• Title/Summary/Keyword: Multidimensional Data Model

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A Study on the Effective Spatial Data Warehouse (효율적인 공간 데이타 웨어하우스에 관한 연구)

  • 이기영
    • Journal of the Korea Society of Computer and Information
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    • v.3 no.4
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    • pp.126-131
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    • 1998
  • Spatial data warehouse, whose importance is being increased, is composed of huge amounts of historical spatial data for organizational decision making and it also allows users to obtain useful geospatial information through analyzing and summmarizing spatial data. In this paper, we survey effective spatial multidimensional model which is based on virtual scenario for spatial data warehouse modelling. Therefore, we describe spatial multidimensional analytical query which provide multiple analytical functions according tom user's requests.

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Web Information Extraction and Multidimensional Analysis Using XML (XML을 이용한 웹 정보 추출 및 다차원 분석)

  • Park, Byung-Kwon
    • Journal of Korea Multimedia Society
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    • v.11 no.5
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    • pp.567-578
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    • 2008
  • For analyzing a huge amount of web pages available in the Internet, we need to extract the encoded information in web pages. In this paper, we propose a method to extract and convert web information from web pages into XML documents for multidimensional analysis. For extracting information from web pages, we propose two languages: one for describing web information extraction rules based on the object-oriented model, and another for describing regular expressions of HTML tag patterns to search for target information. For multidimensional analysis on XML documents, we propose a method for constructing an XML warehouse and various XML cubes from it like the way we do for relational data. Finally, we show the validness of our method through the application to US patent web pages.

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A Hybrid Multi-Level Feature Selection Framework for prediction of Chronic Disease

  • G.S. Raghavendra;Shanthi Mahesh;M.V.P. Chandrasekhara Rao
    • International Journal of Computer Science & Network Security
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    • v.23 no.12
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    • pp.101-106
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    • 2023
  • Chronic illnesses are among the most common serious problems affecting human health. Early diagnosis of chronic diseases can assist to avoid or mitigate their consequences, potentially decreasing mortality rates. Using machine learning algorithms to identify risk factors is an exciting strategy. The issue with existing feature selection approaches is that each method provides a distinct set of properties that affect model correctness, and present methods cannot perform well on huge multidimensional datasets. We would like to introduce a novel model that contains a feature selection approach that selects optimal characteristics from big multidimensional data sets to provide reliable predictions of chronic illnesses without sacrificing data uniqueness.[1] To ensure the success of our proposed model, we employed balanced classes by employing hybrid balanced class sampling methods on the original dataset, as well as methods for data pre-processing and data transformation, to provide credible data for the training model. We ran and assessed our model on datasets with binary and multivalued classifications. We have used multiple datasets (Parkinson, arrythmia, breast cancer, kidney, diabetes). Suitable features are selected by using the Hybrid feature model consists of Lassocv, decision tree, random forest, gradient boosting,Adaboost, stochastic gradient descent and done voting of attributes which are common output from these methods.Accuracy of original dataset before applying framework is recorded and evaluated against reduced data set of attributes accuracy. The results are shown separately to provide comparisons. Based on the result analysis, we can conclude that our proposed model produced the highest accuracy on multi valued class datasets than on binary class attributes.[1]

An Analysis of Multidimensional Productivity for the Shipbuilding Performance (조선 성과 측정을 위한 다차원 생산성의 분석)

  • Kim, Yearnmin
    • Korean Management Science Review
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    • v.34 no.2
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    • pp.57-66
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    • 2017
  • The purpose of this study is to analyze the multidimensional productivity of the shipbuilding performance and to explain the role of different factors, such as man-hour, dock period, number of building block, launching process rate, automatic welding percent, and drawing fault rate which are important production-related variables in most shipbuilding companies. The shipbuilding productivity is obtained using Data Envelopment Analysis (DEA) approach. Then, a Tobit model is considered to measure the influence of different factors on the measured productivity. The results reveal that this productivity measure can substitute a representative shipbuilding productivity index (CGT/man-hour) in shipbuilding industries. Also, this multidimensional productivity analysis using DEA and Tobit reveals complex relationships between production-related variables and CGT and sale.

