“Russia, Rossia, Rus, Kolomna: Province”: Conceptualization of Space in B. Pylnyak’s Novel “Volga Flows into Caspian Sea” by M. A. Dubova

“…The relevance of the article is due to addressing the problem of linguistic expression of world-modeling universals in a literary text. …”
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Technology and implementation of fermentative units for bioprotein production from natural gas by V. M. Kochetkov, I. S. Gaganov, V. V. Kochetkov, P. A. Nyunkov

“…An analysis of publications devoted to the problem of developing technological equipment for conducting the process of obtaining a bioprotein from natural gas is presented. …”
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APT attack threat-hunting network model based on hypergraph Transformer by Yuancheng LI, Yukun LIN

“…To solve the problem that advanced persistent threat (APT) in the Internet of things (IoT) environment had the characteristics of strong concealment, long duration, and fast update iterations, it was difficult for traditional passive detection models to quickly search, a hypergraph Transformer threat-hunting network (HTTN) was proposed.The HTTN model had the function of quickly locating and discovering APT attack traces in IoT systems with long time spans and complicated information concealment.The input cyber threat intelligence (CTI) log graph and IoT system kernel audit log graph were encoded into hypergraphs by the model, and the global information and node features of the log graph were calculated through the hypergraph neural network (HGNN) layer, and then they were extracted for hyperedge position features by the Transformer encoder, and finally the similarity score was calculated by the hyperedge, thus the threat-hunting of APT was realized in the network environment of the Internet of things system.It is shown by the experimental results in the simulation environment of the Internet of things that the mean square error is reduced by about 20% compared to mainstream graph matching neural networks, the Spearman level correlation coefficient is improved by about 0.8%, and improved precision@10 is improved by about 1.2% by the proposed HTTN model.…”
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The application of improved AFCNN model for children’s psychological emotion recognition by Feiqin Wang, Jianping Dong

“…The model initially employs a traditional Convolutional Neural Network (CNN) to extract image features and integrates an attention mechanism to enhance focus on key features, thereby improving recognition accuracy and precision. …”
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Methods for Constructing Artificial Neural Networks for Data Classification by L. V. Serebryanaya

“…The features of the organization of distance learning of students in a higher educational institution, as well as the information and educational technologies necessary for this, are considered. …”
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Meta-path convolution based heterogeneous graph neural network algorithm by QIN Zhilong, DENG Kun, LIU Xingyan

“…Firstly, the feature transformation was used to adaptively adjust the node features. …”
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IQGO: Iterative Quantum Gate Optimiser for Quantum Data Embedding by Tautvydas Lisas, Ruairi de Frein

“…However, kernel methods which leverage feature map embedding, often struggle with overfitting, which compromises their generalisation performance on unseen data. …”
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Detección de situaciones de emergencias usando el modelo Naive- Bayes de machine learning. by Iván Leonel Vásquez-Rojas, Miguel José Vívas-Cortéz

“…This has motivated the generation of a large number of works about the use of this information to face the problems generated by such emergencies, work such as A. …”
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A comprehensive texture segmentation framework for segmentation of capillary non-perfusion regions in fundus fluorescein angiograms. by Yalin Zheng, Man Ting Kwong, Ian J C Maccormick, Nicholas A V Beare, Simon P Harding

“…Capillary non-perfusion (CNP) in the retina is a characteristic feature used in the management of a wide range of retinal diseases. …”
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ARCHITECTURE AND FUNCTIONALITY OF INTEGRATED INFORMATION SYSTEM FOR ANALYSIS OF POTENTIAL OF RENEWABLE ENERGY SOURCES by B. A. Tonkonogov, S. P. Kundas, A. E. Moroz

“…The required functionality of system has led to the solution of a number of problems in the development of appropriate software modules that implement methods, models and algorithms for assessing the energy potential and economic efficiency of the use of renewable energy sources (RES). …”
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Review of Brain Computer Interface Technology in the Treatment of Motor Dysfunction after Stroke by Yulian ZHU, Sijie LIANG

“…The work flow of BCI in treating stroke patients could be roughly divided into five steps: signal acquisition, preprocessing or signal enhancement, feature extraction, classification and control interface. …”
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Characterizing the wheat (Triticum aestivum L.) phosphate transporter gene family and analyzing expression patterns in response to low phosphorus stress during the seedling stage by Meini Song, Meini Song, Pengcheng Li, Pengcheng Li, Lirong Yao, Lirong Yao, Chengdao Li, Erjing Si, Erjing Si, Baochun Li, Baochun Li, Yaxiong Meng, Yaxiong Meng, Xiaole Ma, Xiaole Ma, Ke Yang, Ke Yang, Hong Zhang, Hong Zhang, Xunwu Shang, Huajun Wang, Huajun Wang, Juncheng Wang, Juncheng Wang

