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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.
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.
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.
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.
Spectral–Spatial Transformer-based Semantic Segmentation for Large-scale Mapping of Individual Date Palm Trees using Very High-resolution Satellite Data
(Elsevier, 2024-05-08) Al-Ruzouq, Rami; Gibril, Mohamed Barakat A.; Shanableh, Abdallah; Bolcek, Jan; Lamghari, Fouad; Hammour, Nezar Atalla; Al-Keblawy, Ali; Jena, Ratiranjan
Date palm plantations in the United Arab Emirates (UAE) are under threat from soil salinity, drought, and date palm weevils. Accordingly, monitoring and conserving date palms are crucial to preserving a vital component of the country’s agricultural heritage, economy, food security, and ecological balance. Previous studies have effectively identified date palm trees using RGB-based aerial and UAV imagery utilizing diverse deep learning methods. However, the utilization of very high-resolution satellite data for delineating individual date palm crowns remains unexplored due to the limited spatial resolution capabilities of existing satellite systems. This study primarily aimed to achieve precise and comprehensive mapping of date palm trees using WorldView-3 (WV-3) satellite data by leveraging the high representational power of the state-of-the-art vision transformers (ViT) in capturing global information from the input data. First, an in-depth analysis assessment of the various transformer-based semantic segmentation architectures, including UperNet with vision transformer and Swin transformer, SegFormer, Mask2Former, and UniFormer, was conducted. Second, the integration of spectral data on the performance of ViTs was evaluated. Moreover, the models’ generalizability and complexity effect on the segmentation effectiveness were assessed. Accordingly, a postprocessing strategy was developed to aid in delineating and counting date palm trees from semantic segmentation outputs. Results demonstrated that integration of WV-3 spectral data into the analysis resulted in a marked improvement in segmentation quality. The UniFormer, UperNet-Swin, and Mask2Former models demonstrated considerable improvements in multispectral data analysis, with increases in mean intersection over union (mIoU) of 2.17% (77.88% mIoU, 86.01% mean F-score [mF-score]), 2% (78.10% mIoU, 86.18% mF-score), and 1.15% (77.36% mIoU, 85.59% mF-score), respectively, compared with their RGB-based results. Evaluations of model transferability also indicated that Mask2Former, UniFormer, and UperNet-Swin transformers efficiently adapted to multispectral data in the Dibba region. These models achieved mIoU scores of 84.36%, 84.25%, and 83.17% and mF-scores of 90.95%, 90.87%, and 90.13%, highlighting their effectiveness and potential for broader regional application. This research highlights the efficacy and feasibility of using ViTs with WV-3 multispectral data for accurate and comprehensive surveying of date palm plantations, enabling the development of palm tree inventories and continuously updating geospatial databases.

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