Skip To Main Content
Qin Yin on Muck Rack

Qin Yin

As seen in: Color Research & Application, Wiley Online Library, PLOS Biology, Frontiers, MDPI, Taylor & Francis Online, Science Magazine, Royal Society of Chemistry, Cell Press, Canadian Journal of Infectious Diseases & Medical Microbiology and
Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work. Claim your profile

Get in touch with Qin

Contact Qin, search articles and posts on X, monitor coverage, and track replies from one place.

Learn more about Muck Rack

Actions

Share this page

Is this you?

As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile

Articles

Rhodium-Catalyzed Synthesis of Enantioenriched α-Substituted Primary Amines Through Asymmetric Transfer Hydrogenation

|
By Guillaume Lefevre, Qin Yin, Chonghuo Liu
| Wiley Online Library Verified
Filename Description chem71466-sup-0001-SuppMat.pdf10.7 MB The authors have cited additional references within the [39-49]. Supporting File 1: chem71466-sup-0001-SuppMat.pdf
Open in Who Shared Issue with article?

An atrous spatial pyramid pooling–fully connected network-based machining time prediction method for intelligent manufacturing

|
By Qin Yin, Wenjie Fu, Yuanyuan Song
| Taylor & Francis Online
ABSTRACT Accurate machining time prediction is essential for production planning, cost control and quotation in the small-batch manufacture of custom-made parts for special vehicles. However, traditional approaches based on empirical formulas or tabulated standards often suffer from low efficiency, large prediction errors and limited generalization capability.
Open in Who Shared Issue with article?

A graph attention network for rotating machinery fault diagnosis driven by multi-channel vibration signal

|
By Jian Tang, Qin Yin, Yinchuan Hou
| Taylor & Francis Online
To address the issue of missing feature associations in traditional single-channel analysis methods under multi-sensor monitoring systems, this paper proposes a graph attention network fault diagnosis model based on meta-path guided graph topology construction and hierarchical attention mechanism.
Open in Who Shared Issue with article?
See all 29 licensed articles (31 Total)