Zobrazeno 1 - 10
of 1 209
pro vyhledávání: '"ZHAO Zilong"'
Publikováno v:
Shipin yu jixie, Vol 40, Iss 4, Pp 34-39 (2024)
Objective: This study aimed to explore the aroma differences of Pixian bean paste from different brands and establish an analytical method for quality evaluation and quality control methods in Douban Sauce, based on solid-phase microextraction (SPME)
Externí odkaz:
https://doaj.org/article/d44b9a6fc558443fb05ddb37e76da809
Publikováno v:
IET Cyber-Physical Systems, Vol 9, Iss 1, Pp 87-98 (2024)
Abstract In industrial environments, workers should wear workwear for safety considerations. For the same reason, smoking is also prohibited. Due to the supervision of monitoring devices, workers have reduced smoking behaviours and started wearing wo
Externí odkaz:
https://doaj.org/article/4b0cca6cef2a4fd38eb16bb124d00eb6
Autor:
Sun, Xingwu, Chen, Yanfeng, Huang, Yiqing, Xie, Ruobing, Zhu, Jiaqi, Zhang, Kai, Li, Shuaipeng, Yang, Zhen, Han, Jonny, Shu, Xiaobo, Bu, Jiahao, Chen, Zhongzhi, Huang, Xuemeng, Lian, Fengzong, Yang, Saiyong, Yan, Jianfeng, Zeng, Yuyuan, Ren, Xiaoqin, Yu, Chao, Wu, Lulu, Mao, Yue, Xia, Jun, Yang, Tao, Zheng, Suncong, Wu, Kan, Jiao, Dian, Xue, Jinbao, Zhang, Xipeng, Wu, Decheng, Liu, Kai, Wu, Dengpeng, Xu, Guanghui, Chen, Shaohua, Chen, Shuang, Feng, Xiao, Hong, Yigeng, Zheng, Junqiang, Xu, Chengcheng, Li, Zongwei, Kuang, Xiong, Hu, Jianglu, Chen, Yiqi, Deng, Yuchi, Li, Guiyang, Liu, Ao, Zhang, Chenchen, Hu, Shihui, Zhao, Zilong, Wu, Zifan, Ding, Yao, Wang, Weichao, Liu, Han, Wang, Roberts, Fei, Hao, Yu, Peijie, Zhao, Ze, Cao, Xun, Wang, Hai, Xiang, Fusheng, Huang, Mengyuan, Xiong, Zhiyuan, Hu, Bin, Hou, Xuebin, Jiang, Lei, Ma, Jianqiang, Wu, Jiajia, Deng, Yaping, Shen, Yi, Wang, Qian, Liu, Weijie, Liu, Jie, Chen, Meng, Dong, Liang, Jia, Weiwen, Chen, Hu, Liu, Feifei, Yuan, Rui, Xu, Huilin, Yan, Zhenxiang, Cao, Tengfei, Hu, Zhichao, Feng, Xinhua, Du, Dong, Yu, Tinghao, Tao, Yangyu, Zhang, Feng, Zhu, Jianchen, Xu, Chengzhong, Li, Xirui, Zha, Chong, Ouyang, Wen, Xia, Yinben, Li, Xiang, He, Zekun, Chen, Rongpeng, Song, Jiawei, Chen, Ruibin, Jiang, Fan, Zhao, Chongqing, Wang, Bo, Gong, Hao, Gan, Rong, Hu, Winston, Kang, Zhanhui, Yang, Yong, Liu, Yuhong, Wang, Di, Jiang, Jie
In this paper, we introduce Hunyuan-Large, which is currently the largest open-source Transformer-based mixture of experts model, with a total of 389 billion parameters and 52 billion activation parameters, capable of handling up to 256K tokens. We c
Externí odkaz:
http://arxiv.org/abs/2411.02265
Synthetic tabular data generation has gained significant attention for its potential in data augmentation, software testing and privacy-preserving data sharing. However, most research has primarily focused on larger datasets and evaluating their qual
Externí odkaz:
http://arxiv.org/abs/2410.01933
The activation functions are fundamental to neural networks as they introduce non-linearity into data relationships, thereby enabling deep networks to approximate complex data relations. Existing efforts to enhance neural network performance have pre
Externí odkaz:
http://arxiv.org/abs/2409.17021
In the current artificial intelligence (AI) era, the scale and quality of the dataset play a crucial role in training a high-quality AI model. However, often original data cannot be shared due to privacy concerns and regulations. A potential solution
Externí odkaz:
http://arxiv.org/abs/2409.03612
Autoencoders are popular neural networks that are able to compress high dimensional data to extract relevant latent information. TabNet is a state-of-the-art neural network model designed for tabular data that utilizes an autoencoder architecture for
Externí odkaz:
http://arxiv.org/abs/2404.17990
Using Large Language Models for complex mathematical reasoning is difficult, primarily due to the complexity of multi-step reasoning. The main challenges of this process include (1) selecting critical intermediate results to advance the procedure, an
Externí odkaz:
http://arxiv.org/abs/2402.17786
Given the ubiquitous use of tabular data in industries and the growing concerns in data privacy and security, tabular data synthesis emerges as a critical research area. The recent state-of-the-art methods show that large language models (LLMs) can b
Externí odkaz:
http://arxiv.org/abs/2310.12746
Generative Adversarial Networks (GANs) have achieved state-of-the-art results in tabular data synthesis, under the presumption of direct accessible training data. Vertical Federated Learning (VFL) is a paradigm which allows to distributedly train mac
Externí odkaz:
http://arxiv.org/abs/2302.01706