arXiv subjects

Hui Han

Publications and source records attributed to Hui Han.

24 records · Page 2Linked to original sources

arXiv2023

Robust Implementation of Foreground Extraction and Vessel Segmentation for X-ray Coronary Angiography Image Sequence

The extraction of contrast-filled vessels from X-ray coronary angiography (XCA) image sequence has important clinical significance for intuitively diagnosis and therapy. In this study, the XCA image sequence is regarded as a 3D tensor input, the vessel layer is regarded as a sparse tensor, and the background layer is regarded as a low-rank tensor. Using tensor nuclear norm (TNN) minimization, a novel method for vessel layer extraction based on tensor robust principal component analysis (TRPCA) is proposed. Furthermore, considering the irregular movement of vessels and the low-frequency dynamic disturbance of surrounding irrelevant tissues, the total variation (TV) regularized spatial-temporal constraint is introduced to smooth the foreground layer. Subsequently, for vessel layer images with uneven contrast distribution, a two-stage region growing (TSRG) method is utilized for vessel enhancement and segmentation. A global threshold method is used as the preprocessing to obtain main branches, and the Radon-Like features (RLF) filter is used to enhance and connect broken minor segments, the final binary vessel mask is constructed by combining the two intermediate results. The visibility of TV-TRPCA algorithm for foreground extraction is evaluated on clinical XCA image sequences and third-party dataset, which can effectively improve the performance of commonly used vessel segmentation algorithms. Based on TV-TRPCA, the accuracy of TSRG algorithm for vessel segmentation is further evaluated. Both qualitative and quantitative results validate the superiority of the proposed method over existing state-of-the-art approaches.

cs.CV↗

arXiv2022

Cloud Computing-based Higher Education Platforms during the COVID-19 Pandemic

Cloud computing has become the infrastructure that supports people's daily activities, business operations, and education delivery around the world. Cloud computing-based education platforms have been widely applied to assist online teaching during the COVID-19 pandemic. This paper examines the impact and importance of cloud computing in remote learning and education. This study conducted multiple-case analyses of 22 online platforms of higher education in Chinese universities during the epidemic. A comparative analysis of the 22 platforms revealed that they applied different cloud computing models and tools based on their unique requirements and needs. The study results provide strategic insights to higher education institutions regarding effective approaches to applying cloud computing-based platforms for remote education, especially during crisis situations.

cs.CY↗

arXiv2021

Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning

Heterogeneous graph neural networks (HGNNs) as an emerging technique have shown superior capacity of dealing with heterogeneous information network (HIN). However, most HGNNs follow a semi-supervised learning manner, which notably limits their wide use in reality since labels are usually scarce in real applications. Recently, contrastive learning, a self-supervised method, becomes one of the most exciting learning paradigms and shows great potential when there are no labels. In this paper, we study the problem of self-supervised HGNNs and propose a novel co-contrastive learning mechanism for HGNNs, named HeCo. Different from traditional contrastive learning which only focuses on contrasting positive and negative samples, HeCo employs cross-viewcontrastive mechanism. Specifically, two views of a HIN (network schema and meta-path views) are proposed to learn node embeddings, so as to capture both of local and high-order structures simultaneously. Then the cross-view contrastive learning, as well as a view mask mechanism, is proposed, which is able to extract the positive and negative embeddings from two views. This enables the two views to collaboratively supervise each other and finally learn high-level node embeddings. Moreover, two extensions of HeCo are designed to generate harder negative samples with high quality, which further boosts the performance of HeCo. Extensive experiments conducted on a variety of real-world networks show the superior performance of the proposed methods over the state-of-the-arts.

cs.LG↗

arXiv2018

Topological semimetal state and field-induced Fermi surface reconstruction in antiferromagnetic monopnictide NdSb

We report the experimental realization of Dirac semimetal state in NdSb, a material with antiferromagnetic ground state. The occurrence of topological semimetal state has been well supported by our band structure calculations and the experimental observation of chiral anomaly induced negative magnetoresistance. A field-induced Fermi surface reconstruction is observed, in response to the change of spin polarization. The observation of topological semimetal state in a magnetic material provides an opportunity to investigate the magneto-topological phenomena.

cond-mat.mtrl-sci↗

arXiv2017

Tricritical point and phase diagram based on critical scaling in monoaxial chiral helimagnet Cr1/3NbS2

In this work, the magnetism of the single crystal Cr$_{1/3}$NbS$_{2}$, which exhibits chiral magnetic soliton lattice (CSL) state, is investigated. The magnetization displays strong magnetic anisotropy when the field is applied perpendicularly and parallel to the $c$-axis in low field region ($H<H_{S}$, $H_{S}$ is the saturation field). The critical exponents of Cr$_{1/3}$NbS$_{2}$ are obtained as $β=$ 0.370(4), $γ=$ 1.380(2), and $δ=$ 4.853(6), which are close to the theoretical prediction of three-dimensional Heisenberg model. Based on the scaling equation and the critical exponents, the $H-T$ phase diagram in the vicinity of the phase transition is constructed, where two critical points are determined. One is a tricritical point which locates at the intersection between the CSL, forced ferromagnetic (FFM), and paramagnetic (PM) states. The other one is a critical point situated at the boundaries between CSL, helimagnetic (HM), and PM states.

cond-mat.other↗

arXiv2007

A Comparison of On-Line Computer Science Citation Databases

This paper examines the difference and similarities between the two on-line computer science citation databases DBLP and CiteSeer. The database entries in DBLP are inserted manually while the CiteSeer entries are obtained autonomously via a crawl of the Web and automatic processing of user submissions. CiteSeer's autonomous citation database can be considered a form of self-selected on-line survey. It is important to understand the limitations of such databases, particularly when citation information is used to assess the performance of authors, institutions and funding bodies. We show that the CiteSeer database contains considerably fewer single author papers. This bias can be modeled by an exponential process with intuitive explanation. The model permits us to predict that the DBLP database covers approximately 24% of the entire literature of Computer Science. CiteSeer is also biased against low-cited papers. Despite their difference, both databases exhibit similar and significantly different citation distributions compared with previous analysis of the Physics community. In both databases, we also observe that the number of authors per paper has been increasing over time.

cs.DL↗