• The Journal of Information Systems
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• v.15 no.2
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• pp.173-193
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• 2006

This study first conceptualizes and investigates five dimensions of SCM activities, such as organizational capacity, revitalization support collaboration, appraisal and responsibility, and information system activities. Second, this study develops three dimensions of a supply chain structure, and proposes a balanced scorecard (BSC) model in order to measure business performance. And then, this study establishes too research hypotheses as follows: H1. The SCM activities varies with the supply chain structure. H2. The management performance varies with the supply chain structure. In the questionnaire survey for empirical analysis, this study carefully selected 809 of companies in Korea. We conducted a survey by mail and collected 127 data. Out of 127 data we actually used 103 responses for statistical analysis. After conducting statistical analysis, we could find the results as followed: 1) The supply chain structure was classified into three networks through a clustering procedure, such as supply network, conversion network, and distribution network, and these networks were used to testify hypotheses. As a result the effect of SCM activities varies according to three networks and especially, the companies in distribution network were more active than those in supply and conversion networks doing SCM activities. 2) We may conclude that business performance varies with three networks, and distribution network achieves better performance than supply and conversion networks do.

• Communications for Statistical Applications and Methods
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• v.30 no.5
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• pp.467-483
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• 2023

In this research, a conversion function and a distortion associated with the conversion function are defined and used to derive a unit power Gompertz distortion. A new family of copulas is built using the global distorted function. Four base copulas, namely Clayton, Gumbel, Frank, and Gaussian, are distorted into the family. Some properties including tail dependence coefficients and tail order are examined. Kendall's tau formula is derived for new copulas when the base copula is Clayton, Gumbel, or Frank. The maximum pseudo-likelihood estimation method is employed, and a simulation study was performed. The log-likelihood and AIC are reported to compare the performance of the fitted copulas. According to the applied data, the results indicate that new distorted copulas with additional parameters improve the fit.

• Journal of the Korean Society of Industry Convergence
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• v.7 no.4
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• pp.377-382
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• 2004

This research was about implementing STEP for data exchange among different commercial package(CAD system). STEP was used to share CAD data as follows. ST-Developer implement Solid model was used with a physical file of STEP and represented in a CAD system. And then STEP conversion utility was used to make a neutrality format form in a component modeling. Analysis of Solid model was made possible for CAD system to read in and analyzed Solid model. This research are summarized as follows 1. A basis Model development used Visual C++ for a neutrality data of a programming interface general-use CAD system, and produced Box and Cylinder to a physical file, the result was implemented this in a programming interface to general-use CAD system, it is represented in CAD system as identical one modeling object. 2. STEP was used in different CAD system to utilize to its of each CAD system maximum, CATIA V5R9 user was able to analyze MDT 6 Modeling Arm. 3. STEP was used able to interpret and remodel the existing Solid model.

• Design & Manufacturing
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• v.15 no.4
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• pp.24-31
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• 2021

In this study, an artificial neural network model was constructed to convert CAE analysis data into similar experimental data. In the analysis and experiment, the injection molding data for 50 conditions were acquired through the design of experiment and random selection method. The injection molding conditions and the weight, height, and diameter of the product derived from CAE results were used as the input parameters for learning of the convert model. Also the product qualities of experimental results were used as the output parameters for learning of the convert model. The accuracy of the convert model showed RMSE values of 0.06g, 0.03mm, and 0.03mm in weight, height, and diameter, respectively. As the next step, additional randomly selected conditions were created and CAE analysis was performed. Then, the additional CAE analysis data were converted to similar experimental data through the conversion model. An artificial neural network model was constructed to predict the quality of injection molded product by using converted similar experimental data and injection molding experiment data. The injection molding conditions were used as input parameters for learning of the predicted model and weight, height, and diameter of the product were used as output parameters for learning. As a result of evaluating the performance of the prediction model, the predicted weight, height, and diameter showed RMSE values of 0.11g, 0.03mm, and 0.05mm and in terms of quality criteria of the target product, all of them showed accurate results satisfying the criteria range.

