Qilin Wang

Cross-sectional study of anxiety–cognition network patterns in rehabilitation patients using network analysis

Qilin Wang, Jia-Ju Ren, Jin Zhao

This study aimed to explore the network relationship between anxiety and cognition and its mechanism, providing a theoretical basis for formulating anxiety-related intervention strategies. Data were collected from 146 patients in the Rehabilitation Department of Dongfang Hospital, Beijing University of Chinese Medicine. …

cn (code pays fourni par la source)

Improved Harris Hawk optimization for multilevel thresholding image segmentation

Xinli Du, Peng Yao, Qilin Wang, Xiang Liu et autres

cn (code pays fourni par la source)

A Comparative Study of Augmented Reality-Assisted Orthopedic Surgical Navigation Systems

Shixing Ma, Qilin Wang, Xinzhe Du, Ang Zhang et autres

This study conducts a comparative analysis of two types of augmented reality-assisted surgical navigation systems designed for orthopedic procedures. The first system is the Visual Tag-based navigation System (VTS), and the second is the External Optical tracker-based navigation System (EOS). This study …

cn (code pays fourni par la source)

Simulation of High Density Crowds Based on Improved Social Force Modeling

Zhenguo Wang, Nan Xiang, Bingdi Tian, Qilin Wang

Crowd simulation algorithms based on the social force model are widely used to simulate the movement behavior of real crowds due to their realism and flexibility. However, when modeling the behavior of high-density crowds, the interacting forces between individuals become extraordinarily complex, …

cn (code pays fourni par la source)

Hypergraph network embedding for community detection

Nan Xiang, Mingwei You, Qilin Wang, Bingdi Tian

cn (code pays fourni par la source)

Beyond Emissions: Unveiling the Debt Financing Implications of China's Carbon Emissions Trading Pilot

Xiaoliang Zhang, Jialei Ma, Xinyuan Xu, Qilin Wang

cn (code pays fourni par la source)

Unsupervised hypergraph convolutional clustering networks

Mingwei You, Nan Xiang, Qilin Wang, Zhenguo Wang

Deep clustering algorithms based on graph convolutional networks are widely used due to their strong ability to mine network structure. However, the construction of neighborhood graphs may introduce noise and affect the clustering results. Meanwhile, focusing on ordinary topology alone ignores the …

cn (code pays fourni par la source)

Betweenness centrality approximation in large networks using shortest paths approximation and adaptive sampling

Qilin Wang, Nan Xiang, Mingwei You, Xindi Rao

Betweenness centrality is a measure of node importance in networks, but conventional exact algorithms require a lot of time as the network size grows dramatically. This paper aims to enhance the efficiency and accuracy of betweenness centrality computation for network nodes. We …

cn (code pays fourni par la source)

Estimation and update of betweenness centrality with progressive algorithm and shortest paths approximation

Nan Xiang, Qilin Wang, Mingwei You

Betweenness centrality is one of the key measures of the node importance in a network. However, it is computationally intractable to calculate the exact betweenness centrality of nodes in large-scale networks. To solve this problem, we present an efficient CBCA (Centroids based …

cn (code pays fourni par la source)

Hypergraph network embedding for community detection

Nan Xiang, Mingwei You, Qilin Wang, Bingdi Tian

Abstract Using attribute graphs for node embedding to detect community structure has become a popular research topic. However, most of the existing algorithms mainly focus on the network structure and node features, which ignore the higher-order relationships between nodes. In addition, only …

cn (code pays fourni par la source)

Federated Representation Learning With Data Heterogeneity for Human Mobility Prediction

Xiao Zhang, Qilin Wang, Ziming Ye, Haochao Ying et autres

The advancement of smart wearable devices and location-based smart services has enabled a new paradigm for smart human mobility prediction (HMP), which has a broad range of applications in smart healthcare and smart cities. Due to the privacy concerns and rigorous data …

cn (code pays fourni par la source)