Bi-directional Pre-trained Network for Single-station Seismic Waveform Analysis by Yuqi CAI, Ziye YU, Weitao WANG, Yanru AN, Lu LI

“…However, most neural network models in seismology currently focus on single tasks. Based on the CSNCD dataset released by the China Earthquake Networks Center, we have developed a bi-directional neural network pre-trained model for single-station data analysis. …”
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Hybrid transfer learning and self-attention framework for robust MRI-based brain tumor classification by Soumyarashmi Panigrahi, Dibya Ranjan Das Adhikary, Binod Kumar Pattanayak

“…This paper proposes a novel hybrid model combining Transfer Learning (TL) and attention mechanisms to enhance brain tumor classification accuracy. Leveraging features from the pre-trained DenseNet201 Convolutional Neural Networks (CNN) model and integrating a Transformer-based architecture, our approach overcomes challenges like computational intensity, detail detection, and noise sensitivity. …”
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Generating context-specific sports training plans by combining generative adversarial networks. by Juquan Tan, Jingwen Chen

“…This study aims to develop a Generative Adversarial Network (GAN)- based framework to create context-specific training plans by integrating numeric attributes (e.g., age, heart rate) and motion features from video data. …”
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Overground, Body Weight Supported Gait Training Robots: A Scoping Review by Jaime Ramos-Rojas, Emma Perez-Martin, Antonio J. Del-Ama

“…All devices featured assistance based on predefined joint kinematics. …”
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Abstract 154: Training Independent Artificial Intelligence Models for the Detection of Intracranial Pathology by Mahsa Eskian, Vera Sharashidze, Jeremy Heit, Hesham Masoud, Grahame Gould

“…Conclusion Our auto segmentation model is based on objects features instead of training models, thus providing a fast, generalizable, and feasible AI model. …”
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PEDAGOGICAL CONDITIONS FOR THE FORMATION OF SOCIAL AND ENTREPRENEURIAL COMPETENCE OF STUDENTS IN THE PROCESS OF PROFESSIONAL TRAINING by N. Klushina, V. Roshchupkina

“…Taking into account the considered characteristics and criteria, the essence and structure of social and entrepreneurial competence are revealed. Based on the study of the features of the organization of training in social entrepreneurship in the higher education system, the pedagogical conditions for the formation of socio-pedagogical competence are formulated.…”
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Application of Improved EWT Method in Bearing Fault Diagnosis of High-speed Train by Yuting LIU, Jianhui LIN

“…It is difficult to extract fault features of axle box bearings of high-speed train. …”
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Research on Cooperative Velocity Planning Technology for Urban Rail Train Virtual Coupling by HUANG Qiang, LI Cheng, YUAN Xiwen, CHEN Lin, LUO Jiaxiang

“…Based on the key requirements for urban rail trains, namely punctuality, comfort and sufficient time for platform operations, this study proposed a cooperative speed planning algorithm for virtual coupling, featuring information centralized decision-making, following an investigation into train traction and braking characteristics, vehicle kinematics and dynamics models. …”
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Research on adaptive parking planning of heavy-haul trains on Shenmu-Shuozhou railway by HE Jia, YUAN Peng

“…Planning operation curves in parking scenarios for heavy-haul trains equipped with intelligent driving features on the Shenmu-Shuozhou railway faces two primary challenges: maneuvering difficulties stemming from the inherent characteristics of heavy-haul trains and the complexity of the track environments. …”
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Social and psychological climate as a factor in professional training of students of technical universities by Elena N. Sorokina, Dmitry V. Gulyakin, Denis D. Grinev

“…The purpose is to study the socio–psychological climate of the student body, identify its features and factors affecting the educational process, as well as develop recommendations for its optimization. …”
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PCVR: a pre-trained contextualized visual representation for DNA sequence classification by Jiarui Zhou, Hui Wu, Kang Du, Wengang Zhou, Cong-Zhao Zhou, Houqiang Li

“…PCVR encodes FCGR with a vision transformer into contextualized features containing more global information. To meet the substantial data requirements of the training of vision transformer and learn more robust features, we pre-train the encoder with a masked autoencoder. …”
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Short-term train arrival delay prediction: a data-driven approach by Qingyun Fu, Shuxin Ding, Tao Zhang, Rongsheng Wang, Ping Hu, Cunlai Pu

