• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.500-506
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• 2019

In this study, we present a decision function of optimal smoothing parameter for baseline correction using Asymmetrically reweighted penalized least squares (arPLS). Baseline correction is very important due to influence on performance of spectral analysis in application of spectroscopy. Baseline is often estimated by parameter selection using visual inspection on analyte spectrum. It is a highly subjective procedure and can be tedious work especially with a large number of data. For these reasons, an objective procedure is necessary to determine optimal parameter value for baseline correction. The proposed function is defined by modeling the median value of possible parameter range as the length and order of the background signal. The median value increases as the length of the signal increases and decreases as the degree of the signal increases. The simulated data produced a total of 112 signals combined for the 7 lengths of the signal, adding analytic signals and linear and quadratic, cubic and 4th order curve baseline respectively. According to the experimental results using simulated data with linear, quadratic, cubic and 4th order curved baseline, and real Raman spectra, we confirmed that the proposed function can be effectively applied to optimal parameter selection for baseline correction using arPLS.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.6
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• pp.347-352
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• 2018

This study proposes seismic response analysis technique of a two-mass rack system which sustains heavy loads with frictional behavioral characteristics. In order to deal with the nonlinear frictional characteristics of the mass on the rack system, the equations of motion of the system has been derived and the appropriate numerical simulation technique has been developed. In order to examine the seismic performance of the proposed system, we consider two parameters that are expected to have great influence on the seismic performance of the system. One is the ratio of the two masses of the load and the rack structure, and the other is the friction coefficient between rack and loaded mass. A number of numerical simulations of the seismic response of structures with various natural frequencies for both parameters have been performed in order to investigate the seismic safety of the rack structures. From the simulated results. it is observed that the maximum displacement of the rack system tends to decrease drastically as the natural frequency of the structure increases regardless of the two parameters of mass ratio and friction coefficient. The proposed study provides important reference data to guarantee the seismic safety of the rack system by considering nonlinear frictional behavior of the loaded mass.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.585-590
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• 2019

The purpose of this study is to summarize the changes in virtual reality utilization in model houses through the time-by-year example of model houses and to study the use and future development of virtual reality technologies in model houses. As a result of compiling and analyzing characteristics of virtual reality utilization flow in model houses of apartments, it is as follows. First, the market for apartment model houses using virtual reality was gradually expanded for the purpose of brand promotion by private construction companies. Second, technologies that utilize virtual reality in apartment sales are changing from virtual space construction to virtual content implementation. Third, it is changing from the existing method of face-to-face and method of accessing actual promotional media to the form of publicizing apartments using virtual reality. Through this research, it is estimated that it will be used as an information medium and a form of experience using physical environment and virtual reality in a physical model house for consumers looking for model houses. This study presents the future direction of the model house, and develops it as a post-sale maintenance / management system through ICT technology (3D scanning, 3D modeling, virtual content) Further research on the technology is expected to be needed.

• The Korean Journal of Archival Studies
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• no.46
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• pp.5-44
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• 2015

This article purposes to define archival justice and suggest democratic modeling of the archive on the Truth and Reconciliation Committee (TRC), which is focused on victims of state violence. These purposes come from critical mind that the absence of framework of the records management for collective memory would cause incorporation of TRC archives into mainstream archives systems in which voices of victims have been marginalized. This article intends to expand theoretical prospects of documentation of past affairs through applying humanistic and theoretical frameworks differently from institutional and policy approaches on restoration of collective memory. In order to do this, this article first considers archival justice as archives building in which state violence' victims are pivotal and then extracts theoretical frameworks for building the archives based on archival justice from recent discourses of post-colonial archives and community archives. As the next step, it criticizes current conditions of TRC archives in Korea on the basis of extracted theoretical frames and finally suggests realistic models in which each theoretical frame could be applied effectively into TRC archives that is focused on victims.

• Journal of Korean Society on Water Environment
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• v.35 no.3
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• pp.224-233
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• 2019

Nitrogen components in liquid manure can reduce safety and quality of environment harmfully. To minimize the environmental risks of manure, understanding fate of manure in environment is necessary. This study aimed at investigating applicability of a simplified Level III fugacity model for simulating $NH_3-N$ component to analyze environmental fate and transport of $NH_3-N$ in liquid manure and to provide basis for improving management of N in the liquid manure system and for minimizing the environmental impacts of N. The model simulation conducted for four environmental compartments (air, water, soil, and rice plants) during rice-cropping to trace $NH_3-N$ component and provided applicability of the Level III fugacity model in studying the environmental fate of $NH_3-N$ in manure. Most of $NH_3-N$ was found in water body and in rice plants depending upon the physicochemical properties and proper removal processes. For more precise model results, the model is needed to modify with the detailed removal processes in each compartment and to collect proper and accurate information for input parameters. Further study should be about simulations of various N-typed fertilizers to compare with the liquid manure based on a modified and relatively simplified Level III fugacity model.

