• Communications for Statistical Applications and Methods
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• v.30 no.4
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• pp.355-368
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• 2023

This article introduces the R package ELCIC (https://cran.r-project.org/web/packages/ELCIC/index.html), which provides an empirical likelihood-based information criterion (ELCIC) for model selection that includes, but is not limited to, variable selection. The empirical likelihood is a semi-parametric approach to draw statistical inference that does not require distribution assumptions for data generation. Therefore, ELCIC is more robust and versatile in the context of model selection compared to the currently existing information criteria. This paper illustrates several applications of ELCIC, including its use in generalized linear models, generalized estimating equations (GEE) for longitudinal data, and weighted GEE (WGEE) for missing longitudinal data under the mechanisms of missing at random and dropout.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.7
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• pp.633-641
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• 2015

In this study, we proposed a three-dimensional (3D) scanning system based on laser-vision technique and rotary mechanism for automatic 3D model reconstruction. The proposed scanning system consists of a laser projector, a camera, and a turntable. For laser-camera calibration a new and simple method was proposed. 3D point cloud data of the surface of scanned object was fully collected by integrating extracted laser profiles, which were extracted from laser stripe images, corresponding to rotary angles of the rotary mechanism. The obscured laser profile problem was also solved by adding an addition camera at another viewpoint. From collected 3D point cloud data, the 3D model of the scanned object was reconstructed based on facet-representation. The reconstructed 3D models showed effectiveness and the applicability of the proposed 3D scanning system to 3D model-based applications.

• Smart Structures and Systems
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• v.15 no.3
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• pp.645-663
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• 2015

Recently, an indirect displacement estimation method using data fusion of acceleration and strain (i.e., acceleration-strain-based method) has been developed. Though the method showed good performance on beam-like structures, it has inherent limitation in applying to more general types of bridges that may have complex shapes, because it uses assumed analytical (sinusoidal) mode shapes to map the measured strain into displacement. This paper proposes an improved displacement estimation method that can be applied to more general types of bridges by building the mapping using the finite element model of the structure rather than using the assumed sinusoidal mode shapes. The performance of the proposed method is evaluated by numerical simulations on a deck arch bridge model and a three-span truss bridge model whose mode shapes are difficult to express as analytical functions. The displacements are estimated by acceleration-based method, strain-based method, acceleration-strain-based method, and the improved method. Then the results are compared with the exact displacement. An experimental validation is also carried out on a prestressed concrete girder bridge. The proposed method is found to provide the best estimate for dynamic displacements in the comparison, showing good agreement with the measurements as well.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.99-115
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• 2003

In this paper, we present a knowledge-based object-oriented spatial database system called KOBOS. A knowledge-based approach is introduced to the object-oriented spatial database system for data modeling and approximate query answering. For handling the structure of spatial objects and the approximate spatial operators, we propose three levels of object-oriented data model: (1) a spatial shape model; (2) a spatial object model; (3) an internal description model. We use spatial type abstraction hierarchies(STAHs) to provide the range of the approximate spatial operators. We then propose SOQL, a spatial object-oriented query language. SOQL provides an integrated mechanism for the graphical display of spatial objects and the retrieval of spatial and aspatial objects. To support an efficient hybrid query evaluation, we use the top-down spatial query processing method.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.8
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• pp.1-6
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• 2022

This paper uses the gravity model estimated by the random effect method to analyze the factors affecting Vietnam's coffee export turnover for the period 2007-2020 major markets according to statistics from the General Statistics Office and the General Department of Customs. Coffee export turnover was collected from the General Statistics Office, General Department of Customs, and Vietnam Cacao Coffee Association. The authors calculated the price of coffee based on output and export value from data on coffee export turnover; the authors calculated the economic gap based on population and Gross Domestic Product data (reference: geographic distance metrics on the website: http://www.distancefromto.net/countries.php) and other data was collected based on the databases of the Food and Agriculture Organization of the United Nations, the International Monetary Fund, and World Bank organizations. The results of the study show that from 2007 to 2020, the factors of Vietnam's export price of coffee, geographical distance, Gross Domestic Product of the importing country and Gross Domestic Product of Vietnam, the population of Vietnam, the economic gap between Vietnam and the importing country, the openness of the economy, all have an impact on Vietnam's coffee export turnover. Finally, some conclusions about the policy's impact are made based on the empirical results of the paper.

