Xuefeng Guan

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We report on the fabrication of Cu2+-sensing thermoresponsive poly(N-isopropylacrylamide) (PNIPAM) microgels labeled with metal-chelating acceptor and fluorescent reporter moieties. Cu2+ detection sensitivity can be considerably enhanced via thermo-induced collapse of the sensing matrix, which can easily optimize the relative spatial distribution of(More)
Significant computation challenges are emerging as agent-based modeling becomes more complicated and dynamically data-driven. In this context, parallel simulation is an attractive solution when dealing with massive data and computation requirements. Nearly all the available distributed simulation systems, however, do not support geospatial phenomena(More)
It’s critical to predict the propagation of forest fire to make better decisions in firefighting. CA(cellar automata) model has proved to be a rational approach to simulate the propagation of forest fire in many literatures mainly considering meteorological factors, land cover and geographical factors. However, the computational complexity and memory(More)
Massive spatial data requires considerable computing power for real-time processing. With the help of the development of multicore technology and computer component cost reduction in recent years, high performance clusters become the only economically viable solution for this requirement. Massive spatial data processing demands heavy I/O operations however,(More)
More and more vector-based cellular automata (VCA) models have been built to leverage parallel computing to model rapidly changing cities and urban regions. During parallel simulation, common task decomposition methods based on space partitioning, e.g., grid partitioning (GRID) and recursive binary space partitioning (BSP), do not work well given the(More)
Bo Cheng 1,2, Xuefeng Guan 1,2,*, Huayi Wu 1,2 and Rui Li 1,2 1 State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, China; chengbo@whu.edu.cn (B.C.); wuhuayi@whu.edu.cn (H.W.); ruili@whu.edu.cn (R.L.) 2 Collaborative Innovation Center of Geospatial Technology, 129 Luoyu(More)
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