• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.775-779
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• 2002

Currently, high-resolution satellite imagery such as KOMPSAT and IKONOS has been tentatively utilized to various types of urban engineering problems such as transportation planning, site planning, and utility management. This approach aims at software development and followed applications of remotely sensed imagery to transportation geographic analysis. At first, GDPA (Gradient Direction Profile Algorithm) and main modules in it are overviewed, and newly implemented results under MS visual programming environment are presented with main user interface, input imagery processing, and internal processing steps. Using this software, road network are automatically generated. Furthermore, this road network is used to transportation geographic analysis such as gamma index and road pattern estimation. While, this result, being produced to do-facto format of ESRI-shapefile, is used to several types of road layers to urban/transportation planning problems. In this study, road network using KOMPSAT EOC imagery and IKONOS imagery are directly compared to multiple road layers with NGI digital map with geo-coordinates, as ground truth; furthermore, accuracy evaluation is also carried out through method of computation of commission and omission error at some target area. Conclusively, the results processed in this study is thought to be one of useful cases for further researches and local government application regarding transportation geographic analysis using remotely sensed data sets.

• Structural Engineering and Mechanics
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• 제59권1호
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• pp.153-186
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• 2016

This paper addresses temperature-dependent nonlinear vibration and instability of embedded functionally graded (FG) pipes conveying viscous fluid-nanoparticle mixture. The surrounding elastic medium is modeled by temperature-dependent orthotropic Pasternak medium. Reddy third-order shear deformation theory (RSDT) of cylindrical shells are developed using the strain-displacement relations of Donnell theory. The well known Navier-Stokes equation is used for obtaining the applied force of fluid to pipe. Based on energy method and Hamilton's principal, the governing equations are derived. Generalized differential quadrature method (GDQM) is applied for obtaining the frequency and critical fluid velocity of system. The effects of different parameters such as mode numbers, nonlinearity, fluid velocity, volume percent of nanoparticle in fluid, gradient index, elastic medium, boundary condition and temperature gradient are discussed. Numerical results indicate that with increasing the stiffness of elastic medium and decreasing volume percent of nanoparticle in fluid, the frequency and critical fluid velocity increase. The presented results indicate that the material in-homogeneity has a significant influence on the vibration and instability behaviors of the FG pipes and should therefore be considered in its optimum design. In addition, fluid velocity leads to divergence and flutter instabilities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2529-2543
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• 2019

Scanning electron microscopy (SEM) image can link with the microscopic world through reflecting interaction between electrons and materials. The SEM images are easily subject to blurring distortions during the imaging process. Inspired by the fact that dark channel prior captures the changes to blurred SEM images caused by the blur process, we propose a method to evaluate the SEM images sharpness based on the dark channel prior. A SEM image database is first established with mean opinion score collected as ground truth. For the quality assessment of the SEM image, the dark channel map is generated. Since blurring is typically characterized by the spread of edge, edge of dark channel map is extracted. Then noise is removed by an edge-preserving filter. Finally, the maximum gradient and the average gradient of image are combined to generate the final sharpness score. The experimental results on the SEM blurred image database show that the proposed algorithm outperforms both the existing state-of-the-art image sharpness metrics and the general-purpose no-reference quality metrics.

• 한국산업융합학회 논문집
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• 제25권3호
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• pp.467-476
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• 2022

The Bank of Korea raised the benchmark interest rate by a quarter percentage point to 1.75 percent per year, and analysts predict that South Korea's policy rate will reach 2.00 percent by the end of calendar year 2022. Furthermore, because market volatility has been significantly increased by a variety of factors, including rising rates, inflation, and market volatility, many investors have struggled to meet their financial objectives or deliver returns. Banks and financial institutions are attempting to provide Robo-Advisors to manage client portfolios without human intervention in this situation. In this regard, determining the best hyper-parameter combination is becoming increasingly important. This study compares some activation functions of the Deep Deterministic Policy Gradient(DDPG) and Twin-delayed Deep Deterministic Policy Gradient (TD3) Algorithms to choose a sequence of actions that maximizes long-term reward. The DDPG and TD3 outperformed its benchmark index, according to the results. One reason for this is that we need to understand the action probabilities in order to choose an action and receive a reward, which we then compare to the state value to determine an advantage. As interest in machine learning has grown and research into deep reinforcement learning has become more active, finding an optimal hyper-parameter combination for DDPG and TD3 has become increasingly important.