• Journal of Forest and Environmental Science
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• v.39 no.4
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• pp.213-224
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• 2023

As abnormal weather events due to climate change continue to rise, landslide damage is also increasing. Given the substantial time and financial resources required for post-landslide recovery, it becomes imperative to formulate a proactive response plan. In this regard, landslide susceptibility analysis has emerged as a valuable tool for establishing preemptive measures against landslides. Accordingly, this study conducted an annual landslide susceptibility analysis using the history of landslides that occurred over many years in the Jeolla region, and analyzed areas with a high potential for landslides in the Jeolla region. The analysis employed an ensemble model that amalgamated 10 data-based models, aiming to mitigate uncertainties associated with a single-model approach. Furthermore, based on the cumulative data regarding landslide susceptible areas, this research identified regions vulnerable to recurring landslide damage in Jeolla region and proposed specific strategies for utilizing this information at various levels, including local government initiatives, adaptation plan development, and development approval processes. In particular, this study outlined approaches for local government utilization, the determination of adaptation plan types, and considerations for development permits. It is anticipated that this research will serve as a valuable opportunity to underscore the significance of information concerning regions vulnerable to recurring landslide damage.

• Communications for Statistical Applications and Methods
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• v.24 no.1
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• pp.97-113
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• 2017

This paper proposes a method for sufficient dimension reduction (SDR) of mixture data. We consider mixture data containing more than one component that have distinct central subspaces. We adopt an approach of a model-based sliced inverse regression (MSIR) to the mixture data in a simple and intuitive manner. We employed mixture probabilistic principal component analysis (MPPCA) to estimate each central subspaces and cluster the data points. The results from simulation studies and a real data set show that our method is satisfactory to catch appropriate central spaces and is also robust regardless of the number of slices chosen. Discussions about root selection, estimation accuracy, and classification with initial value issues of MPPCA and its related simulation results are also provided.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.05b
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• pp.154-158
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• 2003

RUP의 Unified Process Model에는 Use Case Model, Analysis Model, Design Model, Deployment Model, Implementation model, Test Model의 6가지 모델이 있다. 이 모델들은 모두 일관성이 있다. 한 모델에서 나오는 요소들은 전, 후 단계에서 다른 모델들과 Trace Dependencies를 갖는다. 이러한 관계들은 각각의 요소들 사이의 진행, 기록 관계를 나타낸다 그러나 일반적인 데이터간의 관계와 데이터 모델 설계는 이러한 관계없이 설계되어져 전체적인 일관성을 이루지 못 하였다 본 논문에서는 이러한 관계를 유지하면서 요구사항에 맞는 데이터 모델을 설계하고자 한다. 따라서 본 논문에서는 대학 종합정보시스템 구축의 일부분인 자산관리 시스템을 분석하여 데이터 모델을 제시한다.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.377-383
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• 2003

In this paper, we consider two components system in which the lifetimes follow the bivariate Pareto model with random censored data. We assume that the censoring time is independent of the lifetimes of the two components. We develop large sample tests for testing independence between two components. Also we present simulated study which is the test based on asymptotic normal distribution in testing independence.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.11-16
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• 2007

Since the seminal work of Engle (1982), many researchers and practitioners have developed ARCH-type models to deal with volatility modelling, which, for instance, is crucial to perform the task of derivative pricing, measuring risk, and risk hedging. In this paper, we base the GARCH(1,1) model to analyze the KOSPI200 data, and perform the CUSUM test for detecting parameter changes in the GARCH model. It is shown that the data suffers from a parameter change.