Window Queries Research Articles

Space-filling approach for fast window query on compressed images

Based on the space-filling approach, this paper presents a fast algorithm for window query on compressed images. Given a query window of size n1xn2, the proposed algorithm takes O(n1logT+P) time to perform the window query, where n1=max(n1, n2) and TxT is the image size; P is the number of outputted codes. The proposed algorithm improves the naive algorithm, which needs O(n1n2logT+P) time, significantly. Some experimentations are carried out to demonstrate the computational advantage of the proposed algorithm. From the experimental results, it is observed that the proposed algorithm has about 72-98% time improvement when compared to the naive algorithm.

Efficient window query processing method usingarea-maximising points

The use of area-maximising points (AMPs) is proposed as a method for improving the performance of window query processing. The AMP method is a progressive approximation method and is used to identify hits from the candidates. It involves the use of four sampled points of an object and shows a higher filter ratio and shorter processing time when compared with established approximation methods.

Efficient Join Processing Using Partial Precomputation

In this paper, we generalize conventional join indexes to a cluster-based join index, in which objects are grouped into clusters based on proximity. Each record of our join index represents a pair of clusters in which the join condition is satisfied by some members of the cluster. This strategy is especially useful for spatial and high-dimensional databases because of their typically large data volume and complex operations. Our approach leverages on the structure of R-trees by exploiting the internal nodes of an R-tree in effectively determining the precomputed clusters which can be used in our join index. By varying the size of the cluster, we are able to fine-tune the join index to achieve a balance between update cost and retrieval cost to suit individual applications. Different implementations of the join index are examined to determine how the join index can be efficiently maintained. To this end, we also conduct a number of experiments on intersection join and window queries, and the results confirm that semi-precomputation of join results is a robust and cost effective approach to join processing.

Data structures for fast searching of SEG-Y seismic data

An index structure for seismic data was designed using a modified PR quadtree data structure and implemented in the C++ computer language. To test the software and to evaluate the implementation of the structures, experiments were carried out with data from a marine seismic survey in the Mid-Pacific Ocean. The section of the survey used spanned 6 days, consisted of ten seismic lines (total of 1904 line kilometres) with a total of 39,720 traces. The seismic data (in SEG-Y format) required 335.8 Mbyte storage on disk. Experimental results of range searching (in two dimensions) with varying query window sizes shows that less than 0.1 s is required to determine which seismic lines intersect the query window. The index structure occupies 9.19 Mbyte (about 2.74% of the original data size) and requires 34.5 s to build using a UNIX® workstation. The modified PR quadtree index structure was compared to a standard PR quadtree index structure, and found to require less time (by up to 67%) to perform a 2D range search.

RHScoresFormat: a tool for formatting radiation hybrid data

Genome maps are important tools in genetic research. They also provide frameworks for large-scale sequencing. A variety of methods have been developed to generate maps from experimental data (Refs [1xCox, D.R. et al. Science. 1990; 250: 245–250Crossref | PubMedSee all References, 2xBoehnke, M., Lange, K., and Cox, D.R. Am. J. Hum. Genet. 1991; 49: 1174–1188PubMedSee all References]). A database for collecting and distributing radiation hybrid raw data (the `scores' representing the retention patterns of a given STS assayed on a specific panel) has been maintained at the European Bioinformatics Institute (EMBL Outstation, Hinxton) since 1995 (Ref. [3xLijnzaad, P., Helgesen, C., and Rodriguez-Tome, P. Nucleic Acids Res. 1998; 26: 102–105Crossref | PubMed | Scopus (16)See all References][3]). This database is available at URL http://www.ebi.ac.uk/RHdbVarious analytical methods and software for constructing radiation hybrid maps have been developed in recent years. Unfortunately, each of these programs requires a different input format for the data. We have developed the RHScoresFormat tool to translate the user data given in a simple format to the format used by a specific program. Translators for the most common mapping programs have been implemented. These include: RHMAP (Ref. [2xBoehnke, M., Lange, K., and Cox, D.R. Am. J. Hum. Genet. 1991; 49: 1174–1188PubMedSee all References][2]), RHMAPPER and RHMapper server [L. Stein, L. Kruglyak, D. Slonim and E. Lander (1995) RHMAPPER, unpublished software, Whitehead Institute/MIT Center for Genome Research], RADMAP/ MULTIMAP (Refs [4xMatise, T., Perlin, M., and Chakravarti, A. Nat. Genet. 1994; 6: 384–390Crossref | PubMed | Scopus (376)See all References, 5xMatise, T.C. and Chakravarti, A. Am. J. Hum. Genet. 1995; 57: A15See all References]), and Stanford RH Server (http://www.shgc.stanford.edu/ RH).It is also possible to query the Radiation Hybrid database through a set of query windows by: STS name, chromosome, RHdb release, species, etc. The results can be merged with the user's own data to be used conjointly in the analysis.The RHScoresFormat Applet is available on the web at: http://corba.ebi.ac.uk/RHdb/Clients, which links also to all the other RHdb clients. A browser supporting Java (minimum JDK1.1.4) is needed to run the applets. The application is also available from the EBI ftp anonymous server (ftp://ftp.ebi.ac.uk/pub/databases/RHdb/software).

