СОДЕРЖАНИЕ
MATHEMATICS AND COMPUTER SCIENCE
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ABSTRACT. This work presents a comparative evaluation of fine-tuning strategies for automatic speech recognition (ASR) across various Armenian dialects. The analysis employs three state-of-the-art multilingual models – Whisper Large v2, Whisper Large v3, and SeamlessM4T v2—to assess the impact of different adaptation strategies on Word Error Rate (WER) and Character Error Rate (CER) under low-resource and dialectally diverse conditions. Three fine-tuning strategies are examined: dialect-specific training, multidialect joint training, and two-stage hierarchical fine-tuning. The best performance was achieved with the Whisper Large v3 model using the two-stage fine-tuning approach, reaching an average WER of 23.7% and CER of 8.9% across all dialects. The findings demonstrate that fine-tuned multilingual ASR models significantly outperform existing Armenian speech recognition systems, underscoring the importance of targeted adaptation for low-resource languages such as Armenian. |
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Melkonyan V. Autonomous UAV Control Based on Camera Video PDF📥 ABSTRACT. This paper presents a vision-based autonomous control system for unmanned aerial vehicles (UAVs) designed to intercept and track moving targets using onboard camera data. The proposed approach integrates real-time visual feedback with a dynamic control mechanism that continuously adjusts the UAV's trajectory based on the estimated target position. |
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Kirakosyan L. System for detection and intelligent suppression of UAV communication channels PDF📥 ABSTRACT. The paper presents an intelligent UAV radio monitoring and countermeasure system based on software-defined radio (SDR). The system performs continuous spectrum scanning, signal classification using a convolutional neural network (CNN), and automatically activates a multiband jamming module upon detection of UAV control or telemetry signals. Experimental results demonstrated a classification accuracy of 97.82% and high efficiency of selective jamming |
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Sahakyan V. Autonomous UAV Navigation without GNSS PDF📥 ABSTRACT. Reliable navigation in GNSS-denied environments remains a major challenge for small unmanned aerial vehicles. When satellite signals are lost or degraded, the vehicle must rely entirely on onboard sensing to maintain control and return safely. This work presents a lightweight fallback navigation framework that combines inertial dead reckoning and optical flow-based velocity estimation. Both methods were implemented and tested in the PX4 Software-in-the-Loop environment with Gazebo, allowing safe and repeatable evaluation under simulated wind and signalloss conditions. Results show that dead reckoning ensures short-term stability but accumulates large drift over distance, while optical flow navigation provides meter-level accuracy over multi-kilometer trajectories. Together, they offer a practical and fully autonomous alternative to GNSS for small UAVs operating in constrained or adversarial environments. |
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PHYSICAL AND TECHNICAL SCIENCES
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ABSTRACT. This paper examines the research and design of an optical signal processing system for a distributed antenna array operating in the microwave range. Traditional signal processing systems, such as radar and direction-finding stations, are highly effective but become vulnerable to attacks and suppression once detected. The proposed concept is based on the use of electro-optical modulators (EOM), which convert radio frequency signals into optical signals for subsequent transmission via fiber-optic communication lines. This approach significantly reduces system vulnerability by enabling the placement of the main signal processing equipment at a considerable distance from the antennas, ensuring its safety. In the event of an attack, the loss is limited to the antenna, thus improving the overall survivability of the system under hostile conditions. Another advantage is the transition to optical technologies, which ensure lower signal losses compared to radio frequency cables, where losses can reach tens of dB over the same length. |
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BIOLOGICAL SCIENCES
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ABSTRACT. РHuman retroelements (REs), which comprise approximately 40% of the genome, have played a pivotal role in the evolution of key molecular processes, such as placental development, by introducing novel regulatory elements near host gene promoters and enhancers. Despite their genomic abundance and regulatory influence, the functional trajectories of REs remain poorly understood. Here, leveraging ChIP-seq profiles of histone modifications (H3K4me1, H3K4me3, H3K9ac, H3K27ac, H3K27me3, and H3K9me3) from five human cell lines deposited in the ENCODE database, we systematically ranked the regulatory impact of REs across 25,075 human genes. Gene sets enriched for promoter- and enhancer-associated RE-linked regulatory sites were identified. Consensus gene sets across cell lines were found to be associated with pathways involved in cancer progression, specifically chronic myeloid leukemia and small cell lung cancer, as well as with host defense responses to infection with human T-cell lymphotropic virus type 1. These findings provide new insights into recent human evolution and highlight the ongoing influence of selfish genetic elements on genome regulation and disease susceptibility. |
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ABSTRACT. Reliable structure-based virtual screening critically depends on the accuracy of experimental protein–ligand complexes. However, many crystallographic models in the Protein Data Bank (PDB) contain crystalpacking neighbors that distort the local geometry of binding sites. In this work, the impact of crystallographic neighbors on molecular docking accuracy using Molsoft ICM-Pro was systematically assessed. All ligands were docked starting from two-dimensional structures, without prior conformational information, to mimic realistic virtual screening conditions. Across three representative systems Schistosoma mansoni SmBRD3(2), human TIM-3, and USP5 ZnF-UBD that crystal neighbors can have a huge impact was observed. Incorporating neighboring molecules yielded dramatic improvements, reducing RMSD values |
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ABSTRACT. Selecting the appropriate crystallographic conformation of a target protein is essential for reliable structure-based virtual screening. In this study, conformational variability of the epidermal growth factor receptor (EGFR) was investigated and how it influences docking accuracy of Afatinib, a dual covalent inhibitor of EGFR, and HER2. Using five EGFR crystal structures (4G5J, 4I22, 3W33, 3POZ, and 5U8L), self- and crossdocking analyses were performed in ICM-Pro to assess binding precision, pose stability, and scoring performance. Self-docking of Afatinib into its native complex (4G5J) reproduced the experimental pose with an RMSD of 0.95 Å, validating the protocol. Among alternative conformations, 4I22 yielded the closest structural agreement, demonstrating an RMSD of 1.02 Å and superior docking scores, while other structures showed substantial deviations in key active-site residues, resulting in distorted poses and lower binding scores. These findings reveal that subtle rearrangements of residues surrounding Cys797, Met793, and Lys745 critically affect ligand accommodation and covalent bond formation. The results emphasize that protein conformational selection, particularly from high-resolution structures - profoundly influences docking fidelity. Incorporating multiple conformations through cross- docking enhances predictive robustness and better reflects the dynamic nature of protein–ligand recognition in virtual screening workflows. |
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| СВЕДЕНИЯ ОБ АВТОРАХ | 93 |