• Title/Summary/Keyword: Data cube

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Efficient Processing method of OLAP Range-Sum Queries in a dynamic warehouse environment (다이나믹 데이터 웨어하우스 환경에서 OLAP 영역-합 질의의 효율적인 처리 방법)

  • Chun, Seok-Ju;Lee, Ju-Hong
    • The KIPS Transactions:PartD
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    • v.10D no.3
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    • pp.427-438
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    • 2003
  • In a data warehouse, users typically search for trends, patterns, or unusual data behaviors by issuing queries interactively. The OLAP range-sum query is widely used in finding trends and in discovering relationships among attributes in the data warehouse. In a recent environment of enterprises, data elements in a data cube are frequently changed. The problem is that the cost of updating a prefix sum cube is very high. In this paper, we propose a novel algorithm which reduces the update cost significantly by an index structure called the Δ-tree. Also, we propose a hybrid method to provide either approximate or precise results to reduce the overall cost of queries. It is highly beneficial for various applications that need quick approximate answers rather than time consuming accurate ones, such as decision support systems. An extensive experiment shows that our method performs very efficiently on diverse dimensionalities, compared to other methods.

Discovery-Driven Exploration Method in Lung Cancer 2-DE Gel Images Using the Data Cube (데이터 큐브를 이용한 폐암 2-DE 젤 이미지에서의 예외 탐사)

  • Shim, Jung-Eun;Lee, Won-Suk
    • The KIPS Transactions:PartD
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    • v.15D no.5
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    • pp.681-690
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    • 2008
  • In proteomics research, the identification of differentially expressed proteins observed under specific conditions is one of key issues. There are several ways to detect the change of a specific protein's expression level such as statistical analysis and graphical visualization. However, it is quiet difficult to handle the spot information of an individual protein manually by these methods, because there are a considerable number of proteins in a tissue sample. In this paper, using database and data mining techniques, the application plan of OLAP data cube and Discovery-driven exploration is proposed. By using data cubes, it is possible to analyze the relationship between proteins and relevant clinical information as well as analyzing the differentially expressed proteins by disease. We propose the measure and exception indicators which are suitable to analyzing protein expression level changes are proposed. In addition, we proposed the reducing method of calculating InExp in Discovery-driven exploration. We also evaluate the utility and effectiveness of the data cube and Discovery-driven exploration in the lung cancer 2-DE gel image.

Replacement Condition Detection of Railway Point Machines Using Data Cube and SVM (데이터 큐브 모델과 SVM을 이용한 철도 선로전환기의 교체시기 탐지)

  • Choi, Yongju;Oh, Jeeyoung;Park, Daihee;Chung, Yongwha;Kim, Hee-Young
    • Smart Media Journal
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    • v.6 no.2
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    • pp.33-41
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    • 2017
  • Railway point machines act as actuators that provide different routes to trains by driving switchblades from the current position to the opposite one. Since point failure caused by the aging effect can significantly affect railway operations with potentially disastrous consequences, replacement detection of point machine at an appropriate time is critical. In this paper, we propose a replacement condition detection method of point machine in railway condition monitoring systems using electrical current signals, after analyzing and relabeling domestic in-field replacement data by means of OLAP(On-Line Analytical Processing) operations in the multidimensional data cube into "does-not-need-to-be replaced" and "needs-to-be-replaced" data. The system enables extracting suitable feature vectors from the incoming electrical current signals by DWT(Discrete Wavelet Transform) with reduced feature dimensions using PCA(Principal Components Analysis), and employs SVM(Support Vector Machine) for the real-time replacement detection of point machine. Experimental results with in-field replacement data including points anomalies show that the system could detect the replacement conditions of railway point machines with accuracy exceeding 98%.

