1709003
On optimal permutation codes
Permutation codes are vector quantizers whose codewords are related by permutations and, in one variant, sign changes. Asymptotically, as the vector dimension grows, optimal Variant I permutation code design is identical to optimal entropy-constrained scalar quantizer (ECSQ) design. However, contradicting intuition and previously published assertions, there are finite block length permutation codes that perform better than the best ones with asymptotically large length; thus, there are Variant I permutation codes whose performances cannot be matched by any ECSQ. Along similar lines, a new asymptotic relation between Variant I and Variant II permutation codes is established but again demonstrated to not necessarily predict the performances of short codes. Simple expressions for permutation code performance are found for memoryless uniform and Laplacian sources. The uniform source yields the aforementioned counterexamples.
33099797
Compression of cDNA and inkjet microarray images
Microarray image technology is a powerful tool for monitoring the expression of thousands of genes simultaneously. Each microarray experiment produces immense amounts of image data, and efficient storage and transmission requires compression that utilizes the microarray image's structure and unique analysis goals. We have developed a progressive compression scheme for microarray images which can be either lossy or lossless. Our scheme has a coded data structure that allows fast decoding and reprocessing of image subsets, and includes summary statistics and image segmentation information. Since visual fidelity is not the end goal for microarray images, we introduce a new measure of distortion for lossy compression: the sensitivity of microarray information extraction to compression loss. We find that a lossy compression ratio of 8:1 for cDNA microarrays minimally affects downstream processing. The average lossless compression ratio is 1.83:1 for cDNA images and 2.43:1 for inkjet images, comparable to state-of-the-art lossless schemas, yet with added flexibility and information.
42728551
Random distributed multiresolution representations with significance querying
2396831
Mining coherent patterns from heterogeneous microarray data
Microarray technology is a powerful tool for geneticists to monitor interactions among tens of thousands of genes simultaneously. There has been extensive research on coherent subspace clustering of gene expressions measured under consistent experimental settings. However, these methods assume that all experiments are run using the same batch of microarray chips with similar characteristics of noise. Algorithms developed under this assumption may not be applicable for analyzing data collected from heterogeneous settings, where the set of genes being monitored may be different and expression levels may be not directly comparable even for the same gene. In this paper, we propose a model, F-cluster, for mining subspace coherent patterns from heterogeneous gene expression data. We compare our model with previously proposed models. We analyze the search space of the problem and give a naïve solution for it.
9409183
A Novel Hybrid Approach to the Permutation Problem of Frequency Domain Blind Source Separation
We explore the permutation problem of frequency domain blind source separation (BSS). Based on performance analysis of three approaches: exploiting spectral continuity, exploiting time envelope structure and beamforming alignment; we present a new hybrid method which incorporates a psychoacoustic filtering process for the misaligned permutations unable to be delt with by these approaches. We use a sub- space based method (MUSIC) rather than conventional beamforming for the accurate estimation of the direction of arrivals (DOAs) of the source components, and a frequency dependent distance for the correla- tion of time envelopes. The proposed methods are compared with other approaches by signal to interference ratio (SIR) evaluation, and the new hybrid approach is shown to have the best performance.
6564567
Stabbing the sky: efficient skyline computation over sliding windows
We consider the problem of efficiently computing the skyline against the most recent N elements in a data stream seen so far. Specifically, we study the n-of-N skyline queries; that is, computing the skyline for the most recent n (/spl forall/n/spl les/N) elements. Firstly, we developed an effective pruning technique to minimize the number of elements to be kept. It can be shown that on average storing only O(log/sup d/ N) elements from the most recent N elements is sufficient to support the precise computation of all n-of-N skyline queries in a d-dimension space if the data distribution on each dimension is independent. Then, a novel encoding scheme is proposed, together with efficient update techniques, for the stored elements, so that computing an n-of-N skyline query in a d-dimension space takes O(log N+s) time that is reduced to O(d log log N+s) if the data distribution is independent, where s is the number of skyline points. Thirdly, a novel trigger based technique is provided to process continuous n-of-N skyline queries with O(/spl delta/) time to update the current result per new data element and O(log s) time to update the trigger list per result change, where /spl delta/ is the number of element changes from the current result to the new result. Finally, we extend our techniques to computing the skyline against an arbitrary window in the most recent N element. Besides theoretical performance guarantees, our extensive experiments demonstrated that the new techniques can support on-line skyline query computation over very rapid data streams.
181647
Geometric modeling with conical meshes and developable surfaces
In architectural freeform design, the relation between shape and fabrication poses new challenges and requires more sophistication from the underlying geometry. The new concept of conical meshes satisfies central requirements for this application: They are quadrilateral meshes with planar faces, and therefore particularly suitable for the design of freeform glass structures. Moreover, they possess a natural offsetting operation and provide a support structure orthogonal to the mesh. Being a discrete analogue of the network of principal curvature lines, they represent fundamental shape characteristics. We show how to optimize a quad mesh such that its faces become planar, or the mesh becomes even conical. Combining this perturbation with subdivision yields a powerful new modeling tool for all types of quad meshes with planar faces, making subdivision attractive for architecture design and providing an elegant way of modeling developable surfaces.
3845821
Performance Analysis of Three Text-Join Algorithms
When a multidatabase system contains textual database systems (i.e., information retrieval systems), queries against the global schema of the multidatabase system may contain a new type of joins-joins between attributes of textual type. Three algorithms for processing such a type of joins are presented and their I/O costs are analyzed in this paper. Since such a type of joins often involves document collections of very large size, it is very important to find efficient algorithms to process them. The three algorithms differ on whether the documents themselves or the inverted files on the documents are used to process the join. Our analysis and the simulation results indicate that the relative performance of these algorithms depends on the input document collections, system characteristics, and the input query. For each algorithm, the type of input document collections with which the algorithm is likely to perform well is identified. An integrated algorithm that automatically selects the best algorithm to use is also proposed.