Zobrazeno 1 - 10
of 80 274
pro vyhledávání: '"Yuting An"'
Publikováno v:
Oil Crop Science, Vol 9, Iss 1, Pp 38-45 (2024)
The objective of this study was to determine the differences of aroma and taste in three black sesame originsbefore and after processing via flavor and widely metabolomics. By analyzing the sensory characteristics and metabolites of raw and treated b
Externí odkaz:
https://doaj.org/article/ffba7b01796946f5a9c8238adbf4fd0a
Autor:
Jang-Won Moon, Yuting An
Publikováno v:
Tourism and Hospitality, Vol 3, Iss 1, Pp 100-113 (2022)
This study introduces and applies the uses and gratifications theory to travel and tourism, resulting in a classification of U & G motivations (extant items) for this field. Uses and gratifications motivations are important for understanding e-touris
Externí odkaz:
https://doaj.org/article/5bb90b7e5bd3449281e0c764c1a6fb92
Autor:
Jang-Won Moon, Yuting An
Publikováno v:
Tourism and Hospitality, Vol 3, Iss 1, Pp 116-136 (2022)
This study employed the Uses and Gratifications Theory to explore the motivations for utilizing a smartphone during trips and satisfactions with travel experience. This study adopted multilevel SEM to explore how U&G motivations affect e-tourist sati
Externí odkaz:
https://doaj.org/article/f569e719fb204bdba6dc8644c10ed3fd
Autor:
Wang, Aoxiang, Zhu, Ya-Nan, Setianegara, Jufri, Lin, Yuting, Xiao, Peng, Xie, Qingguo, Gao, Hao
Background: Intensity-modulated proton therapy (IMPT) using pencil beam technique scans tumor in a layer by layer, then spot by spot manner. It can provide highly conformal dose to tumor targets and spare nearby organs-at-risk (OAR). Fast delivery of
Externí odkaz:
http://arxiv.org/abs/2411.18074
Autor:
Shinde, Nimita, Zhu, Yanan, Wang, Wei, Li, Wangyao, Lin, Yuting, Gan, Gregory N, Lominska, Christopher, Rotondo, Ronny, Chen, Ronald C, Gao, Hao
Objective: Proton spot-scanning arc therapy (ARC) is an emerging modality that can improve the high-dose conformity to targets compared with standard intensity-modulated proton therapy (IMPT). However, the efficient treatment delivery of ARC is chall
Externí odkaz:
http://arxiv.org/abs/2411.17578
Federated learning (FL) has emerged as a powerful approach to safeguard data privacy by training models across distributed edge devices without centralizing local data. Despite advancements in homogeneous data scenarios, maintaining performance betwe
Externí odkaz:
http://arxiv.org/abs/2411.15837
In this paper, we propose a distributionally robust safety verification method for Markov decision processes where only an ambiguous transition kernel is available instead of the precise transition kernel. We define the ambiguity set around the nomin
Externí odkaz:
http://arxiv.org/abs/2411.15622
Multimodal large language models (MLLMs) are closing the gap to human visual perception capability rapidly, while, still lag behind on attending to subtle images details or locating small objects precisely, etc. Common schemes to tackle these issues
Externí odkaz:
http://arxiv.org/abs/2411.13909
Large Vision-Language Models (LVLMs) represent a significant advancement toward achieving superior multimodal capabilities by enabling powerful Large Language Models (LLMs) to understand visual input. Typically, LVLMs utilize visual encoders, such as
Externí odkaz:
http://arxiv.org/abs/2411.14164
Autor:
Qin, Ruiyang, Liu, Dancheng, Xu, Gelei, Yan, Zheyu, Xu, Chenhui, Hu, Yuting, Hu, X. Sharon, Xiong, Jinjun, Shi, Yiyu
The combination of Large Language Models (LLM) and Automatic Speech Recognition (ASR), when deployed on edge devices (called edge ASR-LLM), can serve as a powerful personalized assistant to enable audio-based interaction for users. Compared to text-b
Externí odkaz:
http://arxiv.org/abs/2411.13766