Henk Meijer

Bio: Henk Meijer is an academic researcher from University College Roosevelt. The author has contributed to research in topics: Planar graph & Graph drawing. The author has an hindex of 27, co-authored 180 publications receiving 2361 citations. Previous affiliations of Henk Meijer include Queen's University.

Algorithms for Cluster Busting in Anchored Graph Drawing

Abstract: Given a graph G and a drawing or layout of G, it is sometimes desirable to alter or adjust the layout. The challenging aspect of designing layout adjustment algorithms is to maintain a user’s mental picture of the original layout. We present a new approach to layout adjustment called cluster busting in anchored graph drawing. We then give two algorithms as examples of this approach. The goals of cluster busting in anchored graph drawing are to more evenly distribute the nodes of the graph in a drawing window while maintaining the user’s mental picture of the original drawing. We present simple and ecient iterative heuristics to accomplish these goals. We formally dene some measures of distribution and similarity and give empirical results based on these measures to quantify our methods. The theoretical analysis of our heuristics presents a formidable challenge, thus justifying our empirical analysis.

A Visibility Representation for Graphs in Three Dimensions

Abstract: This paper proposes a 3-dimensional visibility representation of graphs G =( V;E) in which vertices are mapped to rectangles floating in R 3 parallel to the x;y-plane, with edges represented by vertical lines of sight. We apply an extension of the Erd} os-Szekeres Theorem in a geometric setting to obtain an upper bound of n = 56 for the largest representable complete graph Kn. On the other hand, we show by construction that n 22. These are the best existing bounds. We also note that planar graphs and complete bipartite graphs Km;n are representable, but that the family of representable graphs is not closed under graph minors.

Decision trees for geometric models

Abstract: A fundamental problem in model-based computer vision is that of identifying which of a given set of geometric models is present in an image. Considering a “probe” to be an oracle that tells us whether or not a model is present at a given point, we study the problem of computing efficient strategies (“decision trees”) for probing an image, with the goal to minimize the number of probes necessary (in the worst case) to determine which single model is present. We show that a ⌈lg k ⌉ height binary decision tree always exists for k polygonal models (in fixed position), provided (1) they are non-degenerate (do not share boundaries) and (2) they share a common point of intersection. Further, we give an efficient algorithm for constructing such decision trees when the models are given as a set of polygons in the plane. We show that constructing a minimum height tree is NP-complete if either of the two assumptions is omitted. We provide an efficient greedy heuristic strategy and show that, in the general case, it yields a decision tree whose height is at most ⌈lg n ⌉ times that of an optimal tree. Finally, we discuss some restricted cases whose special structure allows for improved results.

The one-round Voronoi game replayed

Abstract: We consider the one-round Voronoi game, where the first player (''White'', called ''Wilma'') places a set of n points in a rectangular area of aspect ratio @r= =3 and @r>2/n, and for n=2 and @r>3/2. Wilma wins in all remaining cases, i.e., for n>=3 and @r=<2/n, for n=2 and @r=<3/2, and for n=1. We also discuss complexity aspects of the game on more general boards, by proving that for a polygon with holes, it is NP-hard to maximize the area Barney can win against a given set of points by Wilma.

Differential Power Analysis

Abstract: Cryptosystem designers frequently assume that secrets will be manipulated in closed, reliable computing environments. Unfortunately, actual computers and microchips leak information about the operations they process. This paper examines specific methods for analyzing power consumption measurements to find secret keys from tamper resistant devices. We also discuss approaches for building cryptosystems that can operate securely in existing hardware that leaks information.

[서평]「Applied Cryptography」

Abstract: The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

The LED block cipher

Abstract: We present a new block cipher LED. While dedicated to compact hardware implementation, and offering the smallest silicon footprint among comparable block ciphers, the cipher has been designed to simultaneously tackle three additional goals. First, we explore the role of an ultra-light (in fact non-existent) key schedule. Second, we consider the resistance of ciphers, and LED in particular, to related-key attacks: we are able to derive simple yet interesting AES-like security proofs for LED regarding related- or single-key attacks. And third, while we provide a block cipher that is very compact in hardware, we aim to maintain a reasonable performance profile for software implementation.

An active testing model for tracking roads in satellite images

Abstract: We present a new approach for tracking roads from satellite images, and thereby illustrate a general computational strategy ("active testing") for tracking 1D structures and other recognition tasks in computer vision. Our approach is related to recent work in active vision on "where to look next" and motivated by the "divide-and-conquer" strategy of parlour games. We choose "tests" (matched filters for short road segments) one at a time in order to remove as much uncertainty as possible about the "true hypothesis" (road position) given the results of the previous tests. The tests are chosen online based on a statistical model for the joint distribution of tests and hypotheses. The problem of minimizing uncertainty (measured by entropy) is formulated in simple and explicit analytical terms. At each iteration new image data are examined and a new entropy minimization problem is solved (exactly), resulting in a new image location to inspect, and so forth. We report experiments using panchromatic SPOT satellite imagery with a ground resolution of ten meters.