• Korean Journal of Computational Design and Engineering
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• v.18 no.4
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• pp.299-307
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• 2013

Introduction of PLM in domestic shipyards is being retarded as ship PLM has yet to firm up return of investment and process integration. To implement a ship PLM system, it is required to share ship CAD model data in various design and manufacturing environments. Lightweight CAD models provide a promising solution for sharing CAD models in the product life cycle, which can expedite implementation of ship PLM in domestic shipyards in the near future. Compared to proprietary CAD models, it is easy for lightweight CAD models to be interfaced with various application systems and be connected to manufacturing information. In this paper, the reason why lightweight CAD models are necessary to implement a ship PLM system is addressed and current implementation results are introduced.

• Korean Management Science Review
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• v.17 no.3
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• pp.147-160
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• 2000

These days, a modeling tool or environment has to know about the others on the market and build bridges to them with which their customers insist on sharing models and data. When it is based on a closed architecture, a tangle of import/export point translators is required. Using an exchange standard, we can design an open architecture for the interchange of models and data. XML(Extensible Markup Language) provides a framework for describing the syntax for creating and exchanging data structures. The explosive growth of XML-based business proposals and standards reflects the urgent requirements and its strength. This paper proposes an XML-based language for sharing decision models within the MSOR/DSS community. The language is able to allow applications and on-line analytic processing tools to models obtained from multiple sources without having to deal with individual differences between those sources. It is expected to be a medium for B2B integration by supporting flexible interchange of decision models.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.4
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• pp.386-393
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• 2015

A study is carried out on investigation on pattern costs, identification of geometric parameters for the cost, and development of cost estimation models for casting patterns. Pattern costs for machine tool structures are collected and analyzed to identify the important geometric parameters that affect the costs. The parameters are used for the development of the costing models. It is found that the geometric parameters can be easily obtained from a CAD system and then the costing models estimate a pattern cost in a minimum time. The models are verified with the structures whose pattern cost was used for this study. It is expected that this costing models can evaluate the cost of casting structures of machine tools in search of a near-optimal design based on manufacturing cost and, for example, weight at the design stage.

• Structural Engineering and Mechanics
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• v.9 no.6
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• pp.601-613
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• 2000

Existing models for the shear strength degradation of reinforced concrete members present varied conceptual approaches to interpreting test data. The relative superiority of one approach over the others is difficult to determine, particularly given the sparseness of ideal test data. Nevertheless, existing models are compared using a suite of test data that were used for the development of one such model, and significant differences emerge. Rather than relying purely on column test data, the body of knowledge concerning degradation of concrete as a material is considered. Confined concrete relations are examined to infer details of the degradation process, and to establish a framework for developing phenomenologically-based models for shear strength degradation in reinforced concrete members. The possibility of linking column shear strength degradation with material degradation phenomena is explored with a simple model. The model is applied to the results of 7 column tests, and it is found that such a link is sustainable. It is expected that models founded on material degradation phenomena will be more reliable and more broadly applicable than the current generation of empirical shear strength degradation models.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.10 no.16
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• pp.149-158
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• 1987

The Adoption/Diffusion of Innovations(New Product), a topic of study and research that has frown rapidly in the past few decades, deals with how a new product is adopted in a society. It is of high importance to marketing organizations because New Products must be brought out continuously in order to service. The purpose of this paper is to examine the Adoption/Diffusion Models for New product which will help to analyze the Adoption/Diffusion process of Adopters. There are a number of models that, with varying degrees of success, have been used to predict market acceptance of new product. In this paper, following types of new product Adoption/Diffusion Models was suggested. (1) Adoption Models : The Alternative Models of Adoption. The Rogers Model of the Innovation Decision Process. (2) Diffusion Models : First Purchase Models(Basic Models, Extension of the Basic Models), Repeat Purchase Models

• Communications for Statistical Applications and Methods
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• v.28 no.2
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• pp.189-204
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• 2021

In a regression analysis, a single best model is usually selected among several candidate models. However, it is often useful to combine several candidate models to achieve better performance, especially, in the prediction viewpoint. Model combining methods such as stacking and Bayesian model averaging (BMA) have been suggested from the perspective of averaging candidate models. When the candidate models include a true model, it is expected that BMA generally gives better performance than stacking. On the other hand, when candidate models do not include the true model, it is known that stacking outperforms BMA. Since stacking and BMA approaches have different properties, it is difficult to determine which method is more appropriate under other situations. In particular, it is not easy to find research papers that compare stacking and BMA when regression model assumptions are violated. Therefore, in the paper, we compare the performance among model averaging methods as well as a single best model in the linear regression analysis when standard linear regression assumptions are violated. Simulations were conducted to compare model averaging methods with the linear regression when data include outliers and data do not include them. We also compared them when data include errors from a non-normal distribution. The model averaging methods were applied to the water pollution data, which have a strong multicollinearity among variables. Simulation studies showed that the stacking method tends to give better performance than BMA or standard linear regression analysis (including the stepwise selection method) in the sense of risks (see (3.1)) or prediction error (see (3.2)) when typical linear regression assumptions are violated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5B
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• pp.364-378
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• 2008