• Advances in nano research
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• 제11권6호
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• pp.621-640
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• 2021

Effect of thickness stretching on mechanical behavior of functionally graded (FG) carbon nanotubes reinforced composite (CNTRC) laminated nanoplates resting on elastic foundation is analyzed in this paper using a novel quasi 3D higher-order shear deformation theory. The key feature of this theoretical formulation is that, in addition to considering the thickness stretching effect, the number of unknowns of the displacement field is reduced to four, and which is more than five in the other models. Single-walled carbon nanotubes (SWCNTs) are the reinforced elements and are distributed with four power-law functions which are, uniform distribution, V-distribution, O-distribution and X-distribution. To cover various boundary conditions, an analytical solution is developed based on Galerkin method to solve the governing equilibrium equations by considering the nonlocal strain gradient theory. A modified two-dimensional variable Winkler elastic foundation is proposed in this study for the first time. A parametric study is executed to determine the influence of the reinforcement patterns, power-law index, nonlocal parameter, length scale parameter, thickness and aspect ratios, elastic foundation, thermal environments, and various boundary conditions on stresses, displacements, buckling loads and frequencies of the CNTRC laminated nanoplate.

• 대한원격탐사학회지
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• 제40권2호
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• pp.123-139
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• 2024

Forest vertical structure is vital for comprehending ecosystems and biodiversity, in addition to fundamental forest information. Currently, the forest vertical structure is predominantly assessed via an in-situ method, which is not only difficult to apply to inaccessible locations or large areas but also costly and requires substantial human resources. Therefore, mapping systems based on remote sensing data have been actively explored. Recently, research on analyzing and classifying images using machine learning techniques has been actively conducted and applied to map the vertical structure of forests accurately. In this study, Sentinel-2 and digital surface model images were obtained on two different dates separated by approximately one month, and the spectral index and tree height maps were generated separately. Furthermore, according to the acquisition time, the input data were separated into cases 1 and 2, which were then combined to generate case 3. Using these data, forest vetical structure mapping models based on random forest, support vector machine, and extreme gradient boost(XGBoost)were generated. Consequently, nine models were generated, with the XGBoost model in Case 3 performing the best, with an average precision of 0.99 and an F1 score of 0.91. We confirmed that generating a forest vertical structure mapping model utilizing bi-seasonal data and an appropriate model can result in an accuracy of 90% or higher.

• Animal cells and systems
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• 제3권2호
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• pp.153-159
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• 1999

In an artificial pH-gradient batch culture system, the effects of acidification on the species composition of a heterotrophic bacterial community were analyzed. As a result of this study, it was found that total bacteria numbers were not affected by acidification and that the population of hetero-trophic bacteria decreased as pH became lower. The heterotrophic bacteria isolated from the entire pH gradient were 12 genera and 22 species. Among them, 64% were gram negative and 36% were gram positive bacteria. As pH decreased, the distribution rate of gram negative bacteria increased while that of gram positive bacteria decreased. The diversity of genera decreased from 13 to 5 as pH decreased from 7 to 3. The G+C content of all of the 202 isolated strains varied from 22.8 to 77.0%, and increased in interspecies of same genus as pH decreased. As a result of clustering analysis, the diversity index of species ranged from 1.13 to 2.37, and it had lower indices as pH decreased. In order to evaluate the diversity of numbers of sample of different size, a rarefaction method was used to analyze the expected number of species appearance according to pH. The statistical significance of species diversity was verified by the fact that the number decreased at lower pH.

