USING E-LEARNING TO PREVENT INFORMATIONAL STRESS OF EMPLOYEES WORKING REMOTELY by Oleksandra Pinchuk, Nataliia I. Pinchuk, Olena I. Bondarchuk, Valentyna V. Balakhtar, Kateryna S. Pavlenok

“…The following specific features of informational stress, by their information impact, are highlighted: 1) features associated with information overload, 2) features associated with human interaction with information technology, and 3) features associated with professional activities. …”
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A Novel Two-Stream Network for Few-Shot Remote Sensing Image Scene Classification by Yaolin Lei, Yangyang Li, Heting Mao

“…This helps solve the problem of features within the same class being spread out and features between classes being too similar in remote sensing images. …”
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Facial Kinship Recognition Through Dilated-Stacked-Unified Attention Network by Ahmed A. Dabas, Mohamed A. Ismail, Nagia M. Ghanem

“…We investigate the effects of learning those features in an alternative domain of decoupled channel-spatial. …”
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Predicting Response to Neoadjuvant Chemotherapy with PET Imaging Using Convolutional Neural Networks. by Petros-Pavlos Ypsilantis, Musib Siddique, Hyon-Mok Sohn, Andrew Davies, Gary Cook, Vicky Goh, Giovanni Montana

“…While the dominant methodology relies on hand-crafted texture features, we explore the potential of automatically learning low- to high-level features directly from PET scans. …”
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Research on an Eye Control Method Based on the Fusion of Facial Expression and Gaze Intention Recognition by Xiangyang Sun, Zihan Cai

“…Based on the self-attention fusion strategy, the fused features are calculated, and the multi-layer perceptron is used to classify the fused features, so as to realize the mutual attention between different features, and improve the accuracy of intention recognition by enhancing the weight of effective features in a targeted manner. …”
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False traffic information detection based on weak classifiers integration in vehicular ad hoc networks by Xiang-wen LIU, Ya-li SHI, ENGXia F

“…Vehicles report traffic information mutually by self-organized manner in vehicular ad hoc networks (VANET),and the message need to be identified in the open network environment.However,it is very difficult for fast moving ve-hicles to detect a lot of traffic alert information in a short time.To solve this problem,a false traffic message detection method was presented based on weak classifiers integration.Firstly,the effective features of traffic alert information was extended and segmentation rules were designed to divide the information feature set into multiple feature subsets,then the corresponding weak classifiers were used to process feature subsets respectively according to the different character-istics of the subsets' features.Simulation experiments and performance analysis show that the selected weak classifiers integration method reduces the detection time,and because of the application of combined features,the detection rate is better than the test of using only some of the characteristics.…”
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A Deep Learning Approach for Crop Disease and Pest Classification Using Swin Transformer and Dual-Attention Multi-Scale Fusion Network by R. Karthik, Armaano Ajay, Akshaj Singh Bisht, T. Illakiya, K. Suganthi

“…This research proposes a new feature fusion-based model that uses two parallel tracks to extract features from plant images. …”
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Medico-Social Approach to the Development of a Methodology for Assessing the “Quality of Life” after Cataract Phacoemulsification. Part 1 by I. G. Ovechkin, N. I. Ovechkin, A. V. Shakula, A. I. Pavlov, D. F. Pokrovsky

“…Along with this, the practical application of the basic provisions of the ICF involves scaling the severity of the patient’s complaints in the context of the ratio of the duration of the complaint to the total active time of the patient with a gradation: “Mild problems” (5–24 %); “Moderate problems” (25–49 %); “Severe problems” (50–95 %); “Absolute problems” (96–100 %).Conclusion. …”
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Optimal Thermal Output of an Absorption Heat Pump with Steam Heating Integrated in a PT-60/70-130/13 Steam Turbine by Oleksandr L. Shubenko, Viktoriia O. Tarasova, Mykola Yu. Babak, Oleksii Yu. Boiarshynov

“…The control parameters of these problems were: thermal capacity of the AHP, steam pressure in the turbine condenser and at the inlet to the heat pump, steam pressure in the turbine headю These problems were solved by the coordinate descent method. …”

Physical Information Neural Network-Based Seepage Behavior Analysis of Earth and Rock Dams by XUE binghan, HUANG zhenhua, LEI Jianwei, FANG Hongyuan

