1,030 research outputs found

    A storage and access architecture for efficient query processing in spatial database systems

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    Due to the high complexity of objects and queries and also due to extremely large data volumes, geographic database systems impose stringent requirements on their storage and access architecture with respect to efficient query processing. Performance improving concepts such as spatial storage and access structures, approximations, object decompositions and multi-phase query processing have been suggested and analyzed as single building blocks. In this paper, we describe a storage and access architecture which is composed from the above building blocks in a modular fashion. Additionally, we incorporate into our architecture a new ingredient, the scene organization, for efficiently supporting set-oriented access of large-area region queries. An experimental performance comparison demonstrates that the concept of scene organization leads to considerable performance improvements for large-area region queries by a factor of up to 150

    The performance of object decomposition techniques for spatial query processing

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    An Evolutionary Analysis of World Energy Consumption and World Population

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    The evolution of large-scale systems is described by a model based on the assumption of hyperbolic growth and saturation processes. It is shown that this Hyper-Logistic Evolution Model (HLEM) successfully describes the development of world population and global primary energy consumption over the past century; the model is also used to provide projections of world population and primary energy consumption up to the year 2100

    Performance comparison of point and spatial access methods

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    In the past few years a large number of multidimensional point access methods, also called multiattribute index structures, has been suggested, all of them claiming good performance. Since no performance comparison of these structures under arbitrary (strongly correlated nonuniform, short "ugly") data distributions and under various types of queries has been performed, database researchers and designers were hesitant to use any of these new point access methods. As shown in a recent paper, such point access methods are not only important in traditional database applications. In new applications such as CAD/CIM and geographic or environmental information systems, access methods for spatial objects are needed. As recently shown such access methods are based on point access methods in terms of functionality and performance. Our performance comparison naturally consists of two parts. In part I we w i l l compare multidimensional point access methods, whereas in part I I spatial access methods for rectangles will be compared. In part I we present a survey and classification of existing point access methods. Then we carefully select the following four methods for implementation and performance comparison under seven different data files (distributions) and various types of queries: the 2-level grid file, the BANG file, the hB-tree and a new scheme, called the BUDDY hash tree. We were surprised to see one method to be the clear winner which was the BUDDY hash tree. It exhibits an at least 20 % better average performance than its competitors and is robust under ugly data and queries. In part I I we compare spatial access methods for rectangles. After presenting a survey and classification of existing spatial access methods we carefully selected the following four methods for implementation and performance comparison under six different data files (distributions) and various types of queries: the R-tree, the BANG file, PLOP hashing and the BUDDY hash tree. The result presented two winners: the BANG file and the BUDDY hash tree. This comparison is a first step towards a standardized testbed or benchmark. We offer our data and query files to each designer of a new point or spatial access method such that he can run his implementation in our testbed

    Tuning and Locking the Localized Surface Plasmon Resonances of CuS (Covellite) Nanocrystals by an Amorphous CuPdxS Shell

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    [Image: see text] We demonstrate the stabilization of the localized surface plasmon resonance (LSPR) in a semiconductor-based core–shell heterostructure made of a plasmonic CuS core embedded in an amorphous-like alloyed CuPd(x)S shell. This heterostructure is prepared by reacting the as-synthesized CuS nanocrystals (NCs) with Pd(2+) cations at room temperature in the presence of an electron donor (ascorbic acid). The reaction starts from the surface of the CuS NCs and proceeds toward the center, causing reorganization of the initial lattice and amorphization of the covellite structure. According to density functional calculations, Pd atoms are preferentially accommodated between the bilayer formed by the S–S covalent bonds, which are therefore broken, and this can be understood as the first step leading to amorphization of the particles upon insertion of the Pd(2+) ions. The position and intensity in near-infrared LSPRs can be tuned by altering the thickness of the shell and are in agreement with the theoretical optical simulation based on the Mie–Gans theory and Drude model. Compared to the starting CuS NCs, the amorphous CuPd(x)S shell in the core–shell nanoparticles makes their plasmonic response less sensitive to a harsh oxidation environment (generated, for example, by the presence of I(2))

