|
|
|
Zeyu Xu, Wenbin Yu, Chengjun Zhang and Yadang Chen
In the era of noisy intermediate-scale quantum (NISQ) computing, the synergistic collaboration between quantum and classical computing models has emerged as a promising solution for tackling complex computational challenges. Long short-term memory (LSTM)...
ver más
|
|
|
|
|
|
|
Min Hu, Fan Zhang and Huiming Wu
Various abnormal scenarios might occur during the shield tunneling process, which have an impact on construction efficiency and safety. Existing research on shield tunneling construction anomaly detection typically designs models based on the characteris...
ver más
|
|
|
|
|
|
|
Aymane Ahajjam, Jaakko Putkonen, Emmanuel Chukwuemeka, Robert Chance and Timothy J. Pasch
Local weather forecasts in the Arctic outside of settlements are challenging due to the dearth of ground-level observation stations and high computational costs. During winter, these forecasts are critical to help prepare for potentially hazardous weathe...
ver más
|
|
|
|
|
|
|
Tala Talaei Khoei and Naima Kaabouch
Intrusion Detection Systems are expected to detect and prevent malicious activities in a network, such as a smart grid. However, they are the main systems targeted by cyber-attacks. A number of approaches have been proposed to classify and detect these a...
ver más
|
|
|
|
|
|
|
Qi Liu, Peng Nie, Hualin Dai, Liyuan Ning and Jiaxing Wang
Convolutional neural networks (CNN) are widely used for structural damage identification. However, the presence of environmental disturbances introduces noise into the acquired acceleration response data, impairing the performance of CNN models. In this ...
ver más
|
|
|
|
|
|
|
Chen Chen, Weidong Zhou and Lina Gao
A proper filtering method for jump Markov system (JMS) is an effective approach for tracking a maneuvering target. Since the coexisting of heavy-tailed measurement noises (HTMNs) and one-step random measurement delay (OSRMD) in the complex scenarios of t...
ver más
|
|
|
|
|
|
|
Ajay Bandi, Pydi Venkata Satya Ramesh Adapa and Yudu Eswar Vinay Pratap Kumar Kuchi
Generative artificial intelligence (AI) has emerged as a powerful technology with numerous applications in various domains. There is a need to identify the requirements and evaluation metrics for generative AI models designed for specific tasks. The purp...
ver más
|
|
|
|
|
|
|
Chen Chen, Weidong Zhou and Lina Gao
A suitable jump Markov system (JMS) filtering approach provides an efficient technique for tracking surface targets. In complex surface target tracking situations, due to the joint influences of lost measurements with an unknown probability and heavy-tai...
ver más
|
|
|
|
|
|
|
Mohit Kumar, Bernhard A. Moser, Lukas Fischer and Bernhard Freudenthaler
In order to develop machine learning and deep learning models that take into account the guidelines and principles of trustworthy AI, a novel information theoretic approach is introduced in this article. A unified approach to privacy-preserving interpret...
ver más
|
|
|
|
|
|
|
Jinhong Wu, Konstantinos Plataniotis, Lucy Liu, Ehsan Amjadian and Yuri Lawryshyn
Synthetic data, artificially generated by computer programs, has become more widely used in the financial domain to mitigate privacy concerns. Variational Autoencoder (VAE) is one of the most popular deep-learning models for generating synthetic data. Ho...
ver más
|
|
|
|