Multidimensional Engine Modeling: NO and Soot Emissions in a Diesel Engine with Exhaust Gas Recirculation

  • Kim, Hongsuk;Nakwon Sung
    • Journal of Mechanical Science and Technology
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    • v.15 no.8
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    • pp.1196-1204
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    • 2001
  • The effects of EGR(Exhaust Gas Recirculation) on heavy-duty diesel engine performance, NO and soot emissions were numerically investigated using the modified KIVA-3V code. For the fuel spray, the atomization model based on the linear stability analysis and spray wall impingement model were developed for the KIVA-3V code. The Zeldovich mechanism for the formation of nitric oxide and the soot model suggested by Hiroyasu et al. were used to predict the diesel emissions. In this paper, the computational results of fuel spray, cylinder pressure, and emissions were compared with experimental data, and the optimum EGR rates were sought from the NO and soot emissions trade-off. The results showed that the EGR is effective in suppressing NO but the soot emission was increased considerably by EGR. Using cooled EGR, soot emission could be enhanced without worsening of NO.

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An Approximate Query Answering Method using a Knowledge Representation Approach (지식 표현 방식을 이용한 근사 질의응답 기법)

  • Lee, Sun-Young;Lee, Jong-Yun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.8
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    • pp.3689-3696
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    • 2011
  • In decision support system, knowledge workers require aggregation operations of the large data and are more interested in the trend analysis rather than in the punctual analysis. Therefore, it is necessary to provide fast approximate answers rather than exact answers, and to research approximate query answering techniques. In this paper, we propose a new approximation query answering method which is based on Fuzzy C-means clustering (FCM) method and Adaptive Neuro-Fuzzy Inference System (ANFIS). The proposed method using FCM-ANFIS can compute aggregate queries without accessing massive multidimensional data cube by producing the KR model of multidimensional data cube. In our experiments, we show that our method using the KR model outperforms the NMF method.

Implementation of the OLAP-based Subway Passenger Transit Pattern Analysis System (OLAP을 활용한 지하철 인구이동 맵 생성에 관한 연구)

  • Cho, Jae-Hee;Seo, Il-Jung
    • Information Systems Review
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    • v.7 no.1
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    • pp.65-80
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    • 2005
  • The Seoul Metropolitan Subway Corporation (SMS) and the Seoul Metropolitan Rapid Transit Corporation (SMRT), which manage the city's eight subway lines, are intending to overcome their operational inefficiencies. The two investigators of the paper realize with emphasis that it is essential for the two subway authorities to analyze subway transit data prior to put policies and plans into practice. In this paper, the investigators propose a new, and an intuitive, way of analyzing subway passenger transit patterns. To achieve this goal, they have implemented a data mart by blending the "Pass Card" log data into the multidimensional model. The subway passenger's transit patterns and the practical implications of this system are also investigated.

A Study on the Estimation of Limits to Life Expectancy (한국인 기대여명의 한계추정에 관한 연구)

