LIPID PEROXIDATION SYSTEM IN TYPE 1 DIABETES: ETHNIC ASPECTS by L. I. Kolesnikova, M. A. Darenskaya, L. A. Grebenkina, T. P. Bardymova, S. V. Gnusina, N. V. Semenova

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MLHI-Net: multi-level hybrid lightweight water body segmentation network for urban shoreline detection by Jianhua Ye, Pan Li, Yunda Zhang, Ze Guo, Shoujin Zeng, Youji Zhan

“…This module guides feature fusion and solves the problem of receptive field mismatch. …”
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Challenges of implementing digital technologies into public administration and forming a “smart government” by O. N. Afanasyeva, E. M. Korostyshevskaya

“…Based on a comprehensive analysis of scientific approaches to the application of digital technologies in public administration, the features of foreign practice of digital technology application in public administration and the formation of Smart Government are identified, problems and recommendations for their elimination are determined.…”
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ETHNIC PECULIARITIES OF SLEEP DISORDERS IN EASTERN SIBERIA by I. M. Madayeva, O. N. Berdina, L. I. Kolesnikova, T. A. Bairova, O. N. Ablamskaya, V. V. Madaev, F. F. Antonenko

“…Standard questionnaire of Stanford Sleep Research Center (USA) included a complex of questions about problems of sleep and their subjective assessment: no problems; light problem, moderate problem, severe problem. …”
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The choice of anti-flood measures with the use of computational experiments (the Pechora River downstream as a study case) by Dmitry I. Perepelitsa, Aleksey A. Tiunov, Anatoly P. Lepikhin, Nikita A. Goldobin, Sergey R. Andreyev, Sergey A. Lepeshkin

“…To solve the problem of flooding, it is necessary to develop a set of flood prevention measures. …”

Mine underground object detection algorithm based on TTFNet and anchor-free by Song Zhen, Qing Xuwen, Zhou Meng, Men Yuting

“…First, CenterNet and TTFNet algorithms are introduced, then pooling is introduced into CSPNet basic structure to design a lightweight feature extraction network, at the same time optimizing the feature fusion way in the original algorithm, optimizing residual shrinkage network structure, and introducing it into object detection task. …”
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Managing Intangible Assets as a Driver for Growth and Development of Industrial Enterprise by O. A. Elina, O. N. Bykova

“…As a rule this feature is typical of enterprises of the highly-technological sector. …”
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APPLICATION OF THE DUAL TREE COMPLEX WAVELET TRANSFORM AND MINIMUM ENTROPY DECONVOLUTION IN INCIPIENT FAULT DIAGNOSIS OF THE GEAR BOX by WANG ChaoGe, LIU TongTong, REN XuePing, ZHANG HaoDong, WANG JianGuo

“…Aiming at the problem that early fault characteristic signal of bearing in gear box is weak and affected by the environmental noise seriously,which makes the fault feature information is difficult to identify,a early fault diagnosis method of gear box is proposed based on dual-tree complex wavelet transform and minimum entropy deconvolution. …”
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MEF-CAAN: Multi-Exposure Image Fusion Based on a Low-Resolution Context Aggregation Attention Network by Wenxiang Zhang, Chunmeng Wang, Jun Zhu

“…However, most existing multi-exposure image fusion methods have insufficient feature extraction ability for recovering information and details in extremely exposed areas. …”
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A LiDAR - camera fusion detection method based on weight allocation by Kang Haotian, Wang Tianshu

“…In automatic driving target detection problem, the neural network is applied to two methods, vision, and LiDAR. …”
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Encoding Coefficient Similarity-Based Multifeature Sparse Representation for Finger Vein Recognition by Lizhen Zhou, Lu Yang, Deqian Fu, Gongping Yang

“…Furthermore, the proposed method is capable of fusing all kinds of features, not limited to specific ones. The optimization problem of the proposed method is efficiently solved using the alternating direction multiplier method algorithm. …”
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A Non-Convex Partition of Unity and Stress Analysis of a Cracked Elastic Medium by Won-Tak Hong

