2025: Recent submissions

Now showing items 121-140 of 169

    • Impact of data augmentation strategies on deep learning-based image classification 

      Yu, L. (БНТУ, 2025)
      This paper explores how data augmentation techniques influence the performance and generalization of deep learning-based image classifiers. Augmentation is essential for enhancing robustness and accuracy, especially when training data are limited or imbalanced. The study discusses various augmentation methods, from basic geometric transformations to advanced approaches such as ...
      2026-01-23

    • 轻量级SAR 船舶检测：散斑注意机制的研究（基于YOLOv12） 

      Wang, W.; Zhang, X. (БНТУ, 2025)
      This paper presents an improved YOLOv12 model that integrates the Speckle Attention Mechanism (SAM) to enhance small target detection in complex scenes. The model utilizes a spatial-channel collaborative attention module to generate energy weight maps, achieving a lightweight design with a channel compression ratio of 1/8 and only a 1.2 % increase in parameters. Experiments on a ...
      2026-01-23

    • Evaluation-oriented data-generating process for performance time series: the perturbation observation decoupling principle 

      Song, Q. (БНТУ, 2025)
      This work proposes the Perturbation-Observation Decoupling Principle: by decoupling structured perturbations – defined with precise temporalboundaries and semantic labels – from performance observation paths at the physical, logical, or resource level during the data generation process (DGP), our approach prevents signal contamination and ensures causal traceability. It establishes ...
      2026-01-23

    • Проблемы, связанные с использованием Искусственного Интеллекта 

      Гордиенко, А. В.; Мельников, В. В.; Няненков, В. М. (БНТУ, 2025)
      The rapid advancement of Artificial Intelligence (AI) has brought to the forefront a series of profound contradictions, algorithmic biases, infringements upon privacy, cybersecurity threats, and potential destabilization of economic systems. The pertinent question is no longer whether AI development will persist, but rather whether humanity can effectively govern its trajectory ...
      2026-01-23

    • The evolution of performance time series analyzability from application to interpretable evaluation 

      Song, Q. (БНТУ, 2025)
      Performance Time Series (PTS) are widely used to monitor system health, yet their analytical value is often limited by a lack of structured event records. This work argues that PTS analyzability is not an inherent property, but a progressive, human-curated and context-dependent property determined by the presence and richness of causal event annotations. We propose a three-level ...
      2026-01-23

    • Enhancing russian handwriting recognition VIA transfer learning and data augmentation with VGG-BiLSTM-CTC 

      Liu, J.; Dang, Z.; Xiong, S. (БНТУ, 2025)
      The VGG-BiLSTM-CTC model has succeeded in many languages, yet Russian handwriting recognition is understudied despite its demand. This research adapts the model to Russian through transfer learning to address this gap.
      2026-01-23

    • Comparison of orb and sift methods under the slam framework 

      Qiyao, Y.; Qinghan, Y.; Jun, M. (БНТУ, 2025)
      This paper presents a comparative study of ORB and SIFT feature matching methods under the SLAM framework. Both algorithms were implemented and tested on identical image sets to evaluate their performance from multiple classical perspectives, including feature distribution, robustness to illumination and rotation, matching accuracy, and computational efficiency. By Analyzing both ...
      2026-01-23

    • Security metrics and countermeasures for NFC payment technology 

      Liu, W.; Balukho, I. N.; Kolchevsky, N. N. (БНТУ, 2025)
      In recent years, Near Field Communication (NFC) technology has been widely applied in the field of modern payment systems. However, in practical applications, NFC technology is vulnerable to attacks such as eavesdropping, data tampering, data corruption, cloning, and phishing, which can lead to the leakage of users' private data and pose serious threats to financial information ...
      2026-01-23

    • Comparative analysis of YOLOv9–YOLOv12 object detection models on a custom non-open dataset 

      Wang, Q.; Zhang, B.; Wang, C.; Zhang, C. (БНТУ, 2025)
      This paper compares YOLOv9–YOLOv12 object detection models on a custom non-open dataset (6,500 images, 11 classes), all trained for 300 epochs under identical settings. Results show YOLOv12 achieves the highest mAP@0.5 (0.678), outperforming YOLOv9 (0.648), YOLOv10 (0.603), and YOLOv11 (0.649). Architectural optimizations and training stability drive performance disparities, with ...
      2026-01-23

    • The confluence of digitalization, management, and artificial intelligence: reshaping the modern enterprise 

      Lingxian, J. (БНТУ, 2025)
      The contemporary business landscape is undergoing a profound transformation, driven by the relentless tide of digitalization. This paper explores the intricate interplay between digital transformation, evolving management practices, and the catalytic role of Artificial Intelligence (AI). It argues that AI is not merely a technological tool but a foundational force that is redefining ...
      2026-01-23

