• Korean Journal of Social Welfare
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• v.64 no.2
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• pp.31-54
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• 2012

Along with increasing mothers' employment, work-family reconciliation has been recognised as a key policy agenda in contemporary welfare states. Although various policy instruments have been introduced and expanded in recent years, the problem of time allocation within couples still remains as a fundamental issue, which has been largely underresearched at a micro perspective. In this context, this study aims to identify dominant types of work-family time allocation within married couple, and to apply these types to the Korean case using the fuzzy-set ideal type analysis. Further, a series of multiple regression analyses will be implemented to find factors affecting each ideal type of work-family time allocation. The 1999 and 2009 Korea Time Use Survey datasets will be adopted for the analyses. Married couples are selected as samples only when men work 40 hours or more per week and they have at least one pre-school child. Empirical analyses cover three parts. First of all, four ideal types on work-family time allocation are classified by intersecting two core variables - the ratio of men's (paid) working and family (caring time plus domestic work) time to total working and family time. In this research, the four types will be labelled the traditional male breadwinner model (TM, high working and low family time), the dual burden model (DB, shared working but low family time), the family-friendly male breadwinner model (FM, high working but shared family time), and the adaptive partnership model (AP, shared working and shared family time). By comparing the composition of the four ideal types in 1999 and 2009, it will examine the trend of work-family time allocation in Korea. In addition, multiple regressions will be useful for investigating which characteristics contribute to the different degree of each fuzzy ideal score in the four models. Finally, policy implications and further research agenda will be discussed.

• Steel and Composite Structures
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• v.35 no.6
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• pp.753-763
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• 2020

In this article, the influence of fuzzified uncertain composite elastic properties on non-linear deformation behaviour of the composite structure is investigated under external mechanical loadings (uniform and sinusoidal distributed loading) including the different end boundaries. In this regard, the composite model has been derived considering the fuzzified elastic properties (through a triangular fuzzy function, α cut) and the large geometrical distortion (Green-Lagrange strain) in the framework of the higher-order mid-plane kinematics. The results are obtained using the fuzzified nonlinear finite element model via in-house developed computer code (MATLAB). Initially, the model accuracy has been established and explored later to show the dominating elastic parameter affect the deflection due to the inclusion of fuzzified properties by solving a set of new numerical examples.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.6
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• pp.64-72
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• 2010

In general, due to the interactions among subsystems, it is difficult to design an decentralized controller for nonlinear interconnected systems. In this study, the model of nonlinear interconnected systems is studied via decentralized fuzzy control method with time delay and polytopic uncertainty. First, the nonlinear interconnected system is represented by an equivalent Takagi-Sugeno type fuzzy model. And the represented model can be rewritten as Parameterized Linear Matrix Inequalities(PLMIs), that is, LMIs whose coefficients are functions of a parameter confined to a compact set. We show that the resulting fuzzy controller guarantees the asymptotic stability and disturbance attenuation of the closed-loop system in spite of controller gain variations within a resulted polytopic region by example and simulations.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.525-531
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• 2020

In today's IT environment where various pieces of information are distributed in large volumes, recommendation systems are in the spotlight capable of figuring out users' needs fast and helping them with their decisions. The current recommendation systems, however, have a couple of problems including that user preference may not be reflected on the systems right away according to their changing tastes or interests and that items with no relations to users' preference may be recommended, being induced by advertising. In an effort to solve these problems, this study set out to propose a Fuzzy-AHP-based movie recommendation system by applying the BRNN(Bidirectional Recurrent Neural Network) language model. Applied to this system was Fuzzy-AHP to reflect users' tastes or interests in clear and objective ways. In addition, the BRNN language model was adopted to analyze movie-related data collected in real time and predict movies preferred by users. The system was assessed for its performance with grid searches to examine the fitness of the learning model for the entire size of word sets. The results show that the learning model of the system recorded a mean cross-validation index of 97.9% according to the entire size of word sets, thus proving its fitness. The model recorded a RMSE of 0.66 and 0.805 against the movie ratings on Naver and LSTM model language model, respectively, demonstrating the system's superior performance in predicting movie ratings.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.268-268
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• 1998

• Spatial Information Research
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• v.7 no.2
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• pp.223-236
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• 1999

