General Analysis
General analysis encompasses a broad range of methodologies applied across diverse scientific domains to extract meaningful insights from data. Current research focuses on developing robust and efficient analytical techniques, including the application of machine learning models like convolutional neural networks, graph neural networks, and transformer architectures, as well as statistical methods for data modeling and hypothesis testing. These advancements are improving the accuracy and efficiency of analyses in fields ranging from medical image processing and materials science to social media analysis and autonomous systems, ultimately leading to more reliable scientific findings and improved decision-making in various applications.
Papers
Analysis of Impulsive Interference in Digital Audio Broadcasting Systems in Electric Vehicles
Chin-Hung Chen, Wen-Hung Huang, Boris Karanov, Alex Young, Yan Wu, Wim van Houtum
Enhancing the analysis of murine neonatal ultrasonic vocalizations: Development, evaluation, and application of different mathematical models
Rudolf Herdt, Louisa Kinzel, Johann Georg Maaß, Marvin Walther, Henning Fröhlich, Tim Schubert, Peter Maass, Christian Patrick Schaaf
SMP Challenge: An Overview and Analysis of Social Media Prediction Challenge
Bo Wu, Peiye Liu, Wen-Huang Cheng, Bei Liu, Zhaoyang Zeng, Jia Wang, Qiushi Huang, Jiebo Luo
Analysis, Modeling and Design of Personalized Digital Learning Environment
Sanjaya Khanal, Shiva Raj Pokhrel