Industrial Internet of things (IIoT) environments need to implement reliable security measures because of the growth in network traffic and overall connectivity. Accordingly, this work provides the architecture of network traffic analysis and the detection of intrusions in a network with the help of edge computing and using machine-learning methods. The study uses k-means and ...

In this study, an analysis of the spectral brightness coefficients (SBC) of agricultural crops in the steppe regions of Kazakhstan was carried out using remote field and space measurements during the growing season. The possibility of assessing structural changes in plants using near-infrared data was explored. An electronic database of corrected spectral data of SBC for the ...

This article presents a comprehensive review of short text clustering using stateof-the-art methods: Bidirectional Encoder Representations from Transformers (BERT), Term Frequency-Inverse Document Frequency (TF-IDF), and the novel hybrid method Latent Dirichlet Allocation + BERT + Autoencoder (LDA + BERT + AE). The article begins by outlining the theoretical foundation of each ...

This article is devoted to a set of important areas of research: the analysis of formal representations and verification of pests and pathogens affecting crops using spectral brightness coefficients (SBR) for the period from 2021 to 2023. The database contains about 10,000 records covering the growing season, types of diseases and pests, as well as their growth phases in a ...

Municipal solid waste (MSW) recycling is critical in addressing the environmental challenges posed by increasing urbanization and waste generation. This study explores the use of fast pyrolysis technology with solid heat carriers for efficient MSW processing. The technology, originally developed for oil shale processing, involves the thermal decomposition of waste in an ...

Additive manufacturing reshapes concrete construction, yet routine strength verification of printed elements still depends on destructive core sampling. This study evaluates whether standard 70 mm cubes—corrected by a single factor—can provide an equally reliable measure of in situ compressive strength. Five Portland-cement mixes, with and without ash-slag techno-mineral ...

Magnetic Resonance Imaging (MRI) is vital in diagnosing brain tumours, offering crucial insights into tumour morphology and precise localisation. Despite its pivotal role, accurately classifying brain tumours from MRI scans is inherently complex due to their heterogeneous characteristics. This study presents a novel integration of advanced segmentation methods with deep learning ...

Smart grids are transforming the generation, distribution, and consumption of power, marking a revolutionary step forward for contemporary energy systems. Communication in smart grid environments is majorly performed through Wireless Sensor Networks (WSNs). The WSNs enable real-time monitoring and management inside smart grids. However, the integration of digital technologies ...

Automating real-time sign language translation through deep learning and machine learning techniques can greatly enhance communication between the deaf community and the wider public. This research investigates how these technologies can change the way individuals with speech impairments communicate. Despite advancements, developing accurate models for recognizing ...

The paper presents a proposed methodology for designing and planning research on driver behavior at pedestrian crossings using whole-vehicle simulators. It was assumed that dedicated research should be conducted in specific problem contexts. The problems identified were the identification of hazards and the risk of accidents involving vulnerable road users. The purpose of this ...