Data Envelopment Analysis(DEA) models can be used for performance evaluation on governmental funding projects for IT small and medium-sized enterprises associated with multiple-outputs/multiple-inputs. In order to enhance the accuracy of DEA efficiency scores, DEA models with exogenously fixed variables are required where the corporate competency is taken into account. Additionally, it is necessary to use multiple DEA basic as well as extended models so as to relax the restriction on the performance evaluation to relying on a single DEA model. In this study; 1)a DEA data structure is designed including exogenously fixed variables representing corporate asset, revenue and the number of employees at the point in time that the governmental funding project concerned is initiated; 2)DEA basic as well as extended models are established according to the DEA data structure presented abovementioned; and 3)a case study is illustrated with an empirical testbed dataset. As for the DEA basic models, CCR, BCC, Super-efficiency model are adopted. The DEA extended models are developed based on the models associated with noncontrollable and nondiscretionary variables. In the case study, it is explained a comparison of DEA models and also major numerical outcomes such as efficiency scores, ranks derived from each DEA model are integrated using Analytic Hierarchy Process(AHP) weights. Performance significance with DEA efficiency scores between technical categories are tested based not only on parametric but also nonparametric single-factor analysis of variance method.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.2
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• pp.190-204
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• 2008

Recently, it has been strongly required to establish a systematic and sustainable performance investigation and evaluation framework on governmental funding projects for IT small and medium-sized enterprises. In this paper, Data Envelopment Analysis (DEA) models are adopted for performance evaluation on governmental funding projects for IT small and medium-sized enterprises. A new data structure is proposed for the DEA performance evaluation. Generally, in using DEA models, DEA multipliers restriction is critical to achieve the reliability of DEA optimal solutions. Based on the outputs and inputs considered in this study, Acceptance Region (AR) constraints are generated and incorporated into the DEA models so as to improve the reliability of DEA efficiency scores. Associated with AR Type I (AR-I), AR Global Model (ARGM) constraints, DEA/ (AR-I, ARGM) models are designed and then sensitivity analysis follows investigating the robustness of DEA efficiency scores relating to AR constraints adjustment. Finally, a performance evaluation is illustrated regarding governmental direct funding projects from Ministry of Information and Communication (MIC) in Korea where each project unit (i.e. Decision Making Unit (DMU)) is determined whether it is efficient or not. By using DEA/(AR-I, ARGM) models designed in this paper, robustly efficient DMUs are gradually identified according to the successive AR constraints adjustment. Among 25 DMUs, results show that 6 DMUs such as B, E, G, Q, S, Y are determined as robustly efficient against AR constraints intermediate adjustment.

• Journal of Information Technology Services
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• v.17 no.4
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• pp.75-83
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• 2018

Enterprises need to monitor systems for reliable IT service operations to quickly detect and respond to events affecting the service, thereby preventing failures. Events in non-critical systems can be seen as a precursor to critical system incidents. Therefore, event relationship analysis in the operation of IT services can proactively recognize and prevent faults by identifying non-critical events and their relationships with incidents. This study used the Recurrent Neural Network and Long Short Term Memory techniques to create a model to analyze event relationships in a system and to verify which models are suitable for analyzing event relationships. Verification has shown that both models are capable of analyzing event relationships and that RNN models are more suitable than LSTM models. Based on the pattern of events occurring, this model is expected to support the prediction of the next occurrence of events and help identify the root cause of incidents to help prevent failures and improve the quality of IT services.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2001.09a
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• pp.295-301
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• 2001

For the seismic analysis of typical roadway bridges provisions are given in most codes for analysis models, which describes however only fundamental modelling methods according to the basic theories of structural dynamics. In practice even conventional non-seismic analysis models, separate super- and substructure models, are applied, which are not adequate because of neglecting connection elements. In this study three typical roadway bridges, a Steel box bridge, a PC beam bridge and a PC box bridge are selected and simple models integrating super- and substructure as well as connection elements are given. The simple models are composed with frame elements with lumped masses representing stiffness and mass characteristics of the selected bridges. To check the properness of the simple models, analysis results with the simple models are compared with those obtained with detailed models in view of bridge failure mechanisms. It is proved that the simple models can be used in the preliminary design phase fur the determination of failure mechanisms of typical roadway bridges.