Sakti Pramanik

A new version of the RDP (Ribosomal Database Project)

The Ribosomal Database Project (RDP-II), previously described by Maidak et al. [ Nucleic Acids Res. (1997), 25, 109-111], is now hosted by the Center for Microbial Ecology at Michigan State University. RDP-II is a curated database that offers ribosomal RNA (rRNA) nucleotide sequence data in aligned and unaligned forms, analysis services, and associated computer programs. During the past two years, data alignments have been updated and now include >9700 small subunit rRNA sequences. The recent development of an ObjectStore database will provide more rapid updating of data, better data accuracy and increased user access. RDP-II includes phylogenetically ordered alignments of rRNA sequences, derived phylogenetic trees, rRNA secondary structure diagrams, and various software programs for handling, analyzing and displaying alignments and trees. The data are available via anonymous ftp (ftp.cme.msu. edu) and WWW (http://www.cme.msu.edu/RDP). The WWW server provides ribosomal probe checking, approximate phylogenetic placement of user-submitted sequences, screening for possible chimeric rRNA sequences, automated alignment, and a suggested placement of an unknown sequence on an existing phylogenetic tree. Additional utilities also exist at RDP-II, including distance matrix, T-RFLP, and a Java-based viewer of the phylogenetic trees that can be used to create subtrees.

The RDP (Ribosomal Database Project) continues

The Ribosomal Database Project (RDP-II), previously described by Maidak et al., continued during the past year to add new rRNA sequences to the aligned data and to improve the analysis commands. Release 7.1 (September 17, 1999) included more than 10 700 small subunit rRNA sequences. More than 850 type strain sequences were identified and added to the prokaryotic alignment, bringing the total number of type sequences to 3324 representing 2460 different species. Availability of an RDP-II mirror site in Japan is also near completion. RDP-II provides aligned and annotated rRNA sequences, derived phylogenetic trees and taxonomic hierarchies, and analysis services through its WWW server (http://rdp.cme.msu.edu/ ). Analysis services include rRNA probe checking, approx-i-mate phylogenetic placement of user sequences, screening user sequences for possible chimeric rRNA sequences, automated alignment, production of similarity matrices and services to plan and analyze terminal restriction fragment length polymorphism (T-RFLP) experiments.

Segmentation and histogram generation using the HSV color space for image retrieval

We have analyzed the properties of the HSV (hue, saturation and value) color space with emphasis on the visual perception of the variation in hue, saturation and intensity values of an image pixel. We extract pixel features by either choosing the hue or the intensity as the dominant property based on the saturation value of a pixel. The feature extraction method has been applied for both image segmentation as well as histogram generation applications - two distinct approaches to content based image retrieval (CBIR). Segmentation using this method shows better identification of objects in an image. The histogram retains a uniform color transition that enables us to do a window-based smoothing during retrieval. The results have been compared with those generated using the RGB color space.

An efficient path computation model for hierarchically structured topographical road maps

In this paper, we have developed a HiTi (Hierarchical MulTi) graph model for structuring large topographical road maps to speed up the minimum cost route computation. The HiTi graph model provides a novel approach to abstracting and structuring a topographical road map in a hierarchical fashion. We propose a new shortest path algorithm named SPAH, which utilizes HiTi graph model of a topographical road map for its computation. We give the proof for the optimality of SPAH. Our performance analysis of SPAH on grid graphs showed that it significantly reduces the search space over existing methods. We also present an in-depth experimental analysis of HiTi graph method by comparing it with other similar works on grid graphs. Within the HiTi graph framework, we also propose a parallel shortest path algorithm named ISPAH. Experimental results show that inter query shortest path problem provides more opportunity for scalable parallelism than the intra query shortest path problem.

Similarity between Euclidean and cosine angle distance for nearest neighbor queries

Understanding the relationship among different distance measures is helpful in choosing a proper one for a particular application. In this paper, we compare two commonly used distance measures in vector models, namely, Euclidean distance (EUD) and cosine angle distance (CAD), for nearest neighbor (NN) queries in high dimensional data spaces. Using theoretical analysis and experimental results, we show that the retrieval results based on EUD are similar to those based on CAD when dimension is high. We have applied CAD for content based image retrieval (CBIR). Retrieval results show that CAD works no worse than EUD, which is a commonly used distance measure for CBIR, while providing other advantages, such as naturally normalized distance.

