Zobrazeno 1 - 10
of 134
pro vyhledávání: '"Junhuai Li"'
Autor:
Aimin Li, Haotian Zhou, Siqi Xiong, Junhuai Li, Saurav Mallik, Rong Fei, Yajun Liu, Hongfang Zhou, Xiaofan Wang, Xinhong Hei, Lei Wang
Publikováno v:
BMC Genomics, Vol 25, Iss 1, Pp 1-10 (2024)
Abstract Background Long non-coding RNAs (lncRNAs) are RNA transcripts of more than 200 nucleotides that do not encode canonical proteins. Their biological structure is similar to messenger RNAs (mRNAs). To distinguish between lncRNA and mRNA transcr
Externí odkaz:
https://doaj.org/article/3842969358e14a56aafe1854bab81fcf
Publikováno v:
PeerJ Computer Science, Vol 10, p e2379 (2024)
Edge computing is a crucial technology to solve the problem of computing resources and bandwidth required for extensive edge data processing, as well as for meeting the real-time demands of applications. Container virtualization technology has become
Externí odkaz:
https://doaj.org/article/4cf3ea6ddcf0491085e3418d50301fa1
Autor:
Xiujuan Li, Junhuai Li
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Semantic segmentation of remote sensing images (RSI) is an important research direction in remote sensing technology. This paper proposes a multi-feature fusion and channel attention network, MFCA-Net, aiming to improve the segmentation accu
Externí odkaz:
https://doaj.org/article/182838ed2bcd415f98aae95a49c45a97
Publikováno v:
Energy Reports, Vol 9, Iss , Pp 277-287 (2023)
The temporal and spatial distribution of electric vehicle charging load (EVCL) is closely related with the drivers’ trip behavior, which has a highly uncertainty. The access of EVCL will increase the risk of safe and stable operation of the distrib
Externí odkaz:
https://doaj.org/article/b84393fdde8b47bc9d0cc0adec015d12
Publikováno v:
Sensors, Vol 24, Iss 10, p 3097 (2024)
During robot-assisted rehabilitation, failure to recognize lower limb movement may efficiently limit the development of exoskeleton robots, especially for individuals with knee pathology. A major challenge encountered with surface electromyography (s
Externí odkaz:
https://doaj.org/article/661e0347023f4162999891541d3c7d1f
Publikováno v:
IET Image Processing, Vol 16, Iss 13, Pp 3579-3588 (2022)
Abstract Removing the undesired reflection layer from images taken through glass windows is an important yet challenging task. Many existing CNN‐based methods try to utilize the gradient as an important clue to guide the training and achieve better
Externí odkaz:
https://doaj.org/article/269db6838fc84b3a98f4a93edb15c210
Publikováno v:
Journal of Innovative Optical Health Sciences, Vol 16, Iss 04 (2023)
Vascular segmentation is a crucial task in biomedical image processing, which is significant for analyzing and modeling vascular networks under physiological and pathological states. With advances in fluorescent labeling and mesoscopic optical techni
Externí odkaz:
https://doaj.org/article/201a7758ea114f44a0d6403e813fe0ed
Publikováno v:
IET Generation, Transmission & Distribution, Vol 16, Iss 3, Pp 467-478 (2022)
Abstract Widespread adoption of electric vehicles (EVs) would significantly increase the electrical load demand in power distribution networks. Most previous studies investigated EV charging demand based on drivers’ trip habits, but the impact of p
Externí odkaz:
https://doaj.org/article/0c8aa39296e74bdf8a06dda51fdc00c0
Publikováno v:
IEEE Access, Vol 10, Pp 52102-52115 (2022)
To balance the objective of all stakeholders’ interests in the electric vehicle (EV) charging station planning, a multi-objective optimization method based on an improved Cuckoo search algorithm is proposed in this paper. Firstly, the temporal and
Externí odkaz:
https://doaj.org/article/b6924109d66c4fa99e78ecd7ff501aa8
Publikováno v:
IEEE Access, Vol 9, Pp 31213-31224 (2021)
Labanotation is a widely used dance recording system, which plays an important role in inheriting and protecting folk dances. However, manual drawing of dance notation is time-consuming and labor-intensive. Therefore, research on the automatic genera
Externí odkaz:
https://doaj.org/article/3e87c59501b14570937a34ac10d88ea0