1201471
Lossy and lossless compression for color-quantized images
An efficient compression scheme for color-quantized images based on progressive coding of color information has been developed. Rather than sorting color indexes into a linear list structure, a binary-tree structure of color indexes is proposed. With this structure the new algorithm can progressively recover an image from 2 colors up to all of the colors contained in the original image, i.e., a lossless recovery achieved. Experimental results show that it can efficiently compress images in both lossy and lossless cases. Typically for color-quantized Lena image with 256 colors, the algorithm achieved 0.5 bpp lower than state-of-the-art lossless compression methods while preserving the efficient lossy compression. Such a compression scheme is very attractive to many applications that require the ability to fast browsing or progressive transmission, and if necessary, to exactly recover the original image.
30296056
Computational inference of regulatory pathways in microbes
We present a computational protocol for inference of regulatory and signaling pathways in a microbial cell, through mining "high-throughput" biological data of various types, literature search, and computer-assisted human inference. This protocol consists of four key components: (a) construction of template pathways for microbial genomes related to the target genome, which have either been thoroughly studied or had a significant amount of relevant experimental data, (b) inference of target pathways for the target genome, by combining the template pathway models and target genome-specific information, (c) assignment of genes of the target genome to each individual functional roles in the pathway model, and (d) validation and refinement of the pathway models using pathway-specific experimental data or other information. To demonstrate the effectiveness of this procedure, we have applied this computational protocol to the construction of the phosphorus assimilation pathways in synechococcus WH8102. In this paper, we present a model of the core component of this pathway and provide our justification in support of the predicted model.
12811258
A Parsimony Approach to Genome-Wide Ortholog Assignment
The assignment of orthologous genes between a pair of genomes is a fundamental and challenging problem in comparative genomics, since many computational methods for solving various biological problems critically rely on bona fide orthologs as input. While it is usually done using sequence similarity search, we recently proposed a new combinatorial approach that combines sequence similarity and genome rearrangement. This paper continues the development of the approach and unites genome rearrangement events and (post-speciation) duplication events in a single framework under the parsimony principle. In this framework, orthologous genes are assumed to correspond to each other in the most parsimonious evolutionary scenario involving both genome rearrangement and (post-speciation) gene duplication. Besides several original algorithmic contributions, the enhanced method allows for the detection of inparalogs. Following this approach, we have implemented a high-throughput system for ortholog assignment on a genome scale, called MSOAR, and applied it to the genomes of human and mouse. As the result will show, MSOAR is able to find 99 more true orthologs than the INPARANOID program did. We have also compared MSOAR with the iterated exemplar algorithm on simulated data and found that MSOAR performed very well in terms of assignment accuracy. These test results indiate that our approach is very promising for genome-wide ortholog assignment.
12010325
An information-based sequence distance and its application to whole mitochondrial genome phylogeny
MOTIVATION
Traditional sequence distances require an alignment and therefore are not directly applicable to the problem of whole genome phylogeny where events such as rearrangements make full length alignments impossible. We present a sequence distance that works on unaligned sequences using the information theoretical concept of Kolmogorov complexity and a program to estimate this distance.


RESULTS
We establish the mathematical foundations of our distance and illustrate its use by constructing a phylogeny of the Eutherian orders using complete unaligned mitochondrial genomes. This phylogeny is consistent with the commonly accepted one for the Eutherians. A second, larger mammalian dataset is also analyzed, yielding a phylogeny generally consistent with the commonly accepted one for the mammals.


AVAILABILITY
The program to estimate our sequence distance, is available at http://www.cs.cityu.edu.hk/~cssamk/gencomp/GenCompress1.htm. The distance matrices used to generate our phylogenies are available at http://www.math.uwaterloo.ca/~mli/distance.html.
8099146
A new compression scheme for color-quantized images
An efficient compression scheme for color-quantized images based on progressive coding of color information has been developed. Instead of sorting color indexes into a linear list struc- ture, a binary-tree structure of color indexes is proposed. With this structure, the new algorithm can progressively recover an image from two colors to all of the colors contained in the original image, i.e., a lossless recovery is achieved. Experimental results showed that it can efficiently compress images in both lossy and lossless cases. Typically for color-quantized Lena image with 256 colors, the algorithm achieved 0.5 bpp below state-of-the-art lossless com- pression methods while preserving the efficient lossy compression. Such a compression scheme is very attractive to many applications that require the ability of fast browsing or progressive transmis- sion, and if necessary, to exactly recover the original image. Index Terms—Color-quantized images, data compression, index sorting, progressive refinement.
12408696
DNACompress: fast and effective DNA sequence compression
While achieving the best compression ratios for DNA sequences, our new DNACompress program significantly improves the running time of all previous DNA compression programs.
38299768
A simplified method for testing the IBM pipeline partial-scan microprocessor
This paper describes a simple test generation method for a high-performance, pipelined partial-scan microprocessor using an automatic test generation tool which was optimized for combinational logic in generating manufacturing test data. Without this method the test generation tool would have had great difficulty in generating the test data needed to achieve the required high fault coverage. User-specified clocking sequences are also allowed for design flexibility. A description of this method is provided and the experimental results are discussed.
14274462
Region-Based Image Clustering and Retrieval Using Multiple Instance Learning
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support Vector Machine (SVM) to solve MIL problem in the region-based Content Based Image Retrieval (CBIR). This is an area where a huge number of image regions are involved. For the sake of efficiency, we adopt a Genetic Algorithm based clustering method to reduce the search space. Relevance Feedback technique is incorporated to provide progressive guidance to the learning process. Performance is evaluated and the effectiveness of our retrieval algorithm is demonstrated in comparative studies.
38430290
3-NASH is PPAD-Complete
In this paper, we improve a recent result of Daskalakis, Goldberg and Papadimitriou on PPAD-completeness of 4-Nash, showing that 3-Nash is PPAD-complete.
14272026
Fully automated facial symmetry axis detection in frontal color images
We consider the problem of automatically detecting a facial symmetry axis in what we will call a standard human face image (acquired when the subject is looking directly into the camera, in front of a clean gray background under controlled illumination). Images of this kind are encountered in face recognition scenarios; this detection should facilitate more sophisticated facial image processing. The proposed method is based on GLDH (gray level difference histogram) analysis and consists of three components: (1) the face region detection stage crops an approximate face region out of the background, (2) symmetry detection discovers a vertical axis to optimally bisect the region of interest, assuming it is bilaterally symmetric, and (3) orientation adjustment aligns the angle of the symmetry axis with the orientation of the face. An implementation of the method is described, and results are presented. This detector's robust performance is evidenced by its success finding symmetry axes in more than 7,500 images collected from 600 distinct subjects. One of our method's most noteworthy contributions is that, according to our experimental results, many of the automatically detected axes are more accurate than the reference axes. Our automated detector is a powerful tool because it is not as susceptible to human error as its manual counterpart and, as the first application of its kind, it could potentially serve as a new biometric.
2587881
Isomap Based on the Image Euclidean Distance
Scientists find that the human perception is based on the similarity on the manifold of data set. Isometric feature mapping (isomap) is one of the representative techniques of manifold. It is intuitive, well understood and produces reasonable mapping results. However, if the input data for manifold learning are corrupted with noises, the isomap algorithm is topologically unstable. In this paper, we present an improved manifold learning method when the input data are images - the image Euclidean distance based isomap (imisomap), in which we use a new distance for images called image Euclidean distance (IMED). Experimental results demonstrate a consistent performance improvement of the algorithm imisomap over the traditional isomap based on Euclidean distance