• Journal of the Korean Society for Precision Engineering
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• v.17 no.11
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• pp.176-184
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• 2000

Recently, it becomes a very important issue to consider the mechanical systems such as high-speed vehicle and railway train moving on a flexible beam structure. Using general approach proposed in the first part of this paper, it tis possible to predict planar motion of constrained mechanical system and elastic structure with various kinds of foundation supporting condition. Combined differential-algebraic equations of motion derived from both multibody dynamics theory and Finite Element Method can be analyzed numerically using generalized coordinate partitioning algorithm. To verify the validity of this approach, results from simply supported elastic beam subjected to a moving load are compared with exact solution from a reference. Finally, parameter study is conducted for a moving vehicle model on a simply supported 3-span bridge.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.11
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• pp.165-175
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• 2000

In recent years, it becomes a very important issue to consider the mechanical systems such as high-speed vehicles and railway trains moving on elastic beam structures. In this paper, a general approach, which can predict the dynamic behavior of constrained mechanical system and elastic beam structure, is proposed. Also, various supporting conditions of a foundation support are considered for the elastic beam structures. The elastic structure is assumed to be a nonuniform and linear Bernoulli-Euler beam with proportional damping effect. Combined Differential-Algebraic Equations of motion are derived using multibody dynamics theory and Finite Element Method. The proposed equations of motion can be solved numerically using generalizd coordinate partitioning method and Predictor-Corrector algorithm, which is an implicit multi-step integration method.

• The Transactions of the Korea Information Processing Society
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• v.4 no.1
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• pp.137-148
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• 1997

Diagnostic problem solving is a major application area of knowledge-based systems research. However, most of the current approaches, both heuristic and model-based, are designed to identify single faults, and do not generalize easily to multiple fault diagnosis without exhibiting exponential behavior in the amount of computation required. In this paper, we employ a decomposition approach based on system configuration to generate an efficient algorithm for multiple fault diagnosis. The basic idea of the algorithm is to reduce the inherent combinatorial explosion that occurs in generating multiple faults by partitioning the circuit into groups that correspond to output measurement points. Rules are multiple faults by partitioning the circuit into groups that correspond to output measurement points. rules are developed for combining candidates from individual groups, and forming consistent sets of minimal candidates.

• Journal of KIISE:Software and Applications
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• v.29 no.3
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• pp.156-166
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• 2002

Decision tree induction is a kind of useful machine learning approach for extracting classification rules from a set of feature-based examples. According to the partitioning style of the feature space, decision trees are categorized into univariate decision trees and multivariate decision trees. Due to observation error, uncertainty, subjective judgment, and so on, real-world data are prone to contain some errors in their feature values. For the purpose of making decision trees robust against such errors, there have been various trials to incorporate fuzzy techniques into decision tree construction. Several researches hove been done on incorporating fuzzy techniques into univariate decision trees. However, for multivariate decision trees, few research has been done in the line of such study. This paper proposes a fuzzy decision tree induction method that builds fuzzy multivariate decision trees named fuzzy oblique decision trees, To show the effectiveness of the proposed method, it also presents some experimental results.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.70-75
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• 2015

In this paper, we explore the efficient processing of continuous range queries over a huge number of moving objects, each of which retrieves the moving objects that are currently located within a geographic query region of interest. The moving objects should continually communicate with the server to report their current locations, so as to keep the results of the continuous range queries up-to-date. However, this increases the server workload and involves a enormous amount of communication as the number of continuous range queries and the moving objects becomes enormous. In this paper, we adopt an approach where we leverage available memory and computational resources of the moving objects in order to resolve these problems. To this end, we propose a query indexing structure, referred to as the Space Partitioning Query Index(SPQI), which enables the server to efficiently cooperate with the moving objects for processing continuous range queries. SPQI improves system performance in terms of server workload and communication cost. Through simulations, we show the superiority of SPQI.

• Annual Conference of KIPS
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• 2016.04a
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• pp.55-58
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• 2016