“…These features showed a high degree of conservation within each subfamily. …”
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Abnormal traffic detection method based on LSTM and improved residual neural network optimization by Wengang MA, Yadong ZHANG, Jin GUO

“…Problems such as a difficulty in feature selection and poor generalization ability were prone to occur when traditional method was exploited to detect abnormal network traffic.Therefore, an abnormal traffic detection method based on the long short term memory network (LSTM) and improved residual neural network optimization was proposed.Firstly, the features and attributes of network traffic were analyzed, and the variability of the feature values was reduced by preprocessing of network traffic.Then, a three-layer stacked LSTM network was designed to extract network traffic features of different depths.Moreover, the problem of weak adaptability of feature extraction was solved.Finally, an improved residual neural network with skipping connecting line was designed to optimize the LSTM.The defects of deep neural network such as overfitting and gradient vanishing were optimized.The accuracy of abnormal traffic detection was improved.Experimental results show that the proposed method has higher training accuracy and better visibility of data processing.The classification accuracy rates under two classifications and multiple classifications are 92.3% and 89.3%.It has the lowest false positive rate when the parameters such as precision rate and recall rate are optimal.Moreover, it has strong robustness when the sample is destroyed.Furthermore, better generalization ability can be achieved.…”
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Dynamic UAV data fusion and deep learning for improved maize phenological-stage tracking by Ziheng Feng, Jiliang Zhao, Liunan Suo, Heguang Sun, Huiling Long, Hao Yang, Xiaoyu Song, Haikuan Feng, Bo Xu, Guijun Yang, Chunjiang Zhao

“…To address these challenges, we employed the Synthetic Minority Oversampling Technique (SMOTE) for sample augmentation, aiming to resolve the small sample modelling problem. Moreover, we utilized enhanced “separation” and “compactness” feature selection methods to identify input features from multiple data sources. …”
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Hyperspectral Image Reconstruction Based on Blur–Kernel–Prior and Spatial–Spectral Attention by Hongyu Xie, Mingyu Yang, Huansong Huang, Mingle Zhang, Wei Zhang, Qingbin Jiao, Liang Xu, Xin Tan

“…Given the problem of spatial detail loss and spectral feature degradation in hyperspectral images (HSIs) characterized as blur, often caused by noise during image acquisition, and methods of removing blur noise designed on HSIs being insufficient, we propose an HSI reconstruction network based on a Blur–Kernel–Prior (BKP) method and Spectral–Spatial Attention (SSA) strategy for noise removal and reconstruction of HSIs. …”
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A Novel Open Circuit Fault Diagnosis for a Modular Multilevel Converter with Modal Time-Frequency Diagram and FFT-CNN-BIGRU Attention by Ziyuan Zhai, Ning Wang, Siran Lu, Bo Zhou, Lei Guo

“…To solve this problem, an intelligent diagnosis method is proposed to integrate the modal time–frequency diagram and FFT-CNN-BiGRU-Attention. …”
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Automated stringed robotechnical complex as a prospective method for monitoring of objects’safety and state border areas by D. V. Нansetski

“…An innovative project to create a prototype of a multifunctional mobile automated stringed robotic complex is announced. A distinctive feature of the project is the mobility in relocation and the maximum use of artificial intelligence to solve problems of ensuring the security of a protected object or territory.…”
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Prerequisites and consequences of modern financial policy of the Government of the Russian Federation by S. A. Krutien

“…In the article the feature of financial policy which is carried out at this stage in the Russian Federation are considered. …”
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Remaining Useful Life Prediction of Bearings via Semi-Supervised Transfer Learning Based on an Anti-Self-Healing Health Indicator by Jung-Woo Kim, Kyoung-Su Park

“…However, recent studies have not addressed feature extraction methods that consider all of these aspects. …”
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Few-Shot Unsupervised Domain Adaptation Based on Refined Bi-Directional Prototypical Contrastive Learning for Cross-Scene Hyperspectral Image Classification by Xuebin Tang, Hanyi Shi, Chunchao Li, Cheng Jiang, Xiaoxiong Zhang, Lingbin Zeng, Xiaolei Zhou

“…To facilitate prototype contrastive learning, we employ a Siamese-style distance metric loss function to aggregate intra-class features while increasing the discrepancy of inter-class features. …”
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