A Multisource Data Fusion Modeling Prediction Method for Operation Environment of High-Speed Train by Decang Li, Juhui Zhang, Ruxun Xu, Jianjun Meng, Jianming Wang, Xiaoqiang Chen, Xin Jia, Junhui Ma

“…Then input the sample site into the BPNN for training and recognition, the feature fusion of heterogeneous sensor data is carried out, the decision output of BPNN is obtained, the output results are normalized, and its output is used as the basic probability assignment of Dempster–Shafer (D-S) evidence theory and synthesis rules. …”
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Combining Local Electromagnetic Scattering and Global Structure Features for SAR Open Set Recognition by Qinjie Lin, Hao Sun, Yanjie Xu, Junyu Wang, Kefeng Ji, Gangyao Kuang

“…Then, a class-anchor-based loss function is constructed by anchor loss and tuple loss, which cluster the features of known classes targets around predefined class anchors. …”
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Features of using methods and platforms for graphical modelling of business processes of enterprises in the context of digitalisation by V.О. Tkachuk, S.V. Obikhod, K.L. Pokhilchenko, A.O. Mikriukova, K.O. Demianchuk

“…Such business process modelling is the process of reflecting a subjective vision of the workflow in the form of a formal model consisting of interdependent operations. Based on a comparison of the features and mechanisms for implementing methods of graphical modelling business processes, the author grouped them, which allowed us to identify, in our opinion, the most modern solutions for modelling business processes, namely, the BPMN and ARIS methods. …”
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Real-time Diagnosis and Prediction of Grounding Insulation Fault inTrain Power Supply System by QIN Fangfang, ZHENG Caihui, LI Xueming, LI Peng

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Deep learning radiomics of left atrial appendage features for predicting atrial fibrillation recurrence by Yanping Yin, Sixiang Jia, Jing Zheng, Wei Wang, Ziwen Wang, Jiangbo Lin, Wenting Lin, Chao Feng, Shudong Xia, Weili Ge

“…LAA segmentation was performed using an nnUNet-based model, followed by radiomic feature extraction. …”
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Distance learning: opportunities and challenges in quarantine. by V. F. Zavizion, I. M. Bondarenko, D. I. Avierin, M. I. Hojouj, N. O. Davlietova, N. O. Cherednychenlo, A. V. Prokhach, V. E. Mashtaler, K. O. Dmytrenko, V. V. Lohvynenko, V. S. Kyslytsyna, O. A. Sukhoversha, Y. M. Khvorostenko, M. H. Elhajj, P. L. Suzdalev, T. F. Myroniuk, I. N. Kichtenko, Y. V. Hrabovskyi, K. V. Smolina, I. V. Baranov

“…A detailed analysis of the communication between the faculty members of the department among themselves and analysis of the features of teaching and self-education of students in the field of medical radiology and oncology based on answers and comments with using Google classroom, Socrative, Messenger Telegram, etc. was made. …”
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Genotypic and Phenotypic Association of Agronomic Features in Triticale Genotypes under Drought Stress Conditions by Hassan Basiri, Omid Alizadeh, Forud Bazrafshan, Mehdi Zare, Mohammad Yazdani

“…In each year, a split-plot design based on a randomized complete block design with three blocks (replication) was used every two years of the experiment (the growing season 2018-2019) in the research station located in the research complex of the Zarghan Agriculture and Natural Resources Research and Training Center, Fars, Iran. …”
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OrthoGPT: multimodal generative pre-trained transformer models for precise diagnosis and treatment of orthopedics by ZHANG Zhicheng, WANG Jing, ZHANG Yang, TIAN Yonglin, ZHANG Mengmeng, LYU Yisheng, WANG Fei-Yue

“…The model leverages multimodal feature alignment and fusion technology, multi-scenario personalized diagnosis and treatment plan generation technology, combined with an orthopedic world model based on parallel theory and multi-agent methods. …”
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Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers by Raja Azlina Raja Mahmood, AmirHossien Abdi, Masnida Hussin

“…In this study, two different sets of selected features have been adopted to train four machine-learning based classifiers.  …”
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Territorial Features of the Development of Russia’s Light Industry in the Early 2020s Tatyana A. Balina by T. A. Balina, L. S. Batalova, M. A. Pospishenko