스카이라인 질의란 다수의 선택지 중 '선호될 만한(preferable)' 선택지를 요청하는 질의이다. 사용자가 검토해야하는 선택지의 수를 대폭 감소시키는 스카이라인 질의는 데이터가 폭증하는 빅데이터 환경에서 매우 유용하게 활용된다. 이러한 배경에서 대용량 데이터에 대한 스카이라인 질의를 분산 병렬 처리하는 기법이 각광을 받고 있으며, 특히 맵리듀스(MapReduce) 기반의 분산 병렬 처리 기법 연구가 활발히 진행 중이다. 맵리듀스 기반 알고리즘의 병렬성 제고를 위해서는 부하 불균등 문제 중복 계산 문제 과다한 네트워크 비용 발생 문제를 해소해야 한다. 최근 각 기반 공간분할 기법을 사용하여 부하 불균등 문제와 중복 계산 문제를 해소하는 맵리듀스 기반 스카이라인 질의 처리 기법이 제안되었으나 해당 기법은 네트워크 비용 관점에서 최적화되어있지 않다. 본 논문에서는 부하 불균등 문제와 중복 계산 문제를 해소하면서도 프루닝을 통해 네트워크 비용 절감 시킬 수 있는 새로운 맵리듀스 기반 병렬 스카이라인 질의 처리 기법인 MR-SEAP(MapReduce sample Skyline object Equality Angular Partitioning)을 제안한다. MR-SEAP에서는 데이터를 샘플링하여 샘플 스카이라인 객체를 추출한 뒤 해당 객체들을 균등 분배하는 각도를 기준으로 공간을 분할하여 스카이라인 질의를 병렬 계산하되, 샘플 스카이라인을 이용하여 다수의 객체를 사전에 프루닝함으로써 네트워크 비용을 절감한다. 본 논문에서는 다양한 데이터 수량(cardinality) 및 분포(distribution)에 따른 제안 기법의 성능을 실험 평가함으로써 제안 기법의 우수성을 검증한다.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.516-524
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• 2004

In this paper, the initial value problem in clustering using K-means or Fuzzy-c-means is considered to reduce the number of iterations. Conventionally the initial values in clustering using K-means or Fuzzy-c-means are chosen randomly, which sometimes brings the results that the process of clustering converges to undesired center points. The choice of intial value has been one of the well-known subjects to be solved. The system of clustering using K-means or Fuzzy-c-means is sensitive to the choice of intial values. As an approach to the problem, the uniform partitioning method is employed to extract the optimal initial point for each clustering of data. Experimental results are presented to demonstrate the superiority of the proposed method, which reduces the number of iterations for the central points of clustering groups.

• The Mathematical Education
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• v.60 no.1
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• pp.1-19
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• 2021

This study investigates students' conceptions of fractions from a measurement approach while providing a technological environment designed to support students' understanding of the relationships between quantities and adjustable units. 13 third-graders participated in this study and they were involved in a series of measurement tasks through task-based interviews. The tasks were devised to investigate the relationship between units and quantity through manipulations. Screencasting videos were collected including verbal explanations and manipulations. Drawing upon the theory of semiotic mediation, students' constructed concepts during interviews were coded as mathematical words and visual mediators to identify conceptual profiles using a fine-grained analysis. Two students changed their strategies to solve the tasks were selected as a representative case of the two profiles: from guessing to recursive partitioning; from using random units to making a relation to the given unit. Dragging mathematical objects plays a critical role to mediate and formulate fraction understandings such as unitizing and partitioning. In addition, static and dynamic representations influence the development of unit concepts in measurement situations. The findings will contribute to the field's understanding of how students come to understand the concept of fraction as measure and the role of technology, which result in a theory-driven, empirically-tested set of tasks that can be used to introduce fractions as an alternative way.

• Water Engineering Research
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• v.1 no.2
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• pp.137-146
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• 2000

A windows-based software package, named DREDGE, is developed for estimating sediment resuspension and contaminant release during dredging operations. DREDGE allows user to enter the necessary dredge information, site characteristics, operational data, and contaminant characteristics, then calculates an array of concentration using the given values. The program mainly consists of the near-field models, which are obtained empirically, for estimating sediment resuspension and the far-field models, which are obtained analytically, for suspended sediment transport. A linear equilibrium partitioning approach is applied to estimate particulate and dissolved contaminant concentrations. This software package which requires only a minimal amount of data consists of three components; user input, tabular output, and graphical output. Combining the near-field and far-field models into a user-friendly windows-based computer program can greatly save dredge operator's, planners', and regulators' efforts for estimating sediment transports and contaminant distribution.

• Journal of the Korean Chemical Society
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• v.56 no.2
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• pp.195-200
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• 2012

In this study we present a new approach for computing the partial atomic charge derived from the wavefunctions of molecules. This charge, which we call the "y_charge", was calculated by taking into account the energy level and orbital populations in each molecular orbital (MO). The charge calculations were performed in the software, which was developed by us, developed using the C# programming language. Partial atomic charges cannot be calculated directly from quantum mechanics. According to a partitioning function, the electron density of constituent molecular atoms depends on the electrostatic attraction field of the nucleus. Taking into account the Boltzmann population of each MO as a function of its energy and temperature we obtain a formula of partial charges.