@inbook{4317,
author = {Nicholas Barton},
booktitle = {Analytical biogeography},
editor = {Myers, Alan A and Giller, Paul S},
pages = {185 -- 218},
publisher = {Chapman Hall},
title = {{Speciation}},
year = {1988},
}
@misc{4318,
author = {Nicholas Barton and Jones, Steve and Mallet, James L},
booktitle = {Nature},
pages = {13 -- 14},
publisher = {Nature Publishing Group},
title = {{No barriers to speciation}},
doi = {10.1038/336013a0},
volume = {336},
year = {1988},
}
@article{3655,
author = {Dallas, John F and Nicholas Barton and Dover, Gabriel A.},
journal = {Molecular Biology and Evolution},
number = {6},
pages = {660 -- 674},
publisher = {Oxford University Press},
title = {{Interracial rDNA variation in the grasshopper Podisma pedestris}},
volume = {5},
year = {1988},
}
@article{2521,
author = {Nishimura, Masaki and Ryuichi Shigemoto and Matsubayashi, K and Mimori, Y and Kameyama, Masakuni},
journal = {Clinical Neurology},
number = {11},
pages = {1441 -- 1444},
publisher = {Societas Neurologica Japonica},
title = {{Meningoencephalitis during the pre-icteric phase of hepatitis A - a case report}},
volume = {27},
year = {1987},
}
@book{3900,
abstract = {Computational geometry as an area of research in its own right emerged in the early seventies of this century. Right from the beginning, it was obvious that strong connections of various kinds exist to questions studied in the considerably older field of combinatorial geometry. For example, the combinatorial structure of a geometric problem usually decides which algorithmic method solves the problem most efficiently. Furthermore, the analysis of an algorithm often requires a great deal of combinatorial knowledge. As it turns out, however, the connection between the two research areas commonly referred to as computa tional geometry and combinatorial geometry is not as lop-sided as it appears. Indeed, the interest in computational issues in geometry gives a new and con structive direction to the combinatorial study of geometry. It is the intention of this book to demonstrate that computational and com binatorial investigations in geometry are doomed to profit from each other. To reach this goal, I designed this book to consist of three parts, acorn binatorial part, a computational part, and one that presents applications of the results of the first two parts. The choice of the topics covered in this book was guided by my attempt to describe the most fundamental algorithms in computational geometry that have an interesting combinatorial structure. In this early stage geometric transforms played an important role as they reveal connections between seemingly unrelated problems and thus help to structure the field.},
author = {Edelsbrunner, Herbert},
isbn = {9783540137221},
publisher = {Springer},
title = {{Algorithms in Combinatorial Geometry}},
volume = {10},
year = {1987},
}
@article{4094,
abstract = {The visibility graph of a finite set of line segments in the plane connects two endpoints u and v if and only if the straight line connection between u and v does not cross any line segment of the set. This article proves that 5n - 4 is a lower bound on the number of edges in the visibility graph of n nonintersecting line segments in the plane. This bound is tight.},
author = {Herbert Edelsbrunner and Shen, Xiaojun},
journal = {Information Processing Letters},
number = {2},
pages = {61 -- 64},
publisher = {Elsevier},
title = {{A tight lower bound on the size of visibility graphs}},
doi = {10.1016/0020-0190(87)90038-X},
volume = {26},
year = {1987},
}
@article{4095,
abstract = {he kth-order Voronoi diagram of a finite set of sites in the Euclidean plane E2 subdivides E2 into maximal regions such that all points within a given region have the same k nearest sites. Two versions of an algorithm are developed for constructing the kth-order Voronoi diagram of a set of n sites in O(n2 log n + k(n - k) log2 n) time, O(k(n - k)) storage, and in O(n2 + k(n - k) log2 n) time, O(n2) storage, respectively.},
author = {Chazelle, Bernard and Herbert Edelsbrunner},
journal = {IEEE Transactions on Computers},
number = {11},
pages = {1349 -- 1354},
publisher = {IEEE},
title = {{An improved algorithm for constructing kth-order Voronoi diagrams}},
doi = {10.1109/TC.1987.5009474},
volume = {36},
year = {1987},
}
@article{4100,
abstract = {This paper investigates the existence of linear space data structures for range searching. We examine thehomothetic range search problem, where a setS ofn points in the plane is to be preprocessed so that for any triangleT with sides parallel to three fixed directions the points ofS that lie inT can be computed efficiently. We also look atdomination searching in three dimensions. In this problem,S is a set ofn points inE 3 and the question is to retrieve all points ofS that are dominated by some query point. We describe linear space data structures for both problems. The query time is optimal in the first case and nearly optimal in the second.
},
author = {Chazelle, Bernard and Herbert Edelsbrunner},
journal = {Discrete & Computational Geometry},
number = {1},
pages = {113 -- 126},
publisher = {Springer},
title = {{Linear space data structures for two types of range search}},
doi = {10.1007/BF02187875},
volume = {2},
year = {1987},
}
@article{4101,
abstract = {In a number of recent papers, techniques from computational geometry (the field of algorithm design that deals with objects in multi-dimensional space) have been applied to some problems in the area of computer graphics. In this way, efficient solutions were obtained for the windowing problem that asks for those line segments in a planar set that lie in given window (range) and the moving problem that asks for the first line segment that comes into the window when moving the window in some direction. In this paper we show that also the zooming problem, which asks for the first line segment that comes into the window when we enlarge it, can be solved efficiently. This is done by repeatedly performing range queries with ranges of varying sizes. The obtained structure is dynamic and yields a query time of O(log2n) and an insertion and deletion time of O(log2n), where n is the number of line segments in the set. The amount of storage required is O(n log n). It is also shown that the technique of repeated range search can be used to solve several other problems efficiently.
},
author = {Herbert Edelsbrunner and Overmars, Mark H},
journal = {Information Processing Letters},
number = {6},
pages = {413 -- 417},
publisher = {Elsevier},
title = {{Zooming by repeated range detection}},
doi = {10.1016/0020-0190(87)90120-7},
volume = {24},
year = {1987},
}
@article{4102,
abstract = {Determining or counting geometric objects that intersect another geometric query object is at the core of algorithmic problems in a number of applied areas of computer science. This article presents a family of space-efficient data structures that realize sublinear query time for points, line segments, lines and polygons in the plane, and points, line segments, planes, and polyhedra in three dimensions.},
author = {Dobkin, David P and Herbert Edelsbrunner},
journal = {Journal of Algorithms},
number = {3},
pages = {348 -- 361},
publisher = {Academic Press},
title = {{Space searching for intersecting objects}},
doi = {10.1016/0196-6774(87)90015-0},
volume = {8},
year = {1987},
}