• Journal of Korea Water Resources Association
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• v.48 no.8
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• pp.647-657
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• 2015

This study assessed the water use vulnerability for 12 basins of South Korea. The annual runoff of 12 basins are derived using a Soil and Water Assessment Tool (SWAT) and the calculated runoff per unit area and population are compared with each basin. The 18 indicators are selected in order to assess the vulnerability. Those are classified by aspects of demand, loss and supply of water use. Their weighting values used Entropy method to determine objective weights. To quantitatively assess the water use vulnerability, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) based on multi-criteria decision making are applied. The results show that the water availability vulnerability of Hyeongsan River has the highest value followed by Sapgyo River; Dongjin River; Seomjin River; Anseong River; Mangyung River; Nakdong River; Tamjin River; Youngsan River, Geum River; Taehwa River; and Han River. The result of this study has a capability to provide references for the index deveopment of climate change vulnerability assessment.

• Convergence Security Journal
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• v.15 no.4
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• pp.43-55
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• 2015

The effective cyber capability assessment methodology does not exist, it's difficult to check the current state of the our country's cyber capabilities and to establish cyber capability enhancement plan based on the result of assessment. The cyber capability assessment is necessary in order to determine the current level of the country, establish policy directions and provide the basis for effective budgeting. But assessment of national cyber capability is multi-criteria decision makink problem. In this paper develops an assessment model based on the AHP and TOPSIS. AHP is used to determine weight of the criteria and TOPSIS method is used to obtain final ranking. We also introduce the result of four major nations cyber capability assessment using the proposed methodology. The experiment used the virtual experimental data. And the result show that the proposed methodology can expand the number of criteria and alternatives for assessment and provide more sophisticated mathematical base for objective assessment comparing methodology using AHP only.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.105-113
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• 2020

The development and application of cultural technologies(CT) are expected to lead to create various service scenarios and business models. Considering the wide range of application and extensibility of CT, it is necessary to design multidimensional evaluation methods for priority of the support of R&D budgets. The method should include the various evaluation criteria such as economic feasibility and user benefit of service made by a cultural technology. Our research addresses priority decision for fosterage of cultural technologies using fuzzy TOPSIS. Seven evaluation attributes are used to compare five specific technologies. Based on the results, service usefulness is the most important factor among the evaluation attributes. Also, technologies of computer graphics and UI/UX have higher priority than the others. We expect our research to help to provide guidelines for selection of promising cultural technologies which foster the culture and contents industry.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.4
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• pp.482-489
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• 2011

In practical design process, designer needs to find an optimal solution by using full factorial discrete combination, rather than by using optimization algorithm considering continuous design variables. So, ANOVA(Analysis of Variance) based on an orthogonal array, i.e. Taguchi method, has been widely used in most parts of industry area. However, the Taguchi method is limited for the shape optimization by using CAE, because the multi-level and multi-objective optimization can't be carried out simultaneously. In this study, a combined method was proposed taking into account of multi-level computational orthogonal array and TOPSIS(Technique for Order preference by Similarity to Ideal Solution), which is known as a classical method of multiple attribute decision making and enables to solve various decision making or selection problems in an aspect of multi-objective optimization. The proposed method was applied to a case study of the multi-level shape optimization of lower arm used to automobile parts, and the design space was explored via an efficient application of the related CAE tools. The multi-level shape optimization was performed sequentially by applying both of the neural network model generated from seven-level four-factor computational orthogonal array and the TOPSIS. The weight and maximum stress of the lower arm, as the objective functions for the multi-level shape optimization, showed an improvement of 0.07% and 17.89%, respectively. In addition, the number of CAE carried out for the shape optimization was only 55 times in comparison to full factorial method necessary to 2,401 times.