Consideration Points for application of KOMPSAT Data to Open Data Cube (다목적실용위성 자료의 오픈 데이터 큐브 적용을 위한 기본 고려사항)

  • LEE, Ki-Won;KIM, Kwang-Seob;LEE, Sun-Gu;KIM, Yong-Seung
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.1
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    • pp.62-77
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    • 2019
  • Open Data Cube(ODC) has been emerging and developing as the open source platform in the Committee on Earth Observation Satellites(CEOS) for the Global Earth Observation System of Systems(GEOSS) deployed by the Group on Earth Observations (GEO), ODC can be applied to the deployment of scalable and large amounts of free and open satellite images in a cloud computing environment, and ODC-based country or regional application services have been provided for public users on the high performance. This study first summarizes the status of ODC, and then presents concepts and some considering points for linking this platform with Korea Multi-Purpose Satellite (KOMPSAT) images. For the reference, the main contents of ODC with the Google Earth Engine(GEE) were compared. Application procedures of KOMPSAT satellite image to implement ODC service were explained, and an intermediate process related to data ingestion using actual data was demonstrated. As well, it suggested some practical schemes to utilize KOMPSAT satellite images for the ODC application service from the perspective of open data licensing. Policy and technical products for KOMPSAT images to ODC are expected to provide important references for GEOSS in GEO to apply new satellite images of other countries and organizations in the future.

A 6 m cube in an atmospheric boundary layer flow -Part 2. Computational solutions

  • Richards, P.J.;Quinn, A.D.;Parker, S.
    • Wind and Structures
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    • v.5 no.2_3_4
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    • pp.177-192
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    • 2002
  • Computation solutions for the flow around a cube, which were generated as part of the Computational Wind Engineering 2000 Conference Competition, are compared with full-scale measurements. The three solutions shown all use the RANS approach to predict mean flow fields. The major differences appear to be related to the use of the standard $k-{\varepsilon}$, the MMK $k-{\varepsilon}$ and the RNG $k-{\varepsilon}$ turbulence models. The inlet conditions chosen by the three modellers illustrate one of the dilemmas faced in computational wind engineering. While all modeller matched the inlet velocity profile to the full-scale profile, only one of the modellers chose to match the full-scale turbulence data. This approach led to a boundary layer that was not in equilibrium. The approach taken by the other modeller was to specify lower inlet turbulent kinetic energy level, which are more consistent with the turbulence models chosen and lead to a homogeneous boundary layer. For the $0^{\circ}$ case, wind normal to one face of the cube, it is shown that the RNG solution is closest to the full-scale data. This result appears to be associated with the RNG solution showing the correct flow separation and reattachment on the roof. The other solutions show either excessive separation (MMK) or no separation at all (K-E). For the $45^{\circ}$ case the three solutions are fairly similar. None of them correctly predicting the high suctions along the windward edges of the roof. In general the velocity components are more accurately predicted than the pressures. However in all cases the turbulence levels are poorly matched, with all of the solutions failing to match the high turbulence levels measured around the edges of separated flows. Although all of the computational solutions have deficiencies, the variability of results is shown to be similar to that which has been obtained with a similar comparative wind tunnel study. This suggests that the computational solutions are only slightly less reliable than the wind tunnel.

Determination of Double-K Fracture Parameters of Concrete Using Split-Tension Cube: A Revised Procedure

  • Pandey, Shashi Ranjan;Kumar, Shailendra;Srivastava, A.K.L.
    • International Journal of Concrete Structures and Materials
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    • v.10 no.2
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    • pp.163-175
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    • 2016
  • This paper presents a revised procedure for computation of double-K fracture parameters of concrete split-tension cube specimen using weight function of the centrally cracked plate of finite strip with a finite width. This is an improvement over the previous work of the authors in which the determination of double-K fracture parameters of concrete for split-tension cube test using weight function of the centrally cracked plate of infinite strip with a finite width was presented. In a recent research, it was pointed out that there are great differences between a finite strip and an infinite strip regarding their weight function and the solution of infinite strip can be utilized in the split-tension specimens when the notch size is very small. In the present work, improved version of LEFM formulas for stress intensity factor, crack mouth opening displacement and crack opening displacement profile presented in the recent research work are incorporated. The results of the double-K fracture parameters obtained using revised procedure and the previous work of the authors is compared. The double-K fracture parameters of split-tension cube specimen are also compared with those obtained for standard three point bend test specimen. The input data required for determining double-K fracture parameters for both the specimen geometries for laboratory size specimens are obtained using well known version of the Fictitious Crack Model.