    • Artificial intelligence drives digital transformation in supply chains 

      Sun, K. (БНТУ, 2025)
      This paper explores the way AI technology systematically promotes the digital transformation of supply chains in Chinese industrial enterprises. It constructs a three-tier organizational economic mechanism model comprising "driving-coresupporting" layers. In this study, the mechanism was confirmed to be effective and significantly improve decision-making optimization, demand ...
      2026-01-23

    • The symbiotic transformation: how artificial intelligence is reshaping corporate culture 

      Lingxian, J.; Xin, C. (БНТУ, 2025)
      The integration of Artificial Intelligence (AI) into business operations is no longer a mere technological upgrade but a profound cultural catalyst. This paper examines the bidirectional relationship between AI and corporate culture, arguing that while a supportive culture is a prerequisite for successful AI adoption, the technology itself simultaneously acts as a powerful force ...
      2026-01-23

    • Hardware implementation of the Column-Line-Code codec 

      Lin, W.; Xinyue, S.; Jiarou, W.; Shuo, W.; Jun, M. (БНТУ, 2025)
      This paper presents a hardware implementation of the Column-Line Code, an error correction code. The design incorporates three key modules: the encoder, the decoder, and an error injection model for simulation and verification.
      2026-01-23

    • Цифровизация преподавания русского языка в китайских вузах на основе крупных языковых моделей на примере учебника «Дорога в Россию 1» 

      Ван, С. (БНТУ, 2025)
      Since 2024, breakthroughs in generative AI for Russian language processing have created new opportunities in education. This paper investigates the application of Large Language Models (LLMs) in a Russian course centered on the textbook “The Way to Russia 1”. The study demonstrates that LLMs facilitate the tailored construction of a three-dimensional graph system – integrating ...
      2026-01-23

    • A survey of CPU-parallel image compression algorithms 

      Li, B.; Ma, J. (БНТУ, 2025)
      This survey reviews classical image compression methods for CPU environments, excluding deep learning techniques. It covers pixel-domain predictive coding (DPCM, JPEG-LS), frequency-domain transform coding (JPEG with DCT, JPEG2000 with wavelets), and modern image formats (WebP, HEIF/AVIF, JPEG XL). The focus is on their operating principles, computational complexity, artifacts, ...
      2026-01-23

    • Nonparametric walking model based on relationship between plantar insole sensor signal time-spatial features 

      Hao, L. (БНТУ, 2025)
      This work contrasts traditional parametric walking models, which handle simple gait well but fail on nonlinear or disease-affected patterns, with a Non-Parametric Walking Model (NPWM) built from plantar insole time–spatial features. The Neurological Disease Detection Feature Mining Method (NDFMM) identifies goal-oriented walking patterns through sorted-metrics–based selection. ...
      2026-01-23

    • Bodily kinesthetic intelligence (BKI) based on plantar insole sensor signal 

      Hao, L. (БНТУ, 2025)
      This paper presents a framework that integrates Goal-Oriented Bodily Kinesthetic Intelligence (BKI) with disease-oriented walking feature mining using plantar insole sensor signals. By combining BKI’s adaptive motor-control mechanisms with a Neurological Disease Detection Feature Mining Method (NDFMM), the system extracts interpretable gait features and links them to decision ...
      2026-01-23

    • Parallel optimization of a DCT image compression algorithm for resource-constrained platforms 

      Li, B.; Ma, J. (БНТУ, 2025)
      For resource-constrained platforms, this paper presents an 8 × 8 blockbased parallel implementation of the DCT/IDCT. The method decomposes the 2D transform into two 1D transforms, uses a slice-safe preallocated 3D buffer together with block-level parfor parallelism, and avoids contention and copying overhead from temporary arrays. Using a batch of 10 images as an example, the ...
      2026-01-23

    • ACO for energy-efficient routing in multi-agent IoT networks 

      Khajynava, N. V.; Khadzhynava, K. A. (БНТУ, 2025)
      A bioinspired ACO algorithm for routing in multi-agent IoT networks is proposed. Route selection uses pheromone concentration, node distances, and residual energy. Simulations show that this approach yields shorter routes and balanced energy usage, improving network robustness and lifetime.
      2026-01-23

    • The synergistic triad: how artificial intelligence is redefining business management and demanding a new paradigm of leadership 

      Fengchi, S.; Xiaojuan, Z. (БНТУ, 2025)
      The integration of Artificial Intelligence (AI) into the corporate fabric is instigating a profound transformation across all layers of organizational functioning. While much attention has been paid to AI's impact on operational efficiency and strategic decision-making, its implications for leadership – the human engine of business management – are equally critical and less ...
      2026-01-23