• Title/Summary/Keyword: multi-dimension

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Efficient Continuous Skyline Query Processing Scheme over Large Dynamic Data Sets

  • Li, He;Yoo, Jaesoo
    • ETRI Journal
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    • v.38 no.6
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    • pp.1197-1206
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    • 2016
  • Performing continuous skyline queries of dynamic data sets is now more challenging as the sizes of data sets increase and as they become more volatile due to the increase in dynamic updates. Although previous work proposed support for such queries, their efficiency was restricted to small data sets or uniformly distributed data sets. In a production database with many concurrent queries, the execution of continuous skyline queries impacts query performance due to update requirements to acquire exclusive locks, possibly blocking other query threads. Thus, the computational costs increase. In order to minimize computational requirements, we propose a method based on a multi-layer grid structure. First, relational data object, elements of an initial data set, are processed to obtain the corresponding multi-layer grid structure and the skyline influence regions over the data. Then, the dynamic data are processed only when they are identified within the skyline influence regions. Therefore, a large amount of computation can be pruned by adopting the proposed multi-layer grid structure. Using a variety of datasets, the performance evaluation confirms the efficiency of the proposed method.

Efficiently Processing Skyline Query on Multi-Instance Data

  • Chiu, Shu-I;Hsu, Kuo-Wei
    • Journal of Information Processing Systems
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    • v.13 no.5
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    • pp.1277-1298
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    • 2017
  • Related to the maximum vector problem, a skyline query is to discover dominating tuples from a set of tuples, where each defines an object (such as a hotel) in several dimensions (such as the price and the distance to the beach). A tuple, an instance of an object, dominates another tuple if it is equally good or better in all dimensions and better in at least one dimension. Traditionally, skyline queries are defined upon single-instance data or upon objects each of which is associated with an instance. However, in some cases, an object is not associated with a single instance but rather by multiple instances. For example, on a review website, many users assign scores to a product or a service, and a user's score is an instance of the object representing the product or the service. Such data is an example of multi-instance data. Unlike most (if not all) others considering the traditional setting, we consider skyline queries defined upon multi-instance data. We define the dominance calculation and propose an algorithm to reduce its computational cost. We use synthetic and real data to evaluate the proposed methods, and the results demonstrate their utility.

Multihazard capacity optimization of an NPP using a multi-objective genetic algorithm and sampling-based PSA

  • Eujeong Choi;Shinyoung Kwag;Daegi Hahm
    • Nuclear Engineering and Technology
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    • v.56 no.2
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    • pp.644-654
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    • 2024
  • After the Tohoku earthquake and tsunami (Japan, 2011), regulatory efforts to mitigate external hazards have increased both the safety requirements and the total capital cost of nuclear power plants (NPPs). In these circumstances, identifying not only disaster robustness but also cost-effective capacity setting of NPPs has become one of the most important tasks for the nuclear power industry. A few studies have been performed to relocate the seismic capacity of NPPs, yet the effects of multiple hazards have not been accounted for in NPP capacity optimization. The major challenges in extending this problem to the multihazard dimension are (1) the high computational costs for both multihazard risk quantification and system-level optimization and (2) the lack of capital cost databases of NPPs. To resolve these issues, this paper proposes an effective method that identifies the optimal multihazard capacity of NPPs using a multi-objective genetic algorithm and the two-stage direct quantification of fault trees using Monte Carlo simulation method, called the two-stage DQFM. Also, a capacity-based indirect capital cost measure is proposed. Such a proposed method enables NPP to achieve safety and cost-effectiveness against multi-hazard simultaneously within the computationally efficient platform. The proposed multihazard capacity optimization framework is demonstrated and tested with an earthquake-tsunami example.

Estimating Parameters in Muitivariate Normal Mixtures

  • Ahn, Sung-Mahn;Baik, Sung-Wook
    • Communications for Statistical Applications and Methods
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    • v.18 no.3
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    • pp.357-365
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    • 2011
  • This paper investigates a penalized likelihood method for estimating the parameter of normal mixtures in multivariate settings with full covariance matrices. The proposed model estimates the number of components through the addition of a penalty term to the usual likelihood function and the construction of a penalized likelihood function. We prove the consistency of the estimator and present the simulation results on the multi-dimensional nor-mal mixtures up to the 8-dimension.

Universal learning network-based fuzzy control

  • Hirasawa, K.;Wu, R.;Ohbayashi, M.
    • 제어로봇시스템학회:학술대회논문집
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    • 1995.10a
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    • pp.436-439
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    • 1995
  • In this paper we present a method to construct fuzzy model with multi-dimension input membership function, which can construct fuzzy inference system on one node of the network directly. This method comes from a common framework called Universal Learning Network (ULN). The fuzzy model under the framework of ULN is called Universal Learning Network-based Fuzzy Inference System (ULNFIS), which possesses certain advantages over other networks such as neural network. We also introduce how to imitate a real system with ULN and a control scheme using ULNFIS.

