• Journal of KIISE:Software and Applications
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• v.32 no.6
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• pp.486-501
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• 2005

XPDL is a XML-based language for process definition exchange that is proposed by WfMC. This paper propose a model which model XPDL document structure (Schema) using UML in order to define and to exchange workflow process, and make business flow understanding ease for inter-business cooperation. So, we define mapping rules in which map XPDL documents into UML class diagram and UML activity diagram. By these mapping rules, elements composing XPDL process meta-model are mapped into UML class diagram, and process activities are mapped into UML activity diagram. Also, we apply proposed mapping technique to model a workflow of (')Credit card state check system.(')

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.56
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• pp.19-34
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• 2000

Impact of business process re-engineering requires the fundamental rethinking of how information systems are analyzed and designed. It is no longer sufficient to establish a monolithic system for fixed business environments. Information systems must be adaptive in nature. This demand is also applied in production domain. Enabling concept for the adaptive information system is reusability. This paper presents a new object-oriented analysis process for creating such reusable software components in production domain, especially for production planning and scheduling. Our process called MeCOMA is based on three meta-models: physical object meta-model, data object meta-model, and activity object meta-model. After the three meta-models are extended independently for a given production system, they are collaboratively integrated on the basis of integration pattern. The main advantages of MeCOMA are (1) to reduce software development time and (2) to consistently build reusable production software components.

• Journal of Korea Technology Innovation Society
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• v.12 no.1
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• pp.113-136
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• 2009

The purpose of this study is to develop meta evaluating indicators for Defense R&D Programs in Korea. At first, the four components of this meta evaluation model were designed, which are evaluation context, evaluation input, evaluation process, evaluation output. And fifty two indicators were developed for this meta evaluation. Basic model of meta evaluation was derived from the literature review and brain storming. And this meta evaluation model was determined by adapting the result of experts who performed evaluations for Defense R&D Programs in recent years. Factor Analysis method was used to verify the validity of meta evaluation model. The survey of fifty three members turned out that Cronbach' ${\alpha}$ was over 0.6 in evaluation components and items. And the reliability of evaluation context was 0.877, that of evaluation input was 0.755, that of evaluation process was 0.755, that of evaluation output was 0.755 respectively. Analytic Hierarchy Process (AHP) method was used in assigning the evaluation weight. The survey of twenty two members showed that the Consistency Ratio was 0.09 in evaluation components and items.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.3
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• pp.74-81
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• 2019

Herein, we performed a comparative study on approximate multi-objective design optimization, to realize a structural design to improve the weight and vibration performances of the knuckle - a car suspension component - considering various load conditions and vibration characteristics. In the approximate multi-objective optimization process, a regression meta-model was generated using the response surfaces method (RSM), while Kriging and back-propagation neural network (BPN) methods were applied for interpolation meta-modeling. The Pareto solutions, multi-objective optimal solutions, were derived using the non-dominated sorting genetic algorithm (NSGA-II). In terms of the knuckle design considered in this study, the characteristics and influence of the meta-model on multi-objective optimization were reviewed through a comparison of the approximate optimization results with the meta-models and the actual optimization.

• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.35-50
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• 2000

Diverse requirements of users on web-based model management force a system agent to develop user-adaptive building a model in reality and providing an adequate solution method of the model. The relationship between models is important knowledge for the agent to effectively build a new model to adaptively adjust an existing model under a problem and to efficiently connect the new model into an adequate solution method. Since the generating process of the inter-model relationship is more difficult than the building a new model however the process mostly depends on the knowledge of operation research experts. Without the adequate scheme of the inter-model relationship the burden of the management for the agent increases rapidly and the quality of the services may worsen. This study shows that meta-knowledge generated from relationship between models is important for the user to build a model in reality and to acquire the solver appropriate to the model. The relationship that consists of common and exclusive objects between models can be represented by frames. The system under development to implement the idea includes user-adaptive ability which identifies a model through forward chaining method and searches the solver appropriate to the model by using the meta knowledge. We illustrate the meta knowledge with an applied delivery system in supply chain management.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.161-175
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• 2001

Meta-analysis refers to quantitative methods for combining results from independent studies in order to draw overall conclusions. Hierarchical models including selection models are introduced and shown to be useful in such Bayesian meta-analysis. Semiparametric hierarchical models are proposed using the Dirichlet process prior. These rich class of models combine the information of independent studies, allowing investigation of variability both between and within studies, and weight function. Here we investigate sensitivity of results to unobserved studies by considering a hierachical selection model with including unknown weight function and use Markov chain Monte Carlo methods to develop inference for the parameters of interest. Using Bayesian method, this model is used on a meta-analysis of twelve studies comparing the effectiveness of two different types of flouride, in preventing cavities. Clinical informative prior is assumed. Summaries and plots of model parameters are analyzed to address questions of interest.

