• Structural Engineering and Mechanics
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• 제69권1호
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• pp.105-120
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• 2019

In this paper, a new efficient method for structural modal reanalysis is proposed, which can handle large finite element (FE) models requiring frequent design modifications. The global FE model is divided into a residual part not to be modified and a target part to be modified. Then, an automated matrix permutation and substructuring algorithm is applied to these parts independently. The reduced model for the residual part is calculated and saved in the initial analysis, and the target part is reduced repeatedly, whenever design modifications occur. Then, the reduced model for the target part is assembled with that of the residual part already saved; thus, the final reduced model corresponding to the new design is obtained easily and rapidly. Here, the formulation of the proposed method is derived in detail, and its computational efficiency and reanalysis ability are demonstrated through several engineering problems, including a topological modification.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2008년 영문 학술대회
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• pp.525-530
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• 2008

We present a model for simulating high energy laser heating and ignition of confined energetic materials. The model considers effect of ablation of steel plate with long laser pulses and continuous lasers of several kilowatts and the thermal response of well-characterized high explosives for ignition. Since there is enough time for the thermal wave to propagate into the target and to create a region of hot spot in the high explosives, electron thermal diffusion of ultra-short(femto- and pico-second) lasing is ignored; instead, heat diffusion of absorbed laser energy in the solid target is modeled with thermal decomposition kinetic models of high explosives are used. Numerically simulated pulsed-laser heating of solid target and thermal explosion of cyclotrimethylenetrinitramine(RDX), triaminotrinitrobenzene(TATB), and octahydrotetranitrotetrazine(HMX) are compared to experimental results. The experimental and numerical results are in good agreement.

• 산업공학
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• 제16권spc호
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• pp.144-148
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• 2003

A group of digital human models with various sizes which properly represents a population under consideration is needed in the design process of an ergonomic product in virtual environment. The present study proposes a two-step method which produces a representative group of human models in terms of stature and weight. The proposed method first generates a designated number of pairs of stature and weight within an accommodation range from the bivariate normal distribution of stature and weight of the target population. Then, from each pair of stature and weight, the method determines the sizes of body segments by using 'hierarchical' regression models and corresponding prediction distributions of individual values. The suggested method was applied to the 1988 US Army anthropometric survey data and implemented to a web-based system which generates a representative group of human models for the following parameters: nationality, gender, accommodation percentage, and number of human models.

• Geomechanics and Engineering
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• 제37권6호
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• pp.629-641
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• 2024

The presence of excavations or cavities beneath the foundations of a building can have a significant impact on their stability and cause extensive damage. Traditional methods for calculating the bearing capacity and subsidence of foundations over cavities can be complex and time-consuming, particularly when dealing with conditions that vary. In such situations, machine learning (ML) and deep learning (DL) techniques provide effective alternatives. This study concentrates on constructing a prediction model based on the performance of ML and DL algorithms that can be applied in real-world settings. The efficacy of eight algorithms, including Regression Analysis, k-Nearest Neighbor, Decision Tree, Random Forest, Multivariate Regression Spline, Artificial Neural Network, and Deep Neural Network, was evaluated. Using a Python-assisted automation technique integrated with the PLAXIS 2D platform, a dataset containing 272 cases with eight input parameters and one target variable was generated. In general, the DL model performed better than the ML models, and all models, except the regression models, attained outstanding results with an R² greater than 0.90. These models can also be used as surrogate models in reliability analysis to evaluate failure risks and probabilities.

• 융합정보논문지
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• 제11권2호
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• pp.82-89
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• 2021

본 연구의 목적은 투자자의 은퇴 시점뿐만 아니라 시장의 예측 변동성을 동시에 고려하여 Target Date Fund의 위험자산 편입 비율을 동적으로 조정하는 새로운 Glide Path를 제안하고, 은퇴 시점만 고려하여 위험자산 편입 비율이 정해지는 전통적 Glide Path와 투자 성과를 비교 분석하는 것이다. 시장 변동성의 예측치로는 역사적 변동성, 시계열모형인 GARCH 변동성, 그리고 변동성지수인 VKOSPI를 활용하였으며, 2003년부터 2020년까지의 분석 기간에서 변동성을 고려하는 새로운 동적 Glide Path의 투자 성과가 우수함을 보여주었다. 3가지 변동성 예측모형 모두에서 은퇴 시점만을 고려하는 Glide Path보다 수익률은 더 높고 위험은 더 낮아지면서 투자 성과 지표인 Sharpe Ratio가 개선되었다. 실증 분석 결과는 은퇴예정자뿐만 아니라 Target Date Fund 운용업계에 새로운 Glide Path의 활용 가능성을 제시하고 있다.

