Features of the Russian Small and Medium-sized Enterprise Lending Market at the Present Stage by E. V. Zhirnel

“…The work shows that the same mechanism works as one of the most rapid and effective in the implementation of anti-crisis policies, which can be observed, including during the 2020 pandemic.The purpose of the study is to identify the features and problems of the modern stage of the development of the lending market for small and medium-sized enterprises in Russia. …”
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On Features of Self-Determination of Adolescent of Indigenous Peoples of Far North (Nenets Adolescents) by Y. Y. Lezina, T. M. Bostandzhiyeva

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Multi-stage detection method for APT attack based on sample feature reinforcement by Lixia XIE, Xueou LI, Hongyu YANG, Liang ZHANG, Xiang CHENG

“…Given the problems that the current APT attack detection methods were difficult to perceive the diversity of stage flow features and generally hard to detect the long duration APT attack sequences and potential APT attacks with different attack stages, a multi-stage detection method for APT attack based on sample feature reinforcement was proposed.Firstly, the malicious flow was divided into different attack stages and the APT attack identification sequences were constructed by analyzing the characteristics of the APT attack.In addition, sequence generative adversarial network was used to simulate the generation of identification sequences in the multi-stage of APT attacks.Sample feature reinforcement was achieved by increasing the number of sequence samples in different stages, which improved the diversity of multi-stage sample features.Finally, a multi-stage detection network was proposed.Based on the multi-stage perceptual attention mechanism, the extracted multi-stage flow features and identification sequences were calculated by attention to obtain the stage feature vectors.The feature vectors were used as auxiliary information to splice with the identification sequences.The detection model’s perception ability in different stages was enhanced and the detection accuracy was improved.The experimental results show that the proposed method has remarkable detection effects on two benchmark datasets and has better effects on multi-class potential APT attacks than other models.…”
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Multi-stage detection method for APT attack based on sample feature reinforcement by Lixia XIE, Xueou LI, Hongyu YANG, Liang ZHANG, Xiang CHENG

“…Given the problems that the current APT attack detection methods were difficult to perceive the diversity of stage flow features and generally hard to detect the long duration APT attack sequences and potential APT attacks with different attack stages, a multi-stage detection method for APT attack based on sample feature reinforcement was proposed.Firstly, the malicious flow was divided into different attack stages and the APT attack identification sequences were constructed by analyzing the characteristics of the APT attack.In addition, sequence generative adversarial network was used to simulate the generation of identification sequences in the multi-stage of APT attacks.Sample feature reinforcement was achieved by increasing the number of sequence samples in different stages, which improved the diversity of multi-stage sample features.Finally, a multi-stage detection network was proposed.Based on the multi-stage perceptual attention mechanism, the extracted multi-stage flow features and identification sequences were calculated by attention to obtain the stage feature vectors.The feature vectors were used as auxiliary information to splice with the identification sequences.The detection model’s perception ability in different stages was enhanced and the detection accuracy was improved.The experimental results show that the proposed method has remarkable detection effects on two benchmark datasets and has better effects on multi-class potential APT attacks than other models.…”
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FEATURES OF FOREIGN INVESTOR ATTRACTION TO FUNDING OF THE RUSSIAN STARTUPS IN THE CONTEXT OF THE POSTCRISIS ECONOMY by Е. A. Poliakova

“…Comparison of positions and approaches of investors allows us to find key features and identify problems of investing in Russian start-ups. …”
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Automatic feature selection and weighting in molecular systems using Differentiable Information Imbalance by Romina Wild, Felix Wodaczek, Vittorio Del Tatto, Bingqing Cheng, Alessandro Laio

“…DII can also produce sparse solutions and determine the optimal size of the reduced feature space. We demonstrate the usefulness of this approach on two benchmark molecular problems: (1) identifying collective variables that describe conformations of a biomolecule, and (2) selecting features for training a machine-learning force field. …”
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Integrated Neural Network for Ordering Optimization with Intertemporal-Dependent Demand and External Features by Minxia Chen, Ke Fu

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The Specific Features of the Contemporary Russian Foreign Energy Policy Shift in Modern Times by E. S. Leonov