“…To address these limitations, this study proposes a novel seepage field solution method based on Physics-Informed Neural Networks (PINNs).MethodsThe core of the proposed method lies in transforming the free-boundary seepage problem into a fixed-boundary optimization problem. …”
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Fault diagnosis of HVCB via the subtraction average based optimizer algorithm optimized multi channel CNN-SABO-SVM network by Qingjun Song, Jiuxin Wang, Qinghui Song, Kai Li, Wenchao Hao, Haiyan Jiang

“…Abstract The mechanical fault diagnosis of HVCB is important to ensure the stability of electric power systems. Aiming at the problem of poor diagnostic performance of deep learning methods under limited samples, this paper proposes an HVCB operating mechanism fault diagnosis model (multi-channel CNN-SABO-SVM, MCCSS) based on multimodal data fusion features and Subtraction-Average-Based Optimizer (SABO). …”
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A swin transformer and CNN fusion framework for accurate Parkinson disease classification in MRI by Sayyed Shahid Hussain, Pir Masoom Shah, Hussain Dawood, Xu Degang, Ahmad Alshamayleh, Muhammad Adnan Khan, Taher M. Ghazal

“…Additionally, the varying magnitude of MR data poses a challenge for ViT, potentially leading to the gradient vanishing problem. To address these limitations, this paper proposed a novel framework that combines the Swin-Transformer and CNN to capture both local and global features effectively. …”
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A Projective-Geometry-Aware Network for 3D Vertebra Localization in Calibrated Biplanar X-Ray Images by Kangqing Ye, Wenyuan Sun, Rong Tao, Guoyan Zheng

“…The network design of ProVLNet features three components: a Siamese 2D feature extractor to extract local appearance features from the biplanar X-ray images, a spatial alignment fusion module to incorporate the projective geometry in fusing the extracted 2D features in 3D space, and a 3D landmark regression module to regress the 3D coordinates of the vertebrae from the 3D fused features. …”
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Deep-Learning-Guided Student Classroom Action Understanding for Preschool Education by Xiaoli Li

“…We attempt to solve the problem of effective preschool teaching, based on which we propose the simple adaptation strategies. …”
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Spatio-temporal Graph Convolutional Neural Network for traffic signal prediction in large-scale urban networks by Shimon Komarovsky, Jack Haddad

“…This research aims at tackling the traffic signal problem for large-scale networks via a deep learning approach. …”
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GDSN-CD: Graph-Guided Diffusion Synergistic Network for Remote Sensing Change Detection by Yunfei Zhu, Jintao Song, Jinjiang Li

“…Based on this approach, we propose an end-to-end GDSN-CD framework. To overcome the problem of semantic and noise feature mismatch that may occur during the denoising process of diffusion models, we innovatively design a semantic-noise collaborative module, which uses a grouped channel fusion strategy to achieve precise feature matching. …”
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Detection Method for Bolts with Mission Pins on Transmission Lines Based on DBSCAN-FPN by Zhenbing ZHAO, Shuai ZHANG, Wei JIANG, Peng WU

“…As the bolt with missing pins are small targets, their positioning is difficult and their features are hard to extract. Aim at this problem, a detection method for bolts with missing pins is proposed based on the DBSCAN algorithm and FPN model. …”
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Innovative financial solutions for sustainable investments using artificial intelligence-based hybrid fuzzy decision-making approach in carbon capture technologies by Serhat Yüksel, Serkan Eti, Hasan Dinçer, Yaşar Gökalp, Gabriela Oana Olaru, Nihal Kalaycı Oflaz

“…Some issues must be considered when developing innovative financial products. An important problem in this process is that these features cannot possibly exist together in the new financial product, because each of these features incurs some costs. …”
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CONSTRUCTING MATHEMATICAL CONCEPTS DENTITION IN COMPLETE DENTURES by Donat Lola, Yuri Majboroda, Anton Nazarov

“…The basic criteria and parameters necessary for the successful solution of the problem of monitoring the individual features of arrangement of teeth in each case on the basis of the mathematical model. …”
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Comparative study of the selected methods of laryngeal tone determination by W. Wszołek, M. Kłaczyński

“…Laryngeal tone (pitch), understood as fundamental frequency of the voice ($F_0$), is one of the most important features in the field of acoustic studies of the speech signal. …”
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