    Querying Probabilistic Neighborhoods in Spatial Data Sets Efficiently

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    \newcommand{\dist}{\operatorname{dist}} In this paper we define the notion of a probabilistic neighborhood in spatial data: Let a set PP of nn points in Rd\mathbb{R}^d, a query point qRdq \in \mathbb{R}^d, a distance metric \dist, and a monotonically decreasing function f:R+[0,1]f : \mathbb{R}^+ \rightarrow [0,1] be given. Then a point pPp \in P belongs to the probabilistic neighborhood N(q,f)N(q, f) of qq with respect to ff with probability f(\dist(p,q)). We envision applications in facility location, sensor networks, and other scenarios where a connection between two entities becomes less likely with increasing distance. A straightforward query algorithm would determine a probabilistic neighborhood in Θ(nd)\Theta(n\cdot d) time by probing each point in PP. To answer the query in sublinear time for the planar case, we augment a quadtree suitably and design a corresponding query algorithm. Our theoretical analysis shows that -- for certain distributions of planar PP -- our algorithm answers a query in O((N(q,f)+n)logn)O((|N(q,f)| + \sqrt{n})\log n) time with high probability (whp). This matches up to a logarithmic factor the cost induced by quadtree-based algorithms for deterministic queries and is asymptotically faster than the straightforward approach whenever N(q,f)o(n/logn)|N(q,f)| \in o(n / \log n). As practical proofs of concept we use two applications, one in the Euclidean and one in the hyperbolic plane. In particular, our results yield the first generator for random hyperbolic graphs with arbitrary temperatures in subquadratic time. Moreover, our experimental data show the usefulness of our algorithm even if the point distribution is unknown or not uniform: The running time savings over the pairwise probing approach constitute at least one order of magnitude already for a modest number of points and queries.Comment: The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-44543-4_3

    How Do You Like Me in This: User Embodiment Preferences for Companion Agents

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    We investigate the relationship between the embodiment of an artificial companion and user perception and interaction with it. In a Wizard of Oz study, 42 users interacted with one of two embodiments: a physical robot or a virtual agent on a screen through a role-play of secretarial tasks in an office, with the companion providing essential assistance. Findings showed that participants in both condition groups when given the choice would prefer to interact with the robot companion, mainly for its greater physical or social presence. Subjects also found the robot less annoying and talked to it more naturally. However, this preference for the robotic embodiment is not reflected in the users’ actual rating of the companion or their interaction with it. We reflect on this contradiction and conclude that in a task-based context a user focuses much more on a companion’s behaviour than its embodiment. This underlines the feasibility of our efforts in creating companions that migrate between embodiments while maintaining a consistent identity from the user’s point of view

    Query processing of spatial objects: Complexity versus Redundancy

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    The management of complex spatial objects in applications, such as geography and cartography, imposes stringent new requirements on spatial database systems, in particular on efficient query processing. As shown before, the performance of spatial query processing can be improved by decomposing complex spatial objects into simple components. Up to now, only decomposition techniques generating a linear number of very simple components, e.g. triangles or trapezoids, have been considered. In this paper, we will investigate the natural trade-off between the complexity of the components and the redundancy, i.e. the number of components, with respect to its effect on efficient query processing. In particular, we present two new decomposition methods generating a better balance between the complexity and the number of components than previously known techniques. We compare these new decomposition methods to the traditional undecomposed representation as well as to the well-known decomposition into convex polygons with respect to their performance in spatial query processing. This comparison points out that for a wide range of query selectivity the new decomposition techniques clearly outperform both the undecomposed representation and the convex decomposition method. More important than the absolute gain in performance by a factor of up to an order of magnitude is the robust performance of our new decomposition techniques over the whole range of query selectivity

    Feed-forward Torque Control of Interior Permanent Magnet Brushless AC Drive for Traction Applications

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    This paper presents a feed-forward torque control (FTC) technique for interior permanent magnet (IPM) brushless AC (BLAC) drives in traction applications. It is shown that by adopting the Newton-Raphson iterative method for solving the proposed high-order nonlinear relationship between the torque demand, flux-linkage and desirable dq-axis currents, FTC with due account of nonlinear machine parameters can be achieved for IPM BLAC drives. It is also proven that the comparison between the reference voltage magnitudes under maximum torque per ampere (MTPA) and field-weakening (FW) operations together with online base speed determination can be utilized for FW operation activation to achieve full exploitation of the available DC-link voltage during the transition between the constant torque and FW operation regions. Since both the dqaxis current references and the base speed for FW operation activation are computed online, the proposed FTC technique provides flexibility for online parameter update or estimation and is able to cope with wide DC-link voltage variation. The proposed FTC strategy is experimentally validated by measurements on a 10kW wide constant power speed range (CPSR) IPM BLAC machine drive
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