“…However, delay predictions often involve imprecise shifts based on known delay times. Real-time and accurate train delay predictions, facilitated by data-driven neural network models, can significantly reduce dispatcher stress and improve adjustment plans. …”
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PFVnet, a feature enhancement network for low recognition coal and rock images by Cai Han, Zhenwen Liu, Shenglei Zhao, Yubo Li, Yanwei Duan, Xinzhou Yang, Chuanbo Hao

“…We characterized the grayscale and texture feature patterns of coal-rock media under varying degrees of interference and established a comprehensive multi-element image training sample library. …”
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SOFT POWER: TRAINING OF VET TEACHERS AND TRAINERS (RESULTS OF THE RUSSIAN-GERMAN COOPERATION) by E. Yu. Esenina, Hannelore Kress

“…Specifics of the German model are shown: existence of several skill levels of teachers of vocational education, distribution of zones of their responsibility, variability of providers of additional education, its market nature and minimum participation in its regulation of the state. Features of the modern Russian theory and training experience of instructors of vocational training are described. …”
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Comparative Analysis of Feature Selection Methods with XGBoost for Malware Detection on the Drebin Dataset by Ines Aulia Latifah, Fauzi Adi Rafrastara, Jevan Bintoro, Wildanil Ghozi, Waleed Mahgoub Osman

“…Traditional detection methods, such as signature-based detection, are often ineffective against new or polymorphic malware. …”
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Patch-Wise-Based Self-Supervised Learning for Anomaly Detection on Multivariate Time Series Data by Seungmin Oh, Le Hoang Anh, Dang Thanh Vu, Gwang Hyun Yu, Minsoo Hahn, Jinsul Kim

“…The proposed approach comprises four key components: (i) maintaining continuous features through patching, (ii) incorporating various temporal information by learning channel dependencies and adding relative positional bias, (iii) achieving feature representation learning through self-supervised learning, and (iv) supervised learning based on anomaly augmentation for downstream tasks. …”
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Boosting adversarial transferability in vision-language models via multimodal feature heterogeneity by Long Chen, Yuling Chen, Zhi Ouyang, Hui Dou, Yangwen Zhang, Haiwei Sang

“…To improve transferability, we propose a cross-modal variance aggregation-based multi-domain feature perturbation method, using text-guided image attacks to perturb consistent spatial and frequency features while combining previous gradient momentum, achieving better transferability. …”
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Federated and ensemble learning framework with optimized feature selection for heart disease detection by Olfa Hrizi, Karim Gasmi, Abdulrahman Alyami, Adel Alkhalil, Ibrahim Alrashdi, Ali Alqazzaz, Lassaad Ben Ammar, Manel Mrabet, Alameen E.M. Abdalrahman, Samia Yahyaoui

“…To improve classification performance while protecting data privacy, this study investigated a combined method that uses ensemble learning, feature selection, and federated learning (FL). The ensemble-based approaches proved the most predictive after testing several different machine learning (ML) models, including random forests, the light gradient boosting machine, support vector machines, k-nearest neighbors, convolutional neural networks, and long short-term memory. …”
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AFQSeg: An Adaptive Feature Quantization Network for Instance-Level Surface Crack Segmentation by Shaoliang Fang, Lu Lu, Zhu Lin, Zhanyu Yang, Shaosheng Wang

“…To address these issues, this paper proposes a crack detection model based on adaptive feature quantization, which primarily consists of a maximum soft pooling module, an adaptive crack feature quantization module, and a trainable crack post-processing module. …”
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Multiview Multimodal Feature Fusion for Breast Cancer Classification Using Deep Learning by Sadam Hussain, Mansoor Ali Teevno, Usman Naseem, Daly Betzabeth Avendano Avalos, Servando Cardona-Huerta, Jose Gerardo Tamez-Pena

“…Various augmentation techniques are applied to both imaging and textual data to expand the training dataset size. Imaging features were extracted using a Squeeze-and-Excitation (SE) network-based ResNet50 model, while textual features were extracted using an artificial neural network (ANN). …”
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