Zobrazeno 1 - 10
of 3 434
pro vyhledávání: '"Lin Chu"'
Publikováno v:
Frontiers in Psychology, Vol 15 (2024)
BackgroundParenting behavior has been reported to be closely associated with children’s creativity, yet the association between challenging parenting behavior and children’s creative tendencies, as well as the potential mechanisms connecting the
Externí odkaz:
https://doaj.org/article/b43a1221cebe47d0984ca2350fb49473
Publikováno v:
Frontiers in Psychology, Vol 15 (2024)
IntroductionThe popularization and widespread use of smartphones and other electronic devices have led to the occurrence of “parents phubbing”, which may have a negative impact on child-parent relationship and preschoolers’ prosocial behavior.M
Externí odkaz:
https://doaj.org/article/99b3665d0b5b4a9fb0d42769db843508
Publikováno v:
Pharmacological Research - Modern Chinese Medicine, Vol 10, Iss , Pp 100374- (2024)
Introduction: In recent years, with the advancement of life sciences, the theories of Traditional Chinese medicine (TCM) have been scientifically elucidated, particularly the integration of the TCM theory of ''the lung and large intestine are interre
Externí odkaz:
https://doaj.org/article/51d984b3020e441b9ce7ee5906cf4cf9
Publikováno v:
International Soil and Water Conservation Research, Vol 11, Iss 3, Pp 507-517 (2023)
Socioeconomic development induced nonpoint source (NPS) pollution has aroused an increasing concern, however, most of the previous studies were concentrated on the impacts of environmental determinants. Here, total nitrogen (TN) and total phosphorus
Externí odkaz:
https://doaj.org/article/3221add4c6904735ad772aaebc427e5f
The rise of deepfake technologies has posed significant challenges to privacy, security, and information integrity, particularly in audio and multimedia content. This paper introduces a Quantum-Trained Convolutional Neural Network (QT-CNN) framework
Externí odkaz:
http://arxiv.org/abs/2410.09250
In the Quantum-Train (QT) framework, mapping quantum state measurements to classical neural network weights is a critical challenge that affects the scalability and efficiency of hybrid quantum-classical models. The traditional QT framework employs a
Externí odkaz:
http://arxiv.org/abs/2409.06992
Flood prediction is a critical challenge in the context of climate change, with significant implications for ecosystem preservation, human safety, and infrastructure protection. In this study, we tackle this problem by applying the Quantum-Train (QT)
Externí odkaz:
http://arxiv.org/abs/2407.08617
Quantum reinforcement learning utilizes quantum layers to process information within a machine learning model. However, both pure and hybrid quantum reinforcement learning face challenges such as data encoding and the use of quantum computers during
Externí odkaz:
http://arxiv.org/abs/2407.06103
Autor:
Zhu, Yun, Gu, Jia-Chen, Sikora, Caitlin, Ko, Ho, Liu, Yinxiao, Lin, Chu-Cheng, Shu, Lei, Luo, Liangchen, Meng, Lei, Liu, Bang, Chen, Jindong
Large language models (LLMs) augmented with retrieval exhibit robust performance and extensive versatility by incorporating external contexts. However, the input length grows linearly in the number of retrieved documents, causing a dramatic increase
Externí odkaz:
http://arxiv.org/abs/2405.16178
Autor:
Liu, Chen-Yu, Kuo, En-Jui, Lin, Chu-Hsuan Abraham, Young, Jason Gemsun, Chang, Yeong-Jar, Hsieh, Min-Hsiu, Goan, Hsi-Sheng
We introduces the Quantum-Train(QT) framework, a novel approach that integrates quantum computing with classical machine learning algorithms to address significant challenges in data encoding, model compression, and inference hardware requirements. E
Externí odkaz:
http://arxiv.org/abs/2405.11304