Zobrazeno 1 - 10
of 1 701
pro vyhledávání: '"Liu Yanming"'
Autor:
LI Fangfang, LIANG Xiuqing, ZHANG Hui, CHEN Qianqian, TIAN Qiyan, LI Haixia, WANG Yanli, ZHANG Hanshuang, LIU Yanming
Publikováno v:
Zhongguo shipin weisheng zazhi, Vol 35, Iss 3, Pp 367-373 (2023)
ObjectiveTo establish a method based on dispersive liquid-liquid microextraction coupled with gas chromatography for the simultaneous determination of seven common preservatives and three common antioxidants in vinegar.MethodsChloroform was used as t
Externí odkaz:
https://doaj.org/article/946e1a50221e483bb08ac93bf5fe8364
Autor:
SUN Shanshan, WANG Mingdong, ZHAO Huinan, ZHENG Wenjing, XUE Xia, HU Mei, WANG Jun, LIU Yanming, ZHANG Yanxia
Publikováno v:
Zhongguo shipin weisheng zazhi, Vol 35, Iss 2, Pp 198-203 (2023)
ObjectiveTo develop an analytical method for fast determination of banned pigment quinoline yellow in pastries by salting out assisted-high performance liquid chromatography.MethodsThe sample was extracted with 40% methanol-sodium chloride-water， p
Externí odkaz:
https://doaj.org/article/56bbe0b03fd84be890dbc262178d8fb9
Autor:
Han Guansheng, Xiang Jiahao, Lu Shuaijie, Zhou Yu, Tang Qiongqiong, Li Guangzhi, Cheng Zhangjianing, Zhang Tao, Chen Weiqiang, Gao Yuan, Liu Yanming
Publikováno v:
Reviews on Advanced Materials Science, Vol 62, Iss 1, Pp pp. 1349-1359 (2023)
Fiber-reinforced concrete (FRC) has apparent benefits over traditional cementitious composites and possesses a great prospect in civil engineering projects. Previous studies reported that fiber admixtures could effectively enhance the mechanical prop
Externí odkaz:
https://doaj.org/article/fb6e02928b6a4edc8ab77d37874d781c
Autor:
DING Yi, XUE Xia, LU Lanxiang, WEI Lili, CUI Yuhua, CHENG Zhi, CAI Ruiqi, WANG Jun, HU Mei, LIU Yanming
Publikováno v:
Zhongguo shipin weisheng zazhi, Vol 34, Iss 4, Pp 750-754 (2022)
ObjectiveTo establish a detection method for thiourea in wheat flour and flour treatment agents（FTA） by pass-through solid phase extraction purification and high performance liquid chromatography.MethodsThe samples were extracted by acetonitrile
Externí odkaz:
https://doaj.org/article/a71d9fdbd49b40a08c346587c622bd51
Publikováno v:
Open Physics, Vol 19, Iss 1, Pp 602-608 (2021)
The influence of acoustic radiation is considered in the prediction of noise attenuation effect of sound barrier, which provides a theoretical reference for further improving the insertion loss of sound barrier. Based on the theory of thin plate vibr
Externí odkaz:
https://doaj.org/article/c0594599fa204afc807e67bbfc54f3e4
Integrated sensing and communication (ISAC) systems have the issue of secrecy leakage when using the ISAC waveforms for sensing, thus posing a potential risk for eavesdropping. To address this problem, we propose to employ movable antennas (MAs) and
Externí odkaz:
http://arxiv.org/abs/2410.03426
Autor:
Liu, Yanming, Peng, Xinyue, Cao, Jiannan, Bo, Shi, Shen, Yanxin, Zhang, Xuhong, Cheng, Sheng, Wang, Xun, Yin, Jianwei, Du, Tianyu
Large language models (LLMs) have shown remarkable capabilities in natural language processing; however, they still face difficulties when tasked with understanding lengthy contexts and executing effective question answering. These challenges often a
Externí odkaz:
http://arxiv.org/abs/2410.01671
Autor:
Liu, Yanming, Peng, Xinyue, Zhang, Yuwei, Ke, Xiaolan, Deng, Songhang, Cao, Jiannan, Ma, Chen, Fu, Mengchen, Zhang, Xuhong, Cheng, Sheng, Wang, Xun, Yin, Jianwei, Du, Tianyu
Large language models have repeatedly shown outstanding performance across diverse applications. However, deploying these models can inadvertently risk user privacy. The significant memory demands during training pose a major challenge in terms of re
Externí odkaz:
http://arxiv.org/abs/2406.11087
Autor:
Liu, Yanming, Peng, Xinyue, Cao, Jiannan, Bo, Shi, Zhang, Yuwei, Zhang, Xuhong, Cheng, Sheng, Wang, Xun, Yin, Jianwei, Du, Tianyu
Large language models (LLMs) have demonstrated exceptional reasoning capabilities, enabling them to solve various complex problems. Recently, this ability has been applied to the paradigm of tool learning. Tool learning involves providing examples of
Externí odkaz:
http://arxiv.org/abs/2406.03807
Object detection methods under known single degradations have been extensively investigated. However, existing approaches require prior knowledge of the degradation type and train a separate model for each, limiting their practical applications in un
Externí odkaz:
http://arxiv.org/abs/2403.11220