• Journal of Korea Trade
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• 제25권1호
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• pp.65-88
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• 2021

Purpose - This paper aims to examine the determinants of SWFs' investment in Asian countries and to identify consistent investment patterns of SWFs in specific target firms from Asia, particularly China and South Korea. Design/methodology - This study extends the Tobin's Q model to examine the relationship between SWF investments in target firms and their returns with other firm-level control variables. We collect consistent data on SWF investments and the matched firm-level data on target firms, which of observation is 1,512 firms (333 in South Korea and 1,179 in China) targeted by 20 SWF sources during 1997-2017. The panel random effect model is used to estimate the extended Tobin's Q model. The robustness of the estimations is tested by the simultaneous equation models and the panel GEE model. Findings - The evidence shows that sovereign wealth funds are more inclined to invest in the financial sector with a monopoly position and in large firms with higher growth opportunity and superior cash asset ratios in China. In contrast to their investments in China, sovereign wealth funds in South Korea prefer to invest in strategic sectors, such as energy and information technology, and in large firms with high performance and low leverage. Sovereign wealth funds' investments tend to significantly improve the target firm's performance measured by sales growth and returns in both Korea and China. Originality/value - The existing literature focuses on examining the determination of SWFs investment in the developed countries, such as Europe and the United States. Our paper contributes to the literature in three ways; first, we analyzes case studies of SWF investments in Asian markets, which are less developed and riskier. Second, we examine whether the determination of SWF investment in Asian target firms depends on the different time periods, on types of sources of SWFs, and on acquiring countries. Third, our research uses vast sample data on target firms in longer time periods (1997-2017) than other previous studies on the SWFs for Asian markets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권2호
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• pp.365-380
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• 2022

The target detection algorithm based on supervised learning is the current mainstream algorithm for target detection. A high-quality dataset is the prerequisite for the target detection algorithm to obtain good detection performance. The larger the number and quality of the dataset, the stronger the generalization ability of the model, that is, the dataset determines the upper limit of the model learning. The convolutional neural network optimizes the network parameters in a strong supervision method. The error is calculated by comparing the predicted frame with the manually labeled real frame, and then the error is passed into the network for continuous optimization. Strongly supervised learning mainly relies on a large number of images as models for continuous learning, so the number and quality of images directly affect the results of learning. This paper proposes a dataset STAR-24K (meaning a dataset for Space TArget Recognition with more than 24,000 images) for detecting common targets in space. Since there is currently no publicly available dataset for space target detection, we extracted some pictures from a series of channels such as pictures and videos released by the official websites of NASA (National Aeronautics and Space Administration) and ESA (The European Space Agency) and expanded them to 24,451 pictures. We evaluate popular object detection algorithms to build a benchmark. Our STAR-24K dataset is publicly available at https://github.com/Zzz-zcy/STAR-24K.

• 대한인간공학회지
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• 제26권1호
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• pp.103-109
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• 2007

Representative human models (RHMs), a group of digital human models which represent the people of the target population within a designated percentage (e.g., 95%), are used for ergonomic design and evaluation in virtual environments. The present study evaluated the grid approach, a RHM generation method, in terms of accommodation percentage. RHMs generated from the grid approach dramatically decreased the accommodation percentage of the target population as the number of anthropometric dimensions under consideration increased. For example, the accommodation percentages by RHMs generated by the grid approach were 95% for 3 key dimensions (selected among 10 anthropometric dimensions), 45% for 5 dimensions, and 10% for 10 dimensions. A standardized multiple regression analysis found that this decreasing accommodation percentage was caused by low correlations between key dimensions and other dimensions. The accommodation evaluation process used in the present study is applicable to evaluation of other RHM generation methods.

• Ocean and Polar Research
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• 제34권1호
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• pp.85-91
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• 2012

Physical properties such as sound speed contrast (h) and density contrast (g) of the interested target are key parameters to understand acoustic characteristics by using theoretical scattering models. The density and sound speed of moon jellyfish (common jellyfish, Aurelia aurita s.l.) were measured. Sound speed contrast (h) was measured from travel time difference (time-of-flight method) of an acoustic signal in a water tank for APOP studies (Acoustic Properties Of zooplankton). Density contrast (g) was measured by the displacement volume and wet weight (dual-density method). The sound speed remained almost constant as the moon jellyfish increased in bell length. The mean values${\pm}$standard deviation of h and g were $1.0005{\pm}0.0012$ and $0.9808{\pm}0.0195$), respectively. These results will provide important input for use in theoretical scattering models for estimating the acoustic target strength of jellyfish.

• 한국우주과학회:학술대회논문집(한국우주과학회보)
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• 한국우주과학회 2009년도 한국우주과학회보 제18권2호
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• pp.49.4-50
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• 2009

We report stray light modeling and analysis results for the current and proposed next generation ocean color imagers with Sun and the target area around Korean penninsular as viewed from geostationary orbit. The imagers used in this study are GOCI of 140mm in diameter and a proposed next generation GOCI (GOCI-II) of about 300mm in diameter. First, we built complete GOCI and GOCI-II 3D optical system models with the realistic surface characteristics. These optical models were incorporated into the in-house built Intergrated Ray Tracing (IRT) algorithm, connecting the Sun, the measurement target area and the instruments via single ray tracing computation for radiative transfer and scattering. The stray light level was then estimated for possible orbital configurations for science measurement and in-orbit calibration operation. The simulation details, results and their implications are presented.