MSTRIQ: No Reference Image Quality Assessment Based on Swin Transformer with Multi-Stage Fusion

Kavli Affiliate: Jing Wang | First 5 Authors: Jing Wang, Haotian Fan, Xiaoxia Hou, Yitian Xu, Tao Li | Summary: Measuring the perceptual quality of images automatically is an essential task in the area of computer vision, as degradations on image quality can exist in many processes from image acquisition, transmission to enhancing. Many Image […]


Continue.. MSTRIQ: No Reference Image Quality Assessment Based on Swin Transformer with Multi-Stage Fusion

Revisit the rate of tidal disruption events: the role of the partial tidal disruption event

Kavli Affiliate: Rainer Spurzem | First 5 Authors: Shiyan Zhong, Shuo Li, Peter Berczik, Rainer Spurzem, | Summary: Tidal disruption of stars in dense nuclear star clusters containing supermassive central black holes (SMBH) is modeled by high-accuracy direct N-body simulation. Stars getting too close to the SMBH are tidally disrupted and a tidal disruption event […]


Continue.. Revisit the rate of tidal disruption events: the role of the partial tidal disruption event

An Efficient Piggybacking Design Framework with Sub-packetization $lle r$ for All-Node Repair

Kavli Affiliate: Ke Wang | First 5 Authors: Ke Wang, Zhifang Zhang, , , | Summary: Piggybacking design has been widely applied in distributed storage systems since it can greatly reduce the repair bandwidth with small sub-packetization. Compared with other existing erasure codes, piggybacking is more convenient to operate and the I/O cost is lower. […]


Continue.. An Efficient Piggybacking Design Framework with Sub-packetization $lle r$ for All-Node Repair

Geometry-Based Stochastic Probability Models for the LoS and NLoS Paths of A2G Channels under Urban Scenario

Kavli Affiliate: Zhuo Li | First 5 Authors: Minghui Pang, Qiuming Zhu, Cheng-Xiang Wang, Zhipeng Lin, Junyu Liu | Summary: Path probability prediction is essential to describe the dynamic birth and death of propagation paths, and build the accurate channel model for air-to-ground (A2G) communications. The occurrence probability of each path is complex and time-variant […]


Continue.. Geometry-Based Stochastic Probability Models for the LoS and NLoS Paths of A2G Channels under Urban Scenario

Sampling with replacement vs Poisson sampling: a comparative study in optimal subsampling

Kavli Affiliate: Jing Wang | First 5 Authors: Jing Wang, Jiahui Zou, HaiYing Wang, , | Summary: Faced with massive data, subsampling is a commonly used technique to improve computational efficiency, and using nonuniform subsampling probabilities is an effective approach to improve estimation efficiency. For computational efficiency, subsampling is often implemented with replacement or through […]


Continue.. Sampling with replacement vs Poisson sampling: a comparative study in optimal subsampling

Semi-inclusive Diffractive Deep Inelastic Scattering at Small-$x$

Kavli Affiliate: Feng Yuan | First 5 Authors: Yoshitaka Hatta, Bo-Wen Xiao, Feng Yuan, , | Summary: Inspired by a recent study of Iancu, Mueller and Triantafyllopoulos [1] and earlier papers by Golec-Biernat and Wusthoff [2,3], we propose semi-inclusive diffractive deep inelastic scattering (SIDDIS) to investigate the gluon tomography in the nucleon and nuclei at […]


Continue.. Semi-inclusive Diffractive Deep Inelastic Scattering at Small-$x$

The initial conditions for young massive cluster formation in the Galactic Centre: convergence of large-scale gas flows

Kavli Affiliate: Luis C. Ho | First 5 Authors: Bethan A. Williams, Daniel L. Walker, Steven N. Longmore, A. T. Barnes, Cara Battersby | Summary: Young massive clusters (YMCs) are compact ($lesssim$1 pc), high-mass (>10${}^4$ M${}_{odot}$) stellar systems of significant scientific interest. Due to their rarity and rapid formation, we have very few examples of […]


Continue.. The initial conditions for young massive cluster formation in the Galactic Centre: convergence of large-scale gas flows

Ensemble Clustering via Co-association Matrix Self-enhancement

Kavli Affiliate: Ran Wang | First 5 Authors: Yuheng Jia, Sirui Tao, Ran Wang, Yongheng Wang, | Summary: Ensemble clustering integrates a set of base clustering results to generate a stronger one. Existing methods usually rely on a co-association (CA) matrix that measures how many times two samples are grouped into the same cluster according […]


Continue.. Ensemble Clustering via Co-association Matrix Self-enhancement