Historia de YLM

YLM Heavy Industry Ciencia y Tecnología duranteel proceso de desarrollo de los últimos 30 años, se fuerma una cultura empresarial y rica en contenido único.

La construcción de la cultura de la empresa YLM Heavy Industry Ciencia y Tecnología ser la cohesión y la solidaridad del punto de agregación y la fuente de energía para el desarrollo sostenible de las empresas.

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Se trata de una moderna empresa con la investigación, fabricación y ventas juntos. La matriz se encuentra enla zona HI-TECH Industry Development de Zhengzhou y cubiertas 80.000 m ².

YLM Heavy Industry

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Gracias por su interés en YLM Heavy Industry. Si usted quiere saber más informaciones sobre las trituradoras y molinos de industria, contáctenos ahora para saber qué podemos hacer para su próximo proyecto.

Gracias por su interés en YLM Heavy Industry. Si usted quiere saber más informaciones sobre las trituradoras y molinos de industria, contáctenos ahora para saber qué podemos hacer para su próximo proyecto.

Address:No.169, Science (Kexue) Avenue, National HI-TECH Industry Development Zone, Zhengzhou, China

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range aggregate processing spatial databases

  • (PDF) Range aggregate processing in spatial databases

    Traditional research in spatial databases often aims at the range query, which retrieves the data objects lying inside (or intersecting) a multi-dimensional hyper-rectangle. In many scenarios (e.g.,

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  • Range Aggregate Processing in Spatial Databases

    A range aggregate query returns summarized information about the points falling in a hyper- rectangle (e.g., the total number of these points instead of their concrete ids). This paper studies

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  • CiteSeerX — Range Aggregate Processing in Spatial

    CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Abstract—A range aggregate query returns summarized information about the points falling in a hyper-rectangle (e.g., the total number of these points instead of their concrete ids). This paper studies spatial indexes that solve such queries efficiently and proposes the aggregate Point-tree (aP

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  • IEEE TRANSACTIONS ON KNOWLEDGE AND DATA

    2005-3-25  Range Aggregate Processing in Spatial Databases Yufei Tao and Dimitris Papadias Abstract—A range aggregate query returns summarized information about the points falling in a hyper-rectangle (e.g., the total number of these points instead of their concrete ids). This paper studies spatial indexes that solve such queries efficiently and

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  • Predicted Range Aggregate Processing in Spatio-temporal

    CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Predicted range aggregate (PRA) query is an important researching issue in spatio-temporal databases. Recent studies have developed two major classes of PRA query methods: (1) accurate approaches, which search the common moving objects indexes to obtain an accurate result; and (2)

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  • Predicted Range Aggregate Processing in Spatio-temporal

    A high dynamic range camera provides the processing unit with image data. Measurement points of lane borders, calculated by a robust edge detection algorithm, are

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  • Predicted range aggregate processing in spatio

    2006-7-31  We start with a concrete definition of aggregate query in spatio-temporal databases before presenting the PRA-tree index. By definition, a spatiotemporal object is a unified object with spatial and temporal extent [2]. A pure spatial object can be a point, a line, or a region in two or three-dimensional space. The position and/or shape either

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  • A Scalable Algorithm for Maximizing Range Sum in

    2017-6-30  in spatial databases. The range aggregate (RA) query was proposed for the scenario where users are interested in sum-marized information about objects in a given range rather than individual objects. Thus, a RA query returns an ag-gregation value over objects qualified for a given range. In order to efficiently process RA queries, usually ...

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  • Indexing range sum queries in spatio-temporal databases

    2007-4-1  The R-tree is known to be one of the most popular index structures to efficiently process window queries in spatial databases. Intuitively, the aggregate R-tree (aR-tree) , improves the R-tree’s performance in range sum queries by storing, in each intermediate entry, pre-aggregated sums of the objects in the subtree. Fig. 1 shows an example of an aR-tree.

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  • A Scalable Algorithm for Maximizing Range Sum in Spatial

    Lei Chen. Maximum Range-Sum (MaxRS) query is an important operator in spatial database for retrieving regions of interest (ROIs). Given a rectangular query size a

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  • Predicted Range Aggregate Processing in Spatio-temporal

    CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Predicted range aggregate (PRA) query is an important researching issue in spatio-temporal databases. Recent studies have developed two major classes of PRA query methods: (1) accurate approaches, which search the common moving objects indexes to obtain an accurate result; and (2)

    Bavarder sur Internet
  • Predicted range aggregate processing in spatio

    2006-7-31  We start with a concrete definition of aggregate query in spatio-temporal databases before presenting the PRA-tree index. By definition, a spatiotemporal object is a unified object with spatial and temporal extent [2]. A pure spatial object can be a point, a line, or a region in two or three-dimensional space. The position and/or shape either

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  • Approximately processing aggregate range queries on

    2013-1-1  Processing aggregate range queries on remote spatial databases suffers from accessing huge and/or large number of databases that operate autonomously and simple and/or restrictive web API interfaces. To overcome these difficulties, this paper applies a revised version of regular polygon-based search algorithm (RPSA) to approximately search aggregate range

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  • Article: Approximately processing aggregate range

    2014-4-7  Abstract: Processing aggregate range queries on remote spatial databases suffers from accessing huge and/or large number of databases that operate autonomously and simple and/or restrictive web API interfaces. To overcome these difficulties, this paper applies a revised version of regular polygon-based search algorithm (RPSA) to approximately ...

