• Title/Summary/Keyword: Snowflake

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Design of Snowflake schema concept using Drill-across Operator (Drill-across연산자를 이용한 Snowflake schema 개념 설계)

  • 김경주;오근탁;이윤배
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2004.05b
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    • pp.354-357
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    • 2004
  • Data warehouse is subject-oriented, integrated, non-volatiled data, and it used for OLAP(On-Line Analytical Processing) the extraction of information from making decision processing. In the present, lots of study have been devoted to multidimensional modeling between OLAP operator and star schema. In this paper, the design of using the snowflake schema for object-oriented conceptual relation is more extended than using drill-across operator. The object-oriented relation schema which was not applicable has been improved through the design.

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Design of a Dual-band Snowflake-Shaped Microstrip patch Antenna With Short-pin For 5.2/5.8 GHz WLAN System (WLAN System을 위한 Short-Pin을 갖는 Snowflake 모양의 Dual-band(5.2/5.8 GBz) 마이크로스트립 패치 안테나 설계 및 제작)

  • Song, Jun-Sung;Choi, Sun-Ho;Lee, Hwa-Choon;Kwak, Kyung-Sup
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.4A
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    • pp.324-329
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    • 2009
  • In this paper, a novel Snowflake-shaped microstrip patch antenna for application in the WLAN(5.2/5.8GHz) band is designed and fabricated. The size of antenna is $21.2{\times}16mm^2$ and substrate is used Taconic-RF30. To obtain sufficient bandwidth in Return loss <-10dB and dual resonance characteristic, the Short-pin is inserted on the patch and the coaxial probe source is used. The measured results of fabricated antenna show 220MHz and 135MHz bandwidth in Return loss <-10dB referenced to the WLAN(5.2/5.8GHz) band. The measured antenna gain is $4.7{\sim}6.9dBi$ in the WLAN(5.2/5.8GHz) band. The experimental 3-dB beam width in I-plane and H-plane are $73.2^{\circ}/82.75^{\circ}$ for 5.1500Hz, $74.56^{\circ}/83.63^{\circ}$ for 5.3500Hz, and $86.24^{\circ}/85.15^{\circ}$ for 5.7850Hz, respectively.

UML based Design of OLAP Meta Data Diagram Model (UML 기반 OLAP 메타 데이터의 다이어그램 모델 설계)

  • Kim Kyung-ju;Lee Yun-bae
    • Proceedings of the Korea Information Processing Society Conference
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    • 2004.11a
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    • pp.133-136
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    • 2004
  • 데이터 웨어하우스(Data Warehouse : DW)는 데이터베이스에 저장되어 있는 데이터를 신속한 의사 결정 지원을 위해 최종 사용자가 여러 곳의 기업 내에 흩어져 있는 방대한 데이터를 손쉽고 빠르게 접근할 수 있도록 활용되고 있다. 현재 데이터 웨어하우스의 중요성이 부각되고 있는 가운데 온라인 분석 처리(On Line Analytical Processing : OLAP) 시스템이 데이터 웨어하우스 안에서 활용되고 발전되고 있다. 기존 연구에서는 서로 다른 OLAP 제품에서 공통으로 사용할 수 있는 모델을 적용하여 OLAP 메타데이터 교환 시스템을 설계해왔다. 그러나 본 논문에서는 서로 다른 OLAP 제품을 공통으로 사용할 수 있는 질의 언어 시스템 설계 전 단계인 논리적 설계를 UML snowflake 다이어그램을 이용하여 설계 하였다. 실험결과, XML 문서의 변환된 OLAP 메타 데이터를 이용하여 UML snowflake 다이어그램 설계를 통해 통합된 OLAP 제품의 XML 문서 구조가 논리적으로 설계되어 메타 데이터가 통합됨을 알 수가 있다.

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A Design and Practical Use of Spatial Data Warehouse for Spatiall Decision Making (공간적 의사결정을 위한 공간 데이터 웨어하우스 설계 및 활용)

  • Park Ji-Man;Hwang Chul-sue
    • Spatial Information Research
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    • v.13 no.3 s.34
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    • pp.239-252
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    • 2005
  • The major reason that spatial data warehousing has attracted a great deal of attention in business GIS in recent years is due to the wide availability of huge amount of spatial data and the imminent need for fuming such data into useful geographic information. Therefore, this research has been focused on designing and implementing the pilot tested system for spatial decision making. The purpose of the system is to predict targeted marketing area by discriminating the customers by using both transaction quantity and the number of customer using credit card in department store. Moreover, the pilot tested system of this research provides OLAP tools for interactive analysis of multidimensional data of geographically various granularities, which facilitate effective spatial data mining. focused on the analysis methodology, the case study is aiming to use GIS and clustering for knowledge discovery. Especially, the importance of this study is in the use of snowflake schema model capabilities for GIS framework.