Geometric query types for data retrieval in relational databases

This paper describes the application of geometric concepts for data retrieval and proposes a geometric model for accessing and manipulating multidimensional data in relational databases. A geometric query model is proposed for the queries based on locations of geometric objects. In the geometric query model, the data from the database are interpreted geometrically as multidimensional geometric points or geometric objects interpolated on these points, and the query window is a query solid of any shape specified by its location. The spatial queries are formulated with geometric objects and operations over them. Descriptions of geometric objects and operations with implicit functions are proposed. This mathematical representation allowed us to develop a compact and easily extensible geometric query model that has been implemented in the geometric query system prototype.

Antiphonary of Sedlec, Antiphonarium Sedlecense XIII A 6

(Memoriae Mundi Series Bohemica, 1.) CD-ROM. National Library of the Czech Republic and Albertina icome Praha Ltd., 1995. $595. Requires 386 or higher IBM PC or compatible, 4 MB RAM, Windows 3.1 or higher, CD-ROM drive, mouse, EGA/VGA graphics, and color monitor. When UNESCO's Memory of the World project began in 1992, the National Library of the Czech Republic welcomed the opportunity to discover new solutions to problems of access and preservation for its fragile materials. Within a year, the library had produced a pilot CD-ROM containing sample images and a list of its most valuable historical holdings. The library formed a partnership with Albertina icome Praha Ltd. to establish the digitization project known as Memoriae Mundi Series Bohemica. The first product of their collaboration is this publication of the Antiphonarium Sedlecense, billed as the first CD-ROM of a complete medieval manuscript. The manuscript is given a detailed treatment that will be extended to only the most important items in this digitization project, but in fact the great detail offered here illustrates the capabilities of the CD-ROM format for the access and study of manuscript materials. The manuscript was created in the thirteenth century and is notable for the quality of its decorations, which show the influences of the crusaders' art on Bohemian illumination. It was repaired and bound in the seventeenth century with the addition of new paper pages, some containing new texts and others replacing damaged parchment pages. A number of hands were involved in the manuscript's creation, correction, and revision through the centuries. This product provides access to clear images of each manuscript page, thus giving researchers an opportunity to make comparisons among illuminations, notation, handwriting, and other features. This focus on the visual content of the manuscript, especially concerning the nature and artistic value of the illuminations, influenced the design of the CD-ROM. The CD contains English and Czech versions of a database describing and providing access to each page of the manuscript. The database uses fourteen fields: Pagination/Foliation, Writing Medium, Description of the Written Space, State of Preservation, Scribe, Additions, Type of Illumination, Motif of Illumination, Author of Illumination, Liturgical Section, Liturgical Day, Hora, Function, and Incipit (text). All but the last three fields are indexed and can be used for searching. The fields are described in full in the main Help area under Current Database. This region also contains an introduction to the CD-ROM by project administrators Adolf Knoll and Stanislav Psohlavec (from the National Library and Albertina icome Praha, respectively); an analysis of the manuscript, which includes a bibliographic description of the manuscript and its binding by Zdenka Hledikova, discussion of the illuminations by Hana Hlavackova, and remarks on the notation and a description of the contents by David Eben; a bibliography of related research; and imprint and acknowledgments. The Help area's index provides guidance for the use of the database, and many of the topics are also available as contextual help. WiniFreT software, a product of Albertina icome Praha Ltd., is the user interface that provides access to the full-color images and the database of descriptive information. The program opens to the main Query window, presenting eleven fields in which to input search terms. At this point, the user may opt to click on the search button located on the toolbar (or pull down the Query menu and select F5) to retrieve all 525 database records for the cover and 524 pages of the manuscript. Searches like this one, resulting in more than one hit, return a display showing a spreadsheet arrangement of information, the List of Selected Records window, with field descriptors across the top and data below. For the longer fields, such as Supplement (which is called Additions in the Help area outlined above and describes later corrections and changes to the manuscript), only the first forty or so characters in the field are displayed. …

