• Title/Summary/Keyword: Range Accuracy

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Influence of Digestion Temperature on the Extraction of Soil Heavy Metal by Korean Ministry of Environment Standard Method (토양오염공정시험기준에 따른 토양 중금속 추출 시 분해 온도가 미치는 영향)

  • Shin, Gunhwan;Park, Hyunjung;Oh, Kiseok;Jung, Gain;Shin, Dongjun;Lee, Goontaek;Joo, Changkyu;Lee, Sangmo;Kim, Taeseung
    • Journal of Soil and Groundwater Environment
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    • v.27 no.3
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    • pp.11-21
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    • 2022
  • The purpose of this study was to evaluate the influences of digestion temperature on the extraction of heavy metals from soil using the standard method established by Korean Ministry of Environment (KMES). A total of 7 heavy metals (As, Cd, Cr, Cu, Ni, Pb and Zn) in soil samples were extracted at varying digestion temperatures [(66 ± 2.0)℃, (73 ± 1.9)℃, (80 ± 1.3)℃, (85 ± 1.7)℃, (92 ± 2.0)℃, (98 ± 1.7)℃]. As, Cd, Cu, Pb and Zn concentrations remained relatively constant over the temperature range, but Ni and Cr concentrations greatly varied with the digestion temperature. The extent of variation in extraction efficiencies as compared to the concentration obtained at 66℃ was in following order; Ni (7.09% ~ 35.42%) > Cr (4.79% ~ 25.40%) > Zn (3.99% ~ 17.52%) > Cu (2.22% ~ 19.34%) > As (3.54% ~ 8.26%) > Cd (-5.08% ~ 1.08%) > Pb (-4.71% ~ -1.70%). The accuracy for certified reference materials at the digestion temperature of 80 and 85℃ was 98.7% ~ 105.8%. Therefore, digestion temperature of 80℃ ~ 85℃ is suggested to obtain reliable and reproducible data when the standard method by Korean Ministry of Environment is employed to analyze multiple heavy metal components in soil samples.

The Effect of Ground Heterogeneity on the GPR Signal: Numerical Analysis (지반의 불균질성이 GPR탐사 신호에 미치는 영향에 대한 수치해석적 분석)

  • Lee, Sangyun;Song, Ki-il;Ryu, Heehwan;Kang, Kyungnam
    • Journal of the Korean GEO-environmental Society
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    • v.23 no.8
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    • pp.29-36
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    • 2022
  • The importance of subsurface information is becoming crucial in urban area due to increase of underground construction. The position of underground facilities should be identified precisely before excavation work. Geophyiscal exporation method such as ground penetration radar (GPR) can be useful to investigate the subsurface facilities. GPR transmits electromagnetic waves to the ground and analyzes the reflected signals to determine the location and depth of subsurface facilities. Unfortunately, the readability of GPR signal is not favorable. To overcome this deficiency and automate the GPR signal processing, deep learning technique has been introduced recently. The accuracy of deep learning model can be improved with abundant training data. The ground is inherently heteorogeneous and the spacially variable ground properties can affact on the GPR signal. However, the effect of ground heterogeneity on the GPR signal has yet to be fully investigated. In this study, ground heterogeneity is simulated based on the fractal theory and GPR simulation is carried out by using gprMax. It is found that as the fractal dimension increases exceed 2.0, the error of fitting parameter reduces significantly. And the range of water content should be less than 0.14 to secure the validity of analysis.

