Covering Points by Disjoint Boxes with Outliers

For a set of n points in the plane, we consider the axis--aligned (p,k)-Box Covering problem: Find p axis-aligned, pairwise-disjoint boxes that together contain n-k points. In this paper, we consider the boxes to be either squares or rectangles, and we want to minimize the area of the largest box. For general p we show that the problem is NP-hard for both squares and rectangles. For a small, fixed number p, we give algorithms that find the solution in the following running times: For squares we have O(n+k log k) time for p=1, and O(n log n+k^p log^p k time for p = 2,3. For rectangles we get O(n + k^3) for p = 1 and O(n log n+k^{2+p} log^{p-1} k) time for p = 2,3. In all cases, our algorithms use O(n) space.Comment: updated version: - changed problem from 'cover exactly n-k points' to 'cover at least n-k points' to avoid having non-feasible solutions. Results are unchanged. - added Proof to Lemma 11, clarified some sections - corrected typos and small errors - updated affiliations of two author

The scheduling of sparse matrix-vector multiplication on a massively parallel dap computer

An efficient data structure is presented which supports general unstructured sparse matrix-vector multiplications on a Distributed Array of Processors (DAP). This approach seeks to reduce the inter-processor data movements and organises the operations in batches of massively parallel steps by a heuristic scheduling procedure performed on the host computer. The resulting data structure is of particular relevance to iterative schemes for solving linear systems. Performance results for matrices taken from well known Linear Programming (LP) test problems are presented and analysed

Multiple rooks of chess - a generic integral field unit deployment technique

A new field re-configuration technique, Multiple Rooks of Chess (MRC), for multiple deployable Integral Field Spectrographs has been developed. The method involves mechanical geometry as well as an optimized deployment algorithm. The geometry is found to be simple for mechanical implementation. The algorithm initially assigns the IFUs to the target objects and then devises the movement sequence based on the current and the desired IFU positions. The reconfiguration time using the suitable actuators which runs at 20 cm/s is found to be a maximum of 25 seconds for the circular DOTIFS focal plane (180 mm diameter). The Geometry Algorithm Combination (GAC) has been tested on several million mock target configurations with object-to-IFU ({\tau} ) ratio varying from 0.25 to 16. The MRC method is found to-be efficient in target acquisition in terms of field revisit and deployment time without any collision or entanglement of the fiber bundles. The efficiency of the technique does not get affected by the increase in number density of target objects. The technique is compared with other available methods based on sky coverage, flexibility and overhead time. The proposed geometry and algorithm combination is found to have an advantage in all of the aspects.Comment: 18 Pages, 13 Figures, 1 Tabl

Partial-Matching and Hausdorff RMS Distance Under Translation: Combinatorics and Algorithms

We consider the RMS distance (sum of squared distances between pairs of points) under translation between two point sets in the plane, in two different setups. In the partial-matching setup, each point in the smaller set is matched to a distinct point in the bigger set. Although the problem is not known to be polynomial, we establish several structural properties of the underlying subdivision of the plane and derive improved bounds on its complexity. These results lead to the best known algorithm for finding a translation for which the partial-matching RMS distance between the point sets is minimized. In addition, we show how to compute a local minimum of the partial-matching RMS distance under translation, in polynomial time. In the Hausdorff setup, each point is paired to its nearest neighbor in the other set. We develop algorithms for finding a local minimum of the Hausdorff RMS distance in nearly linear time on the line, and in nearly quadratic time in the plane. These improve substantially the worst-case behavior of the popular ICP heuristics for solving this problem.Comment: 31 pages, 6 figure

Exact and fixed-parameter algorithms for metro-line crossing minimization problems

A metro-line crossing minimization problem is to draw multiple lines on an underlying graph that models stations and rail tracks so that the number of crossings of lines becomes minimum. It has several variations by adding restrictions on how lines are drawn. Among those, there is one with a restriction that line terminals have to be drawn at a verge of a station, and it is known to be NP-hard even when underlying graphs are paths. This paper studies the problem in this setting, and propose new exact algorithms. We first show that a problem to decide if lines can be drawn without crossings is solved in polynomial time, and propose a fast exponential algorithm to solve a crossing minimization problem. We then propose a fixed-parameter algorithm with respect to the multiplicity of lines, which implies that the problem is FPT.Comment: 19 pages, 15 figure