MOF-tree: A spatial access method to manipulate multiple overlapping features

In this paper we investigate the manipulation of large sets of 2-dimensional data representing multiple overlapping features (e.g. semantically distinct overlays of a given region), and we present a new access method, the MOF-tree. We perform an analysis with respect to the storage requirements and a time analysis with respect to window query operations involving multiple features (e.g. to verify if a constraint defined on multiple overlays holds or not inside a certain region). We examine both the pointer-based as well as the pointerless MOF-tree representations, using as space complexity measure the number of bits used in main memory and the number of disk pages in secondary storage respectively. In particular, we show that the new structure is space competitive in the average case, both in the pointer version and in the linear version, with respect to multiple instances of a region quadtree and a linear quadtree respectively, where each instance represents a single feature. Concerning the time performance of the new structure, we analyze the class of window (range) queries, posed on the secondary memory implementation. We show that the I/O worst-case time complexity for processing a number of window queries in the given image space, is competitive with respect to multiple instances of a linear quadtree, as confirmed by experimental results. Finally, we show that the MOF-tree can efficiently support spatial join processing in a spatial DBMS.

Point representation of spatial objects and query window extension: a new technique for spatial access methods

The use of Spatial Access Methods (SAMs) in spatial database systems, such as Geographical Information Systems, is necessary to achieve efficient retrieval of data items according to their spatial properties. Existing SAMs organizing minimum bounding rectangle (MBR) approximations of spatial objects can be classified into four groups. Each group is characterized by the special technique adopted for managing MBRs: (a) Ordering, (b) Transformation, (c) Clipping, and (d) Overlapping. This paper introduces a new technique. The basic idea of this technique is to represent all spatial objects by their MBRs and further reduce them into points of the same dimensionality, so that any multidimensional Point Access Method (PAM) may be used to support access. Essential for the functionality of the new method is the query window extension. The results of both analytical and experimental work show that SAMs using the new technique clearly outperform popular SAMs, such as the R- and R*-trees for data sets consisting of equal-sized MBRs. As for data sets of varying MBR sizes a competitive performance can be obtained.

Orthogonal queries in segments

We consider theorthgonal clipping problem in a set of segments: Given a set ofn segments ind-dimensional space, we preprocess them into a data structure such that given an orthogonal query window, the segments intersecting it can be counted/reported efficiently. We show that the efficiency of the data structure significantly depends on a geometric discrete parameterK named theProjected-image complexity, which becomes ź(n2) in the worst case but practically much smaller. If we useO(m) space, whereK log4dź7nźmźn log4dź7n, the query time isO((K/m)1/2 logmax{4, 4dź5}n). This is near to an Ω((K/m)1/2) lower bound.

Time and space efficient secondary memory representation of quadtrees

Efficient management of spatial data is becoming more and more important and for very large sets of 2-dimensional data, secondary memory data representations are required. An important class of queries for spatial data are those that extract a subset of the data: they are called window queries (also region or range queries). In this paper we propose and analyze a new data structure, namely the hybrid linear quadtree, for the efficient secondary memory processing of three kinds of window queries, that is the exist, the report and the select query. In particular we prove that for a window of size n × n in a feature space (e.g., an image) of size T × T using the hybrid linear quadtree stored on a B +-tree with bucket size r, the exist and report query can be answered with O( n log r T) accesses to secondary storage, while the select query can be answered with O(n log r T + n 2 r ) accesses to secondary storage. This is an improvement in worst-case I/O time complexity over previous results and shows that multiple non-overlapping features (i.e., coloured images) can be treated with the same I/O complexity as single features (i.e., black and white images). Furthermore, we show that the hybrid linear quadtree has a low space occupancy overhead with respect to the classic linear quadtree.