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Automatic Feature Engineering-Based Optimization Method for Car Loan Fraud Detection by Jian Yang, Zixin Tang, Zhenkai Guan, Wenjia Hua, Mingyu Wei, Chunjie Wang, Chenglong Gu

“…Problems like feature dimension explosion, low interpretability, long training time, and low detection accuracy are solved by compressing abstract and uninterpretable features to limit the depth of DFS algorithm. …”
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Improving unsupervised pedestrian re‐identification with enhanced feature representation and robust clustering by Jiang Luo, Lingjun Liu

“…The above structures are connected through a clustering contrastive learning framework, which not only improves the discriminative power of features and the accuracy of clustering, but also solves the problem of inconsistent clustering updates. …”
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An Unbiased Feature Estimation Network for Few-Shot Fine-Grained Image Classification by Jiale Wang, Jin Lu, Junpo Yang, Meijia Wang, Weichuan Zhang

“…To address the problems mentioned, we propose an unbiased feature estimation network. …”
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Feature-Based Dataset Fingerprinting for Clustered Federated Learning on Medical Image Data by Daniel Scheliga, Patrick Mäder, Marco Seeland

“…Additionally, shared raw data fingerprints can directly leak sensitive visual information, in certain cases even resembling the original client training data. To alleviate these problems, we propose a Feature-based dataset FingerPrinting mechanism (FFP). …”
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Multiscale feature cross‐layer fusion remote sensing target detection method by Yuting Lin, Jianxun Zhang, Jiaming Huang

“…To address the above problems, this article proposes an improved multiscale feature cross‐layer fusion remote sensing target detector based on YOLOv5. …”
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Features of the district bodies of the Ministry of Internal Affairs in Siberia in the 19th century by Igor A. Konovalov

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Fan Blade Crack Detection Algorithm Based on Multi-Scale Feature Fusion by Yongjun Qi, Hailin Tang, Altangerel Khuder

“…In order to quickly and accurately detect and maintain the fan blades, based on the intelligent big data from the environment, we propose the convolutional neural network model to solve the problem of low recognition rate due to the lack of feature extraction in the fan blade crack image, and the long short-term memory network (Long Short-Term Memory, LSTM) convolutional neural network model, and the dimensionality reduction of the captured image data, which is beneficial to improve the recognition rate of the picture and reduce the loss rate of the picture through the detection model’s suitable recognition of complex background problems such as target occlusion and overlap. …”
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Design features of a high-pressure transmission devices for hydro-jet technologies by V. I. Novikov, O. V. Kuzmin

“…The design methodologies, taking into account the identified problems and features, for high-pressure transmitting devices are given.Discussion and conclusions. …”
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Improvement and Optimization of Feature Selection Algorithm in Swarm Intelligence Algorithm Based on Complexity by Bingsheng Chen, Huijie Chen, Mengshan Li

“…The swarm intelligence algorithm simulates the behavior of animal populations in nature and is a new type of intelligent solution that is different from traditional artificial intelligence. Feature selection is a very common data dimensionality reduction method, which requires us to select the feature subset with the best evaluation criteria from the original feature set. …”
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GLNet: global-local feature network for wheat leaf disease image classification by Shangze Li, Shen Liu, Mingyu Ji, Yuhao Cao, Bai Yun, Bai Yun

“…Addressing the issues with insufficient multi-scale feature perception and incomplete understanding of global information in traditional convolutional neural networks for image classification of wheat leaf disease, this paper proposes a global local feature network, i.e. …”
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An Edge Recognition Method for Insulator State Based on Multi-dimension Feature Fusion by Dongmei HUANG, Yueqi WANG, Anduo HU, Jinzhong SUN, Shuai SHI, Yuan SUN, Lingfeng FANG

“…Traditional insulator state recognition methods have such problems as poor real-time performance and insufficient feature extraction ability. …”
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Dynamic Node Privacy Feature Decoupling Graph Autoencoder Based on Attention Mechanism by Yikai Huang, Jinchuan Tang, Shuping Dang

“…Graph autoencoders’ inherent capability to capture node feature correlations poses significant privacy risks through attackers inference. …”
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