USE OF ICT IN DISTANCE LEARNING by Y. Zaporozhchenko

Subjects: “…synchronous and asynchronous methods of learning interaction…”
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Impact of Digital Drawing Tools on the Experimental Learning Process: A Mixed-Methods Study at Jadara University

“…This mixed-methods research uses controlled experiments on 45 randomly chosen students in two groups: Group A, the control, and Group B, the experimental The experimental group learns visual communication using modern digital sketching tools, whereas the control group uses conventional techniques. …”
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Implementation of Case-Based Learning in 1st-Year MBBS Students -Future of Medical Professionals Learning Methods in Indian Medical Colleges? by Mandar Vilas Ambike, Jayshree Sachin Kharche, Shraddha Shripad Kulkarni, T Vijaya Sagar, K Vijayakumar, Suresh Babu Kondaveeti

“…Background: Case Based Learning (CBL) is the best method for correlation of knowledge with clinical scenarios. …”
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Integrating AI-based adaptive learning into the flipped classroom model to enhance engagement and learning outcomes by Jozsef Katona, Klara Ida Katonane Gyonyoru

Subjects: “…AI-Based adaptive learning…”
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New Approaches to AI Methods for Screening Cardiomegaly on Chest Radiographs by Patrycja S. Matusik, Zbisław Tabor, Iwona Kucybała, Jarosław D. Jarczewski, Tadeusz J. Popiela

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Artificial intelligence-driven computational methods for antibody design and optimization by Luiz Felipe Vecchietti, Bryan Nathanael Wijaya, Azamat Armanuly, Begench Hangeldiyev, Hyunkyu Jung, Sooyeon Lee, Meeyoung Cha, Ho Min Kim

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Reinforcement Learning for Data-driven Workflows in Radio Interferometry. I. Principal Demonstration in Calibration by Brian M. Kirk, Urvashi Rau, Ramyaa Ramyaa

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Challenges faced by the Teachers and Students in online learning during COVID-19 by Muhammad Hafeez, Qaiser Abbas Kazmi, Fatima Tahira

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Application Of Machine Learning Models To Predict Warping Of Plastic Automotive Parts by Evandro Menezes de Souza Amarante, João Paulo Rios Brandão de Oliveira, Pedro Guilherme Carvalho de Souza Marconi, Armando Sá Ribeiro Júnior

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A fine‐grained image classification method based on information interaction by Shuo Zhu, Xukang Zhang, Yu Wang, Zongyang Wang, Jiahao Sun

“…The experimental results show that the method has good generalization on different datasets.…”
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A Review of Vision-Based Multi-Task Perception Research Methods for Autonomous Vehicles by Hai Wang, Jiayi Li, Haoran Dong

“…In this paper, we review the research progress in the field of vision-based multi-task perception for autonomous driving and introduce the methods of traffic object detection, drivable area segmentation, and lane detection in detail. …”
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Research on Underwater Echo Generation Method Based on Small Sample by Chen-yu WANG, Li-wen LIU, Gang LIU, Bo LI, Yun-chuan YANG

“…Under the tide led by artificial intelligence, the application of deep learning methods in underwater target recognition has gained increasing attention. …”
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Panoptic Segmentation Method Based on Feature Fusion and Edge Guidance by Lanshi Yang, Shiguo Wang, Shuhua Teng

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Complex Network Method for Inferring Well Interconnectivity in Hydrocarbon Reservoirs by M. Mayoral-Villa, F. A. Godínez, J. A. González-Guevara, J. Klapp, J. E. V. Guzmán

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LDoS attack detection method based on simple statistical features by Xueyuan DUAN, Yu FU, Kun WANG, Bin LI

“…Traditional low-rate denial of service (LDoS) attack detection methods were complex in feature extraction, high in computational cost, single in experimental data background settings, and outdated in attack scenarios, so it was difficult to meet the demand for LDoS attack detection in a real network environment.By studying the principle of LDoS attack and analyzing the features of LDoS attack traffic, a detection method of LDoS attack based on simple statistical features of network traffic was proposed.By using the simple statistical features of network traffic packets, the detection data sequence was constructed, the time correlation features of input samples were extracted by deep learning technology, and the LDoS attack judgment was made according to the difference between the reconstructed sequence and the original input sequence.Experimental results show that the proposed method can effectively detect the LDoS attack traffic in traffic and has strong adaptability to heterogeneous network traffic.…”
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C-SHAP: A Hybrid Method for Fast and Efficient Interpretability by Golshid Ranjbaran, Diego Reforgiato Recupero, Chanchal K. Roy, Kevin A. Schneider

“…C-SHAP excels across various datasets and machine learning methods, matching SHAP’s accuracy in selected features while maintaining an accuracy of 0.73 for Random Forest with substantially faster performance. …”
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Advanced Financial Fraud Malware Detection Method in the Android Environment by Jaeho Shin, Daehyun Kim, Kyungho Lee

“…This study proposes a machine learning (ML) model based on static analysis to detect malware. …”
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A kinetic-based regularization method for data science applications by Abhisek Ganguly, Alessandro Gabbana, Vybhav Rao, Sauro Succi, Santosh Ansumali

“…We also show that thanks to its local nature, the method offers computational and memory efficiency advantages over Radial Basis Function interpolators, especially for large datasets.…”
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An intelligent simplification method for river networks with an unsupervised variational autoencoder by Di Wang, Haizhong Qian, Xiao Wang, Limin Xie, Yue Chen, Linghui Kong

“…Traditional rule-based methods often have limitations, such as relying on the determination of parameters and thresholds. …”
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Combined Method for Informative Feature Selection for Speech Pathology Detection by D. S. Likhachov, M. I. Vashkevich, N. A. Petrovsky, E. S. Azarov

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