Efficient Window Block Retrieval in Quadtree-Based Spatial Databases

An algorithm is presented to answer window queries in a quadtree-based spatial database environment by retrieving all of the quadtree blocks in the underlying spatial database that cover the quadtree blocks that comprise the window. It works by decomposing the window operation into sub-operations over smaller window partitions. These partitions are the quadtree blocks corresponding to the window. Although a block b in the underlying spatial database may cover several of the smaller window partitions, b is only retrieved once rather than multiple times. This is achieved by using an auxiliary main memory data structure called the active border which requires O\left(n\right) additional storage for a window query of size n\times n . As a result, the algorithm generates an optimal number of disk I/O requests to answer a window query (i.e., one request per covering quadtree block). A proof of correctness and an analysis of the algorithm’s execution time and space requirements are given, as are some experimental results.

Nearly Balanced Quad List Quad Tree -A Data Structure for VLSI Layout Systems

In the past ten years, many researchers have focused attention on developing better data structures for storing graphical information. Among the proposed data structures, the quad tree data structure provides a good way to organize objects on a 2-D plane. Region searches proceed at logarithmic speeds a desirable characteristic, but no previously proposed VLSI quad tree data structure distributed objects to subdivide the spatial area. This has been a major drawback for operations such as tree searching and window query. In this paper, we present a new division method to reconstruct those quad trees including the multiple storage quad tree (MSQT) and the quad list quad tree (QLQT) into nearly balanced quad tree data structures. Nearly balanced quad trees based on our new spatial division method are constructed by dynamically translating unbalanced multiple storage quad trees or unbalanced quad list quad trees into balanced structures. All benefits of the original quad tree data structures are completely retained. In addition, this method is simple and balanced quad trees memory require less than the original quad trees. Experimental results illustrate that the improvement in region queries of the presented nearly balanced quad trees to both of the QLQT and the MSQT is better than the improvement of the QLQT to the MSQT.

Efficient secondary memory processing of window queries on spatial data

Efficient management of spatial data is becoming more and more important, requiring very large spatial database secondary memory data representations. An important class of queries for spatial data are those which extract a subset of the data; they are called window queries. In this paper, we analyze the efficient secondary memory processing of three kinds of window queries, namely, the exist, the report, and the select queries. In particular, we show that for the three queries, both for single feature and for multiple non-overlapping features, the number of accesses is never greater than the number of pixels inside the window. More precisely, we prove that for a window of size n × n in a feature space (e.g., an image) of size T × T (e.g., pixel elements), the exist query for binary image can be answered with O( nlog r T) accesses on secondary storage, while in all the other cases, window queries on generic images can be answered with O( nlog r T + n 2/ r) accesses on secondary storage. We also show that for two-dimensional range searching where output size is proportional to the search space size, the proposed data structure is optimal against other data structures proposed in the literature.

Design and evaluation of access method for multi-dimensional objects in spatial databases

The existing conventional access methods are not suitable to many complex applications such as geographic information systems, computer-aided design, and computer vision. Therefore, it is important to use a highly efficient access method for complex applications. In this paper, we propose a new dynamic access method, called Binary divided Region (BR) tree, for spatial data and then implement search, insertion, deletion, and splitting algorithms used for the BR tree. The proposed access method is compared with the two representative spatial access methods, R-tree and R +-tree, through performance results from analytical study and simulation approach for a VLSI data. For search, when the size of a user-specified rectangular region, called query window, is relatively small, BR tree produces the best performance with respect to the number of disk accesses since it generates the smallest number of nodes and avoids overlapping of rectangles. For insertion, BR tree achieves up to 20 percent saving in the amount of storage over R-tree and R +-tree since it does not need the values of coordinates in representing a region. Also, BR tree achieves up to 60 percent saving in insertion time over R-tree and R +-tree since it does not require the reorganization of tree.

