• Wind and Structures
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• 제3권4호
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• pp.267-277
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• 2000

This paper aims to describe the aerodynamic vibrations of various structural elements of bridges, which are particular issues at present. The aerodynamic countermeasures for those vibrations are also discussed considering the generation mechanisms of the aerodynamic instabilities. In this paper, an example of vortex-induced oscillation of bridge deck and its lesson are discussed. Next, the wind-induced cable vibration and its aerodynamic countermeasures are reviewed. Then, the aerodynamic characteristics on two edge girders and their feasibility for application to long span cable-stayed bridges are considered. Furthermore, the bridge decks for future long span bridges are proposed and their aerodynamic characteristics are also discussed.

• 한국전자파학회논문지
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• 제13권8호
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• pp.790-796
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• 2002

우리나라에는 역사적으로 아름답고 소중한 목조 건축물들이 문화재로 보존되고 있다. 그러나 목조 건축물들은 오랜 세월동안 풍화작용, 병충해 등과 같은 거친 환경조건에 노출되어 있다. 이러한 원인으로 인하여 건축물에 구조적 결함을 야기하기도 한다. 따라서 사전에 목조 건축물을 진단할 수 있는 방법이 필요하다. 본 논문에서는 목조 건축물의 비파괴 검사에 표면하부 탐사 레이더의 적용 가능성을 3차원 유한차분 시간영역 모의계산과 실제 측정을 통하여 조사하였다.

• Smart Structures and Systems
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• 제12권3_4호
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• pp.381-397
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• 2013

In this paper, wireless health monitoring of stay cables using piezoelectric strain sensors and a smart skin technique is presented. For the cables, tension forces are estimated to examine their health status from vibration features with consideration of temperature effects. The following approaches are implemented to achieve the objective. Firstly, the tension force estimation utilizing the piezoelectric sensor-embedded smart skin is presented. A temperature correlation model to recalculate the tension force at a temperature of interest is designed by correlating the change in cable's dynamic features and temperature variation. Secondly, the wireless health monitoring system for stay cables is described. A piezoelectric strain sensor node and a tension force monitoring software which is embedded in the sensor are designed. Finally, the feasibility of the proposed monitoring technique is evaluated on stay cables of the Hwamyung Grand Bridge in Busan, Korea.

• 한국방재학회:학술대회논문집
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• 한국방재학회 2008년도 정기총회 및 학술발표대회
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• pp.67-70
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• 2008

This study is to analyzes the global behavior of frame structures with local cracks in structural members by frame analysis, using the stiffness matrix of cracked frame element. This local compliance is utilized to derive the stiffness matrix of the cracked frame element and the effects of interaction among multiple cracks are also examined. The proposed technique is applied to frame structures with local cracks. Analysis results confirm the possibility of quantitative analysis of a structure damaged with local cracks and the feasibility of the technique as a tool for analyzing the global behavior of frame structures, reflecting effects of local cracks.

• International Journal of Safety
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• 제5권2호
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• pp.1-5
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• 2006

A data acquisition and processing system for measuring the current collection signals of the Korean High-speed Railway is developed. The current collection system is composed of a pantograph and the overhead catenary that supplies electrical power to the train through the pantograph. The system simultaneously measures the signals generated at the interface between the catenary and the pantograph through the accelerometers, load cells and strain gauges placed at various locations. The on-track test data are processed to evaluate the current collection reliability. The fiequency analysis of the signals reveals the presence of several structural vibration modes in the pantograph, as well as the components arising from the periodicity in the structure of the catenary and pantograph at the interface. The feasibility of predicting the contact performance from the measured signals is also demonstrated.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2003년도 춘계학술대회
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• pp.329-337
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• 2003

Stock market prediction is regarded as a challenging task of financial time-series prediction. There have been many studies using artificial neural networks in this area. Recently, support vector machines (SVMs) are regarded as promising methods for the prediction of financial time-series because they me a risk function consisting the empirical ewer and a regularized term which is derived from the structural risk minimization principle. In this study, I apply SVM to predicting the Korea Composite Stock Price Index (KOSPI). In addition, this study examines the feasibility of applying SVM in financial forecasting by comparing it with back-propagation neural networks and case-based reasoning. The experimental results show that SVM provides a promising alternative to stock market prediction.

• Journal of Contemporary Eastern Asia
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• 제20권2호
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• pp.237-258
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• 2021

The COVID-19 pandemic has highlighted the risks of an over-concentration of supply chains in one country. It has motivated stakeholders to pursue diversification strategies. However, a paradox exists. Stakeholders have shied away from a complete decoupling and preferring to selectively enhance economic ties with China. This article explores this paradox by examining supply chain concentration in China as a form of asymmetric interdependence and the countermeasures from the U.S., Japan, Australia, and India to minimize vulnerabilities. It argues that while the COVID-19 disruptions have brought to light the risk of supply chain overconcentration in China, countermeasures are also driven by coercive diplomacy and the deepening U.S.-China rivalry. The paper also examines the feasibility of diversification efforts by focusing on the capacity and capabilities of alternative supply chain hubs. It finds that while states are actively seeking ways to prevent China from using asymmetric interdependence of supply chains and trade to gain political leverage, there are structural limits to the degree of diversification in the short to mid-term.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권2호
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• pp.871-891
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• 2019

Visual tracking is a challenging task that needs learning an effective model to handle the changes of target appearance caused by factors such as pose variation, illumination change, occlusion and motion blur. In this paper, a novel tracking algorithm based on weighted local sub-space reconstruction error is presented. First, accounting for the appearance changes in the tracking process, a generative weight calculation method based on structural reconstruction error is proposed. Furthermore, a template update scheme of occlusion-aware is introduced, in which we reconstruct a new template instead of simply exploiting the best observation for template update. The effectiveness and feasibility of the proposed algorithm are verified by comparing it with some state-of-the-art algorithms quantitatively and qualitatively.

• 국제강구조저널
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• 제18권5호
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• pp.1560-1576
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• 2018

With the aim to provide an efficient platform for the elastic-plastic analysis of steel structures, reinforced concrete (RC) structures and steel-concrete composite structures, a program iFiberLUT based on the fiber model was developed within the framework of ABAQUS. This program contains an ABAQUS Fiber Generator which can automatically divide the beam and column cross sections into fiber sections, and a material library which includes several concrete and steel uniaxial material models. The range of applications of iFiberLUT is introduced and its feasibility is verified through previously reported test data of individual structural members as well as planar steel frames, RC frames and composite frames subjected to various loadings. The simulation results indicate that the developed program is able to achieve high calculation accuracy and favorable convergence within a wide range of applications.

• Structural Engineering and Mechanics
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• 제80권5호
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• pp.539-551
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• 2021

With the continuous increase of computational capacity, more and more complex nonlinear elastoplastic constitutive models were developed to study the mechanical behavior of elastoplastic materials. These constitutive models generally contain a large amount of physical and phenomenological parameters, which often require a large amount of computational costs to determine. In this paper, an inverse parameter determination method is proposed to identify the constitutive parameters of elastoplastic materials, with the consideration of both strain rate effect and temperature effect. To carry out an efficient design, a hybrid optimization algorithm that combines the genetic algorithm and the Nelder-Mead simplex algorithm is proposed and developed. The proposed inverse method was employed to determine the parameters for an elasto-viscoplastic constitutive model and Johnson-cook model, which demonstrates the capability of this method in considering strain rate and temperature effect, simultaneously. This hybrid optimization algorithm shows a better accuracy and efficiency than using a single algorithm. Finally, the predictability analysis using partial experimental data is completed to further demonstrate the feasibility of the proposed method.