Field measurement study on snow accumulation process around a cube during snowdrift

  • Wenyong Ma;Sai Li;Xuanyi Zhou;Yuanchun Sun;Zihan Cui;Ziqi Tang
    • Wind and Structures
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    • v.37 no.1
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    • pp.25-38
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    • 2023
  • Due to the complexity and difficulty in meeting the multiphase flow complexity, similarity, and multiscale characteristics, the mechanism of snow drift is so complicated that the snow deposition prediction is still inaccurate and needs to be far improved. Meanwhile, the validation of prediction methods is also limited due to a lack of field-measured data about snow deposition. To this end, a field measurement activity about snow deposition around a cube with time was carried out, and the snow accumulation process was measured under blowing snow conditions in northwest China. The maximum snow depth, snow profile, and variation in snow depth around the cube were discussed and analyzed. The measured results indicated three stages of snow accumulation around the cube. First, snow is deposited in windward, lateral and leeward regions, and then the snow depth in windward and lateral regions increases. Secondly, when the snow in the windward region reaches its maximum, the downwash flow erodes the snow against the front wall. Meanwhile, snow range and depth in lateral regions have a significant increase. Thirdly, a narrow road in the leeward region is formed with the increase in snow range and depth, which results in higher wind speed and reforming snow deposition there. The field measurement study in this paper not only furthers understanding of the snow accumulation process instead of final deposition under complex conditions but also provides an important benchmark for validating prediction methods.

Design and Implementation of multi-dimensional BI System for Information Integration and Analysis in University Administration (대학 행정의 정보통합 및 통계분석을 위한 다차원 BI 시스템의 설계 및 구현)

  • Ji, Keung-yeup;Yang, Hee Sung;Kwon, Youngmi
    • Journal of Korea Multimedia Society
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    • v.19 no.5
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    • pp.939-947
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    • 2016
  • As the number of legacy database systems and the size of data to manipulate have been vastly increased, it has become more difficult and complex to analyze characteristics of data. To improve the efficiency of data analysis and help administrators to make decisions in business life, BI(Business Intelligence) system is used. To construct data warehouse and cube from legacy database systems makes it easy and fast to transform raw data into integrated and categorized meaningful information. In this paper, we built a BI system for an University administration. Several source system databases were integrated to data warehouse to build data cubes. The implemented BI system shows much faster data analysis and reporting ability than the manipulation in legacy systems. It is especially efficient in multi dimensional data analysis, nonetheless in single dimensional analysis.

1H*-tree: An Improved Data Cube Structure for Multi-dimensional Analysis of Data Streams (1H*-tree: 데이터 스트림의 다차원 분석을 위한 개선된 데이터 큐브 구조)

  • XiangRui Chen;YuXiang Cheng;Yan Li;Song-Sun Shin;Dong-Wook Lee;Hae-Young Bae
    • Proceedings of the Korea Information Processing Society Conference
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    • 2008.11a
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    • pp.332-335
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    • 2008
  • In this paper, based on H-tree, which is proposed as the basic data cube structure for multi-dimensional data stream analysis, we have done some analysis. We find there are a lot of redundant nodes in H-tree, and the tree-build method can be improved for saving not only memory, but also time used for inserting tuples. Also, to facilitate more fast and large amount of data stream analysis, which is very important for stream research, H*-tree is designed and developed. Our performance study compare the proposed H*-tree and H-tree, identify that H*-tree can save more memory and time during inserting data stream tuples.

Error Prediction Considering the Measurement Direction in OMM System (OMM 시스템에서 측정방향을 고려한 가공물의 오차평가)

  • 최진필;이상조;권혁동
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2002.05a
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    • pp.632-635
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    • 2002
  • In this paper, a general procedure to determine machine tool errors from the on-machine measurement (OMM) data is described. First, a parameterized error model of a machine tool is illustrated by approximating error components as linear function of axis positions, and a modified error model is proposed which includes backlash effects. To determine the unknown model coefficient vectors of the forward and backward error model, an artifact with 8 cutes is made and calibrated on CMM. Then, lower-left and upper-right cube corners are measured with a touch-trigger probe mounted on the machine tool spindle. Measured error data are used to determine the coefficient vectors. The positioning errors in the XY plane at the fixed z position are simulated for the forward and backward error model.

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