Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Yuyun Kang"'
Publikováno v:
Frontiers in Physiology, Vol 13 (2022)
Depression is an undetectable mental disease. Most of the patients with depressive symptoms do not know that they are suffering from depression. Since the novel Coronavirus pandemic 2019, the number of patients with depression has increased rapidly.
Externí odkaz:
https://doaj.org/article/680a9d0e67ff48e788850bdc4e2d675c
Publikováno v:
Frontiers in Physiology, Vol 13 (2022)
Reasonable exercise is beneficial to human health. However, it is difficult for ordinary athletes to judge whether they are already in a state of fatigue that is not suitable for exercise. In this case, it is easy to cause physical damage or even lif
Externí odkaz:
https://doaj.org/article/3bcfcadd4beb4a6e855b8afae0f43390
Publikováno v:
Entropy, Vol 24, Iss 11, p 1618 (2022)
The gearbox is an important component in the mechanical transmission system and plays a key role in aerospace, wind power and other fields. Gear failure is one of the main causes of gearbox failure, and therefore it is very important to accurately di
Externí odkaz:
https://doaj.org/article/4288f71334a64f439176338be8c6e9e3
Publikováno v:
Advances in Mechanical Engineering, Vol 12 (2020)
In order to timely identify and mitigate the adverse effect of the random disturbance in the manufacturing system, a method of identifying and mitigating the random disturbance is proposed. In the method, the disturbance is structured into several ca
Externí odkaz:
https://doaj.org/article/4f2dbcdd91b446efaecba168a50e005d
Autor:
Yuyun Kang, Dunbing Tang
Publikováno v:
Advances in Mechanical Engineering, Vol 5 (2013)
In order to integrate two single-function products to a multifunction product, a matrix-based conceptual solution generation approach is proposed in this paper. In the approach, the overall function of a single-function product is decomposed into a n
Externí odkaz:
https://doaj.org/article/5337511889c14d3d9414018251c83878
Publikováno v:
Processes; Volume 10; Issue 7; Pages: 1426
With the development of information technology, it has become increasingly important to use intelligent algorithms to diagnose mechanical equipment faults based on vibration signals of rolling bearings. However, with the application of high-performan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::33cbfa9df66082fb07c8fbf7aeaabba1
A DQN-based workflow task assignment approach in cloud-fog cooperative considering terminal mobility
Publikováno v:
The 6th International Conference on Control Engineering and Artificial Intelligence.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b9620fcb5cc794ca4062a5883e648e51
https://doi.org/10.1145/3522749.3523083
https://doi.org/10.1145/3522749.3523083
Publikováno v:
The 6th International Conference on Control Engineering and Artificial Intelligence.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ff726afa972ce7f28b8b73c8eea42cd8
https://doi.org/10.1145/3522749.3523084
https://doi.org/10.1145/3522749.3523084
Publikováno v:
Psychiatry Research: Neuroimaging. 328:111582
Depression is a mental illness and can even lead to suicide if not be diagnosed and treated. Electroencephalograph (EEG) is used to diagnose depression and it is more complexity to extract the features from all the multimodal channel information . In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f968a898391964acf604bada85c465e9
https://doi.org/10.1016/j.pscychresns.2022.111582
https://doi.org/10.1016/j.pscychresns.2022.111582
Publikováno v:
Journal of Physics: Conference Series. 2281:012019
In order to solve the problem of AGV fault detection system’s complexion and low accuracy, a convolutional neural network (CNN) based on the status monitoring and fault diagnosis method for automatic guided vehicle (AGV) is proposed. Firstly, the v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c178b39655fd99f8d03598d9e2fa673d
https://doi.org/10.1088/1742-6596/2281/1/012019
https://doi.org/10.1088/1742-6596/2281/1/012019