• Journal of the Korean Operations Research and Management Science Society
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• v.3 no.1
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• pp.81-91
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• 1978

Decision models are an attempt to reduce uncertainty in the decision making process. The models describe the relationships of variables and given proper input data generate solutions to managerial problems. These solutions may not be answers to the problems for one of two reasons. First, the data input into the model may not be consistant with the underlying assumptions of the model being used. Frequently parameters are assumed to be deterministic when in fact they are probabilistic in nature. The second failure is that often the decision maker recognizes that the data available are not appropriate for the model being used and begins to collect the required data. By the time these data has been compiled the solution is no longer an answer to the problem. This relates to the timeliness of decision making. The authors point out throught the use of an illustrative problem that stocastic models are well developed and that they do not suffer from any lack of mathematical exactiness. The primary problem is that generally accepted procedures for data generation are historical in nature and not relevant for probabilistic decision models. The authors advocate that management information system designers and accountants must become more familiar with these decision models and the input data required for their effective implementation. This will provide these professionals with the background necessary to generate data in a form that makes it relevant and timely for the decision making process.

• Fashion & Textile Research Journal
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• v.7 no.6
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• pp.585-593
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• 2005

Diverse and complicated trends of fashion design which were initiated at the latter part of the 20th century have been evolving in the cultural framework of Postmodernism. At this point of time, Poststructuralism, with its aims to interpret and understand modern fashion design, is a new system of thinking that reveals the contradictory aspects of rationalistic Western philosophy and accepts uncertainty and disorder as they exist. The main purpose of this study is to examine the various theoretic systems and characteristic concepts of Poststructuralism, and supply a new cognizance frame to understand the processes of fashion design with free and varied notions of deconstruction and generation, in place of the former systematic and consistent interpretation of meaning. Concerning fashion design, analysis of theories and analysis of contents. By probing and examining deconstruction theory, 'I'-other theory, textual theory, and nomadic thinking, the concepts of cognizance are classified into Nonboundariness, Otherness, and Textualism. The theoretic foundation for this analysis and classification is supplied by Derrida's deconstructional philosophy, Lacan's mental analysis, Bartes's textual theory, Deleuze's change and generation theory, together with other theories of Poststructuralism. In analysis of theories, a cognizance frame is proposed that can categorize the concepts, derived from various theories of Poststructuralism, as traits expressed in fashion design.

• International Journal of Automotive Technology
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• v.8 no.3
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• pp.383-394
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• 2007

Due to the clutch's non-linear dynamics, time-delays, external disturbance and parameter uncertainty, the automated clutch is difficult to control precisely during the launch process or automatic mechanical transmission (AMT) vehicles. In this paper, an enhanced fuzzy sliding mode controller (EFSMC) is proposed to control the automated clutch. The sliding and global stability conditions are formulated and analyzed in terms of the Lyapunov full quadratic form. The chattering phenomenon is handled by using a saturation function to replace the pure sign function and fuzzy logic adaptation system in the control law. To meet the real-time requirement of the automated clutch, the region-wise linear technology s adopted to reduce the fuzzy rules of the EFSMC. The simulation results have shown hat the proposed controller can achieve a higher performance with minimum reaching time and smooth control actions. In addition, our data also show that the controller is effective and robust to the parametric variation and external disturbance.

• Journal of the Korean Society of Safety
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• v.25 no.3
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• pp.91-99
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• 2010

In this study, the advanced numerical algorithm is developed which can performed the static and dynamic stochastic finite element analysis by considering the effect of uncertainties included in the member stiffness of steel cable-stayed bridges and seismic load. After conducting the linear and nonlinear initial shape analysis, the advanced numerical algorithm is the assessment tool which can performed structural the response analysis considering the static linearity and non-linearity of before or after induced intial tensile force, and examined the reliability assessment more efficiently. The verification of the developed numerical algorithm is evaluated by analyzing the regression analysis and coefficient of correlation using the direct monte carlo simulation. Also, the dynamic response characteristic and coefficient of variation of the steel cable-stayed bridge is calculated by considering the uncertainty of random variables using the developed numerical algorithm. In addition, the quantitative structural safety of the steel cable-stayed bridges is evaluated by conducting the reliability assessment based upon the dynamic stochastic finite element analysis result.

• Structural Engineering and Mechanics
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• v.26 no.5
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• pp.517-544
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• 2007

This study shows a fuzzy tuning scheme to fuzzy sliding mode controller (FSMC) for seismic isolation of earthquake-excited structures. The sliding surface can rotate in the phase plane in such a direction that the seismic isolation can be improved. Since ideal sliding mode control requires very fast switch on the input, which can not be provided by real actuators, some modifications to the conventional sliding-mode controller have been proposed based on fuzzy logic. A superior control performance has been obtained with FSMC to deal with problems of uncertainty, imprecision and time delay. Furthermore, using the fuzzy moving sliding surface, the excellent system response is obtained if comparing with the conventional sliding mode controller (SMC), as well as reducing chattering effect. For simulation validation of the proposed seismic response control, 16-floor tall building has been considered. Simulations for six different seismic events, Elcentro (1940), Hyogoken (1995), Northridge (1994), Takochi-oki (1968), the east-west acceleration component of D$\ddot{u}$zce and Bolu records of 1999 D$\ddot{u}$zce-Bolu earthquake in Turkey, have been performed for assessing the effectiveness of the proposed control approach. Then, the simulations have been presented with figures and tables. As a result, the performance of the proposed controller has been quite remarkable, compared with that of conventional SMC.

