Modern Methods for Diagnosing Faults in Rotor Systems: A Comprehensive Review and Prospects for AI-Based Expert Systems by Oleksandr Roshchupkin, Ivan Pavlenko

“…Some techniques like the vibration signal analysis method, spectral analysis, thermography, ultrasound diagnosis, and machine learning algorithms for predicting failure are of particular interest among them. …”
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A comparative analysis of fault detection and process diagnosis methods based on a signal processing paradigm by Dorel Aiordăchioaie

“…Seven methods are considered for evaluation: two in the time domain, two in the frequency domain and three in the time–frequency domain. The main problem is to extract and select the right features to use in the classification stage. …”
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A Literature Review on Security in the Internet of Things: Identifying and Analysing Critical Categories by Hannelore Sebestyen, Daniela Elena Popescu, Rodica Doina Zmaranda

“…From leveraging machine learning and blockchain for anomaly detection and real-time threat response to optimising lightweight algorithms for resource-limited devices, researchers propose innovative and adaptive solutions to address emerging threats. …”
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Spectral Method of Measuring of Changes in Time Intervals between Periodic Pulse Sequences by A. A. Sheinikov, A. V. Isaev, V. V. Zelenko, Yu. V. Sukhodolov

“…Methods of measuring delay time between periodic sequences of pulses are mostly based on the considered parameter direct measurement. The main disadvantage of this approach is the difficulty of ensuring the measurements accuracy in the noise conditions. …”
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A Spatial–Temporal Time Series Decomposition for Improving Independent Channel Forecasting by Yue Yu, Pavel Loskot, Wenbin Zhang, Qi Zhang, Yu Gao

“…In this paper, we improve the performance of single-channel forecasting algorithms by designing an interpretable front-end that extracts the spatial–temporal components from the input multivariate time series. …”
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Automatic Fault Classification in Photovoltaic Modules Using Denoising Diffusion Probabilistic Model, Generative Adversarial Networks, and Convolutional Neural Networks by Carlos Roberto da Silveira Junior, Carlos Eduardo Rocha Sousa, Ricardo Henrique Fonseca Alves

“…Deep convolutional neural networks (CNNs) are machine learning algorithms that perform tasks involving images, such as image classification and object recognition. …”
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Introduction of self-control of enterprise information system through accounting documentation process of by K.О. Volskа

“…The article considers the concept of self-control, its main criteria as well as the possibility of implementing the self-control in the information system of the enterprise. …”
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«Obscenities give rise to thugs»: Obscene vocabulary in the practice of the poet Vsevolod Nekrasov (based on archive materials) by E. N. Penskaya

“…They relate to his polemics in relation to phenomena that claim to be the main position in both official and unofficial culture. …”
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PROPERTIES OF GROUPS G OF DOUBLE ERRORS AND ITS INVARIANTS IN BCH CODES by V. A. Lipnitskij, A. V. Serada

“…The goal of the work is the further extending the scope of application of code automorthism in methods and algorithms of error correction by these codes. The effectiveness of such approach was demonstrated by norm of syndrome theory that was developed by Belarusian school of noiseless coding at the turn of the XX and XXI century. …”
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Posttraumatic epilepsy: clinical, diagnostic and therapeutic features by N. E. Maslov, A. A. Litvinova, P. S. Kovalev, N. N. Maslova, N. V. Yuryeva, E. I. Khamtsova

“…According to 2019 statistics records, traumatic brain injuries (TBI) are the most common type of injuries and one of the main causes for disability in Russia. Every year 200 people per 10,000 subjects around the world suffer from serious brain injuries. …”
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Evaluative representations of the student audience in the context of current processes in Donbas: comparison of studies by L. B. Vnukova

“…Due to the difficulty of reaching respondents in new territories, the survey was conducted using the "snowball" method. The main research method is a comparative analysis of the data obtained using sociological information and relevant academic research. …”
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The Neural Frontier of Future Medical Imaging: A Review of Deep Learning for Brain Tumor Detection by Tarek Berghout

“…This review also incorporates an analysis of previous reviews and targets three main aspects: feature extraction, segmentation, and classification. …”
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River Surface Space–Time Image Velocimetry Based on Dual-Channel Residual Network by Ling Gao, Zhen Zhang, Lin Chen, Huabao Li

“…Space–Time Image Velocimetry (STIV) estimates the one-dimensional time-averaged velocity by analyzing the main orientation of texture (MOT) in space–time images (STIs). …”
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Quasi-synchronous thermocompensation for ISFET-based ionometric devices. Part 2: Implementation by Alexey Pavluchenko, Aleksandr Kukla

“…Consecutive switching between ionometric and thermometric modes of sensor operation, along with subsequent algorithmic processing of the obtained data by a microprocessor incorporated into the transducer structure, allows to compensate the temperature dependence of the ISFET electrode potential. …”
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Control problem for the impulse process under stochastic optimization procedure and Levy conditions by Ya. M. Chabanyuk, A. V. Nikitin, U. T. Khimka

“…This allows one to construct explicit algorithms for the analysis of the asymptotic behavior of a controlled process. …”
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PERFORMANCE EVALUATION OF LIGHTWEIGHT OBJECT DETECTION MODELS FOR REAL-TIME PERSONAL PROTECTIVE EQUIPMENT DETECTION IN THE CONSTRUCTION SITES by Herman, Sandy Alferro Dion, Andik Yulianto

“…Using lightweight machine learning algorithms, object recognition can help to detect if the PPEs are worn correctly. …”
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COMPARISON OF THE METHOD OF ELECTROMETRIC DETERMINATION OF ROOT CANAL PARAMETERS AND THE METHOD OF THRESHOLD SEGMENTATION OF RADIOGRAPHS by Oleksii Perepelytsia, Oleg Avrunin

“…The following results were obtained: the existing methods of determining the working length of the root canal were analyzed, the main advantages and disadvantages of each method were highlighted. …”
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A Review of Embodied Grasping by Jianghao Sun, Pengjun Mao, Lingju Kong, Jun Wang

“…Then, the embodied algorithms are introduced, starting from pre-trained models, with three main research goals: (1) embodied perception, using data captured by visual sensors to perform point cloud extraction or 3D reconstruction, combined with pre-trained models, to understand the target object and external environment and directly predict the execution of actions; (2) embodied strategy: In imitation learning, the pre-trained model is used to enhance data or as a feature extractor to enhance the generalization ability of the model. …”
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LCD: IDENTIFYING INFLUENTIAL NODES IN COMPLEX NETWORKS WITH LAYERED CLUSTERING AND DEGREE by Abdulhakeem Othman Mohammed

“… Identifying influential nodes in networks is a key challenge in understanding how information spreads. While numerous algorithms have been proposed in the literature, many struggle with either limited spreading efficiency or high computational complexity. …”
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IMMUNOPATHOGENESIS OF MYASTHENIA GRAVIS (REVIEW) by E. D. Gasymly

“…High clinical heterogeneity of autoimmune myasthenia, initiating the flow, increases the urgency of studying its pathogenesis, searching for specific methods of marker diagnostics, developing algorithms for predicting the features of the development of the disease. …”
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