Recently, the need of wast incineratory has been recognized. However, the waste incinerator is considered the typical example of NYMB syndrome as a locally unwanted facilities. Therefore, the site selection of waste incineratory should be determined very carefully with consideration of various location factors. The purpose of this study is to provide a new decision-making process model for site selection that provides a rational and a systematic way. The fuzzy set theory and AHP theory, which have merits to overcome uncertainly and complexity of spatial data, are applied to select candidate sites for the waste incineratory. The method is able to produce a more flexible and objective solution for selecting suitability sites in comparison to rigid boolean logic. The result of this study shows that geographic information systems have clear implication for informing the spatial decision making process.

• Earthquakes and Structures
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• v.24 no.6
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• pp.429-437
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• 2023

This paper studied the prediction of structural damage indices to buildings after earthquake occurrence using Multiple Linear Regression (MLR) and Fuzzy Linear Regression (FLR) methods. Particularly, the structural damage degree, represented by the Maximum Inter Story Drift Ratio (MISDR), is an essential factor that ensures the safety of the building. Thus, the seismic response of a steel building was evaluated, utilizing 65 seismic accelerograms as input signals. Among the several response quantities, the focus is on the MISDR, which expresses the postseismic damage status. Using MLR and FLR methods and comparing the outputs with the corresponding evaluated by nonlinear dynamic analyses, it was concluded that the FLR method had the most accurate prediction results in contrast to the MLR method. A blind prediction applying a set of another 10 artificial accelerograms also examined the model's effectiveness. The results revealed that the use of the FLR method had the smallest average percentage error level for every set of applied accelerograms, and thus it is a suitable modeling tool in earthquake engineering.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.546-551
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• 2004

In this paper, a level controller is designed with the neuro-fuzzy model based on Takagi-Sugeno fuzzy system. The fuzzy system is employed as the controller, which can be tuned by the neural network mechanism based on a gradient descent technique. The tuning mechanism will provide an optimal process input by forcing the process error to zero. The proposed controller provides the online tunable mode to adjust the consequent membership function parameters. The controller is implemented with M-file and graphic user interface (GUI) of Matlab program. The program uses MPIBM3 interface card to connect with the industrial processes In the experimentation, the proposed method is tested to vary of the process parameters, set points and load disturbance. Processes of one tank and two tanks are used to evaluate the efficiency of our controller. The results of the both processes are compared with two PID systems that are 3G25A-PIDO1-E and E5AK of OMRON. From the comparison results, our controller performance can be archived in the case of more robustness than the two PID systems.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1272-1278
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• 1999

A fault is considered as a variation of physical parameters; therefore the design of fault detection and identification(FDI) can be reduced to the parameter identification of a non linear system and to the association of the set of the estimated parameters with the mode of faults. Neuro-Fuzzy Inference System which contains multiple linear models as consequent part is used to model nonlinear systems. Generally, the linear parameters in neuro-fuzzy inference system can be effectively utilized to fault diagnosis. In this paper, we proposes an FDI system for nonlinear systems using neuro-fuzzy inference system. The proposed diagnostic system consists of two neuro-fuzzy inference systems which operate in two different modes (parallel and series-parallel mode). It generates the parameter residuals associated with each modes of faults which can be further processed by additional RBF (Radial Basis Function) network to identify the faults. The proposed FDI scheme has been tested by simulation on two-tank system.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.25-36
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• 2005

In this study, we suggested a new approach method forecasting distribution demand of urban rail transit usign fuzzy control, with intend to reflect irregularity and various functional relationship between trip length and distribution demand. To establish fuzzy control model and test this model, the actual trip volume(production, attraction and distribution volume) and trip length (space distance between a departure and arrival station) of Daegu subway line 1 were used. Firstly, usign these data we established a fuzzy control model, nd the estimation accuracy of the model was examined and compared with that of generalized gravity model. The results showed that the fuzzy control model was superior to gravity model in accuracy of estimation. Therefore, wwe found that fuzzy control was able to be applied as a effective method to predict the distribution demand of urban rail transit. Finally, to increase the estimation precision of the model, we expect studies that define membership functions and set up fuzzy rules organized with neural networks.