• Journal of Institute of Control, Robotics and Systems
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• v.21 no.4
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• pp.321-329
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• 2015

This paper addresses a new algorithm for a stereo visual odometry to measure the ego-motion of a vehicle. The new algorithm introduces an inlier grouping method based on Delaunay triangulation and vanishing point computation. Most visual odometry algorithms rely on RANSAC in choosing inliers. Those algorithms fluctuate largely in processing time between images and have different accuracy depending on the iteration number and the level of outliers. On the other hand, the new approach reduces the fluctuation in the processing time while providing accuracy corresponding to the RANSAC-based approaches.

• Journal of the Korean Statistical Society
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• v.14 no.2
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• pp.63-75
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• 1985

This paper considers a statistical calibration problem in which the standard as wel as the nonstandard measurement is subject to error. Since the classicla approach cannot handle this situation properly, a functional relationship model with additional feature of prediction is proposed. For the analysis of the problem four different approaches-two estimation techniques (ordinary and grouping least squares) combined with two prediction methods (classical and inverse prediction)-are considered. By Monte Carlo simulation the perromance of each approach is assessed in term of the probability of concentration. The simulation results indicate that the ordinary least squares with inverse prediction is generally preferred in interpolation while the grouping least squares with classical prediction turns out to be better in extrapolation.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.1
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• pp.1-9
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• 2005

This paper proposes the heuristic algorithm for the generalized GT problems to consider the restrictions which are given the number of machine cell and maximum number of machines in machine cell as well as minimum number of machines in machine cell. This approach is split into two phase. In the first phase, we use the similarity coefficient which proposes and calculates the similarity values about each pair of all machines and sort these values descending order. If we have a machine pair which has the largest similarity coefficient and adheres strictly to the constraint about birds of a different feather (BODF) in a machine cell, then we assign the machine to the machine cell. In the second phase, we assign parts into machine cell with the smallest number of exceptional elements. The results give a machine-part grouping. The proposed algorithm is compared to the Modified p-median model for machine-part grouping.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.354-358
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• 2006

This study is concerned with the part-machine grouping(PMG) based on the non-binary part-machine incidence matrix in which real manufacturing Factors such as the operation sequences with multiple visits to the same machine and production volumes of parts are incorporated and each entry represents actual moves due to different operation sequences. The proposed approach adopts Fuzzy ART neural network to quickly create the initial part families and their associated machine cells. To enhance the poor solution due to category proliferation inherent to most artificial neural networks, a supplementary procedure reassigning parts and machines is added. To show effectiveness of the proposed approach to large-size PMG problems, a psuedo-replicated clustering procedure is designed and implemented.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.41-44
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• 2001

In the wide variety of radio propagation channel models, frequency selective fading which from multipath waves and diversity noises, electric and electronic devices ...etc in our environment, change characteristics of the sub channels in the wide bandwidth. so orthogonality among the OFDM subcarriers would be distorted and ICI(Inter Channel Interference), ISI(Inter Symbol Interference) be generated. This paper investigate BER characteristics of the OFDM System using Subband Grouping Method which adopted different channel modulation for each subband.

• Research in Mathematical Education
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• v.3 no.2
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• pp.89-98
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• 1999

The purpose of this review of literature is to investigate what kinds of research have been done on social construction of mathematics understanding among elementary students in small groups. Only empirical studies were reviewed, and then grouping was done in terms of the purpose of the study. This grouping identified three categories: 1) Social and mathematical norms in mathematics classroom, 2) Teaching productive communication behaviors for active learning in small group, and 3) Participation roles and communication behaviors in different group structure. To enhance social construction of mathematics understanding in small group settings two suggestions are made: the importance of the selection of collaborative tasks or problems and teachers' beliefs about mathematics and the teaching an learning of mathematics.

• Communications for Statistical Applications and Methods
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• v.29 no.4
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• pp.441-451
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• 2022

In the era of bigdata, scalability is a crucial issue in learning models. Among many others, the Alternating Direction of Multipliers (ADMM, Boyd et al., 2011) algorithm has gained great popularity in solving large-scale problems efficiently. In this article, we propose applying the ADMM algorithm to solve the least square problem penalized by the pairwise-difference penalty, frequently used to identify group structures among coefficients. ADMM algorithm enables us to solve the high-dimensional problem efficiently in a unified fashion and thus allows us to employ several different types of penalty functions such as LASSO, Elastic Net, SCAD, and MCP for the penalized problem. Additionally, the ADMM algorithm naturally extends the algorithm to distributed computation and real-time updates, both desirable when dealing with large amounts of data.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.45 no.1
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• pp.34-45
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• 2009

In this study, the hydrodynamic coefficients were measured using various nettings to analyze the change of drag coefficients and lift coefficients as a basic study for deriving hydrodynamic coefficients. The data on hydrodynamic force obtained from the flume tank tests were used to compare and analyze the hydrodynamic coefficients based on Reynolds number. Standardized hydrodynamic coefficients were then assumed during the analysis procedures. The hydrodynamic coefficients were measured using the 9 kinds of nettings in which had the same total projected area with different diameters and mesh-grouping ratio. These different netting systems : mesh-grouping ratio. The results of the test of nettings were as follows; First, the drag coefficients of nettings increased when the higher attack angles applied, and decreased with the increased flow speed and netting twine diameter. Second, the lift coefficients of nettings showed the increased values until the attack angle 30 degree, but decreased for the attack angle over 40 degree. Third, the hydrodynamic coefficients of netting decreased as the Reynolds number increased, and reach at slightly states in the highest numbers. Fourth, the hydrodynamic coefficients were derived from a functional formula considering attack angles and Reynolds number, and presented in the three dimensional space.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.589-594
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• 1991

Group Technology (GT) is a technique for identifying and bringing together related or similar components in a production process in order to take advantage of their similarities by making use of, for example, the inherent economies of flow production methods. The process of identification, from large variety and total of components, of the part families requiring similar manufacturing operations and forming the associated groups of machines is referred as 'machine-component grouping'. First part of this paper is devoted to describing a hierarchical divisive algorithm based on graph theory to find the natural part families. The objective is to form components into part families such that the degree of inter-relations is high among components within the same part family and low between components of different part families. Second part of this paper focuses on establishing cell design procedures. The aim is to create cells in which the most expensive and important machines-called key machine - have a reasonably high utilization and the machines should be allocated to minimize the intercell movement of machine loads. To fulfil the above objectives, 0-1 integer programming model is developed and the solution procedures are found. Next an attempt is made to test the feasibility of the proposed method. Several different problems appearing in the literature are chosen and the results air briefly showed.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.181-191
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• 1999

We consider Bayesian models allow multiple grouping of parameters for the normal means estimation problem. In particular, we consider a typical Bayesian hierarchical approach based on thepartial exchangeability where the components within a subgroup are exchangeable, but the different subgroups are not. We discuss implementation of such Bayesian procedures via Gibbs sampling. We illustrate the proposed methods with numerical examples.