• Structural Engineering and Mechanics
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• v.71 no.1
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• pp.89-98
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• 2019

In this study, the mechanical bending behaviors of functionally graded porous nanobeams are investigated. Four types of porosity which are, the classical power porosity function, the symmetric with mid-plane cosine function, bottom surface distribution and top surface distribution are proposed in analysis of nanobeam for the first time. A comparison between four types of porosity are illustrated. The effect of nano-scale is described by the differential nonlocal continuum theory of Eringen by adding the length scale into the constitutive equations as a material parameter comprising information about nanoscopic forces and its interactions. The graded material is designated by a power function through the thickness of nanobeam. The beam is simply-supported and is assumed to be thin, and hence, the kinematic assumptions of Euler-Bernoulli beam theory are held. The mathematical model is solved numerically using the finite element method. Numerical results show effects of porosity type, material graduation, and nanoscale parameters on the static deflection of nanobeam.

• Journal of the Ergonomics Society of Korea
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• v.25 no.2
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• pp.187-196
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• 2006

This study aims to develop luxuriousness models based on both users' subjective feelings and objective material characteristics of automobile crash pad using Kansei engineering approach. Based on the results of literature survey and FGI, 12 Kansei variables describing look-and-feel and touch feel and crash pad design variables were extracted for systematically developing both a conceptual model of luxuriousness and a questionnaire for Kansei evaluation. A total of 41 various crash pad samples and 60 participants(customers: 30, designers: 30) were employed to evaluate the crash pad samples using the questionnaire with 9-point semantic differential scale and 100-point modified magnitude estimate scale. Based on the survey results, luxuriousness models were developed by using regression and quantification I method. In addition, they were compared and contrasted with respect to the relative importance of Kansei variables. Consequently, the developed luxurious model could suggest the preferred combination of material properties of crash pad.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.109-117
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• 2015

This paper proposes the comparison results of various optimal power flow algorithms (OPF) to calculate the locational marginal prices (LMP) of the unreduced full scale Korean transmission system. Five different types of optimal power flow models are employed: Full AC OPF, Cubic AC OPF, Quadratic AC OPF, Linear AC OPF and DC OPF. As the results, full AC OPF and cubic AC OPF model provides LMP calculation results very similar to each other while the calculation time of cubic AC OPF model is faster than that of the Full AC OPF. Other simplified OPF models, quadratic AC OPF, linear AC OPF and DC OPF offer erroneous results even though the calculation times are much faster than the Full AC OPF and the Cubic AC OPF. Given the condition that the OPF models sometimes fail to find the optimal solution due to the severe complexity of the Korean transmission power system, the Full AC OPF should be used as the primary OPF model while the Cubic AC OPF can be a promising backup OPF model for the LMP calculations and/or real-time operation.

• Biotechnology and Bioprocess Engineering:BBE
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• v.10 no.5
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• pp.408-417
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• 2005

Increasing numbers of value added chemicals are being produced using microbial fermentation strategies. Computational modeling and simulation of microbial metabolism is rapidly becoming an enabling technology that is driving a new paradigm to accelerate the bioprocess development cycle. In particular, constraint-based modeling and the development of genome-scale models of industrial microbes are finding increasing utility across many phases of the bioprocess development workflow. Herein, we review and discuss the requirements and trends in the industrial application of this technology as we build toward integrated computational/experimental platforms for bioprocess engineering. Specifically we cover the following topics: (1) genome-scale models as genetically and biochemically consistent representations of metabolic networks; (2) the ability of these models to predict, assess, and interpret metabolic physiology and flux states of metabolism; (3) the model-guided integrative analysis of high throughput 'omics' data; (4) the reconciliation and analysis of on- and off-line fermentation data as well as flux tracing data; (5) model-aided strain design strategies and the integration of calculated biotransformation routes; and (6) control and optimization of the fermentation processes. Collectively, constraint-based modeling strategies are impacting the iterative characterization of metabolic flux states throughout the bioprocess development cycle, while also driving metabolic engineering strategies and fermentation optimization.

• Structural Engineering and Mechanics
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• v.53 no.3
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• pp.393-410
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• 2015

Two dimensional numerical models and physical models have been developed to study the highly nonlinear interactions between waves and breakwaters, but several of these models consider the effects of the structural dynamic responses and the shape of the breakwater axis on the wave pressures. In this study, a multi-material Arbitrary Lagrangian Eulerian (ALE) method is developed to simulate the nonlinear interactions between nonlinear waves and elastic seawalls on a coastal rubble mound breakwater, and is validated experimentally. In the experiment, a solitary wave is generated and used with a physical breakwater model. The wave impact is validated computationally using a breakwater - flume coupling model that replicates the physical model. The computational results, including those for the wave pressure and the water-on-deck, are in good agreement with the experimental results. A local breakwater model is used to discuss the effects of the structural dynamic response and different design parameters of the breakwater on wave loads, together with pressure distribution up the seawall. A large-scale breakwater model is used to numerically study the large-scale wave impact problem and the horizontal distribution of the wave pressures on the seawalls.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.36-39
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• 1998