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3-D Topology Optimization of Magneto-Thermal Systems (자계-열계 시스템의 3차원 위상최적설계)

  • Shim, Ho-Kyung;Wang, Se-Myung
    • Proceedings of the KIEE Conference
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    • 2005.07b
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    • pp.939-941
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    • 2005
  • This research presents a 3D multi-objective approach regarding both magnetic and thermal characteristics associated with design of C-core actuator. The adjoint variable topology sensitivity equations are derived using the continuum method for three dimension. The sensitivity is verified using the Finite Difference Method(FDM). Convection interpolation function is proposed for density method of topologies such that convection term can be taken into consideration for practical design in the process of the optimization.

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Hilbert Cube for Spatio-Temporal Data Warehouses (시공간 데이타웨어하우스를 위한 힐버트큐브)

  • 최원익;이석호
    • Journal of KIISE:Databases
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    • v.30 no.5
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    • pp.451-463
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    • 2003
  • Recently, there have been various research efforts to develop strategies for accelerating OLAP operations on huge amounts of spatio-temporal data. Most of the work is based on multi-tree structures which consist of a single R-tree variant for spatial dimension and numerous B-trees for temporal dimension. The multi~tree based frameworks, however, are hardly applicable to spatio-temporal OLAP in practice, due mainly to high management cost and low query efficiency. To overcome the limitations of such multi-tree based frameworks, we propose a new approach called Hilbert Cube(H-Cube), which employs fractals in order to impose a total-order on cells. In addition, the H-Cube takes advantage of the traditional Prefix-sum approach to improve Query efficiency significantly. The H-Cube partitions an embedding space into a set of cells which are clustered on disk by Hilbert ordering, and then composes a cube by arranging the grid cells in a chronological order. The H-Cube refines cells adaptively to handle regional data skew, which may change its locations over time. The H-Cube is an adaptive, total-ordered and prefix-summed cube for spatio-temporal data warehouses. Our approach focuses on indexing dynamic point objects in static spatial dimensions. Through the extensive performance studies, we observed that The H-Cube consumed at most 20% of the space required by multi-tree based frameworks, and achieved higher query performance compared with multi-tree structures.

A Study on the Characteristics and Use of Multi-Visual Expression Techniques in Architectural Design Process of Zaha Hadid (자하 하디드의 건축디자인과정에서 다시점 표현기법의 활용과 특성에 관한 연구)

  • 박영호
    • Korean Institute of Interior Design Journal
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    • v.13 no.5
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    • pp.56-65
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    • 2004
  • This study divides the expression techniques of Zaha Hadid into various types who has manipulated her targeted drawings as her unique design tools in the process of architectural design, analyzes them in terms of the vanishing point, visual point for observation and object of observation and attempts to figure out how the multi-visual expression is applied in the conception of form and space and method of observation. By doing so, this study will suggest the characteristics of the expression techniques using multi-visual. Through the above study, the utilization and characteristics of multi-visual expression of the architecture design process of Zaha Hadid are summarized as follows. Firstly, Zaha Hadid utilizes the strained multi-visual perspective technique which can look out over the interaction between masses simultaneously at multi-angles by changing a perspective drawing of vanishing point 1, 2, and 3. Secondly, it utilizes a landscape perspective technique and embodies an Idea of landscape's spatial arrangement through it as the means to search a dynamic relation of architecture, city, land, and space. Thirdly, there is a projected expression using X-ray perspective technique to make the relations between inside and outside of building to three-dimension volume. Zaha Hadid has used the expression techniques using multi-visual by utilizing various points and has developed and used them as her creative tools for idea. By means of escaping from the expression techniques of simple revival, she has used a new expression technique that can represent recognized space. In the past, the content could change the expression techniques in architecture; however, the liberation of architectural expression techniques can change the content in modern times when require new attempts.

Clipping Value Estimate for Iterative Tree Search Detection

  • Zheng, Jianping;Bai, Baoming;Li, Ying
    • Journal of Communications and Networks
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    • v.12 no.5
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    • pp.475-479
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    • 2010
  • The clipping value, defined as the log-likelihood ratio (LLR) in the case wherein all the list of candidates have the same binary value, is investigated, and an effective method to estimate it is presented for iterative tree search detection. The basic principle behind the method is that the clipping value of a channel bit is equal to the LLR of the maximum probability of correct decision of the bit to the corresponding probability of erroneous decision. In conjunction with multilevel bit mappings, the clipping value can be calculated with the parameters of the number of transmit antennas, $N_t$; number of bits per constellation point, $M_c$; and variance of the channel noise, $\sigma^2$, per real dimension in the Rayleigh fading channel. Analyses and simulations show that the bit error performance of the proposed method is better than that of the conventional fixed-value method.