• Journal of the Korea Fashion and Costume Design Association
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• v.22 no.1
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• pp.1-13
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• 2020

The purpose of this study is to create a 3D avatar from 3D human body shape data using the CLO 3D virtual clothing program and to verify the feasibility of avatar production using the virtual clothing system for verifying size and shape. The research method was to select one virtual representative model that is the closest to the mean size of each body item for each age group. Using the 3D human body scan shape of a 40-69 years old male was applied to the CLO 3D virtual wearing system. Using the CLO 3D Avatar conversion menu, we verified the feasibility of creating a 3D avatar that reproduces the human body scan shape. In the dimension comparison between the 3D avatar and the fictitious representative model, the dimension difference was noticeable in height, circumference, and length. However, as a result, the converted 3D avatar showed less than a 5% difference in most human dimensions. In addition, since the body shape and posture were reproduced similarly, the utilization of the avatar was verified.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.417-425
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• 2020

Multi-resolution modeling(MRM) is required when simulating objects in variable resolution and can be applied for interoperating systems, which simulate objects in fixed resolution. However, most interoperation middleware do not support MRM, so participating models must handle several issues to simulate MRM system. In this paper, we propose an interoperation system, which is composed of several different resolution models, based on the High Level Architecture and Run-Time Infrastructure(HLA/RTI). In the proposed architecture, each model participates to a HLA federation through MRM adapter application, which supports data resolution conversion and HLA services while communicating with the model. MRM adapter application can be implemented based on an MRM adapter, and an adapter application development tool is proposed to support developing the application. Using the tool, developers can easily implement data resolution conversion component plugged-in HLA adapter. A case study is implemented in the proposed MRM system, and shows that models of different resolution works successfully with dynamic resolution changes.

• Journal of Korean Society for Geospatial Information Science
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• v.2 no.1 s.3
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• pp.99-106
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• 1994

Raster data mode and Vector data are the two major model in geographic information systems. These two data models are difficult to be intergrated because of their differences in structures and properties. Almost all of the current GIS systems process in one data model by converting one data type to another type. So. the loss and change of information caused by data conversiion degrades the accuracy of data. In this paper, we propose a new data model which can process two data models without conversion. We use quadtree for raster data and topological vector model for vector data. The output is formed as raster data model of quadtree. We can get more accurate overay output, and this intergrated model is more suitable for data like forest, landuses, soils that consist of classes which have small distribution changes.

• Journal of the Korea Society for Simulation
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• v.29 no.3
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• pp.83-91
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• 2020

To use the OneSAF model for the analysis of Defence M&S, the most critical factor is the acquisition of input data. The model user is hard to determine the input data such as the probability of hit(P_h) and the probability of kill(P_k). These data can be obtained directly by live fire during the development test and the operational test. Therefore, this needs more time and resources to get the P_h and P_k. In this paper, we reviewed possible ways to obtain the P_h and P_k. We introduced several data producing methodologies. In particular, the error budget method was presented to convert the P_h(%) data of AWAM model to the error(mil) data of OneSAF model. Also, the conversion method which can get the adjusted results from the JMEM is introduced. The probability of a hit was calculated based on the error budget method in order to prove the usefulness of the given method. More accurate data were obtained when the error budget method and the projected area from the published photo were used simultaneously. The importance of the P_h calculation was demonstrated by sensitivity analysis of the P_h on combat effectiveness. This paper emphasizes the importance of determining the P_h data and improving the reliability of the M&S system though steady collection and analysis of the P_h data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.6
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• pp.1293-1308
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• 2014

The cause of privacy extrusion in credit card company at 2014 is usage of the original data in test system. By Electronic banking supervision regulations of the Financial Supervisory Service and Information Security business best practices of Finance information technology (IT) sector, the data to identify the customer in the test system should be used to convert. Following this guidelines, Financial firms use converted customer identificaion data by loading in test system. However, there is some risks that may be introduced unintentionally by user mistake or lack of administrative or technical security in the process of testing. also control and risk management processes for those risks did not studied. These situations are conducive to increasing the compliance violation possibility of supervisory institution. So in this paper, we present and prove the process to eliminate the compliance violation possibility of supervisory institution by controlling and managing the unidentified conversion customer identification data and check the effectiveness of the process.

• ETRI Journal
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• v.46 no.1
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• pp.127-136
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• 2024

The Korean language has written (formal) and spoken (phonetic) forms that differ in their application, which can lead to confusion, especially when dealing with numbers and embedded Western words and phrases. This fact makes it difficult to automate Korean speech recognition models due to the need for a complete transcription training dataset. Because such datasets are frequently constructed using broadcast audio and their accompanying transcriptions, they do not follow a discrete rule-based matching pattern. Furthermore, these mismatches are exacerbated over time due to changing tacit policies. To mitigate this problem, we introduce a data-driven Korean spoken-to-written transcription conversion technique that enhances the automatic conversion of numbers and Western phrases to improve automatic translation model performance.