• Journal of Industrial Convergence
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• v.19 no.1
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• pp.65-70
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• 2021

This study aims to propose specific directions for developing digital twin contents. This aim is achieved by thorough literature review and applying the grounded theory. Based on customers' need analysis, this study suggests the priorities of contents development of digital twins. As a result, complex workflows and dangerous training contents are adequate to be developed. Moreover, large-scale projects such as nuclear powerplants that are hard to build the mock-ups were considered to be effective. This study provides significant information for not only software developers but also clients who desire to reduce training fees and improve the complex workflows. Since these client companies operate based upon multiple complex workflows, this study encourages stakeholders to make effective decisions. This research needs further analysis of current digital twin technology- possibilities and limitations.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.131-141
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• 2024

The aging population and worsening lifestyle habits have increased the risk of chronic diseases. This has heightened the importance of preventive healthcare, particularly through personalized health management services based on individual health data. Despite this, the domestic digital healthcare industry remains underdeveloped. Given the need for acceptance from both consumers and providers, this study uses the Analytic Hierarchy Process (AHP) to identify success factors for health management service platforms. AHP evaluates the relative importance of various factors to aid decision-making. Results show that providers prioritize data analysis and platform design, laws and regulations, and data standardization, while consumers prioritize system stability, laws and regulations, and system security. These findings highlight the need for strategies to bridge the expectation gap to effectively promote health management service platforms.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1411-1419
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• 2016

Nonparametric procedures in randomized block design was proposed by Friedman (1937) as a general alternative. This method is used to find out the difference in treatment effect. It can cause a loss of inter block information using the ranking in each block. This paper proposed nonparametric procedures using an aligned method proposed by Hodges and Lehmann (1962) to reduce block information based on joint placement suggest by Jo and Kim (2013) in a randomized block design. We also compared the power of the test of the proposed procedures and established method through a Monte Carlo simulation.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1289-1312
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• 2015

This paper studies the comovement of industry defaults among listed companies. Rank correlation coefficients of Spearman's ${\rho}$ and Kendall's ${\tau}$ measure the concordance of default. These non-parametric coefficients do not require distributional assumptions and are easily used even with less data and extreme values. This study predicts a future financial crisis by looking at the comovement of industry defaults. We expect our analyses will aid market participants (including company executives) in making investment or risk management decisions.

• Journal of the Korean Data and Information Science Society
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• v.24 no.1
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• pp.95-103
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• 2013

Nonparametric procedure in randomized block design (RBD) was proposed by Friedman (1937) for general alternatives. Also Page (1963) suggested the test for ordered alternatives in RBD. In this paper, we proposed the new nonparametric method in randomized block design using aligned method suggested by Hodges and Lehmann (1962) and the joint placement described in Chung and Kim (2007). Also, Monte Carlo simulation study was adapted to compare the power of the proposed procedure with those of previous procedure.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.4 no.1
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• pp.63-85
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• 1996

의사 결정의 문제는 기본적으로 다수의 상충되는 기준(Criteria)하에서 최적의 대안을 선택하는 문제이며, 특히 국가나 항공사 또는 어느 기관에서 항공기의 구입시 기종 선정의 문제는 항공기 자체의 높은 가격 및 기술 파급효과, 안전성, 경쟁성 등 다수의 요인들을 심도 있게 고려하여야만 한다. 따라서 다수의 전문가 집단의 의견을 종합할 수 있다면 실패의 확률을 줄일 수 있을 것이다. 본 논문은 한국항공대학교의 훈련용 항공기의 도입 필요성이 제기됨에 따라 대상 기종인 Mooney MSE와 Cessna 172RG 기종에 대하여 현재 한국항공대학교에서 비행 교육을 담당하고 있는 운항학과 전임교수와 비행교육원 비행 교관들의 설문을 통하여 계층화 의사결정법을 이용하여 전문가 의견을 종합하였다. 계층화 의사결정법(AHP; Analytic Heirarchy Process)은 1970년대 초 T. L. Saaty에 의해 개발된 기법으로 다수의 목표, 다수의 기준, 다수의 의사결정 주체가 포함되어 있는 의사결정 문제를 계층화한 후, 상위 계층의 한 기준의 관점에서 직하위 계층의 요소들의 상대적 중요도(Relative Importance) 또는 가중치(Weight)를 쌍별비교(Pairwise Comparison)에 의해 측정하여 궁극적으로 최하위 계층의 대안의 우선순위를 구하는 기법으로 앞으로 항공기의 기종선 정시(특히 훈련용 항공기) 계층화 의사결정법(AHP)을 활용할 수 있도록 모델을 제시하고자 하였다.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.707-717
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• 2016

