We analyze the correlation between different assets in the cryptocurrency market throughout
different phases, specifically bearish and bullish periods. Taking advantage of a fine-grained …

Dramatic geographic variations in healthcare expenditures were documented by developed
countries, but little is known about such variations under China's context, and what causes …

Community detection in complex networks is widely used across fields, from sociology to
biology. Despite its broad applications, there has been limited exploration of real-world …

Spatial networks are useful for modeling geographic phenomena where spatial interaction
plays an important role. To analyze the spatial networks and their internal structures, graph …

Importance There is growing interest in develo** coordinated regional systems for
nontraumatic surgical emergencies; however, our understanding of existing emergency …

Existing regionalization methods tend to be either spatial attribute-or spatial interaction-
based, while real-world tasks usually involve both considerations to satisfy multiple …

Collaborative representation (CR) models have been widely used in hyperspectral image
(HSI) classification tasks. However, most CR classification models lack stability and …

Over the past 20 years, there has been a significant increase in publication in complex
network analysis research, especially in community detection. Many methods were …

With the emergence of new forms of geospatial/urban big data and advanced spatial
analytics and machine learning methods, new patterns and phenomena can be explored …

Health care accessibility studies are well established in the US but lacking in Austria, even
though both experience high costs and have hospital care as the largest contributor to …