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Now showing 1 - 5 of 378
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    Optimizing Wireless Connectivity: A Deep Neural Network-Based Handover Approach for Hybrid LiFi and WiFi Networks
    (MDPI, 2024-03-22) Usman Ali Khan, Mohammad; Inayatullah Babar, Mohammad; Rehman, Saeed; Komosný, Dan; Han Joo Chong, Peter
    A Hybrid LiFi and WiFi network (HLWNet) integrates the rapid data transmission capabilities of Light Fidelity (LiFi) with the extensive connectivity provided by Wireless Fidelity (WiFi), resulting in significant benefits for wireless data transmissions in the designated area. However, the challenge of decision-making during the handover process in HLWNet is made more complex due to the specific characteristics of electromagnetic signals’ line-of-sight transmission, resulting in a greater level of intricacy compared to previous heterogeneous networks. This research work addresses the problem of handover decisions in the Hybrid LiFi and WiFi networks and treats it as a binary classification problem. Consequently, it proposes a handover method based on a deep neural network (DNN). The comprehensive handover scheme incorporates two sets of neural networks (ANN and DNN) that utilize input factors such as channel quality and the mobility of users to enable informed decisions during handovers. Following training with labeled datasets, the neural-network-based handover approach achieves an accuracy rate exceeding 95%. A comparative analysis of the proposed scheme against the benchmark reveals that the proposed method considerably increases user throughput by approximately 18.58% to 38.5% while reducing the handover rate by approximately 55.21% to 67.15% compared to the benchmark artificial neural network (ANN); moreover, the proposed method demonstrates robustness in the face of variations in user mobility and channel conditions.
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    Hybrid Keys in Practice: Combining Classical, Quantum and Post-Quantum Cryptography
    (IEEE, 2024-02-10) Ricci, Sara; Dobiáš, Patrik; Malina, Lukáš; Hajný, Jan; Jedlička, Petr
    Currently, with the threat of quantum computer attacks, the idea of combining several same-type primitives has reemerged. This is also the case for cryptographic keys where a hybrid quantum key exchange combination allows for preserving the security guarantees of pre-quantum schemes and achieving quantum resistance of post-quantum schemes. In this article, we present a concrete 3-key combiner system implemented on a Field Programmable Gate Arrays (FPGA) platform. Our system involves a pre-quantum Key EXchange scheme (KEX), a post-quantum key encapsulation mechanism, and a Quantum Key Distribution (QKD) algorithm. The proposed 3-key combiner is proven to be secure in the quantum standard model and it is INDistinguishable under a Chosen-Ciphertext Attack (IND-CCA). Our combiner can run in small FPGA platforms due to its relatively low resources usage. In particular, the key combiner without QKD is able to output up to 1 624 keys per second and the key combiner with QKD is able to output up to 9.2 keys per second.
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    The effectiveness of glucocorticoid treatment in post-COVID-19 pulmonary involvement
    (BioMed Central, 2024-02-05) Mizera, Jan; Genzor, Samuel; Sova, Milan; Stanke, Ladislav; Burget, Radim; Jakubec, Petr; Vykopal, Martin; Pobeha, Pavol; Zapletalová, Jana
    RationalePersistent respiratory symptoms following Coronavirus Disease 2019 (COVID-19) are associated with residual radiological changes in lung parenchyma, with a risk of development into lung fibrosis, and with impaired pulmonary function. Previous studies hinted at the possible efficacy of corticosteroids (CS) in facilitating the resolution of post-COVID residual changes in the lungs, but the available data is limited.AimTo evaluate the effects of CS treatment in post-COVID respiratory syndrome patients.Patients and methodsPost-COVID patients were recruited into a prospective single-center observational study and scheduled for an initial (V1) and follow-up visit (V2) at the Department of Respiratory Medicine and Tuberculosis, University Hospital Olomouc, comprising of pulmonary function testing, chest x-ray, and complex clinical examination. The decision to administer CS or maintain watchful waiting (WW) was in line with Czech national guidelines.ResultsThe study involved 2729 COVID-19 survivors (45.7% male; mean age: 54.6). From 2026 patients with complete V1 data, 131 patients were indicated for CS therapy. These patients showed significantly worse radiological and functional impairment at V1. Mean initial dose was 27.6 mg (SD +/- 10,64), and the mean duration of CS therapy was 13.3 weeks (SD +/- 10,06). Following therapy, significantly better improvement of static lung volumes and transfer factor for carbon monoxide (DLCO), and significantly better rates of good or complete radiological and subjective improvement were observed in the CS group compared to controls with available follow-up data (n = 894).ConclusionBetter improvement of pulmonary function, radiological findings and subjective symptoms were observed in patients CS compared to watchful waiting. Our findings suggest that glucocorticoid therapy could benefit selected patients with persistent dyspnea, significant radiological changes, and decreased DLCO.
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    Effects of Micro-Scale Mobility and Beam Misalignment in On-Body mmWave Systems
    (IEEE, 2024-01-02) Ali, Asad; Galinina, Olga; Hošek, Jiří; Andreev, Sergey
    Wearable devices positioned on a human body have challenges in millimeter-wave (mmWave) communication due to micro-scale mobility, such as subtle shakes and rotations. These movements can compromise the radio link performance. It may be problematic for high-rate immersive applications, where this can lead to substantial degradation in the user’s quality of experience. In this letter, we propose a framework to quantify the impact of micro-scale mobility and beam misalignment on the performance of on-body mmWave links. Our findings reveal that for varying levels of beam misalignment, it is possible to adjust the antenna half-power beamwidth to enhance the data rates.
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    Design of fractional-order transitional filters of the Butterworth-Sync-Tuned, Butterworth-Chebyshev, and Chebyshev-Sync-Tuned types: optimization, simulation, and experimental verification
    (Elsevier, 2024-03-25) Mahata, Shibendu; Kubánek, David; Herencsár, Norbert
    This paper presents the optimal and generalized design of three different fractional-order (FO) transitional filters for the first time in the literature. The transitional filters considered are of the FO Butterworth-sync-tuned, the FO Butterworth-Chebyshev, and the FO Chebyshev-sync-tuned types. A metaheuristic swarm intelligence optimizer, namely the Crow Search Algorithm (CSA), helps to achieve the optimal FO filter model that minimizes the magnitude error with the theoretical function. The accuracy of the proposed approximants is examined for 19 different combinations of orders of the constituent filters for each of the three types of FO transitional filters. Comparisons with the modified stability boundary locus-based second-, third-, and fourth-order filter approximants demonstrate the compactness and superior accuracy of the proposed models. The average performance regarding the approximation accuracy, computational time, and convergence of CSA for solving the proposed filter design problems is investigated. Circuit simulations conducted on the OrCAD PSPICE platform for the proposed filter using the current feedback operational amplifier as an active element highlight good matching between the proposed model and theoretical filter function. Experimental validation is also carried out to justify the practical feasibility of the proposed filter with printed circuit board fabricated FO capacitor emulators.