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Quantitative Analysis of Snow Particles Using a Multi-Angle Snowflake Camera in the Yeongdong Region (영동지역에서 눈결정 카메라를 활용한 눈결정의 정량 분석)

  • Kim, Su-Hyun;Ko, Dae-Hong;Seong, Dae-Kyung;Eun, Seung-Hee;Kim, Byung-Gon;Kim, Baek-Jo;Park, Chang-Geun;Cha, Ju-Wan
    • Atmosphere
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    • v.29 no.3
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    • pp.311-324
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    • 2019
  • We employed a Multi-Angle Snowflake Camera (MASC) to quantitatively analyze snow particles at the ground level in the Yeongdong region of Korea. The MASC captures high-resolution photographs of hydrometeors from three angles and simultaneously measures fallspeed. Based on snowflake images of the several episodes in 2017 and 2018, we derived statistics of size, aspect ratio, orientation, complexity, and fallspeed of snow crystals, which generally showed similar characteristics to the previous studies in other regions of the world. Dominant snow crystal habits of January 22, 2018 generated by northerly were melted aggregates when 850 hPa temperature was about $-6{\sim}-8^{\circ}C$. Average fallspeed of snow crystals was $1.0m\;s^{-1}$ though its size gradually increased as temperature decreased. Another snowfall event (March 8, 2018) was driven by the baroclinic instability as accompanied with a deep trough. Snow crystal habits were largely rimed aggregates (complexity ~1.8) and melting particles of dark images. Meanwhile, in the extreme snowfall event whose snow rate was greater than $10cm\;hr^{-1}$ on January 20, 2017, main snow crystals appeared to be heavily rimed particles with relatively smaller size when convective clouds developed vertically up to 9 km in association with tropopause folding. MASC also could successfully measure a decrease in snow crystal size and an increase in riming degree after AgI seeding at Daegwallyeong on March 14, 2017.

Analysis of Airline Network using Incheon and Narita Passenger Flight Origin-Destination Data (인천/나리타 공항의 여객기 출.도착 데이터를 이용한 항공노선 분석 연구)

  • Baik, Euiyoung;Cho, Jaehee
    • Journal of Information Technology Applications and Management
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    • v.20 no.1
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    • pp.87-106
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    • 2013
  • This study is to explore the airline network patterns of Incheon and Narita International Airports using passenger flight departure and arrival data of the two airports. The so-called Origin-Destination data is collected from the airports' websites and some of the important data items are flight number, city of origin, destination city, departure/arrival time, number of flights, and delay time. A snowflake schema dimensional model is proposed and implemented. Tableau Public, a well-known visual analytic tool, is used to connect the dimensional model and played an important role in navigating the data space to find interesting and visual patterns among corresponding airports and airlines. For the efficiency of analyzing this spacious data mart, data visualization method was used. Four types of visualization method proposed by Yau was used; visualizing patterns over time, visualizing proportions, visualizing relationships, and visualizing spatial relationships. The strength of connectivity of each flight segments is calculated to evaluate the degree of globalization of Seoul and Tokyo. We anticipate that various patterns and new findings produced by the data mart would provide airline managers, airport authorities, and policy makers in the field of travel and transportation with insightful information.

Design and Implementation of Multidimensional Data Model for OLAP Based on Object-Relational DBMS (OLAP을 위한 객체-관계 DBMS 기반 다차원 데이터 모델의 설계 및 구현)

  • 김은영;용환승
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.6A
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    • pp.870-884
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    • 2000
  • Among OLAP(On-Line Analytical Processing) approaches, ROLAP(Relational OLAP) based on the star, snowflake schema which offer the multidimensional analytical method has performance problem and MOLAP (Multidimensional OLAP) based on Multidimensional Database System has scalability problem. In this paper, to solve the limitaions of previous approaches, design and implementation of multidimensional data model based on Object-Relation DBMS was proposed. With the extensibility of Object-Relation DBMS, it is possible to advent multidimensional data model which more expressively define multidimensional concept and analysis functions that are optimized for the defined multidimensional data model. In addition, through the hierarchy between data objects supported by Object-Relation DBMS, the aggregated data model which is inherited from the super-table, multidimensional data model, was designed. One these data models and functions are defined, they behave just like a built-in function, w th the full performance characteristics of Object-Relation DBMS engine.

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Self Maintainable Data Warehouse Views for Multiple Data Sources (다중 데이터 원천을 가지는 데이터웨어하우스 뷰의 자율갱신)

  • Lee, Woo-Key
    • Asia pacific journal of information systems
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    • v.14 no.3
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    • pp.169-187
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    • 2004
  • Self-maintainability of data warehouse(DW) views is an ability to maintain the DW views without requiring an access to (i) any underlying databases or (ii) any information beyond the DW views and the delta of the databases. With our proposed method, DW views can be updated by using only the old views and the differential files such as different files, referential integrity differential files, linked differential files, and backward-linked differential files that keep the truly relevant tuples in the delta. This method avoids accessing the underlying databases in that the method achieves self-maintainability even in preparing auxiliary information. We showed that out method can be applicable to the DW views that contain joins over relations in a star schema, a snowflake schema, or a galaxy schema.