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The longest common subsequence (LCS) problem is a classic and well-studied problem in computer science with extensive applications in diverse areas ranging from spelling error corrections to molecular biology. This paper focuses on LCS for fixed alphabet size and fixed run-lengths (i.e., maximum number of consecutive occurrences of the same symbol). We show… (More)

- Pedro J. Tejada, Xiaojun Qi, Minghui Jiang
- CCCG
- 2009

We present a method for extracting contours from digital images using techniques from computational geometry. Our approach is different from traditional pixel-based methods in image processing. Instead of working directly with pixels, we extract a set of oriented feature points from the input digital images, then apply classical geometric techniques such as… (More)

- Minghui Jiang, Xiaojun Qi, Pedro J. Tejada
- Trans. Computational Science
- 2011

We present a simple method based on computational-geometry for extracting contours from digital images. Unlike traditional image processing methods , our proposed method first extracts a set of oriented feature points from the input images, then applies a sequence of geometric techniques, including clustering , linking, and simplification, to find contours… (More)

RNA secondary structure prediction is a fundamental problem in structural bioinformatics. The prediction problem is difficult because RNA secondary structures may contain pseudoknots formed by crossing base pairs. We introduce k-partite secondary structures as a simple classification of RNA secondary structures with pseudoknots. An RNA secondary structure… (More)

- Minghui Jiang, Vincent Pilaud, Pedro J. Tejada
- CCCG
- 2010

Given k labelings of a finite d-dimensional grid, define the combined distance between two labels to be the sum of the ℓ 1-distance between the two labels in each labeling. We present asymptotically optimal constructions of k labelings of cubical d-dimensional grids which maximize the minimum combined distance.

- Minghui Jiang, Pedro J. Tejada
- ArXiv
- 2009

Let S be a set of n 2 symbols. Let A be an n × n square grid with each cell labeled by a distinct symbol in S. Let B be another n × n square grid, also with each cell labeled by a distinct symbol in S. Then each symbol in S labels two cells, one in A and one in B. Define the combined distance between two symbols in S as the distance between the two cells in… (More)

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