MRI-based 2.5D deep learning radiomics nomogram for the differentiation of benign versus malignant vertebral compression fractures by Wenhua Liang, Hong Yu, Lisha Duan, Xiaona Li, Ming Wang, Bing Wang, Jianling Cui

“…These features were combined through feature fusion to construct deep learning radiomics (DLR) models. …”
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Postural Orthostatic Tachycardia Syndrome as a Manifestation of Post-COVID-19 Syndrome by E. L. Trisvetova

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КУЛЬТУРА МОВИ ВИКЛАДАЧА В СУЧАСНІЙ ПЕДАГОГІЧНІЙ МАЙСТЕРНОСТІ: СОЦІОЛІНГВІСТИЧНИЙ АСПЕКТ by Оксана Назаренко

“…The most typical language problems in learners' communication are characterized, with the aim of preventing them in future pedagogical practice. …”
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Optimal Consumption, Leisure, and Investment with Partial Borrowing Constraints over a Finite Horizon by Geonwoo Kim, Junkee Jeon

“…We study an optimal consumption, leisure, and investment problem over a finite horizon in a continuous-time financial market with partial borrowing constraints. …”
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CSPPNet: A Convolution and State-Space-Based Photovoltaic Panel Extraction Network Using Gaofen-2 High-Resolution Imagery by Wenqing Liu, Hongtao Huo, Luyan Ji, Yongchao Zhao, Xiaowen Liu, Jialei Xie

“…Finally, the encoder of our network adopts a parallel structure of depthwise separable convolution and state-space module to capture local detailed features and global semantic features of PV panels layer by layer. …”
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A Dual-Branch Network for Intra-Class Diversity Extraction in Panchromatic and Multispectral Classification by Zihan Huang, Pengyu Tian, Hao Zhu, Pute Guo, Xiaotong Li

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FTDZOA: An Efficient and Robust FS Method with Multi-Strategy Assistance by Fuqiang Chen, Shitong Ye, Lijuan Xu, Rongxiang Xie

“…This study introduces an enhanced zebra optimization algorithm (ZOA), termed FTDZOA, for superior feature dimensionality reduction. To address the challenges of ZOA, such as susceptibility to local optimal feature subsets, limited global search capabilities, and sluggish convergence when tackling FS problems, three strategies are integrated into the original ZOA to bolster its FS performance. …”
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IMPROVING FINANCIAL ANALYSIS OF ORGANIZATIONS IN ORDER TO PREVENT THEIR INSOLVENCY by V. N. Alferov, E. A. Seredyuk

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Mental Health Assessment Model for College Students Using Circular q-Rung Orthopair Fuzzy Muirhead Means and MULTIMOORA Method by Gou Ying

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Features of drug-drug interactions rivaroxaban and calcium channel blockers depending on the ABCB1 genotype (rs1045642 and rs4148738) in patients 80 years of age and older with non... by D. A. Sychev, K. B. Mirzaev, M. S. Cherniaeva, N. V. Shakhgildyan, Sh. P. Abdullaev, N. P. Denisenko, Zh. A. Sozaeva, A. A. Kachanova, V. R. Shastina, S. V. Gorbatenkova

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INFLUENCE OF PSYCHOPHYSIOLOGICAL FACTORS OF ETHICAL RELATIONSHIP OF DRIVERS ON THE EFFICIENCY OF THE FREIGHT TRANSPORTATION IN INTERNATIONAL TRAFFIC by О. А. Tettsoeva

“…In the face of increasing tension on the roads, issues of compliance with the drivers’ professional ethics, which are a set of moral norms, that determine a person’s attitude to his professional duty, become relevant. The main problems of international transportation are inefficient communications, the causes of which are the following: psychophysiological features of drivers’ work; lack of communication skills among drivers; lack of an international ethical code of conduct for drivers. …”
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Bioconvective thermal estimation of radiative micropolar nanofluid with mass suction and variable Brownian diffusion: Cattaneo–Christov model by D. K. Almutairi

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Enhancing image retrieval through optimal barcode representation by Rasa Khosrowshahli, Farnaz Kheiri, Azam Asilian Bidgoli, H. R. Tizhoosh, Masoud Makrehchi, Shahryar Rahnamayan

“…This research addresses this problem by optimizing feature sequences based on retrieval performance metrics. …”
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Deep Learning Method for Bearing Fault Diagnosis by LIU Xiu, MA Shan-tao, XIE Yi-ning, HE Yong-jun

“…In recent years, deep learning technology has shown great potential in bearing fault diagnosis based on vibration signals.However, in the fault diagnosis method based on deep learning, the traditional single network topology feature extraction has weak discrimination and low noise robustness, and the accuracy of fault diagnosis is not high.In addition, most of the current research methods have a low fault recognition rate in a variable load environment.In response to the above problems, this paper proposes an improved neural network end-to-end fault diagnosis model.The model combines convolutional neural networks (CNN) and the attention long short-term memory (ALSTM) based on the attention mechanism, and uses ALSTM to capture long-distance correlations in time series data , Effectively suppress the high frequency noise in the input signal.At the same time, a multi-scale and attention mechanism is introduced to broaden the range of the convolution kernel to capture high and low frequency features, and highlight the key features of the fault. …”
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A Method of Word Sense Disambiguation with Recurrent Netural Networks by ZHANG Chunxiang, ZHOU Xuesong, GAO Xueyao

“…Word, part.of.speech and semantic categories are extracted as disambiguation features. Based on disambiguation features, recurrent neural network is used to construct word sense disambiguation classifier. …”
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THE SPECIFICITY OF THE FICTIONAL SPACE IN THE NOVELS BY CRÉBILLON-FILS by Natalia T. Pakhsarian

“…The interest of contemporary literary theory and literary history in the problem of fictional space and in the space in the 18 th century novels in particular reveals both achievements and gaps in this field. …”
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Emotional and Aesthetic Values as Basis for Popularity of TV Programs: Contrastive-Comparative Experience by E. S. Radiontseva

“…The article is devoted to the problem of identifying the competitive advantages of journalistic TV works. …”
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Classification of Russian Texts by Genres Based on Modern Embeddings and Rhythm by Ksenia Vladimirovna Lagutina

“…The article investigates modern vector text models for solving the problem of genre classification of Russian-language texts. …”
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CFSE: a Chinese short text classification method based on character frequency sub-word enhancement by Xingguang Wang, Shunxiang Zhang, Zichen Ma, Yunduo Liu, Youqiang Zhang

“…As a foundation task of natural language processing, text classification is widely used in information retrieval, public opinion analysis, and other related tasks. Facing the problem of sparse features of Chinese short texts, which affects the classification accuracy of Chinese short texts, this paper proposes a Chinese short text classification method based on the Character Frequency Sub-word Enhancement (CFSE), which can effectively improve the classification accuracy of Chinese short texts. …”
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Crowd counting in domain generalization based on multi-scale attention and hierarchy level enhancement by Jiarui Zhou, Jianming Zhang, Yan Gui

“…Finally, the fusion of multi-scale features derived from different receptive fields is further enhanced through multi-scale hierarchy level feature fusion, thereby enabling the model to learn high-level semantic information and low-level multi-scale visual field feature information. …”
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