“…Geopolitical challenges have shown that it is necessary to make maximum use of the existing potential by creating new production facilities, introducing modern technologies, forming our own raw material bases, and training personnel for the sustainable development of the industry. …”
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Model and training method for aerial image object detector with optimization of both robustness and computational efficiency by Alona Moskalenko, Mykola Zaretskyi, Maksym Vynohradov, Vladyslav Babych

“…The following results were obtained. A detector with a feature extractor based on ViT-S/16, modified with gate modules for dynamic examination was developed. …”
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Accurate prediction of virulence factors using pre-train protein language model and ensemble learning by Guanghui Li, Jian Zhou, Jiawei Luo, Cheng Liang

“…We calculated the true TM-score of the proteins based on their 3D structures and trained a TM-predictor model to predict structural similarity, thereby capturing hidden remote homology information within the sequences. …”
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3D CNN Approach for Tennis Movement Recognition Using Spatiotemporal Features of Video by Volodymyr Shymanskyi, Ilona Klymenok

“…The primary goal of this investigation is to develop a model for recognizing tennis movements using the spatiotemporal features of the video data. The study collects and organizes relevant video data, employing machine learning algorithms to create and train neural network models for movement classification. …”
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Features of Sheriff Court in Scotland in Early 19th Century (Exemplified by Selkirkshire County) by S. N. Gavrilov, M. A. Mukhin

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A Framework for Breast Cancer Classification with Deep Features and Modified Grey Wolf Optimization by Fathimathul Rajeena P.P, Sara Tehsin

“…Due to low-contrast images and irrelevant information in publicly available breast cancer datasets, existing models generally perform poorly. Pre-trained convolutional neural network models trained on generic datasets tend to extract irrelevant features when applied to domain-specific classification tasks, highlighting the need for a feature selection mechanism to transform high-dimensional data into a more discriminative feature space. …”
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Effect of Noises and GSM Codings on Pre-Trained Speaker Embedding Models in Forensic Voice Comparison by Mohammed Hamzah Alsalihi, David Sztaho

“…Samples are compared pairwise with and without enrollment for suspect speakers (known) because, often, forensic voice comparisons don’t have multiple samples of offenders. Speaker embedding features are extracted using four pre-trained techniques: X-vector, Emphasized channel attention, propagation and aggregation in time delay neural network (ECAPA-TDNN), large-scale self-supervised (Wavlm) and framework for self-supervised learning (Wav2vec) pre-trained. …”
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A lightweight YOLO network using temporal features for high-resolution sonar segmentation by Sen Gao, Sen Gao, Wei Guo, Wei Guo, Gaofei Xu, Gaofei Xu, Ben Liu, Ben Liu, Yu Sun, Bo Yuan

“…Current segmentation methods often struggle to balance processing speed with accuracy.MethodsWe propose a novel YOLO-based segmentation framework featuring: (1) A lightweight backbone(ghostnet) network optimized for sonar imagery processing (2) A bypass BiLSTM network for temporal feature learning across consecutive frames. …”
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Vehicle Exhaust Estimation Using YOLOv7 and Support Vector Regression with Image Features by Yun-Sin Lin, Ting-Yu Chen, Jiun-Jian Liaw, Hsi-Hsien Yang, Cheng-Hsiung Hsieh

“…Then, a support vector regression was trained, with four image features extracted from the ROI as the input vectors, while OP or PM was used as the output. …”
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Classification of SERS spectra for agrochemical detection using a neural network with engineered features by Mateo Frausto-Avila, Monserrat Ochoa-Elias, Jose Pablo Manriquez-Amavizca, María del Carmen González-López, Gonzalo Ramírez-García, Mario Alan Quiroz-Juárez

“…Our approach consists of a highly compact neural network combined with feature engineering that was trained using SERS patterns from experimental measurements. …”
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Sliding-Window CNN + Channel-Time Attention Transformer Network Trained with Inertial Measurement Units and Surface Electromyography Data for the Prediction of Muscle Activation an... by Aoyang Bai, Hongyun Song, Yan Wu, Shurong Dong, Gang Feng, Hao Jin

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