• Genomics & Informatics
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• v.20 no.4
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• pp.49.1-49.7
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• 2022

Many packages for a meta-analysis of genome-wide association studies (GWAS) have been developed to discover genetic variants. Although variations across studies must be considered, there are not many currently-accessible packages that estimate between-study heterogeneity. Thus, we propose a python based application called Beta-Meta which can easily process a meta-analysis by automatically selecting between a fixed effects and a random effects model based on heterogeneity. Beta-Meta implements flexible input data manipulation to allow multiple meta-analyses of different genotype-phenotype associations in a single process. It provides a step-by-step meta-analysis of GWAS for each association in the following order: heterogeneity test, two different calculations of an effect size and a p-value based on heterogeneity, and the Benjamini-Hochberg p-value adjustment. These methods enable users to validate the results of individual studies with greater statistical power and better estimation precision. We elaborate on these and illustrate them with examples from several studies of infertility-related disorders.

• Knowledge Management Research
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• v.10 no.2
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• pp.65-84
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• 2009

The purpose of this study is to develop Meta Evaluation Indicators for Defense R&D Programs in Korea. At first, the four components of this meta evaluation model were designed, which are evaluation context, evaluation input, evaluation process and evaluation outcome. And fifty two indicators for this meta evaluation were developed by experts who performed evaluations for Defense R&D Programs. The reliability of components and items was verified by Cronbach's ${\alpha}$ coefficient. It was over 0.6 in all areas. The validity of components and items was verified by Factor Analysis. Analytic Hierarchy Process method was used in assigning the evaluation weight. The survey of twenty two evaluators participated in Defense R&D Programs showed that the Consistency Ratio was under 0.1 in evaluation components and items. In this study, an objective and reasonable set of Defense R&D Meta Evaluation Indicators was developed to increase the responsibility of Defense R&D Programs and improve the quality of evaluation results.

• Journal of Ocean Engineering and Technology
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• v.29 no.5
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• pp.351-358
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• 2015

This paper presents an effective damage detection method using a meta model. A meta model is an approximation model that uses the relations between the design and response variables. It eliminates the need for repetitive analyses of computationally expensive models during the optimization process. In this study, a response surface model was employed as the meta model. The surface model was estimated using the correlation of the stiffness and natural frequencies of the structures. The locations and values of the damages were identified using a meta model-based damage detection method. Two numerical examples (a cantilever beam and jacket structure) were considered to verify the performance of the proposed method. As a result, the damages to the structures were accurately detected.

• Education of Primary School Mathematics
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• v.2 no.1
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• pp.3-13
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• 1998

In mathematics education we have focused on how to improve the problem-solving ability, which makes its way to the new direction with the introduction of meta-cognition. As meta-cognition is based on cognitive activity of learners and concerned about internal properties, we may find a more effective way to generate learners problem-solving power. Its means that learners can regulate cognitive process according to their gorls of learning by themselves. Moreover, they are expected to make active participation through this process. If specific meta problems designed to develop meta-cognition are offered, learners are able to work alone by means of their own cognition and regulation while solving problems. They can transfer meta-cognition to the other subjects as well as mathematics. The studies on meta-cognition conducted so far may be divided into these three types. First in Flavell(［3］) meta-cognition is defined as the matter of being conscious of one's own cognition, that is, recognizing cognition. He conducted an experiment with presschoolers and children who just entered primary school and concluded that their cognition may be described as general stage that can not link to specific situation in line with Piaget. Second, Brown(［1］, ［2］) and others argued that meta-cognition means control and regulation of one's own cognition and tried to apply such concept to classrooms. He tried to fined out the strategies used by intelligent students and teach such types of activity to other students. Third, Merleary-Ponty (1962) claimed that meta-cognition is children's way of understanding phenomena or objects. They worked on what would come out in children's cognition responding to their surrounding world. In this paper following the model of meta-cognition produced by Lester (［7］) based on such ideas, we develop types of meta-cognition. In the process of meta-cognition, the meta-cognition working for it is to be intentionally developed and to help unskilled students conduct meta-cognition. When meta-cognition is disciplined through meta problems, their problem-solving power will provide more refined methods for the given problems through autonomous meta-cognitive activity without any further meta problems.