Comparison of Style Features for the Authorship Verification of Literary Texts by Ksenia Vladimirovna Lagutina

“…The article compares character-level, word-level, and rhythm features for the authorship verification of literary texts of the 19th-21st centuries. …”
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FEATURES OF INFORMAL BEHAVIOR NORMS IN THE CONDITIONS OF PLACES OF DETENTION by A. Volkov, M. Volkov, I. Uvarov

“…The article deals with the specific features of informal behavior norms of convicts in prison. …”
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Epidemiological Features of Sexually Transmitted Infections in the Republic of Tatarstan by Zh. G. Eremeeva, R. Z. Ibragimova, S. T. Agliullina

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Refining features for underwater object detection at the frequency level by Wenling Wang, Zhibin Yu, Zhibin Yu, Mengxing Huang

“…To address this issue, we design a multi-scale high-frequency information enhancement module to enhance the high frequency features extracted by the backbone network and improve the detection effect of the network on underwater objects. …”
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Features of assessing the condition and behavior of low-water bridges by A. A. Loktev, V. V. Korolev, I. V. Shishkina

“…The article describes features of operation and monitoring of low-water bridges, which are found on highways of regional, intermunicipal and local importance. …”
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Reflection in Speech of the Individual-Typological Features of Language Personality by Наталія Фоміна

“…The article is devoted to the actual psycholinguistic problem of reflecting in the various parameters of speech the features of a linguistic personality. …”
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Features of Recruitment: Intelligent Text Analysis of Resume and Vacancies by Irina L. Sizova

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PSYCHOLOGICAL AND PEDAGOGICAL FEATURES OF TEACHING MEDICAL AND BIOLOGICAL PHYSICS by Fediv Volodymyr, Olar Оlena, Biriukova Tetiana

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Features of “Inverted” Educational Resources for Distance Learning of Pupils by D. A. Barkhatova, A. L. Simonova, P. S. Lomasko, L. B. Khegay

“…The purpose of the paper is to describe the features of the “inverted” educational resources intended for the implementation of additional subject training of schoolchildren in a distance mode, which are created on the basis of the concepts of the problem-solving approach and micro-learning.Distance learning technologies, widely introduced into educational practice, require a high level of self-organization and internal motivation from the student to work independently, which necessitates the search for new approaches to the development of educational resources that would help maintain the interest and attention of students until the end of training. …”
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Features of the Structure of Age-related Expenses in the Russian Federation by K. V. Kuznetsov

“…The paper examines the features of the methods of redistribution of expenditures of the population. …”
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A two stage grading approach for feature selection and classification of microarray data using Pareto based feature ranking techniques: A case study by Rasmita Dash

“…It is often found in literature that the ranking approaches are used for feature selection. Different ranking techniques may assign different rank to the same gene and the selection made based on these ranks may not be suitable for different problems. …”
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LANGUAGE SPACE OF NEURAL NETWORKS: FEATURES AND DIFFERENCES FROM NATURAL LANGUAGE by Natalia B. Egorchenkova, Olga V. Korobova

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STRUCTURAL AND GRAMMATICAL FEATURES OF ADJECTIVAL PHRASEOLOGICAL UNITS IN THE RUSSIAN AND ENGLISH LANGUAGES by Elena A. Bibik

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Editorial for the Special Issue on “Feature Papers in Section AI in Imaging” by Antonio Fernández-Caballero

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MFAN: Multi-Feature Attention Network for Breast Cancer Classification by Inzamam Mashood Nasir, Masad A. Alrasheedi, Nasser Aedh Alreshidi

“…Despite various AI-based strategies in the literature, similarity in cancer and non-cancer regions, irrelevant feature extraction, and poorly trained models are persistent problems. …”
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Human activity recognition algorithm based on the spatial feature for WBAN by Chi JIN, Zhijun LI, Dayang SUN, Fengye HU

“…Traditional image-based activity recognition algorithms have some problems,such as high computational cost,numerous blind spots and easy privacy leakage.To solve the problem above,the CCLA (convolution-convolutional long short-term memory-attention) activity recognition algorithm based on the acceleration and gyroscope data was proposed.The convolutional neural network was used to extract spatial features of activity data and got the hidden time series information from the convolutional long short-term memory network.Simulating human brain selecting attention mechanism,attention-encoder was constructed to extract the spatial and temporal features at a higher level.The CCLA algorithm was tested on UCI-HAPT (university of California Irvine-smartphone-based recognition of human activities and postural transitions) public data set,and realized the classification of 12 types of activity with the accuracy of 93.27%.…”
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Multi-label feature selection based on dynamic graph Laplacian by Yonghao LI, Liang HU, Ping ZHANG, Wanfu GAO

“…In view of the problems that graph-based multi-label feature selection methods ignore the dynamic change of graph Laplacian matrix, as well as such methods employ logical-value labels to guide feature selection process and loses label information, a multi-label feature selection method based on both dynamic graph Laplacian matrix and real-value labels was proposed.The robust low-dimensional space of feature matrix was used to construct a dynamic graph Laplacian matrix, and the robust low-dimensional space was used as the real-value label space.Furthermore, manifold and non-negative constraints were adopted to transform logical labels into real-valued labels to address the issues mentioned above.The proposed method was compared to three multi-label feature selection methods on nine multi-label benchmark data sets in experiments.The experimental results demonstrate that the proposed multi-label feature selection method can obtain the higher quality feature subset and achieve good classification performance.…”
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Multi-label feature selection based on dynamic graph Laplacian by Yonghao LI, Liang HU, Ping ZHANG, Wanfu GAO

“…In view of the problems that graph-based multi-label feature selection methods ignore the dynamic change of graph Laplacian matrix, as well as such methods employ logical-value labels to guide feature selection process and loses label information, a multi-label feature selection method based on both dynamic graph Laplacian matrix and real-value labels was proposed.The robust low-dimensional space of feature matrix was used to construct a dynamic graph Laplacian matrix, and the robust low-dimensional space was used as the real-value label space.Furthermore, manifold and non-negative constraints were adopted to transform logical labels into real-valued labels to address the issues mentioned above.The proposed method was compared to three multi-label feature selection methods on nine multi-label benchmark data sets in experiments.The experimental results demonstrate that the proposed multi-label feature selection method can obtain the higher quality feature subset and achieve good classification performance.…”
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Environmental Monitoring Smart System with Self-Sustaining Wireless Sensor Network Using Data Validation Algorithms by Kanwal T., Altaf S., Javed M. K.

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A Lightweight Single-Image Super-Resolution Method Based on the Parallel Connection of Convolution and Swin Transformer Blocks by Tengyun Jing, Cuiyin Liu, Yuanshuai Chen

“…However, existing methods still face issues such as incomplete high-frequency information reconstruction, training instability caused by residual connections, and insufficient cross-window information exchange. To address these problems and better leverage both local and global information, this paper proposes a super-resolution reconstruction network based on the Parallel Connection of Convolution and Swin Transformer Block (PCCSTB) to model the local and global features of an image. …”
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