A LiDAR-based Visual Sensor System for Automatic Mooring of a Ship (선박 자동계류를 위한 LiDAR기반 시각센서 시스템 개발)

  • Kim, Jin-Man;Nam, Taek-Kun;Kim, Heon-Hui
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.6
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    • pp.1036-1043
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    • 2022
  • This paper discusses about the development of a visual sensor that can be installed in an automatic mooring device to detect the berthing condition of a vessel. Despite controlling the ship's speed and confirming its location to prevent accidents while berthing a vessel, ship collision occurs at the pier every year, causing great economic and environmental damage. Therefore, it is important to develop a visual system that can quickly obtain the information on the speed and location of the vessel to ensure safety of the berthing vessel. In this study, a visual sensor was developed to observe a ship through an image while berthing, and to properly check the ship's status according to the surrounding environment. To obtain the adequacy of the visual sensor to be developed, the sensor characteristics were analyzed in terms of information provided from the existing sensors, that is, detection range, real-timeness, accuracy, and precision. Based on these analysis data, we developed a 3D visual module that can acquire information on objects in real time by conducting conceptual designs of LiDAR (Light Detection And Ranging) type 3D visual system, driving mechanism, and position and force controller for motion tilting system. Finally, performance evaluation of the control system and scan speed test were executed, and the effectiveness of the developed system was confirmed through experiments.

Automated Image Matching for Satellite Images with Different GSDs through Improved Feature Matching and Robust Estimation (특징점 매칭 개선 및 강인추정을 통한 이종해상도 위성영상 자동영상정합)

  • Ban, Seunghwan;Kim, Taejung
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1257-1271
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    • 2022
  • Recently, many Earth observation optical satellites have been developed, as their demands were increasing. Therefore, a rapid preprocessing of satellites became one of the most important problem for an active utilization of satellite images. Satellite image matching is a technique in which two images are transformed and represented in one specific coordinate system. This technique is used for aligning different bands or correcting of relative positions error between two satellite images. In this paper, we propose an automatic image matching method among satellite images with different ground sampling distances (GSDs). Our method is based on improved feature matching and robust estimation of transformation between satellite images. The proposed method consists of five processes: calculation of overlapping area, improved feature detection, feature matching, robust estimation of transformation, and image resampling. For feature detection, we extract overlapping areas and resample them to equalize their GSDs. For feature matching, we used Oriented FAST and rotated BRIEF (ORB) to improve matching performance. We performed image registration experiments with images KOMPSAT-3A and RapidEye. The performance verification of the proposed method was checked in qualitative and quantitative methods. The reprojection errors of image matching were in the range of 1.277 to 1.608 pixels accuracy with respect to the GSD of RapidEye images. Finally, we confirmed the possibility of satellite image matching with heterogeneous GSDs through the proposed method.

Evaluation of Short and Long-Term Modal Parameters of a Cable-Stayed Bridge Based on Operational Modal Analysis (운용모드해석에 기반한 사장교의 장단기 동특성 평가)

  • Park, Jong-Chil
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.26 no.4
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    • pp.20-29
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    • 2022
  • The operational modal analysis (OMA) technique, which extracts the modal parameters of a structural system using ambient vibrations, has been actively developed as a field of structural health monitoring of cable-supported bridges. In this paper, the short and long-term modal parameters of a cable-stayed bridge were evaluated using the acceleration data obtained from the two ambient vibration tests (AVTs) and three years of continuous measurements. A total of 27 vertical modes and 1 lateral mode in the range 0.1 ~ 2.5 Hz were extracted from the high-resolution AVTs which were conducted in the 6th and 19th years after its completion. Existing OMA methods such as Peak-Picking (PP), Eigensystem Realization Algorithm with Data Correlation (ERADC), Frequency Domain Decomposition (FDD) and Time Domain Decomposition (TDD) were applied for modal parameters extraction, and it was confirmed that there was no significant difference between the applied methods. From the correlation analysis between long-term natural frequencies and environmental factors, it was confirmed that temperature change is the dominant factor influencing natural frequency fluctuations. It was revealed that the decreased natural frequencies of the bridge were not due to changes in structural performance and integrity, but to the environmental effects caused by the temperature difference between the two AVTs. In addition, when the TDD technique is applied, the accuracy of extracted mode shapes is improved by adding a proposed algorithm that normalizes the sequence so that the autocorrelations at zero lag equal 1.