• International Journal of Automotive Technology
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• v.8 no.1
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• pp.83-91
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• 2007

Nowadays, the increasing global competition forces manufacturing enterprises to apply new technologies such as laser welding to manufacturing of their products. In case of automotive industries, they interest in assembly system for BIW (Body in White) carrying out laser welding. In this paper, the method of implementation for digital laser welding assembly system is proposed. Based on the requirements of assembly tasks obtained through product analysis, process modeling is executed by using the IDEF0 and UML model. For digital assembly system, the selected components are modeled by using 3D CAD tools. According to the system configuration strategy, lots of the alternative solutions for the assembly system of welding side panels are generated. Finally, the optimal laser welding system is chosen by the evaluation of the alternative solutions with TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2239-2256
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• 2022

In this paper, a model is proposed to comprehensively evaluate the computational power. The five forces model of computational power solves the problem that the measurement units of different indexes are not unified in the process of computational power evaluation. It combines the bidirectional projection method with TOPSIS method. This model is more scientific and effective in evaluating the comprehensive situation of computational power. Lastly, an example shows the validity and practicability of the model.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.620-621
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• 2015

In this study, the multi-criteria decision-making model based on Quality Function Deployment Method is proposed. Multicriteria decision-making is an attempt to link QFD method with the TOPSIS. By this effort, a model that makes client's decision-making more rational and objective in design phase is suggested. The multi-criteria decisionmaking model confirming to the Owner's requirements will improve the productivity of the construction industry and the satisfaction of the customer. Further study extending the range of the requirements, not only the Owner's requirement will be necessary to cover the various factors as much as possible. And then, finally as a flexible platform to achieve a sustainable quality management, web-based multi-criteria decision-making model can be utilized by the relevant stakeholders simultaneously with the feed-back and sharing the necessary informations.

• Knowledge Management Research
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• v.19 no.2
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• pp.151-162
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• 2018

Response surface methodology (RSM) is one of popular tools to support a systematic improvement of quality of design in the product and process development stages. It consists of statistical modeling and optimization tools. RSM can be viewed as a knowledge management tool in that it systemizes knowledge about a manufacturing process through a big data analysis on products and processes. The conventional RSM aims to optimize the mean of a response, whereas dual-response surface optimization (DRSO), a special case of RSM, considers not only the mean of a response but also its variability or standard deviation for optimization. Recently, a posterior preference articulation approach receives attention in the DRSO literature. The posterior approach first seeks all (or most) of the nondominated solutions with no articulation of a decision maker (DM)'s preference. The DM then selects the best one from the set of nondominated solutions a posteriori. This method has a strength that the DM can understand the trade-off between the mean and standard deviation well by looking around the nondominated solutions. A posterior method has been proposed for DRSO. It employs an interval selection strategy for the selection step. This strategy has a limitation increasing inefficiency and complexity due to too many iterations when handling a great number (e.g., thousands ~ tens of thousands) of nondominated solutions. In this paper, a TOPSIS-based method is proposed to support a simple and efficient selection of the most preferred solution. The proposed method is illustrated through a typical DRSO problem and compared with the existing posterior method.

• Land and Housing Review
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• v.10 no.1
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• pp.19-23
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• 2019

In recent years, many studies have been conducted on smart low carbon cities through the fusion of ICT information technology for the purpose of reducing carbon. In this study, we investigated 13 cities in three continents that implement low-carbon city policies and analyzed the size, economic and social characteristics of each city to identify the degree of dynamic mechanism for carbon reduction. To this end, we quantified the elements of the city and analyzed the basic requirements for low-carbon cities using the TOPSIS method. The study found that most cities were better able to activate institutions and cultural conditions, facilities and functional conditions, and economic and industrial conditions than other engines, and these three were the main forms of power for smart low carbon cities. The results of this study are expected to be used as a basis for suggesting policy recommendations and improvement measures for future smart low carbon cities.

• Journal of Distribution Science
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• v.19 no.8
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• pp.25-35
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• 2021

Purpose: This study aims to propose an integrated MCDM model to support the qualified personnel selection in the distribution science. Research design, data, and methodology: The integrated approach of AHP and TOPSIS was employed to address the personnel selection problem. The AHP method was used to define the weights of the selection criteria, whereas the TOPSIS was applied to rank alternatives. The proposed model was then applied into a leading logistics company to select the best alternatives to be the sales deputy manager. Results: The results showed that Candidate 3 is the most qualified personnel for the sales deputy manager position as he is ranked first in the order of preference for recruitment. Conclusions: The proposed model provides the decision makers with more effective and time-saving methods than conventional ones. Therefore, the model can be applied to personnel selection around the world. In terms of theoretical contribution, this study proposes a personnel selection model for choosing the most appropriate candidates. In addition, the study adds to the theory of human resources management and logistics management the full set of personnel selection criteria including education, experience, skills, health, personality traits and foreign language.