• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.2A
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• pp.89-96
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• 2011

The damping ratio as an index of bridge vibration could be considered as one of the important dynamic characteristics of a suspension bridge. But estimating of damping ratio on an existing suspension bridge under ambient vibration condition could be a laborious task. Moreover, it is not simple to directly distinguish aerodynamic damping and friction damping from apparent damping. According to previous studies, the aerodynamic damping properties can be linearly affected by wind speed level, and apparent damping ratio can be affected by amplitude of vibration. Therefore, in this article, the relationships among damping ratio, wind speed level and amplitude of acceleration were studied for separating extract aerodynamic damping and friction damping from apparent damping. Damping ratios on Sorok Bridge, a suspension bridge which is a located in Go-Heung, Korea, were estimated by two different methods as using Hilbert transform and extended Kalman filter which were well known as effective estimation methods for non-linear state. It was possible to distinguish aerodynamic damping and friction damping from apparent damping using averaged normal components of wind speed, RMQ values of acceleration, and estimated damping ratios from wind-induced vibration responses and vehicle loading responses.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.7 s.98
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• pp.671-680
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• 2005

The CFL linearisation chip which is one of key devices in ultra-narrowband mobile radio transmitter using CQPSK digital modulation method is designed and implemented with $0.35{\mu}m$ CMOS technology. The reduced size and low cost of transmitter are available by the use of direct-conversion and CFL ASIC chip, which improve the power effi챠ency and linearity of transmitting path. In addition, low power operation is possible through CMOS technology The performance test results of transmitter show -25 dBc improvement of IMD level at the 3 kHz frequency offset and then satisfy FCC 47 CFR 90.210 E emission mask in the operation of CFL ASIC chip. At that time, the transmitting power is about PEP(Peak-to-Envelope Power) 5 W. The main parameters to improve the transmitting characteristic and to compensate the distortion in feed back loop such as DC-offset, loop gain and phase value are interfaced with notebook PC to be controlled with S/W.

• Journal of the Korean Society of Radiology
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• v.3 no.1
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• pp.11-15
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• 2009

In this study, the basic research verifying possibility of applications as radiology image sensor in Digital Radiography was performed, the radiology image sensor was fabricated using a multi-layer technique to decrease dark current. High efficiency materials in substitution for Amorphous Selenium(a-Se) have been studied as a direct method of imaging detector in Digital Radiography to decrease dark current by using PN junction or Hetero junction already used as solar cell, semiconductor. Particle-In -Binder method is used to fabricate radiology image sensor because it has a lot of advantages such as fabrication convenient, high yield, suitability for large area sensor. But high leakage current is one of main problem in Particle-In -Binder method. To make up for the weak points, multi-layer technique is used, and it is considered that high efficient digital radiation sensor can be fabricated with easy and convenient process. In this study, electrical properties such as leakage current, sensitivity, signal linearity is measured to evaluate multi-layer radiation sensor material.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.939-953
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• 2023

Shallow water equations (SWE) serve as fundamental equations governing the movement of the water. Traditional numerical approaches for solving these equations generally face various challenges, such as sensitivity to mesh generation, and numerical oscillation, or become more computationally unstable around shock and discontinuities regions. In this study, we present a novel approach that leverages the power of physics-informed neural networks (PINNs) to approximate the solution of the SWE. PINNs integrate physical law directly into the neural network architecture, enabling the accurate approximation of solutions to the SWE. We provide a comprehensive methodology for formulating the SWE within the PINNs framework, encompassing network architecture, training strategy, and data generation techniques. Through the results obtained from experiments, we found that PINNs could be an accurate output solution of SWE when its results were compared with the analytical method. In addition, PINNs also present better performance over the Artificial Neural Network. This study highlights the transformative potential of PINNs in revolutionizing water resources research, offering a new paradigm for accurate and efficient solutions to the SVE.

• Geophysics and Geophysical Exploration
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• v.11 no.1
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• pp.26-33
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• 2008

The analysis of wide-angle seismic reflection and refraction data plays an important role in lithospheric-scale crustal structure study. However, it is extremely difficult to develop an appropriate velocity structure model directly from the observed data, and we have to improve the structure model step by step, because the crustal structure analysis is an intrinsically non-linear problem. There are several subjective processes in wide-angle crustal structure modelling, such as phase identification and trial-and-error forward modelling. Because these subjective processes in wide-angle data analysis reduce the uniqueness and credibility of the resultant models, it is important to reduce subjectivity in the analysis procedure. From this point of view, we describe two software tools, PASTEUP and MODELING, to be used for developing crustal structure models. PASTEUP is an interactive application that facilitates the plotting of record sections, analysis of wide-angle seismic data, and picking of phases. PASTEUP is equipped with various filters and analysis functions to enhance signal-to-noise ratio and to help phase identification. MODELING is an interactive application for editing velocity models, and ray-tracing. Synthetic traveltimes computed by the MODELING application can be directly compared with the observed waveforms in the PASTEUP application. This reduces subjectivity in crustal structure modelling because traveltime picking, which is one of the most subjective process in the crustal structure analysis, is not required. MODELING can convert an editable layered structure model into two-way traveltimes which can be compared with time-sections of Multi Channel Seismic (MCS) reflection data. Direct comparison between the structure model of wide-angle data with the reflection data will give the model more credibility. In addition, both PASTEUP and MODELING are efficient tools for handling a large dataset. These software tools help us develop more plausible lithospheric-scale structure models using wide-angle seismic data.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.17 no.2
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• pp.33-44
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• 2012

