571 research outputs found
Optimal Deployments of UAVs With Directional Antennas for a Power-Efficient Coverage
To provide a reliable wireless uplink for users in a given ground area, one
can deploy Unmanned Aerial Vehicles (UAVs) as base stations (BSs). In another
application, one can use UAVs to collect data from sensors on the ground. For a
power-efficient and scalable deployment of such flying BSs, directional
antennas can be utilized to efficiently cover arbitrary 2-D ground areas. We
consider a large-scale wireless path-loss model with a realistic
angle-dependent radiation pattern for the directional antennas. Based on such a
model, we determine the optimal 3-D deployment of N UAVs to minimize the
average transmit-power consumption of the users in a given target area. The
users are assumed to have identical transmitters with ideal omnidirectional
antennas and the UAVs have identical directional antennas with given half-power
beamwidth (HPBW) and symmetric radiation pattern along the vertical axis. For
uniformly distributed ground users, we show that the UAVs have to share a
common flight height in an optimal power-efficient deployment. We also derive
in closed-form the asymptotic optimal common flight height of UAVs in terms
of the area size, data-rate, bandwidth, HPBW, and path-loss exponent
DETERMINATION OF EUCLIDEAN DISTANCES FOR SYMMETRY MOLECULES
Abstract This paper represents the geometric analysis of molecular surfaces of the molecules, indicates the blending operation of an atoms constitute to the small molecules. The decision which indicates advantages of Euclidean Voronoi diagram of an atom includes the blending surface among the atoms to make a fundamental study of docking, interactions with macromolecules. The algorithm which proposes the topological part of surfaces discussed through the Euclidean Voronoi Diagram of various accessibility procedures
Two triangulations methods based on edge refinement
In this paper two curvature adaptive methods of surface triangulation
are presented. Both methods are based on edge refinement to obtain a
triangulation compatible with the curvature requirements. The first
method applies an incremental and constrained Delaunay triangulation
and uses curvature bounds to determine if an edge of the triangulation
is admissible. The second method uses this function also in the edge
refinement process, i.e. in the computation of the location of a
refining point, and in the re-triangulation needed after the insertion
of this refining point. Results are presented, comparing both
approachesPostprint (published version
Efficient computation of discrete Voronoi diagram and homotopy-preserving simplified medial axis of a 3d polyhedron
The Voronoi diagram is a fundamental geometric data structure and has been well studied in computational geometry and related areas. A Voronoi diagram defined using the Euclidean distance metric is also closely related to the Blum medial axis, a well known skeletal representation. Voronoi diagrams and medial axes have been shown useful for many 3D computations and operations, including proximity queries, motion planning, mesh generation, finite element analysis, and shape analysis. However, their application to complex 3D polyhedral and deformable models has been limited. This is due to the difficulty of computing exact Voronoi diagrams in an efficient and reliable manner. In this dissertation, we bridge this gap by presenting efficient algorithms to compute discrete Voronoi diagrams and simplified medial axes of 3D polyhedral models with geometric and topological guarantees. We apply these algorithms to complex 3D models and use them to perform interactive proximity queries, motion planning and skeletal computations. We present three new results. First, we describe an algorithm to compute 3D distance fields of geometric models by using a linear factorization of Euclidean distance vectors. This formulation maps directly to the linearly interpolating graphics rasterization hardware and enables us to compute distance fields of complex 3D models at interactive rates. We also use clamping and culling algorithms based on properties of Voronoi diagrams to accelerate this computation. We introduce surface distance maps, which are a compact distance vector field representation based on a mesh parameterization of triangulated two-manifolds, and use them to perform proximity computations. Our second main result is an adaptive sampling algorithm to compute an approximate Voronoi diagram that is homotopy equivalent to the exact Voronoi diagram and preserves topological features. We use this algorithm to compute a homotopy-preserving simplified medial axis of complex 3D models. Our third result is a unified approach to perform different proximity queries among multiple deformable models using second order discrete Voronoi diagrams. We introduce a new query called N-body distance query and show that different proximity queries, including collision detection, separation distance and penetration depth can be performed based on Nbody distance query. We compute the second order discrete Voronoi diagram using graphics hardware and use distance bounds to overcome the sampling errors and perform conservative computations. We have applied these queries to various deformable simulations and observed up to an order of magnitude improvement over prior algorithms
A Systematic Review of Algorithms with Linear-time Behaviour to Generate Delaunay and Voronoi Tessellations
Triangulations and tetrahedrizations are important geometrical discretization procedures applied to several areas, such as the reconstruction of surfaces and data visualization. Delaunay and Voronoi tessellations are discretization structures of domains with desirable geometrical properties. In this work, a systematic review of algorithms with linear-time behaviour to generate 2D/3D Delaunay and/or Voronoi tessellations is presented
Segmentation of 3D pore space from CT images using curvilinear skeleton: application to numerical simulation of microbial decomposition
Recent advances in 3D X-ray Computed Tomographic (CT) sensors have stimulated
research efforts to unveil the extremely complex micro-scale processes that
control the activity of soil microorganisms. Voxel-based description (up to
hundreds millions voxels) of the pore space can be extracted, from grey level
3D CT scanner images, by means of simple image processing tools. Classical
methods for numerical simulation of biological dynamics using mesh of voxels,
such as Lattice Boltzmann Model (LBM), are too much time consuming. Thus, the
use of more compact and reliable geometrical representations of pore space can
drastically decrease the computational cost of the simulations. Several recent
works propose basic analytic volume primitives (e.g. spheres, generalized
cylinders, ellipsoids) to define a piece-wise approximation of pore space for
numerical simulation of draining, diffusion and microbial decomposition. Such
approaches work well but the drawback is that it generates approximation
errors. In the present work, we study another alternative where pore space is
described by means of geometrically relevant connected subsets of voxels
(regions) computed from the curvilinear skeleton. Indeed, many works use the
curvilinear skeleton (3D medial axis) for analyzing and partitioning 3D shapes
within various domains (medicine, material sciences, petroleum engineering,
etc.) but only a few ones in soil sciences. Within the context of soil
sciences, most studies dealing with 3D medial axis focus on the determination
of pore throats. Here, we segment pore space using curvilinear skeleton in
order to achieve numerical simulation of microbial decomposition (including
diffusion processes). We validate simulation outputs by comparison with other
methods using different pore space geometrical representations (balls, voxels).Comment: preprint, submitted to Computers & Geosciences 202
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