It is very difficult for the large-scale retailers, who deal with tens of thousands of items, to price all the items dynamically reflecting all the constraints and policies. In spite of its importance, the prices are determined by human experts because the process of setting the prices of all the items is not established yet. To solve this problem, we adopt a mixed model that combines three typical pricing models: cost-plus model, competition-oriented model, and demand-oriented model. Since each model an be converted to a set of constraints in point and interval forms, solving the pricing problem with the three groups of models requires an algorithm which can solve the problem with weighted constraints of intervals and points. So we have devised an algorithm named “Point Determination Algorithm”. From the rules that represents tile models, the constraints are extracted to be solvable by tile Point Determination Algorithm. A prototype KAPA (Knowledge Assisted pricing Advisor) is developed with this idea using the expert system environment UNIK - a tool developed by KAIST. According to the experiment with 76 items in comparison with 53 human pricing experts we confirmed that the KAPA can perform highly consistent with human experts. This implies KAPA system is applicable to pricing millions of items dynamically.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.3
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• pp.67-72
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• 2010

This paper presents biometrical driver verification system in car experiment through analysis of speech, and face information. We have used Mel-scale Frequency Cesptral Coefficients (MFCCs) for speaker verification using speech information. For face verification, face region is detected by AdaBoost algorithm and dimension-reduced feature vector is extracted by using principal component analysis only from face region. In this paper, we apply the extracted speech- and face feature vectors to an SVM kernel with Gaussian Mixture Models(GMM) supervector. The experimental results of the proposed approach show a clear improvement compared to a simple GMM or SVM approach.

• Journal of the Korea Safety Management & Science
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• v.13 no.1
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• pp.195-202
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• 2011

The study interprets each of three classification models based on Bath-Tub Failure Rate (BTFR), Extreme Value Distribution (EVD) and Conjugate Bayesian Distribution (CBD). The classification model based on BTFR is analyzed by three failure patterns of decreasing, constant, or increasing which utilize systematic management strategies for reliability of time. Distribution model based on BTFR is identified using individual factors for each of three corresponding cases. First, in case of using shape parameter, the distribution based on BTFR is analyzed with a factor of component or part number. In case of using scale parameter, the distribution model based on BTFR is analyzed with a factor of time precision. Meanwhile, in case of using location parameter, the distribution model based on BTFR is analyzed with a factor of guarantee time. The classification model based on EVD is assorted into long-tailed distribution, medium-tailed distribution, and short-tailed distribution by the length of right-tail in distribution, and depended on asymptotic reliability property which signifies skewness and kurtosis of distribution curve. Furthermore, the classification model based on CBD is relied upon conjugate distribution relations between prior function, likelihood function and posterior function for dimension reduction and easy tractability under the occasion of Bayesian posterior updating.

• Advances in biomechanics and applications
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• v.1 no.1
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• pp.67-76
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• 2014

Bone properties are one of the key components when constructing models that can simulate the mechanical behavior of a mandible. Due to the complexity of the structure, the tooth, ligaments, different bones etc., some simplifications are often considered and bone properties are one of them. The objective of this study is to understand if a simplification of the problem is possible and assess its influence on mandible behavior. A cadaveric toothless mandible was used to build three computational models from CT scan information: a full cortical bone model; a cortical and cancellous bone model, and a model where the Young's modulus was obtained as function of the pixel value in a CT scan. Twelve muscle forces were applied on the mandible. Results showed that although all the models presented the same type of global behavior and proximity in some locations, the influence of cancellous bone can be seen in strain distribution. The different Young's modulus defined by the CT scan gray scale influenced the maximum and minimum strains. For modeling general behavior, a full cortical bone model can be effective. However, when cancellous bone is included, maximum values in thin regions increase the strain distribution. Results revealed that when properties are assigned to the gray scale some peaks could occur which did not represent the real situation.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.40.4-41
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• 2018

The current 'standard model' of cosmology provides a minimal theoretical framework that can explain the gaussian, nearly scale-invariant density perturbations observed in the CMB to the late time clustering of galaxies. However accepting this framework, requires that we include within our cosmic inventory a vacuum energy that is ~122 orders of magnitude lower than Quantum Mechanical predictions, or alternatively a new scalar field (dark energy) that has negative pressure. An alternative approach to adding extra components to the Universe would be to modify the equations of Gravity. Although GR is supported by many current observations there are still alternative models that can be considered. Recently there have been many works attempting to test for modified gravity using the large scale clustering of galaxies, ISW, cluster abundance, RSD, 21cm observations, and weak lensing. In this work, we compare various modified gravity models using cosmic shear data from the Deep Lens Survey as well as data from CMB, SNe Ia, and BAO. We use the Bayesian Evidence to quantify the comparison robustly, which naturally penalizes complex models with weak data support. In this talk we present our methodology and preliminary results that show f(R) gravity is mildly disfavoured by the data.