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  • Indexing range sum queries in spatio-temporal databases

    2007-4-1  The R-tree is known to be one of the most popular index structures to efficiently process window queries in spatial databases. Intuitively, the aggregate R-tree (aR-tree) , improves the R-tree’s performance in range sum queries by storing, in each intermediate entry, pre-aggregated sums of the objects in the subtree. Fig. 1 shows an example of an aR-tree.

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  • Clustering spatial networks for aggregate query

    2008-3-1  In spatial networks, clustering adjacent data to disk pages is highly likely to reduce the number of disk page accesses made by the aggregate network operations during query processing. For this purpose, different techniques based on the clustering graph model are proposed in the literature.

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  • PDF - Query processing in spatial network databases

    2003-9-8  Abstract: Given two spatial datasets P (eg, facilities) and Q (queries), an aggregate nearest neighbor (ANN) query retrieves the point(s) of P with the smallest aggregate distance(s) to points in Q Assuming, for example, n users at locations q1,qn, an ANN query outputs the facility p ∈ P that minimizes the sum of distances vpqiv for 1 ≤ i ≤ n that the users have to

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  • Supporting Spatial Aggregation in Sensor Network

    2016-5-21  network processing of the aggregation queries on the data generated in the sensor network. We use the ad-hoc query routing algorithm of TAG to disseminate our query into the network. Our spatial aggregate operators are compatible with the aggregate processing of TAG and easily portable to TinyDB. Zhao et al. in [9] introduce an architecture for ...

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  • Euler Histogram Tree: A Spatial Data Structure for

    2015-1-13  tial databases and GIS General Terms Algorithms Keywords aggregate query, spatial histogram, hierarchical data structure 1. INTRODUCTION This paper addresses the problem of processing a variant of range queries in spatial databases for vehicle trajectories. More specifi-cally, we tackle the, so called, distinct vehicle query – which is,

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  • Data structures for range-aggregate extent queries

    A fundamental and well-studied problem in computational geometry is range searching, where the goal is to preprocess a set, S, of geometric objects (e.g., points in the plane) so that the subset S^'@?S that is contained in a query range (e.g., an axes-...

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  • Article: Approximately processing aggregate range

    2014-4-7  Abstract: Processing aggregate range queries on remote spatial databases suffers from accessing huge and/or large number of databases that operate autonomously and simple and/or restrictive web API interfaces. To overcome these difficulties, this paper applies a revised version of regular polygon-based search algorithm (RPSA) to approximately ...

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  • Spatial Databases - University of Minnesota

    2007-5-1  Spatial Databases 1.1 Introduction 1.1.1 Spatial Database Spatial database management systems [43, 58, 120, 119, 97, 74] aim at the effective and efficient management ... spatial query processing including point, regional, range, and nearest neighbor queries; and spatial data methods using a variety of indexes such as ... set of aggregate ...

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  • Clustering spatial networks for aggregate query

    2008-3-1  1. Introduction1.1.. MotivationIn the last two decades, numerous conceptual models, spatial access methods, and query processing techniques are proposed , to overcome the problems faced within the extensive scale of geographic information systems (GIS). The increasing demand on geographic applications made spatial databases quite popular.

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  • Supporting spatial aggregation in sensor network databases

    Our spatial aggregate operators are compatible as the primary keys. with the aggregate processing of TAG and easily portable A set of different aggregation queries are now formally to TinyDB. definable on the the realized conceptual model of the sensor Zhao et al. in [9] introduce an architecture for sensor network.

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  • PDF - Query processing in spatial network databases

    2003-9-8  Abstract: Given two spatial datasets P (eg, facilities) and Q (queries), an aggregate nearest neighbor (ANN) query retrieves the point(s) of P with the smallest aggregate distance(s) to points in Q Assuming, for example, n users at locations q1,qn, an ANN query outputs the facility p ∈ P that minimizes the sum of distances vpqiv for 1 ≤ i ≤ n that the users have to

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  • Algorithms for Fundamental Spatial Aggregate

    2020-3-10  Aggregate operations have a long history of use and study in databases (see the survey [11]). The development of spa-tial aggregates is more recent, but has similarly received much attention. A signi cant portion of the literature on spatial aggregates is devoted to mechanisms to support range queries, or box queries. Aggregate range queries ...

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  • Materialized views for count aggregates of spatial data

    title = "Materialized views for count aggregates of spatial data", abstract = "We address the problem of efficient processing of count aggregate queries for spatial objects in OLAP systems. One of the main issues affecting the efficient spatial analysis is the, so called, distinct counting problem. The core of the problem is due to the fact ...

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  • Clustering spatial networks for aggregate query

    2013-2-25  models, spatial access methods, and query processing techniques are proposed [1,2] to overcome the problems faced within the extensive scale of geo-graphic information systems (GIS). The increasing demand on geographic applications made spatial databases quite popular. The research on spatial databases focused on the Euclidean space, where the

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  • Probabilistic Threshold Range Aggregate Query

    2009-5-30  A range aggregate query (RA query) on certain data returns summarized information about objects satisfying a given query range, such as the total num-ber of qualified objects [19]. This type of query is important since users may be interested only in aggregate information instead of specific IDs. For instance, to

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  • Data structures for range-aggregate extent queries

    A fundamental and well-studied problem in computational geometry is range searching, where the goal is to preprocess a set, S, of geometric objects (e.g., points in the plane) so that the subset S^'@?S that is contained in a query range (e.g., an axes-...

    Bavarder sur Internet