Prediction of Beach Profile Change Using Machine Learning Technique (머신러닝을 이용한 해빈단면 변화 예측)

  • Shim, Kyu Tae;Cho, Byung Sun;Kim, Kyu Han
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.42 no.5
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    • pp.639-650
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    • 2022
  • In areas where large-scale sediment transport occurs, it is important to apply appropriate countermeasure method because the phenomenon tends to accelerate by time duration. Among the various countermeasure methods applied so far, beach nourishment needs to be reviewed as an erosion prevention measure because the erosion pattern is mitigated and environmentally friendly depending on the particle size. In the case of beach nourishment. a detailed review is required to determine the size, range, etc., of an appropriate particle diameter. In this study, we investigated the characteristics of the related topographic change using the change in the particle size of nourishment materials, the application of partial area, and the condition under the coexistence of waves and wind as variables because those factors are hard to be analyzed and interpreted within results and limitation of that the existing numerical models are not able to calculate and result out so that it is required that phenomenon or efforts are reviewed at the same time through physical model experiments, field monitoring and etc. So we attempt to reproduce the tendency of beach erosion and deposition and predict possible phenomena in the future using machine learning techniques for phenomena that it is not able to be interpreted by numerical models. we used the hydraulic experiment results for the training data, and the accuracy of the prediction results according to the change in the training method was simultaneously analyzed. As a result of the study it was found that topographic changes using machine learning tended to be similar to those of previous studies in short-term predictions, but we also found differences in the formation of scour and sandbars.

Development of a Microspot Spectroscopic Ellipsometer Compatible with Atomic Force Microscope (원자힘 현미경 융합형 마이크로스폿 분광타원계 개발)

  • In, Sun Ja;Lee, Min Ho;Cho, Sung Yong;Hong, Jun Seon;Baek, In Ho;Kwon, Yong Hyun;Yoon, Hee Kyu;Kim, Sang Youl
    • Korean Journal of Optics and Photonics
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    • v.33 no.5
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    • pp.201-209
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    • 2022
  • The previously developed microspot spectroscopic ellipsometer (SE) is upgraded to a microspot SE compatible with the atomic force microscope (AFM). The focusing optical system of the previous microspot SE is optimized to incorporate an AFM head. In addition, the rotating compensator ellipsometer in polarizer-sample-compensator-analyzer configuration is adopted in order to minimize the negative effects caused by beam wobble. This research leads to the derivation of the expressions needed to get spectro-ellipsometric constants despite the fact that the employed rotating compensator is far from the ideal achromatic quarter-wave plate. The spot size of the developed microspot SE is less than 20 ㎛ while the AFM head is mounted. It operates in the wavelength range of 190-850 nm and has a measurement accuracy of δΔ ≤ 0.05° and δΨ ≤ 0.02°, respectively. Fast measurement of ≤3 s/sp is realized by precisely synchronizing the azimuthal angle of a rotating compensator with the spectrograph. The microspot SE integrated with an AFM is expected to be useful in characterizing the structure and optical properties of finely patterned samples.

Implementation of Real-time Sedentary Posture Correction Cushion Using Capacitive Pressure Sensor Based on Conductive Textile

  • Kim, HoonKi;Park, HyungSoo;Oh, JiWon
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.2
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    • pp.153-161
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    • 2022
  • Physical activities are decreasing and sitting time is increasing due to the automation, smartization, and intelligence of necessary household items throughout daily life. Recent healthcare studies have reported that the likelihood of obesity, diabetes, cardiovascular disease, and early death increases in proportion to sitting time. In this paper, we develop a sitting posture correction cushion in real time using capacitive pressure sensor based on conductive textile. It develops a pressure sensor using conductive textile, a key component of the posture correction cushion, and develops a low power-based pressure measurement circuit. It provides a function to transmit sensor values measured in real time to smartphones using BLE short-range wireless communication on the posture correction cushion, and develops a mobile application to check the condition of the sitting posture through these sensor values. In the mobile app, you can visualize your sitting posture and check it in real time, and if you keep it in the wrong posture for a certain period of time, you can notify it through an alarm. In addition, it is possible to visualize the sitting time and posture accuracy in a graph. Through the correction cushion in this paper, we experiment with how effective it is to correct the user's posture by recognizing the user's sitting posture, and present differentiation and excellence compared to other product.