Transparent exopolymer particles (TEP) are formed by aggregation of polysaccharide products excreted by phytoplankton and have sticky character like gel. They play important role in the production of marine snow in water column. To study the distribution pattern of TEP concentration and its role in carbon cycle in the surface ocean, we measured pH, Total alkalinity (TA), and chlorophyll-a in addition to physical characteristics of seawater within the surface water column. TEP concentrations ranged from nearly undetectable values to $338{\mu}g\;Xeq\;l^{-1}$. They were considerably lower than previously reported values from costal sites, but showed similar values observed in other oceanic region during phytoplankton bloom periods. The spatial distribution of TEP concentrations were similar to those of chlorophyll-a, which indicate that the production of TEP were closely related to phytoplankton. Calculated total dissolved inorganic carbon ($TCO_2$) from the pH and TA was normalized to 35 psu of salinity ($NTCO_2$) and showed negative linear relationship with temperature. Biological drawdown of $NTCO_2$ ($NTCO_{2bio}$) was estimated from the difference between theoretical $NTCO_2$ values and observed $NTCO_2$. In the warm region located south of $40^{\circ}N$ along the $132.5^{\circ}N$ meridional lines, $NTCO_{2bio}$ showed negative value and TEP concentrations were high. This suggested that negative $NTCO_{2bio}$ may be attributed to the biological processes. At the stations located between 44 and $46^{\circ}N$, TEP concentrations showed high concentration at the chlorophyll-a maximum layer within the water column while they showed low concentration in the surface layer. Carbon content of TEP constituted about 40% of $NTCO_{2bio}$ at the chlorophylla maximum layer. In this study, we could not observe any positive and negative relationship between TEP concentration and $NTCO_2$ or pH. It is obvious that we should consider the importance of TEP in the biological carbon cycling processes within surface layer.

• Journal of radiological science and technology
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• v.39 no.1
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• pp.59-69
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• 2016

The objective of this study was to analyze the factors influencing integrated bolus peak timing in contrast-enhanced computed tomographic angiography (CTA) and to determine a method of calculating personal peak time. The optimal time was calculated by performing multiple linear regression analysis, after finding the influence factors through correlation analysis between integrated peak time of contrast medium and personal measured value by monitoring CTA scans. The radiation exposure dose in CTA was $716.53mGy{\cdot}cm$ and the radiation exposure dose in monitoring scan was 15.52 mGy (2 - 34 mGy). The results were statistically significant (p < .01). Regression analysis revealed, a -0.160 times decrease with a one-step increase in heart rate in male, and -0.004, -0.174, and 0.006 times decrease with one-step in DBP, heart rate, and blood sugar, respectively, in female. In a consistency test of peak time by calculating measured peak time and peak time by using the regression equation, the consistency was determined to be very high for male and female. This study could prevent unnecessary dose exposure by encouraging in clinic calculation of personal integrated peak time of contrast medium prior to examination.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.387-397
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• 2023

Plant height is a growth parameter that provides visible insights into the plant's growth status and has a high correlation with yield, so it is widely used in crop breeding and cultivation research. Investigation of the growth characteristics of crops such as plant height has generally been conducted directly by humans using a ruler, but with the recent development of sensing and image analysis technology, research is being attempted to digitally convert growth measurement technology to efficiently investigate crop growth. In this study, the canopy height of rice grown at various nitrogen fertilization levels was measured using a laser scanner capable of precise measurement over a wide range, and a comparative analysis was performed with the actual plant height. As a result of comparing the point cloud data collected with a laser scanner and the actual plant height, it was confirmed that the estimated plant height measured based on the average height of the top 1% points showed the highest correlation with the actual plant height (R² = 0.93, RMSE = 2.73). Based on this, a linear regression equation was derived and used to convert the canopy height measured with a laser scanner to the actual plant height. The rice growth curve drawn by combining the actual and estimated plant height collected by various nitrogen fertilization conditions and growth period shows that the laser scanner-based canopy height measurement technology can be effectively utilized for assessing the plant height and growth of rice. In the future, 3D images derived from laser scanners are expected to be applicable to crop biomass estimation, plant shape analysis, etc., and can be used as a technology for digital conversion of conventional crop growth assessment methods.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.