• Journal of Korea Water Resources Association
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• v.54 no.10
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• pp.747-757
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• 2021

Quantification of extreme rainfall is very important in establishing a flood protection plan, and a general measure of extreme rainfall is expressed as an T-year return level. In this study, a method was proposed for quantifying spatial distribution and uncertainty of daily rainfall depths with various return periods using a hierarchical Bayesian model combined with climate and geographical information, and was applied to the Seoul-Incheon-Gyeonggi region. The annual maximum daily rainfall depth of six automated synoptic observing system weather stations of the Korea Meteorological Administration in the study area was fitted to the generalized extreme value distribution. The applicability and reliability of the proposed method were investigated by comparing daily rainfall quantiles for various return levels derived from the at-site frequency analysis and the regional frequency analysis based on the index flood method. The uncertainty of the regional frequency analysis based on the index flood method was found to be the greatest at all stations and all return levels, and it was confirmed that the reliability of the regional frequency analysis based on the hierarchical Bayesian model was the highest. The proposed method can be used to generate the rainfall quantile maps for various return levels in the Seoul-Incheon-Gyeonggi region and other regions with similar spatial sizes.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.446-457
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• 2020

Crescentic sand bar in the coastal zone of eastern Korea is a common morphological feature and the rhythmic patterns exist constantly except for high wave energy events. However, four consecutive typhoons that directly and indirectly affected the East Sea of Korea from September to October in 2019 impacted the formation of longshore uniform sand bar and overall shoreline retreats (approx. 2 m) although repetitive erosion and accretion patterns exist near the shoreline. Widely used XBeach to predict storm erosions in the beach is utilized to investigate the morphological response to a series of storms and each storm impact (NE-E wave incidence). Several calibration processes for improved XBeach modeling are conducted by recently reported calibration methods and the optimal calibration set obtained is applied to the numerical simulation. Using observed wave, tide, and pre & post-storm bathymetries data with optimal calibration set for XBeach input, XBeach successfully reproduces erosion and accretion patterns near MSL (BSS = 0.77 (Erosion profile), 0.87 (Accretion profile)) and observed the formation of the longshore uniform sandbar. As a result of analysis of simulated total sediment transport vectors and bed level changes at each storm peak Hs, the incident wave direction contributes considerable impact to the behavior of crescentic sandbar. Moreover, not only the wave height but also storm duration affects the magnitude of the sediment transport. However, model results suggest that additional calibration processes are needed to predict the exact crest position of bar and bed level changes across the inner surfzone.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.6
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• pp.547-553
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• 2020

As aging infrastructures increase along with time, the efficient maintenance becomes more significant and accurate responses from the sensors are pre-requisite. Among various responses, strain is commonly used to detect damage such as crack and fatigue. Optical fiber sensor is one of the promising sensing techniques to measure strains with high-durability, immunity for electrical noise, long transmission distance. Fiber Bragg Grating (FBG) is a point sensor to measure the strain based on reflected signals from the grating, while Brillouin Optic Correlation Domain Analysis (BOCDA) is a distributed sensor to measure the strain along with the optical fiber based on scattering signals. Although the FBG provides the signal with high accuracy and reproducibility, the number of sensing points is limited. On the other hand, the BOCDA can measure a quasi-continuous strain along with the optical fiber. However, the measured signals from BOCDA have low accuracy and reproducibility. This paper proposed a multi-fidelity data-fusion method based on Gaussian Process Regression to improve the fidelity of the strain distribution by fusing the advantages of both systems. The proposed method was evaluated by laboratory test. The result shows that the proposed method is promising to improve the fidelity of the strain.

• The Journal of Bigdata
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• v.5 no.2
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• pp.53-67
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• 2020

This study employees a supervised learning prediction model to detect nonconformity in advance of processed food manufacturing and processing businesses. The study was conducted according to the standard procedure of machine learning, such as definition of objective function, data preprocessing and feature engineering and model selection and evaluation. The dependent variable was set as the number of supervised inspection detections over the past five years from 2014 to 2018, and the objective function was to maximize the probability of detecting the nonconforming companies. The data was preprocessed by reflecting not only basic attributes such as revenues, operating duration, number of employees, but also the inspections track records and extraneous climate data. After applying the feature variable extraction method, the machine learning algorithm was applied to the data by deriving the company's risk, item risk, environmental risk, and past violation history as feature variables that affect the determination of nonconformity. The f1-score of the decision tree, one of ensemble models, was much higher than those of other models. Based on the results of this study, it is expected that the official food control for food safety management will be enhanced and geared into the data-evidence based management as well as scientific administrative system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.175-182
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• 2020

The non-contact eye tracking is a nonintrusive human-computer interface providing hands-free communications for people with severe disabilities. Recently. it is expected to do an important role in non-contact systems due to the recent coronavirus COVID-19, etc. This paper proposes a novel approach for an eye mouse using an eye tracking method based on a context-aware based AdaBoost multi-region classifier and ASSL algorithm. The conventional AdaBoost algorithm, however, cannot provide sufficiently reliable performance in face tracking for eye cursor pointing estimation, because it cannot take advantage of the spatial context relations among facial features. Therefore, we propose the eye-region context based AdaBoost multiple classifier for the efficient non-contact gaze tracking and mouse implementation. The proposed method detects, tracks, and aggregates various eye features to evaluate the gaze and adjusts active and semi-supervised learning based on the on-screen cursor. The proposed system has been successfully employed in eye location, and it can also be used to detect and track eye features. This system controls the computer cursor along the user's gaze and it was postprocessing by applying Gaussian modeling to prevent shaking during the real-time tracking using Kalman filter. In this system, target objects were randomly generated and the eye tracking performance was analyzed according to the Fits law in real time. It is expected that the utilization of non-contact interfaces.