Nonparametric procedures in a randomized block design was proposed by Friedman (1937) as a general alternative as well as suggested as a test for ordered alternatives by Page (1963). These methods are used for the rank of treatments in each block. In this paper, we proposed nonparametric procedures using aligned method proposed by Hodges and Lehmann (1962) to reduce among block information and based on placement suggested by Kim (1999) in a randomized block design. We also perform a Monte Carlo study to compare the empirical powers of the proposed procedures and established method.

• Convergence Security Journal
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• v.18 no.5_1
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• pp.33-43
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• 2018

In this paper, we want to solve the problems that users want to search the progress of attack, continuity of attack, association between attackers and victims, blocking priority and countermeasures by using visualization interface with multi-rotational axis and radial axis structure. It is possible to effectively monitor and track security events by arranging a time series event based on a multi-rotational axis structured by an event generation order, a subject of an event, an event type, and an emission axis, which is an objective time indicating progress of individual events. The proposed interface is a practical visualization interface that can apply attack blocking and defense measures by providing the progress and progress of the whole attack, the details and continuity of individual attacks, and the relationship between attacker and victim in one screen.

• Journal of the Korean Chemical Society
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• v.23 no.4
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• pp.237-242
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• 1979

The equivalent conductances of sodium, potassium, ammonium, tetramethylammonium, triethylammonium, diethylammonium and ethylammonium iodide, and picrate salts of sodium and potassium in ethylene carbonate have been measured at 40.0 $^{\circ}C. The limiting equivalent conductances of the salts have been computed by Fuoss-Onsager-Skinner equation. The limiting ionic equivalent conductances of $Na^+,\;K^+,\;and\;NH^+$ are in order of $Na^+ which is the reverse order of solvation for the ions in any solution, And the order of limiting ionic equivalent conductances for alkylammonium ions is $(C_2H_5)_4N^+<(C_2H_5)_3NH^+<(CH_3)_4N^+<(C_2H_5)_2NH_2^+<(C_2H_5)NH_3^+$ which coincides with the order of mass transfer. From the dissociation constants of the saltss determinde by Fuoss-Kraus method, it is found that ethyene carbonate is a good ionizing solvent for the salts. In addition, Stokes radii and effective fadii of ions have been calculated by Stokes law and Nightingale method, repectively. From the results, it appears tha alkylammonium ions and picrate ion seem to be not solvated, and tha iodide ion is fairly solvated in ethylene carbonate.

• Knowledge Management Research
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• v.22 no.4
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• pp.27-40
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• 2021

Click-Through Rate (CTR) prediction is a key function that determines the ranking of candidate items in the recommendation system and recommends high-ranking items to reduce customer information overload and achieve profit maximization through sales promotion. The fields of natural language processing and image classification are achieving remarkable growth through the use of deep neural networks. Recently, a transformer model based on an attention mechanism, differentiated from the mainstream models in the fields of natural language processing and image classification, has been proposed to achieve state-of-the-art in this field. In this study, we present a method for improving the performance of a transformer model for CTR prediction. In order to analyze the effect of discrete and categorical CTR data characteristics different from natural language and image data on performance, experiments on embedding regularization and transformer normalization are performed. According to the experimental results, it was confirmed that the prediction performance of the transformer was significantly improved when the L2 generalization was applied in the embedding process for CTR data input processing and when batch normalization was applied instead of layer normalization, which is the default regularization method, to the transformer model.