• Structural Engineering and Mechanics
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• v.68 no.4
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• pp.423-442
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• 2018

In this paper, masonry infilled reinforced concrete (RC) frames are analyzed through a probabilistic approach. A macro-modeling technique, based on an equivalent diagonal pin-jointed strut, has been resorted to for modelling the stiffening contribution of the masonry panels. Since it is quite difficult to decide which mechanical characteristics to assume for the diagonal struts in such simplified model, the strut width is here considered as a random variable, whose stochastic characterization stems from a wide set of empirical expressions proposed in the literature. The stochastic analysis of the masonry infilled RC frame is conducted via the Probabilistic Transformation Method by employing a set of space transformation laws of random vectors to determine the probability density function (PDF) of the system response in a direct manner. The knowledge of the PDF of a set of response indicators, including displacements, bending moments, shear forces, interstory drifts, opens an interesting discussion about the influence of the uncertainty of the masonry infills and the resulting implications in a design process.

• Wind and Structures
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• v.31 no.1
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• pp.59-73
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• 2020

Wind fragility analysis (WFA) of concrete chimney is often executed disregarding temperature effects. But combined wind and temperature effect is the most critical limit state to define the safety of a chimney. Hence, in this study, WFA of a 70 m tall RC chimney for combined wind and temperature effects is explored. The wind force time-history is generated by spectral representation method. The safety of chimney is assessed considering limit states of stress failure in concrete and steel. A moving-least-squares method based dual response surface method (DRSM) procedure is proposed in WFA to alleviate huge computational time requirement by the conventional direct Monte Carlo simulation (MCS) approach. The DRSM captures the record-to-record variation of wind force time-histories and uncertainty in system parameters. The proposed DRSM approach yields fragility curves which are in close conformity with the most accurate direct MCS approach within substantially less computational time. In this regard, the error by the single-level RSM and least-squares method based DRSM can be easily noted. The WFA results indicate that over temperature difference of 150℃, the temperature stress is so pronounced that the probability of failure is very high even at 30 m/s wind speed. However, below 100℃, wind governs the design.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.1
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• pp.43-48
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• 2012

This paper proposes a practical linear recursive robust motion deblurring filter using the inertial sensor measurements for strapdown image seekers. The angular rate information obtained from the gyro mounted on the missile is used to define the PSF(point spread function). Since the gyro output contains a unknown but bounded bias error. the motion blur image model can be expressed as the linear uncertain system. In consequence, the motion deblurring problem can be cast into the robust Kalman filtering which provides reliable state estimates even in the presence of the parametric uncertainty due to the gyro bias. Through the computer simulations using the actual IR scenes, it is verified that the proposed algorithm guarantees the robust motion deblurring performance.

• Earthquakes and Structures
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• v.14 no.5
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• pp.389-398
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• 2018

The seismic isolation system makes a structure isolated from ground motions to protect the structure from seismic events. Seismic isolation techniques have been implemented in full-scale buildings and bridges because of their simplicity, economic effectiveness, inherent stability and reliability. As for the responses of an isolated structure due to seismic events, it is well known that the most uncertain aspects are the seismic loading itself and structural properties. Due to the randomness of earthquakes and uncertainty of structures, seismic response distributions of an isolated structure are needed when evaluating the seismic fragility assessment (or probabilistic seismic safety assessment) of an isolated structure. Seismic response time histories are useful and often essential elements in its design or evaluation stage. Thus, a large number of non-linear dynamic analyses should be performed to evaluate the seismic performance of an isolated structure. However, it is a monumental task to gather the design or evaluation information of the isolated structure from too many seismic analyses, which is impractical. In this paper, a new methodology that can evaluate the seismic fragility assessment of an isolated structure is proposed by using stochastic response database, which is a device that can estimate the seismic response distributions of an isolated structure without any seismic response analyses. The seismic fragility assessment of the isolated nuclear power plant is performed using the proposed methodology. The proposed methodology is able to evaluate the seismic performance of isolated structures effectively and reduce the computational efforts tremendously.

• Earthquakes and Structures
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• v.14 no.5
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• pp.425-436
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• 2018

The design of seismically isolated structures considering the stochastic nature of excitations, base isolators' design parameters, and superstructure properties requires robust reliability analysis methods to calculate the failure probability of the entire system. Here, by applying artificial neural networks, we proposed a robust technique to accelerate the estimation of failure probability of equipped isolated structures. A three-story isolated building with susceptible facilities is considered as the analytical model to evaluate our technique. First, we employed a sensitivity analysis method to identify the critical sources of uncertainty. Next, we calculated the probability of failure for a particular set of random variables, performing Monte Carlo simulations based on the dynamic nonlinear time-history analysis. Finally, using a set of designed neural networks as a surrogate model for the structural analysis, we assessed once again the probability of the failure. Comparing the obtained results demonstrates that the surrogate model can attain precise estimations of the probability of failure. Moreover, our proposed approach significantly increases the computational efficiency corresponding to the dynamic time-history analysis of the structure.