Multi-fidelity uncertainty quantification of high Reynolds number turbulent flow around a rectangular 5:1 Cylinder

  • Sakuma, Mayu;Pepper, Nick;Warnakulasuriya, Suneth;Montomoli, Francesco;Wuch-ner, Roland;Bletzinger, Kai-Uwe
    • Wind and Structures
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    • v.34 no.1
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    • pp.127-136
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    • 2022
  • In this work a multi-fidelity non-intrusive polynomial chaos (MF-NIPC) has been applied to a structural wind engineering problem in architectural design for the first time. In architectural design it is important to design structures that are safe in a range of wind directions and speeds. For this reason, the computational models used to design buildings and bridges must account for the uncertainties associated with the interaction between the structure and wind. In order to use the numerical simulations for the design, the numerical models must be validated by experi-mental data, and uncertainties contained in the experiments should also be taken into account. Uncertainty Quantifi-cation has been increasingly used for CFD simulations to consider such uncertainties. Typically, CFD simulations are computationally expensive, motivating the increased interest in multi-fidelity methods due to their ability to lev-erage limited data sets of high-fidelity data with evaluations of more computationally inexpensive models. Previous-ly, the multi-fidelity framework has been applied to CFD simulations for the purposes of optimization, rather than for the statistical assessment of candidate design. In this paper MF-NIPC method is applied to flow around a rectan-gular 5:1 cylinder, which has been thoroughly investigated for architectural design. The purpose of UQ is validation of numerical simulation results with experimental data, therefore the radius of curvature of the rectangular cylinder corners and the angle of attack are considered to be random variables, which are known to contain uncertainties when wind tunnel tests are carried out. Computational Fluid Dynamics (CFD) simulations are solved by a solver that employs the Finite Element Method (FEM) for two turbulence modeling approaches of the incompressible Navier-Stokes equations: Unsteady Reynolds Averaged Navier Stokes (URANS) and the Large Eddy simulation (LES). The results of the uncertainty analysis with CFD are compared to experimental data in terms of time-averaged pressure coefficients and bulk parameters. In addition, the accuracy and efficiency of the multi-fidelity framework is demonstrated through a comparison with the results of the high-fidelity model.

A study on the selection of evapotranspiration observatory representative location in Chuncheon Dam basin (증발산량 관측 대표위치 선정에 관한 연구: 춘천댐 유역을 중심으로)

  • Park, Jaegon;Kim, Kiyoung;Lee, Yongjun;Hwag-Bo, Jong Gu
    • Journal of Korea Water Resources Association
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    • v.55 no.11
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    • pp.979-989
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    • 2022
  • In hydrological surveys, observation through representative location is essential due to temporal and spatial limitations and constraints. Regarding the use of hydrological data and the accuracy of the data, there are still insufficient observatories to be used in a specific watershed. In addition, since there is virtually no standard for the location of the current evapotranspiration, this study proposes a method for determining the location of the evapotranspiration. To determining the location of evapotranspiration, a grid is selected in consideration of the operating range of the Flux Tower using the eddy covariance measurement method, which is mainly used to measure evapotranspiration. The grid of representative location was calculated using the factors affecting evapotranspiration and satellite data of evapotranspiration. The grid of representative location was classified as good, fair, and poor. As a result, the number of good grids calculated was 54. It is judged that the classification of the grid has been achieved regarding topography and land use as a characteristic that appeared in the classification of the grid. In particular, in the case of elevation or city area, there was a large deviation, and the calculated good grid was judged to be a group between the two distributions.