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Kenneth Lange
The current paper proposes and tests algorithms for finding the diameter of a compact convex set and the farthest point in the set to another point. For these two nonconvex problems, I construct Frank?Wolfe and projected gradient ascent algorithms. Altho...
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Wenqi Lyu, Wei Ke, Hao Sheng, Xiao Ma and Huayun Zhang
In response to the challenge of handling large-scale 3D point cloud data, downsampling is a common approach, yet it often leads to the problem of feature loss. We present a dynamic downsampling algorithm for 3D point cloud maps based on an improved voxel...
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Min Liu, Meng Xu, Liang Yuan, Shuiqin Zhang, Yanting Li and Bingqiang Zhao
Due to its broad yield-increasing effect and low cost, humic acid urea (HAU) has become one of the leading modified fertilizers worldwide. The fertisphere is the primary space where urea (U) granules participate in the soil nitrogen cycle, forming a nutr...
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Aidi Yu, Yujia Wang and Sixing Zhou
A distance-independent background light estimation method is proposed for underwater overhead images. The method addresses the challenge of the absence of the farthest point in underwater overhead images by adopting a global perspective to select the opt...
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Hyung-Ju Cho
Given a set of facilities F and a query point q, a k-farthest neighbor (kFN) query returns the k farthest facilities f1,f1,⋯,fk" role="presentation">??1,??1,?,????f1,f1,?,fk
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from q. This study considers the moving k-farthe...
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Hyung-Ju Cho
This paper considers k-farthest neighbor (kFN) join queries in spatial networks where the distance between two points is the length of the shortest path connecting them. Given a positive integer k, a set of query points Q, and a set of data points P, the...
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Cristiana Tudor and Robert Sova
The European Union (EU) has positioned itself as a frontrunner in the worldwide battle against climate change and has set increasingly ambitious pollution mitigation targets for its members. The burden is heavier for the more vulnerable economies in Cent...
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Adiel Statman, Liat Rozenberg and Dan Feldman
The k-means problem is to compute a set of k centers (points) that minimizes the sum of squared distances to a given set of n points in a metric space. Arguably, the most common algorithm to solve it is k-means++ which is easy to implement and provides a...
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