“…The partition of unity that we use has a unique feature: the mapped partition of unity has a curved shape in the physical coordinate system. …”
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Population level inference for multivariate MEG analysis. by Anna Jafarpour, Gareth Barnes, Lluis Fuentemilla, Emrah Duzel, Will D Penny

“…Multivariate analysis is a very general and powerful technique for analysing Magnetoencephalography (MEG) data. An outstanding problem however is how to make inferences that are consistent over a group of subjects as to whether there are condition-specific differences in data features, and what are those features that maximise these differences. …”
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Workflow Detection with Improved Phase Discriminability by ZHANG, M., HU, H., LI, Z.

“…Specifically, temporal self-attention is firstly designed to learn the relationship between different positions of feature sequence. Then, multi-scale Transformer is introduced to encode pyramid features, which fuses multiple context cues for discriminative feature representation. …”
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HR-NeRF: advancing realism and accuracy in highlight scene representation by Shufan Dai, Shanqin Wang

“…HRNet incorporates Swish activation functions, affine transformations, multilayer perceptrons (MLPs), and residual blocks, which collectively enable smooth non-linear transformations, adaptive feature scaling, and hierarchical feature extraction. …”
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Research on HMM based link prediction method in heterogeneous network by Rong QIAN, Jianting XU, Kejun ZHANG, Hongyu DONG, Fangyuan XING

“…In order to solve the problem that incomplete mining of structural information and semantic information in heterogeneous networks, a link prediction method combining meta-path-based analysis and hidden Markov model was proposed for link prediction of heterogeneous network.Considering that clustering could effectively capture the structural information of heterogeneous network, the k-means algorithm was improved to obtain the initial clustering center method based on the minimum distance mean square error, and it was applied to the hidden Markov model, first-order cluster hidden markov model (C-HMM⁽¹⁾) link prediction method, and a link prediction method for heterogeneous network with second-order cluster hidden Markov model (C-HMM⁽²⁾) were designed.Further, considering the feature information of the data, a link prediction method called ME-HMM that combined the maximum entropy model and the second-order Markov model was proposed.The experimental results show that the ME-HMM has higher link prediction accuracy than the C-HMM, and the ME-HMM method has better performance than the C-HMM method because it fully considers the feature information of the data.…”
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Soft label collaborative view consistency enhancement with application to incomplete multi-view clustering. by Jie Zhang, Jiali Tang

“…Firstly, we leverage the encoders of Transformers to construct a soft-label view information interaction module, which fully utilizes soft-labels to enhance view feature embeddings. Secondly, we employ soft labels to collaboratively impute missing features, addressing the incomplete multi-view data problem. …”
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2001 Sonrasında Türkiye Ekonomisinde Büyüme ve İstihdam: Türkiye’deki İşsizliğin Dinamikleri (Economic Growth and Unemployment in Turkey after 2001: Dynamics of Unemployment in Tur... by Gökhan Umut

“…After 2001, it has been seen that these problems have been eliminated. On the other hand, some problems which are different than the problems before 2001 have started to emerge in the economy. …”
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Research on an underwater high-speed vehicle target recognition method based on deep learning by WU Yajun, LIU Liwen

“…Due to the complexity of marine environment and the constantly upgrading of new countermeasure equipment, underwater high-speed vehicles are currently faced with the problem of insufficient recognition ability in complex marine environment, and it is urgent to find a new way of feature extraction and target recognition. …”
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Colony-YOLO: A Lightweight Micro-Colony Detection Network Based on Improved YOLOv8n by Meihua Wang, Junhui Luo, Kai Lin, Yuankai Chen, Xinpeng Huang, Jiping Liu, Anbang Wang, Deqin Xiao

“…Next, C2f-MLCA is designed by embedding MLCA (Mixed Local Channel Attention) into the C2f module of YOLOv8 to integrate local and global feature information, thereby enhancing feature representation capabilities. …”
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