20947625
Optimal interleaving schemes for correcting two-dimensional cluster errors
We present an elementary theory of optimal interleaving schemes for correcting cluster errors in two-dimensional digital data. It is assumed that each data page contains a fixed number of, say n, codewords with each codeword consisting of m code symbols and capable of correcting a single random error (or erasure). The goal is to interleave the codewords in the mxn array such that different symbols from each codeword are separated as much as possible, and consequently, an arbitrary error burst with size up to t can be corrected for the largest possible value of t. We show that, for any given m, n, the maximum possible interleaving distance, or equivalently, the largest size of correctable error bursts in an mxn array, is given by [email protected][email protected]? if n= [email protected]?m^2/[email protected]?. Furthermore, we develop a simple cyclic shifting algorithm that can provide a systematic construction of an mxn optimal interleaving array for arbitrary m and n. This extends important earlier work on the complementary problem of constructing interleaving arrays that, given the burst size t, minimize the interleaving degree, that is, the number of different codewords in a 2-D (or 3-D) array such that any error burst with given size t can be corrected. Our interleaving scheme thus provides the maximum burst error correcting power without requiring prior knowledge of the size or shape of an error burst.
14934278
Optimal 2-D interleaving with latin rectangles
One of the key problems in the study of optimal interleaving schemes for correcting two-dimensional (2-D) cluster errors is how to place, say, n distinct symbols, each appearing m times, in an m/spl times/n array such that the resulting array has the maximum possible burst error-correcting power. In a previous paper, the authors have proved that for any given m, n, the maximum possible interleaving distance, and hence, the largest possible value t such that an arbitrary error burst of size t can be corrected in an m/spl times/n interleaved array, is given by t=/spl lfloor//spl radic/2n/spl rfloor/ for n = /spl les/ /spl lceil/m/sup 2//2/spl rceil/, and t=m+/spl lfloor/(n-/spl lceil/m/sup 2//2/spl rceil/)/m/spl rfloor/ for n /spl ges/ /spl lceil/m/sup 2//2/spl rceil/. In this work, we extend these results and show that for all m, n with n /spl ges/ m, an optimal m/spl times/n interleaving array can always be obtained by a Latin rectangle in which each row and each column contains each symbol at most once. This provides additional error-correcting power to the array in that all linear error bursts occupying a whole row or column can also be corrected.
18611881
Optimal Interleaving Schemes for Two-Dimensional Arrays
Given an mtimesn array of k single random error correction (or erasure) codewords, each having length l such that mn=kl, we construct optimal interleaving schemes that provide the maximum burst error correction power such that an arbitrarily shaped error burst of size t can be corrected for the largest possible value of t. We show that for all such mtimesn arrays, the maximum possible interleaving distance, or equivalently, the largest value of t such that an arbitrary error burst of size up to t can be corrected, is bounded by lfloorradic2krfloor if kleslceil(min{m,n})2/2rceil, and by min{m,n}+lfloor(k-lceil(min{m,n})2 /2rceil)/min{m,n}rfloor if kgeslceil(min{m,n})2/2rceil. We generalize the cyclic shifting algorithm developed by the authors in a previous paper and construct, in several special cases, optimal interleaving arrays achieving these upper bounds. Additionally, for codewords of variable lengths, we solve a related array coloring problem for which the same upper bounds hold and can be achieved
32102689
On Integrating Peptide Sequence Analysis and Relational Distance-Based Indexing
Managing data with distance-based indexing methods has the potential to provide scalability and integration with relational database management systems and the SQL programming model. We previously demonstrated the advantages of such an approach for nucleotide sequences using Hamming distance (mismatch). However, the larger alphabet size of peptide sequences increases the dimensionality of the problem, making algorithmic results more challenging. The development of a metric-PAM substitution matrix enables metric-distance based indexing for peptide sequences. The performance of distance-based indexing for homologous protein retrieval entails trade-off among accuracy, scalability and computational cost. We investigate the application of the multi-vantage point (MVP) tree algorithm to index peptide k-mers based on global mPAM alignment. We show that k-mer retrieval can still maintain accuracy when k is at least as large as 6 that creates a domain of over 60 million key values and enables scalability sufficient for effective performance on large disk-resident sequence databases
19710386
Snake-Aided Automatic Organ Delineation
This paper presents a knowledge-based image segmentation tool for organ delineation in CT (Computed Tomography) images. The noise and low contrast make the detection difficult. Therefore in this method, radial search, noise reduction method and post-processing algorithm have been implemented to improve the quality of contour detection. Three edge detection algorithms have been used and after detection several optimization methods have been employed to get the accurate contour from three detected contours. Finally to achieve higher accuracy of detection, active contour model (ACM), snake, has been used after the contour detected by previous methods.
57229289
An algorithm for multiple object trajectory tracking
Most tracking algorithms are based on the maximum a posteriori (MAP) solution of a probabilistic framework called Hidden Markov Model, where the distribution of the object state at current time instance is estimated based on current and previous observations. However this approach is prone to errors caused by temporal distractions such as occlusion, background clutter and multi-object confusion. In this paper we propose a multiple object tracking algorithm that seeks the optimal state sequence which maximizes the joint state-observation probability. We name this algorithm trajectory tracking since it estimates the state sequence or "trajectory" instead of the current state. The algorithm is capable of tracking multiple objects whose number is unknown and varies during tracking. We introduce an observation model which is composed of the original image, the foreground mask given by background subtraction and the object detection map generated by an object detector The image provides the object appearance information. The foreground mask enables the likelihood computation to consider the multi-object configuration in its entirety. The detection map consists of pixel-wise object detection scores, which drives the tracking algorithm to perform joint inference on both the number of objects and their configurations efficiently.
115053
A metric model of amino acid substitution
MOTIVATION
We address the question of whether there exists an effective evolutionary model of amino-acid substitution that forms a metric-distance function. There is always a trade-off between speed and sensitivity among competing computational methods of determining sequence homology. A metric model of evolution is a prerequisite for the development of an entire class of fast sequence analysis algorithms that are both scalable, O(log n) and sensitive.


RESULTS
We have reworked the mathematics of the point accepted mutation model (PAM) by calculating the expected time between accepted mutations in lieu of calculating log-odds probabilities. The resulting substitution matrix (mPAM) forms a metric. We validate the application of the mPAM evolutionary model for sequence homology by executing sequence queries from a controlled yeast protein homology search benchmark. We compare the accuracy of the results of mPAM and PAM similarity matrices as well as three prior metric models. The experiment shows that mPAM significantly outperforms the other three metrics and sufficiently approaches the sensitivity of PAM250 to make it applicable to the management of protein sequence databases.
156293
An efficient and backwards-compatible transformation to ensure memory safety of C programs
Memory-related errors, such as buffer overflows and dangling pointers, remain one of the principal reasons for failures of C programs. As a result, a number of recent research efforts have focused on the problem of dynamic detection of memory errors in C programs. However, existing approaches suffer from one or more of the following problems: inability to detect all memory errors (e.g., Purify), requiring non-trivial modifications to existing C programs (e.g., Cyclone), changing the memory management model of C to use garbage collection (e.g., CCured), and excessive performance overheads. In this paper, we present a new approach that addresses these problems. Our approach operates via source code transformation and combines efficient data-structures with simple, localized optimizations to obtain good performance.