Optimal file distribution for partial match retrieval

In this paper we present data distribution methods for parallel processing environment. The primary objective is to process partial match retrieval type queries for parallel devices. The main contribution of this paper is the development of a new approach called FX (Fieldwise eXclusive) distribution for maximizing data access concurrency. An algebraic property of exclusive-or operation, and field transformation techniques are fundamental to this data distribution techniques. We have shown through theorems and corollaries that this FX distribution approach performs better than other methods proposed earlier. We have also shown, by computing probability of optimal distribution and query response time, that FX distribution gives better performance than others over a large class of partial match queries. This approach presents a new basis in which optimal data distribution for more general type of queries can be formulated.

Multiple sequence alignment using simulated annealing.

Multiple sequence alignment is a useful technique for studying molecular evolution and analyzing structure-sequence relationships. Dynamic programming of multiple sequence alignment has been widely used to find an optimal alignment. However, dynamic programming does not allow for certain types of gap costs, and it limits the number of sequences that can be aligned due to its high computational complexity. The focus of this paper is to use simulated annealing as the basis for developing an efficient multiple sequence alignment algorithm. An algorithm called Multiple Sequence Alignment using Simulated Annealing (MSASA) has been developed. The computational complexity of MSASA is significantly reduced by replacing the high-temperature phase of the annealing process by a fast heuristic algorithm. This heuristic algorithm facilitates in minimizing the solution set of the low-temperature phase of the annealing process. Compared to the dynamic programming approach, MSASA can (i) use natural gap costs which can generate better solution, (ii) align more sequences and (iii) take less computation time.

Optimizing join queries in distributed databases

A reduced cover set of the set of full reducer semijoin programs for an acyclic query graph for a distributed database system is given. An algorithm is presented that determines the minimum cost full reducer program. The computational complexity of finding the optimal full reducer for a single relation is of the same order as that of finding the optimal full reducer for all relations. The optimization algorithm is able to handle query graphs where more than one attribute is common between the relations. A method for determining the optimum profitable semijoin program is presented. A low-cost algorithm which determines a near-optimal profitable semijoin program is outlined. This is done by converting a semijoin program into a partial order graph. This graph also allows one to maximize the concurrent processing of the semijoins. It is shown that the minimum response time is given by the largest cost path of the partial order graph. This reducibility is used as a post optimizer for the SSD-1 query optimization algorithm. It is shown that the least upper bound on the length of any profitable semijoin program is N(N-1) for a query graph of N nodes. >

HiTi graph model of topographical road maps in navigation systems

In navigation systems, a primary task is to compute the minimum cost route from the current location to the destination. One of the major problems for navigation systems is that a significant amount of computation time is required to find a minimum cost path when the topographical road map is large. Since navigation systems are real time systems, it is critical that the path be computed while satisfying a time constraint. We propose a new graph model named HiTi (hierarchical multi graph model), for efficiently computing an optimal minimum cost path. Based on HiTi graph model, we propose a new single pair minimum cost path algorithm. We empirically show that our proposed algorithm performs far better than the traditional A* algorithm. Further, we empirically analyze our algorithm by varying both edge cost distribution and hierarchical level number of HiTi graphs.

A tree-structured index allocation method with replication over multiple broadcast channels in wireless environments

Broadcast has often been used to disseminate frequently requested data efficiently to a large volume of mobile units over single or multiple channels. Since mobile units have limited battery power, the minimization of the access and tuning times for the broadcast data is an important problem. There have been many research efforts that focus on minimizing access and tuning times by providing indexes on the broadcast data. We have studied an efficient index allocation method for broadcast data with skewed access frequencies over multiple physical channels which cannot be coalesced into a single high bandwidth channel. Previously proposed index allocation techniques have one of two problems. The first problem is that they require equal size for both index and data. The second problem is that their performance degrades when the number of given physical channels is not enough. These two problems result in an increased average access time for the broadcast data. To cope with these problems, we propose a tree-structured index allocation method. Our method minimizes the average access time by broadcasting the hot data and their indices more frequently than the less hot data and their indexes over the dedicated index and data channels. We present an in-depth experimental and theoretical analysis of our method by comparing it with other similar techniques. Our performance analysis shows that it significantly decreases the average access and tuning times for the broadcast data over existing methods.