Zobrazeno 1 - 10
of 47
pro vyhledávání: '"YanGe Sun"'
Autor:
Yan Liu, Chao Pan, Kangfeng Wang, Yan Guo, YanGe Sun, Xiang Li, Peng Sun, Jun Wu, Hengliang Wang, Li Zhu
Publikováno v:
Microbial Cell Factories, Vol 22, Iss 1, Pp 1-13 (2023)
Abstract Background Engineered strains of Escherichia coli have been used to produce bioconjugate vaccines using Protein Glycan Coupling Technology (PGCT). Nanovaccines have also entered the vaccine development arena with advances in nanotechnology a
Externí odkaz:
https://doaj.org/article/136ebd322693411e9f743f186a065243
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
Accurate detection of tea diseases is essential for optimizing tea yield and quality, improving production, and minimizing economic losses. In this paper, we introduce TeaDiseaseNet, a novel disease detection method designed to address the challenges
Externí odkaz:
https://doaj.org/article/0584e4c3d57d4a6a9033a9d1cb042e5c
Publikováno v:
IEEE Access, Vol 10, Pp 34228-34235 (2022)
Time-varying linear equation systems have been solved by the traditional zeroing neural dynamics approach in recent years. However, this method has to satisfy the stability constraint, which is a very rigorous condition. For this reason, traditional
Externí odkaz:
https://doaj.org/article/8d774cec38d043c292d53b867b99afea
Publikováno v:
IEEE Access, Vol 8, Pp 191942-191955 (2020)
Most methods for classifying data streams operate under the hypothesis that the distribution of classes is balanced. Unfortunately, the phenomenon of class imbalance widely exists in many real-world applications. In addition, the underlying concept o
Externí odkaz:
https://doaj.org/article/726ac992426441739ab702789b7a2e38
Publikováno v:
Applied Sciences, Vol 12, Iss 23, p 11967 (2022)
Strip steel is an important raw material for the related industries, such as aerospace, shipbuilding, and pipelines, and any quality defects in the strip steel would lead to huge economic losses. However, it is still a challenge task to effectively d
Externí odkaz:
https://doaj.org/article/ddf04a6790d54d49b858e7bc07f6a2e6
Autor:
Yixin Shi, Chao Pan, Kangfeng Wang, Yan Liu, Yange Sun, Yan Guo, Peng Sun, Jun Wu, Ying Lu, Li Zhu, Hengliang Wang
Publikováno v:
Nanomaterials, Vol 12, Iss 5, p 734 (2022)
Proteinaceous nanovaccine delivery systems have significantly promoted the development of various high-efficiency vaccines. However, the widely used method of coupling the expression of scaffolds and antigens may result in their structural interferen
Externí odkaz:
https://doaj.org/article/3507da39619f497eb1ef1f7462eb5299
Publikováno v:
Information, Vol 10, Iss 5, p 158 (2019)
Most existing multi-label data streams classification methods focus on extending single-label streams classification approaches to multi-label cases, without considering the special characteristics of multi-label stream data, such as label dependency
Externí odkaz:
https://doaj.org/article/40e44c4cf91a430b9b55fa6137e86e7d
Publikováno v:
International Journal of Distributed Sensor Networks, Vol 12 (2016)
Data streams, which can be considered as one of the primary sources of what is called big data, arrive continuously with high speed. The biggest challenge in data streams mining is to deal with concept drifts, during which ensemble methods are widely
Externí odkaz:
https://doaj.org/article/312e55d16bcf4693b49bd413b0ec34e4
Publikováno v:
Electronics; Volume 12; Issue 12; Pages: 2631
The use of convolutional neural networks (CNN) for crowd counting has made significant progress in recent years; however, effectively addressing the scale variation and complex backgrounds remain challenging tasks. To address these challenges, we pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::1f5a5e46f2416c5297bc816c16578b71
Autor:
Honghua Dai, Yange Sun
Publikováno v:
Neural Computing and Applications. 33:6119-6132
Ensemble learning is one of the most frequently used techniques for handling concept drift, which is the greatest challenge for learning high-performance models from big evolving data streams. In this paper, a Pareto-based multi-objective optimizatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f7baec815070876df187b02ee5d2801c
https://doi.org/10.1007/s00521-020-05386-5
https://doi.org/10.1007/s00521-020-05386-5