• Journal of Digital Contents Society
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• v.19 no.7
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• pp.1365-1372
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• 2018

The purpose of this study is to analyze the importance of the determinants of housing sales agency's role in the sale of apartment housing. For this purpose, a hierarchical decision model was constructed to understand the role and importance of the sales agency. The analytical variable items structured by the research model were set up through literature review, precedent research, and expert brainstorming. The questionnaire consisted of two comparisons for AHP analysis and the importance of absolute importance for fuzzy analysis. Afterwards, the work of correcting the importance was carried out. As a result of the analysis, it was found that the contractor prioritized the sale conditions and the sales agency had priority over the planning for the sale. As a result of analysis, planning of customer pre-sale counseling data, planning of client subscription and contract maximization plan, planning method of advertisement public media method were found to be the most important factors. The results of measurement of absolute importance(fuzzy) & relative importance(,AHP) showed similar tendency. Therefore, it can be seen that the timing of the model house operation is an important period in which the subscription rate depends on the role of the sales agency and the marketing strategy.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.174-179
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• 2015

Failure Mode and Effects Analysis (FMEA) has been used by Dynamic Positioning (DP) system for risk and reliability analysis. However, there are limitations associated with its implementation in offshore project. 1) since the failure data measured from the SCADA system is missing or unreliable, assessments of Severity, Occurrence, Detection are based on expert's knowledge; 2) it is not easy for experts to precisely evaluate the three risk factors. The risk factors are often expressed in a linguistic way. 3) the relative importance among three risk factors are rarely even considered. To solve these problems and improve the effectiveness of the traditional FMEA, we suggest a Fuzzy-FMEA method for risk and failure mode analysis in Dynamic Positioning System of offshore. The information gathered from DP FMEA report and DP FMEA Proving Trials is expressed using fuzzy linguistic terms. The proposed method is applied to an offshore Dynamic Positioning system, and the results are compared with traditional FMEA.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1694-1704
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• 2015

In this paper, a robust trajectory tracking control method of a wheeled mobile robot is newly proposed combining the PDC and the ISMC. The PDC is a relatively simple and easy control method for nonlinear system compared to the other non-linear control methods. And the ISMC can have robust and stable control characteristics against model uncertainties and disturbances from the initial time by placing the states on the sliding plane with desired nominal dynamics. Therefore, the proposed PDC+ISMC trajectory tracking control method shows robust trajectory tracking performance in spite of external disturbance. The tracking performance of the proposed method is verified through simulations. Even though the disturbance increases, the proposed method keeps the performance of the PDC method when there is no disturbance. However, the PDC trajectory tracking control method has increasing tracking error unlike the proposed method when the disturbance increases.

• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.721-731
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• 2010

The rainfall-runoff relationship is very difficult to predict because it is complicate factor affected by many temporal and spatial parameters of the basin. In recent, models which is based on artificial intelligent such as neural network, genetic algorithm fuzzy etc., are frequently used to predict discharge while stochastic or deterministic or empirical models are used in the past. However, the discharge data which are generally used for prediction as training and validation set are often estimated from rating curve which has potential error in its estimation that makes a problem in reliability. Therefore, in this study, water stage is predicted from antecedent rainfall and water stage data for short term using three models of neural network which trained by error back propagation algorithm and optimized by genetic algorithm and training error back propagation after it is optimized by genetic algorithm respectively. As the result, the model optimized by Genetic Algorithm gives the best forecasting ability which is not much decreased as the forecasting time increase. Moreover, the models using stage data only as the input data give better results than the models using precipitation data with stage data.

• Journal of Energy Engineering
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• v.27 no.4
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• pp.80-85
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• 2018

Usable capacity is one of the most important parameters for evaluating the performance of an adsorbent for $CO_2$ capture from flue gas streams. In the pressure swing adsorption (PSA) process, the usable capacity is calculated as the difference between the quantity adsorbed in flue gas at high pressure (ca. 20 bar) and the quantity adsorbed at lower purge pressure (ca. 2 bar). In this paper, two stereo-types of metal-organic framework (MOF) were evaluated as an promising adsorbent for $CO_2$ capture: flexible structured MOF (MIL-53) and MOF possessing strong binding sites (MOF-74). The results showed that a total $CO_2$ capture capacity is strongly related to the specific surface area and heat of adsorption, revealing high uptake in MOF-74. However, the usable capacity was more pronounced in MIL-53 due to a structural transition.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.99-104
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• 2021

In this paper, we propose health risk management using feature extraction and cluster analysis considering time flow. The proposed method proceeds in three steps. The first is the pre-processing and feature extraction step. It collects user's lifelog using a wearable device, removes incomplete data, errors, noise, and contradictory data, and processes missing values. Then, for feature extraction, important variables are selected through principal component analysis, and data similar to the relationship between the data are classified through correlation coefficient and covariance. In order to analyze the features extracted from the lifelog, dynamic clustering is performed through the K-means algorithm in consideration of the passage of time. The new data is clustered through the similarity distance measurement method based on the increment of the sum of squared errors. Next is to extract information about the cluster by considering the passage of time. Therefore, using the health decision-making system through feature clusters, risks able to managed through factors such as physical characteristics, lifestyle habits, disease status, health care event occurrence risk, and predictability. The performance evaluation compares the proposed method using Precision, Recall, and F-measure with the fuzzy and kernel-based clustering. As a result of the evaluation, the proposed method is excellently evaluated. Therefore, through the proposed method, it is possible to accurately predict and appropriately manage the user's potential health risk by using the similarity with the patient.

• 한국사회정책
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• v.19 no.3
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• pp.185-214
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• 2012

After the introduction of the three welfare regimes by Esping-Andersen, discussion on 'other' types of welfare regimes was facilitated and the scholarly focus on East Asian economic development gradually shifted to the East Asian welfare states discussion from the late 1990s. Literature on East Asian welfare states increased our understanding on the characteristics of not only the East Asian welfare state as a whole but also of each country in the region. However, compared the attention given to developing variables and empirical studies on the East Asian welfare state, less attention has been given to the concept of East Asian welfare states. Recognizing the limitation in developing comparable variables without a concept analysis of the East Asian welfare states, this study highlights the importance of conceptualization and concept analysis in comparative social policy studies. This paper first discusses on the concepts, conceptualization and on the use of set theory in comparative social policy research. Next, the study argues the validity of 'functional equivalence' in the East Asian welfare state studies and critically reviews the existing literature. Lastly, this paper suggests how the concept of functional equivalence can be successfully employed for the East Asian welfare states studies with a concept analysis and by applying a set theory including the fuzzy set theory.

• Korean Journal of Social Welfare Studies
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• v.41 no.2
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• pp.279-308
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• 2010

This study examines the association between family policies and family gap using data for 14 OECD countries. As family policies have different assumptions about women's roles and include variant sub-policies, this study identify two distinct family policies: 'employment support policy' to support women as employed workers and 'caregiving support policy' to support women as caregivers. Meanwhile, women's wage cannot be determined by the effect of 'only' family policy. Therefore, analysis model includes variant macro structure supposed to affect women's labor status and wage, like labor market structure, wage structure(compression), women's social status and economic status, and examines interaction effects between family policies and these labor market and social structures using Fuzzy-Set Qualitative Comparative Analysis (FSQCA). The FSQCA result shows that relatively low family gap is associated with the conjunctual causation of developed 'employment support policy' and compressed wage structure.