Decomposing a window into maximal quadtree blocks

Window operations serve as the basis of a number of queries that can be posed in a spatial database. Examples of window-based queries include the exist query (i.e., determining whether or not a spatial feature exists inside a window), the report query (i.e., report the identity of all the features that exist inside a window), and the select query (i.e., determine the locations covered by a given feature inside a window). Often spatial databases make use of a quadtree decomposition, which yields a set of maximal blocks, to enable the features to be accessed quickly without having to search the entire database. One way to perform a window query is to decompose the window into its maximal quadtree blocks. An algorithm is described for decomposing a two-dimensional window into its maximal quadtree blocks inO(nlog logT) time for a window of sizen×n in a feature space (e.g., an image) of sizeT×T (e.g., pixel elements).

A new method for planar graph drawings on a grid (abstract)

Drawing graphs is an important problem that combines flavors of computational geometry and graph theory. Applications can be found in a variety of areas including circuit layout, network management, software engineering, and graphics. The main contributions of this paper can be summarized as follows: (i) We devise a model for dynamic graph algorithms, based on performing queries and updates on an implicit representation of the drawing, and we show its applications. (ii) We present several efficient dynamic drawing algorithms for trees, series-parallel digraphs, planar st -digraphs, and planar graphs. These algorithms adopt a variety of representations (e.g., straight-line, polyline, visibility), and update the drawing in a smooth way. (iii) We show that the implicit representation of the layout used by our algorithms for trees and series-parallel digraphs also supports point-location and window queries. (Joint work with P. Bertolazzi, G. Di Battista, R. Tamassia, and I. G. Tollis.)

A qualitative comparison study of data structures for large line segment databases

A qualitative comparative study is performed of the performance of three popular spatial indexing methods - the R-tree, R + -tree, and the PMR quadtree-in the context of processing spatial queries in large line segment databases. The data is drawn from the TIGER/Line files used by the Bureau of the Census to deal with the road networks in the US. The goal is not to find the best data structure as this is not generally possible. Instead, their comparability is demonstrated and an indication is given as to when and why their performance differs. Tests are conducted with a number of large datasets and performance is tabulated in terms of the complexity of the disk activity in building them, their storage requirements, and the complexity of the disk activity for a number of tasks that include point and window queries, as well as finding the nearest line segment to a given point and an enclosing polygon.

Efficient access method for multi-dimensional complex objects in spatial databases: BR tree

In this paper we propose a new dynamic access method for spatial databases, called BR(Binary divided Region) tree. Search, insertion, and deletion algorithms for the access method are discussed in detail. Then, the proposed access method is compared with the representative spatial access methods like the R-tree and R +-tree through experimental results. For search, when the size of a user-specified rectangular region, called query window, is small, the proposed access method produces the best performance with respect to the number of disk accesses since it generates the smallest number of nodes and avoids overlapping rectangles. However, when the size of a query window is large, the search performance of the proposed access method becomes poor since it increases empty space, and R-tree requires the smallest number of disk accesses. For insertion, the proposed access method achieves up to 40 percent saving in the number of disk accesses and up to 20 percent saving in the amount of storage over R-tree and R +-tree.

Extending SQL for Graphical Display

A language has been designed to describe the cartographic display of query results in geographic information systems. Its syntax is based on SQL, the standard query languages for relational data bases. The syntactical separation of data-base query and display specifications into a query language and graphical presentation language, respectively, is a novel approach. Spatial SQL introduces spatial data types and the corresponding spatial relationships, allowing users to inquire about spatial objects in the familiar SELECT-FROM-WHERE form, extended by spatial conditions. The cartographic display of spatial objects selected is directed with the Spatial SQL-based Graphical Presentation Language (GPL), so that complex graphic descriptions can be formulated in a language similar to SQL. GPL contains commands to direct the display of objects, spatial context, the query window, map scale, etc. This lets users formulate separately queries and display specifications, which are integrated during query processing so ...