The R-tree, one of the most popular access methods for rectangles, is based on heuristic optimization area enclosing rectangle in each inner node. By running numerous experiments a standardized testbed under highly varying data, queries and operations, we were able to design R*-tree which incorporates combined area, margin overlap directory. Using our an exhaustive performance comparison, it turned out that clearly outperforms existing R-tree variants. Guttman's linear quadratic Greene's...

The R-tree, one of the most popular access methods for rectangles, is based on heuristic optimization area enclosing rectangle in each inner node. By running numerous experiments a standardized testbed under highly varying data, queries and operations, we were able to design R * -tree which incorporates combined area, margin overlap directory. Using our an exhaustive performance comparison, it turned out that clearly outperforms existing R-tree variants. Guttman's linear quadratic Greene's...

The skyline of a d -dimensional dataset contains the points that are not dominated by any other point on all dimensions. Skyline computation has recently received considerable attention in database community, especially for progressive methods can quickly return initial results without reading entire database. All existing algorithms, however, have some serious shortcomings which limit their applicability practice. In this article we develop branch-and-bound (BBS), an algorithm based...

The skyline of a set d-dimensional points contains the that are not dominated by any other point on all dimensions. Skyline computation has recently received considerable attention in database community, especially for progressive (or online) algorithms can quickly return first without having to read entire data file. Currently, most efficient algorithm is NN (<u>n</u>earest <u>n</u>eighbors), which applies divide -and-conquer framework datasets indexed R-trees. Although some desirable...

Spatial joins are one of the most important operations for combining spatial objects several relations. The efficient processing a join is extremely since its execution time superlinear in number participating relations, and this may be very high. In paper, we present first detailed study using R-trees, particularly R*-trees. R-trees suitable supporting queries R*-tree members R-tree family. Starting from straightforward approach, techniques improving with respect to both, CPU- I/O-time....

Spatial joins are one of the most important operations for combining spatial objects several relations. In this paper, join processing is studied in detail extended two-dimensional data space. We present an approach that based on three steps. First, a performed minimum bounding rectangles returning set candidates. Various approaches accelerating step have been examined at last year's conference [BKS 93a]. we focus problem how to compute answers from candidate which handled by following two...

Many recent database applications need to deal with similarity queries. For such applications, it is important measure the between two objects using distance them. Focusing on this problem, paper proposes slim-tree, a new dynamic tree for organizing metric data sets in pages of fixed size. The slim-tree uses triangle inequality prune calculations that are needed answer queries over spaces. proposed insertion algorithm policies select nodes where incoming stored. When node overflows, minimal...

Information about clouds is important for observing and predicting weather climate as well generating distributing solar power. Most existing approaches extract cloud information from satellite data by classifying individual pixels instead of using closely integrated spatial information, ignoring the fact that are highly dynamic, spatially continuous entities. This paper proposes a novel classification method based on deep learning. Relying Convolutional Neural Network (CNN) architecture...

Spatial joins are one of the most important operations for combining spatial objects several relations. The efficient processing a join is extremely since its execution time superlinear in number participating relations, and this may be very high. In paper, we present first detailed study using R-trees, particularly R*-trees. R-trees suitable supporting queries R*-tree members R-tree family. Starting from straightforward approach, techniques improving with respect to both, CPU- I/O-time....

In recent years the processing of continuous queries over potentially infinite data streams has attracted a lot research attention. We observed that majority work addresses individual stream operations and system-related issues rather than development general-purpose basis for systems. Furthermore, example are often formulated in some declarative query language without specifying underlying semantics precisely enough. To overcome these deficiencies, this article presents consistent powerful...

Herbaria worldwide are housing a treasure of 100s millions herbarium specimens, which increasingly being digitized in recent years and thereby made more easily accessible to the scientific community. At same time, deep learning algorithms rapidly improving pattern recognition from images these techniques applied biological objects. We using digital specimens order identify taxa traits collection objects by applying convolutional neural networks (CNN). Images 1000 species most frequently...

We show that spatial joins are very suitable to be processed on a parallel hardware platform. The system is equipped with so called shared virtual memory which well suited for the design and implementation of join algorithms. start an algorithm consists three phases: task creation, assignment execution. In order reduce CPU I/O cost, phases in fashion preserves locality. Dynamic load balancing achieved by splitting tasks into smaller ones reassigning some idle processors. experimental...

In this paper we present an improved redesign of the R*-tree that is entirely suitable for running within a DBMS. Most importantly, insertion guaranteed to be restricted single path because re-insertion could abandoned. We re-engineered both, subtree choice and split algorithm, more robust against specific data distributions orders, as well peculiarities often found in real multidimensional sets. This comes along with substantial reduction CPU-time.

ABSTRACT Due to the rapid cost decline of synthesizing and sequencing deoxyribonucleic acid (DNA), high information density, its durability up centuries, utilizing DNA as an storage medium has received attention many scientists. State-of-the-art systems exploit capacity enable random access (predominantly reads) by primers, which serve unique identifiers for directly accessing data. However, primers come with a significant limitation regarding maximum available number per library. The...

The partition-based spatial-merge join (PBSM) of J.M. Patel and D.J. DeWitt (1996) the size separation spatial (S/sup 3/J) N. Koudas K.C. Sevcik (1997) are considered to be among most efficient methods for processing (intersection) joins on two or more relations. Neither method assumes presence pre-existing indices In this paper, we propose several improvements these algorithms. particular, deal with impact data redundancy duplicate detection performance methods. For PBSM, present a simple...