blades. The efficiency of axial fans with variable pitch is controlled by adjustment of blade angle. BTT analysis may lead to incorrect results when ...

Recently, smart system integration was identified as a key competence for optimizing machines and robots. However, when one wants to ’tune’ the entire production process a step further is necessary. We should evaluate performance indicators (e.g. energy and material consumption) over the...

In this paper we present a hybrid neural network augmented physics-based modeling (APBM) framework for Bayesian nonlinear latent space estimation. The proposed APBM strategy allows for model adaptation when new operation conditions come into play or the physics-based model is insufficient (o...

This paper introduces Tiira – an open-source hardware-based Global Navigation Satellite Systems (GNSS) receiver and multi-sensor navigation system. Its unique features include system modularity, an openness of software and hardware designs, signal processing running in dedicated soft-core proces- sors ...

The paper considers the solution to the state estimation problem of nonlinear dynamic stochastic systems by the particle filters. It focuses on the marginal particle filter algorithms which generate samples directly in the marginal space for the recent state. Their standard implementation&#x...

The paper deals with the state estimation of nonlinear stochastic dynamic systems with special attention on a grid-based numerical solution to the Bayesian recursive relations, the point-mass filter (PMF). In the paper, a novel functional decomposition of the transient density describing the...

This paper presents a novel method for partial discharge detection. Generally, the presence of partial discharge in the power grid is unfavorable as it reduces the electricity transmission efficiency and also adversely affects the durability of the line. A partial discharge manifests it...

We introduce a novel fine-grained dataset and bench-mark, the Danish Fungi 2020 (DF20). The dataset, constructed from observations submitted to the Atlas of Danish Fungi, is unique in its taxonomy-accurate class labels, small number of errors, highly unbalanced long-tailed class distribution,...