  • 천성수;김정근
    • Korea journal of population studies
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    • v.16 no.2
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    • pp.65-83
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    • 1993
  • The purpose of this study is estimate limits of Korean life expectancy at birth by 'Gompertz growth curse Model', 'Cause-Elimination Model' and Multidimensional models of Senescencee and Mortality'. Data used in Gompertz curve were obtained from all life tables published from 1905 to 1990 in Korea, and life expectancies at birth of eighteen groups were selected at five-year interval in consideration of time-series changes. Data used in Cause-Elimination Model are 'Cause of Death statistics in 1991' published in 1992 by National Bureau of Statistics of Korea and 'life table of 1989' published in 1990 by National Bureau of Statistics, Economic Planning Board of Korea. The materials are all classifiable death data, 119, 253 cases of male and 82, 420 cases of female, which is from 1991 Causes of Death statistics. The cases of death analyzed belong to one of 8 categories; i.e., Infectious and Parasitic Diseases(001-139; with notation of Infectious Diseases), Malignant Neoplasms(140-208), Hypertensive Diseases(401-405), Ischemic Heart Dieases and Diseases of Pulmonary Circulation and Other Forms of Heart Diseases(410-429;with notation of Heart Disease), Cerebrovascular Diseases(430-438), Chronic Liver Diseases and Cirrhosis(571; with notation of Liver Diseases), Injury and Poisoning(800-999) and all other disease. Data used in 'Multidimensional models of senescence and mortality' were life table of 1989 published by National Bureau of statistics, Economic Planning Board of Korea and life table of 1970, 1978-79, 1983, 1985 and 1987. The major findings may be summarised as follows: 1. Estimate equations of Gompertz growth curve using life expectancy at birth during the 1905-1990 period are as the following. Male : y = 88.047697 $\times$ $0.199690^{0.903381x}$ Female : y = 95.632828 $\times$ $0.199690^{0.903381x}$ Limits of life expectancy at birth, which were estimated by Gompertz growth curve, are 88.05 for male and 95.63 for female. 2. The effect on life expectancy at birth eliminationg all causes death is 14.04 years(for male) and 10.86 years(for female). Astonishingly, eliminating the malignant neoplasms increase life expectancy at birth by 2.85 years for male 2.03 years for female in 1991. In table 8 we show the effect on life expectancy at birth of separately eliminating each of the 8 categorical causes of death. The theoretical limit to life expectancy by Cause-Elimination Model is 80.96 for male and 85.82 for female. 3. If the same rate of delay [0.376 year(male), 0.435 year(femable) per calendar year] continued, then life expectancy at birth would reach 74.82(male) years and 84, 10(female) years in 2010. With 14.04-years(male) and 10.86-years(female) effect attributable in 2010 would be 88.86 years(male) and 94.96(femable) years. 4. 'Multidimensional models of senescence and death' permits calculations of the value of the attribution coefficient (B), percent of loss per year of physiologic function. The results of Ro and B during the 1970-1989 period are listed in table 9. Estimate of limit to Korean life expectancy at birth by 'Multidimensional models of senescence and death' is 99.47 years for male and 104.74 years for female in 1989.

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VRTEC : Multi-step Retrieval Model for Content-based Video Query (VRTEC : 내용 기반 비디오 질의를 위한 다단계 검색 모델)

  • 김창룡
    • Journal of the Korean Institute of Telematics and Electronics T
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    • v.36T no.1
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    • pp.93-102
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    • 1999
  • In this paper, we propose a data model and a retrieval method for content-based video query After partitioning a video into frame sets of same length which is called video-window, each video-window can be mapped to a point in a multidimensional space. A video can be represented a trajectory by connection of neighboring video-window in a multidimensional space. The similarity between two video-windows is defined as the euclidean distance of two points in multidimensional space, and the similarity between two video segments of arbitrary length is obtained by comparing corresponding trajectory. A new retrieval method with filtering and refinement step if developed, which return correct results and makes retrieval speed increase by 4.7 times approximately in comparison to a method without filtering and refinement step.

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A Multidimensional Simulation of Swirl Flow and Turbulent Combustion in a Cylinder of SI Engine (전기점화 기관의 선회 유동 및 연소에 관한 수치해석)

  • 정진은;김응서
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.16 no.9
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    • pp.1744-1759
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    • 1992
  • A multidimensional simulation of turbulent flow and combustion with swirl in the cylinder of SI engine is implemented to clarify the effects of swirl. present simulation employs the ICED-ALE numerical technique, the skew-upwind difference scheme, a modified k_.epsilon. turbulence model, a combustion model of Arrhenius type and turbulence-mixing-control type. First, the calculations for swirling flow in an axisymmetric cylinder are carried out. The results are compared with the experimental data to validate the numerical analysis. Second, the calculations for intake, compression and combustion processes in an axisymmetric cylinder are performed. The effects of swirl on turbulent flow and combustion are examined through the parametric study of swirl number 0.0, 0.6, 1.2 and 2.4. As a result, it is numerically shown that the turbulent kinetic energy and the swirl velocity, which are produced during the intake process, affect the combustion process.