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    Enhanced metabolomic predictions using concept drift analysis: identification and correction of confounding factors
    (Oxford Academic, 2025-04-04) Schwarzerová, Jana; Olešová, Dominika; Šabatová, Kateřina; Kvasnička, Aleš; Koštoval, Aleš; Friedecký, David; Sekora, Jiří; Dluhá, Jitka; Provazník, Valentýna; Popelinsky, Lubos; Weckwerth, Wolfram
    Motivation The increasing use of big data and optimized prediction methods in metabolomics requires techniques aligned with biological assumptions to improve early symptom diagnosis. One major challenge in predictive data analysis is handling confounding factors—variables influencing predictions but not directly included in the analysis. Results Detecting and correcting confounding factors enhances prediction accuracy, reducing false negatives that contribute to diagnostic errors. This study reviews concept drift detection methods in metabolomic predictions and selects the most appropriate ones. We introduce a new implementation of concept drift analysis in predictive classifiers using metabolomics data. Known confounding factors were confirmed, validating our approach and aligning it with conventional methods. Additionally, we identified potential confounding factors that may influence biomarker analysis, which could introduce bias and impact model performance. Availability and implementation Based on biological assumptions supported by detected concept drift, these confounding factors were incorporated into correction of prediction algorithms to enhance their accuracy. The proposed methodology has been implemented in Semi-Automated Pipeline using Concept Drift Analysis for improving Metabolomic Predictions (SAPCDAMP), an open-source workflow available at https://github.com/JanaSchwarzerova/SAPCDAMP.
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    Novel Second-Order Transfer Section for Frequency-Selective Response Generation in Comb Filters
    (IEEE, 2025-03-07) Šotner, Roman; Semenov, Dmitrii; Andriukaitis, Darius; Svoboda, Marek; Polák, Ladislav
    This article introduces a novel unified second-order filtering topology for standard band-reject (sBR) and inverting band-reject filter, enabling selective response generation. It is applied in the design of special comb filters that allow attenuation as well as amplification of specific bands. The presented solution offers several advantageous features in topology, enhanced cascadability, better parameter-setting performance, and the use of readily available off-the-shelf components, all while reducing overall costs. This is a significant improvement compared to the previous solutions in this field, which relied on a very expensive CMOS process. The topology employs a combination of an operational transconductance amplifier (OTA) and a current feedback amplifier. The intended center frequencies and transfer values of the comb filter are set to 50 Hz (-20 dB), 1 kHz (+26 dB), 10 kHz (+17 dB), and 100 kHz (-30 dB). The comb filter was experimentally verified via simulations as well as laboratory measurements utilizing LT1228 devices in a fabricated prototype.
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    Comments on "Transient Magnetic Shielding of a Planar Conductive ThinScreen via Exact Image Theory"
    (IEEE, 2024-05-14) Štumpf, Martin
    The main result of Lovat et al. (2023) is put into context of previously published papers on the subject. Its correction is described.
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    Characterizing the 80 GHz Channel in Static Scenarios: Diffuse Reflection, Scattering, and Transmission Through Trees Under Varying Weather Conditions
    (IEEE ACCESS, 2024-10-02) Závorka, Radek; Mikulášek, Tomáš; Vychodil, Josef; Blumenstein, Jiří; Chandra, Aniruddha; Hammoud, Hussein; Kelner, Jan M.; Ziółkowski, Cezary; Zemen, Thomas; Mecklenbräuker, Christoph; Prokeš, Aleš
    The deployment of wireless systems in millimeter wave relies on a thorough understanding of electromagnetic wave propagation under various weather conditions and scenarios. In this study, we characterize millimeter wave propagation effects from measurement data, utilizing channel impulse response analysis with a focus on root mean square delay spread and Rician K-factor. The obtained results highlight the significant influence of weather conditions and foliage on propagation, including diffuse reflection, scattering, and absorption. Particularly, we observed a notable increase in scattering from deciduous trees with leaves, in comparison with bare trees or ones covered by snow or ice. The attenuation of the signal propagated through a tree with foliage is 2.16 dB/m higher compared to a bare tree. Our validation measurements within a semi-anechoic chamber confirmed these observations and aided in quantifying the differences. These findings offer valuable insights into the dynamics of millimeter-wave signals that are important for advancing wireless communication technologies.
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    Short-Term Entropy of Signal Energy Used for Effective Detecting of Weak Gunshots in Noisy Environments
    (MDPI, 2024-07-30) Sigmund, Milan
    Conventional gunshot detection systems can quickly and reliably detect gunshots in the area where the acoustic sensors are placed. This paper presents the detection of weak hunting gunshots using the short-term entropy of signal energy computed from acoustic signals in an open natural environment. Our research in this field was primarily aimed at detecting gunshots fired at close range with the usual acoustic intensity to protect wild elephants from poachers. The detection of weak gunshots can extend existing detection systems to detect more distant gunshots. The developed algorithm was optimized for the detection of gunshots in two categories of the surrounding sounds, short impulsive events and continuous noise, and tested in acoustic scenes where the power ratios between the weak gunshots and louder surroundings range from 0 dB to -14 dB. The overall accuracy was evaluated in terms of recall and precision. Depending on impulsive or noise sounds, binary detection was successful down to -8 dB or -6 dB; then, the efficiency decreases, but some very weak gunshots can still be detected at -13 dB. Experiments show that the proposed method has the potential to improve the efficiency and reliability of gunshot detection systems.