• 한국토양비료학회지
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• 제45권1호
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• pp.30-36
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• 2012

The active fraction of soil organic matter, which includes organic debris and light organic fraction, plays a major role in nutrient cycling. In addition, particulate organic matter is a valuable index of labile soil organic matter and can reflect differences in various soil behaviors. Since soil organic matter bound to soil mineral particles has its density lower than soil minerals, we partitioned soil organic matter into debris ($<1.5g\;cm^{-3}$), light fraction ($1.5-2.0g\;cm^{-3}$), and heavy fraction ($>2.0g\;cm^{-3}$), based on high density $ZnCl_{2-}$ sucrose solutions. Generally, partitioned organic bands were clearly separated, demonstrating that the $ZnCl_{2-}$ sucrose solutions are useful for such a density gradient centrifugation. The available gradient ranges from 1.2 to $2.0g\;cm^{-3}$. Although there was not a statistically meaningful difference in organic debris and organomineral fractions among the examined soils, there was a general trend that a higher content of organic debris resulted in a higher proportion of light organomineral fraction. In addition, high clay content was associated with increased fraction of light organomineals. Partitioning of soil organic carbon revealed that carbon content is reduced in the heavy fraction than in the light fraction, reflecting that the light fraction contains more fresh and abundant carbon than the passive resistant fraction. It was also found that carbon contents in the overall organic matter, debris, light fraction, and heavy fractions may differ considerably in response to different farming practices.

• 한국수자원학회논문집
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• 제51권8호
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• pp.713-727
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• 2018

본 연구는 국내 하천의 고유성을 반영할 수 있는 물리적 환경평가 체계를 개발하는 것이다. 하천유형 분류, 평가구간 선정, 평가 항목 및 지표에 대하여 종합적으로 요약하였다. 하천의 물리적 구조는 하천 유수력에 의한 반응의 결과이므로 하도경사, 하상재료의 입경 및 하도지형의 특성에 따라 하천을 3가지 유형으로 분류하였다. 평가구간은 각 하천 유형의 대표적인 특징인 step 또는 여울출현 간격, 사행도에 따라 저수로 폭의 10배와 25배 기준으로 선정하였다. 평가지표는 하도 안정성, 흐름 상태, 횡단면 형상, 하안 안정성, 하도개수 및 하천횡단구조물과 같은 공통지표와 유효 서식지, 하상 매몰도, 흐름의 다양성 및 step과 여울 출현빈도와 같은 하천 유형별 특성지표로 구성되어 있다. 적용성 검토를 위하여 개발된 평가체계를 9개의 하천에 적용하고 그 결과를 제시하였다.

• Geomechanics and Engineering
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• 제37권5호
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• pp.475-498
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• 2024

The prediction of the susceptibility of soil to liquefaction using a limited set of parameters, particularly when dealing with highly unbalanced databases is a challenging problem. The current study focuses on different ensemble learning classification algorithms using highly unbalanced databases of results from in-situ tests; standard penetration test (SPT), shear wave velocity (V_s) test, and cone penetration test (CPT). The input parameters for these datasets consist of earthquake intensity parameters, strong ground motion parameters, and in-situ soil testing parameters. liquefaction index serving as the binary output parameter. After a rigorous comparison with existing literature, extreme gradient boosting (XGBoost), bagging, and random forest (RF) emerge as the most efficient models for liquefaction instance classification across different datasets. Notably, for SPT and V_s-based models, XGBoost exhibits superior performance, followed by Light gradient boosting machine (LightGBM) and Bagging, while for CPT-based models, Bagging ranks highest, followed by Gradient boosting and random forest, with CPT-based models demonstrating lower G_mean(error), rendering them preferable for soil liquefaction susceptibility prediction. Key parameters influencing model performance include internal friction angle of soil (ϕ) and percentage of fines less than 75 µ (F₇₅) for SPT and V_s data and normalized average cone tip resistance (q_c) and peak horizontal ground acceleration (a_max) for CPT data. It was also observed that the addition of V_s measurement to SPT data increased the efficiency of the prediction in comparison to only SPT data. Furthermore, to enhance usability, a graphical user interface (GUI) for seamless classification operations based on provided input parameters was proposed.