Zobrazeno 1 - 10
of 7 274
pro vyhledávání: '"Feng, Cheng"'
Semantic communication (SemCom) has emerged as a new paradigm for 6G communication, with deep learning (DL) models being one of the key drives to shift from the accuracy of bit/symbol to the semantics and pragmatics of data. Nevertheless, DL-based Se
Externí odkaz:
http://arxiv.org/abs/2406.06644
Autor:
Feng, Cheng, Zheng, Kedi, Shan, Lanqing, Alers, Hani, Stergioulas, Lampros, Guo, Hongye, Chen, Qixin
Peer-to-peer (P2P) trading is seen as a viable solution to handle the growing number of distributed energy resources in distribution networks. However, when dealing with large-scale consumers, there are several challenges that must be addressed. One
Externí odkaz:
http://arxiv.org/abs/2402.11769
We present General Time Transformer (GTT), an encoder-only style foundation model for zero-shot multivariate time series forecasting. GTT is pretrained on a large dataset of 200M high-quality time series samples spanning diverse domains. In our propo
Externí odkaz:
http://arxiv.org/abs/2402.07570
Autor:
Feng, Cheng
While new and effective methods for anomaly detection are frequently introduced, many studies prioritize the detection task without considering the need for explainability. Yet, in real-world applications, anomaly explanation, which aims to provide e
Externí odkaz:
http://arxiv.org/abs/2312.10968
The proliferation of novel industrial applications at the wireless edge, such as smart grids and vehicle networks, demands the advancement of cyber-physical systems. The performance of CPSs is closely linked to the last-mile wireless communication ne
Externí odkaz:
http://arxiv.org/abs/2311.02911
As renewable generation becomes more prevalent, traditional power systems dominated by synchronous generators are transitioning to systems dominated by converter-interfaced generation. These devices, with their weaker damping capabilities and lower i
Externí odkaz:
http://arxiv.org/abs/2309.01321
Depth sensing is of paramount importance for unmanned aerial and autonomous vehicles. Nonetheless, contemporary monocular depth estimation methods employing complex deep neural networks within Convolutional Neural Networks are inadequately expedient
Externí odkaz:
http://arxiv.org/abs/2308.10569
Publikováno v:
Biology Direct, Vol 19, Iss 1, Pp 1-11 (2024)
Abstract Background Hepatocellular carcinoma (HCC) ranks as the second leading cause of global cancer-related deaths and is characterized by a poor prognosis. Eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) have been proved to play import
Externí odkaz:
https://doaj.org/article/6be795aa0027494ba667787e9f502eea
Publikováno v:
Saudi Journal of Medicine and Medical Sciences, Vol 12, Iss 3, Pp 223-229 (2024)
Background: Central venous catheterization (CVC) is a critical clinical procedure. To avoid complications, possessing good knowledge regarding the CVC care bundle and skills for the proper insertion and maintenance of CVC are important. Objectives: T
Externí odkaz:
https://doaj.org/article/0b8c7f60a4804866b49e5219af15149b
Autor:
Minghua Li, Yanhong Wang, Xiaoyang Lin, Haiqiang Yang, Xiaolin Zhang, Yun Bai, Xiankun Li, Lulu Zhang, Feng Cheng, Chuanhai Cao, Qingyu Zhou
Publikováno v:
Exploration of Targeted Anti-tumor Therapy, Vol 5, Iss 3, Pp 600-626 (2024)
Aim: The main objective of this study was to investigate the antitumor effect of a mouse anti-human glypican-1 (GPC1) monoclonal antibody (mAb) on non-small cell lung carcinoma (NSCLC) and associated molecular mechanisms. Methods: The anti-proliferat
Externí odkaz:
https://doaj.org/article/83d4b1062b894c658d53bdaea8155123