• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1493-1507
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• 2020

The LEOP Cal/Val (Launch and Early Operation Phase Calibration/Validation) was carried out during 6 months after KOMPSAT-3A (KOMPSAT-3A Korea Multi-Purpose Satellite-3A) was launched in March 2015. After LEOP Cal/Val was successfully completed, high resolution KOMPSAT-3A has been successfully distributing to users over the past 8 years. The sub-meter high-resolution satellite image data obtained from KOMPSAT-3A is used as basic data for qualitative and quantitative information extraction in various fields such as mapping, GIS (Geographic Information System), and national land management, etc. The KARI (Korea Aerospace Research Institute) periodically checks and manages the quality of KOMPSAT-3A's product and the characteristics of satellite hardware to ensure the accuracy and reliability of information extracted from satellite data of KOMPSAT-3A. To minimize the deterioration of image quality due to aging of satellite hardware, payload and attitude sensors of KOMPSAT-3A, continuous improvement of image quality has been carried out. In this paper, the Cal/Val work-flow defined in the KOMPSAT-3A development phase was illustrated for the period of before and after the launch. The MTF, SNR, and location accuracy are the key parameters to estimate image quality and the methods of the measurements of each parameter are also described in this work. On the basis of defined quality parameters, the performance was evaluated and measured during the period of after LEOP Cal/Val. The current status and characteristics of MTF, SNR, and location accuracy of KOMPSAT-3A from 2016 to May 2020 were described as well.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.7
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• pp.931-941
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• 2020

There is a growing interest this paper for ocean sensing where autonomous vehicles can play an essential role in assisting engineers, researchers, and scientists with environmental monitoring and collecting oceanographic data. This study was conducted to develop a rigid sail for the autonomous sailing drone. Our study aims to numerically analyze the aerodynamic characteristics of curvy twin sail and compare it with wing sail. Because racing regulations limit the sail shape, only the two-dimensional geometry (2D) was open for an optimization. Therefore, the first objective was to identify the aerodynamic performance of such curvy twin sails. The secondary objective was to estimate the effect of the sail's spacing and shapes. A viscous Navier-Stokes flow solver was used for the numerical aerodynamic analysis. The 2D aerodynamic investigation is a preliminary evaluation. The results indicated that the curvy twin sail designs have improved lift, drag, and driving force coefficient compared to the wing sails. The spacing between the port and starboard sails of curvy twin sail was an important parameter. The spacing is 0.035 L, 0.07 L, and 0.14 L shows the lift coefficient reduction because of dramatically stall effect, while flow separation is improved with spacing is 0.21 L, 0.28 L, and 0.35 L. Significantly, the spacing 0.28 L shows the maximum high pressure at the lower area and the small low pressure area at leading edges. Therefore, the highest lift was generated.

• Journal of Wetlands Research
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• v.24 no.1
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• pp.59-67
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• 2022

The interest in LID facilities is increasing worldwide for recovery of natural water cycle system to destroy by urbanization. However, problems are raised when installation of LID because comprehensive analysis about design capacity adequacy of LID facilities was not conducted completely. In this research, removal efficiency and design volume adequacy of LID facilities were analyzed based on rainfall monitoring data in four LID facilities(Vegetated Swale, Vegetative Filter Strip, Bio-Retention and Permeable Pavement). As a result, group of LID facility designed on WQV was shown higher flow(37%) and pollutants(TSS, BOD, TN and TP) removal efficiencies(20 ~ 37%) than group of LID facility designed on WQF. SA/CA graph was drawn for evaluation of design volume adequacy based on rainfall monitoring data. In this SA/CA graph, coefficient of determination show over 0.5 in all parameter, especially, Flow and TP were show over 0.95. And, 'SA/CA & L/CA' graph considering difference of structure mechanism in LID facility suggested in this research was confirmed that improved coefficient of determination in flow, TSS and TP than SA/CA graph. According to this research results, feasibility of applying 'SA/CA & L/CA' graph for evaluation of design volume adequacy in LID facility, and it is necessary to follow up research for generalization and normalization.

• 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.

• Journal of Bio-Environment Control
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• v.31 no.1
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• pp.1-7
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• 2022

Strawberry is a stand-out cultivating fruit in Korea. The optimum production of strawberry is highly dependent on growing environment. Smart farm technology, and automatic monitoring and control system maintain a favorable environment for strawberry growth in greenhouses, as well as play an important role to improve production. Moreover, physiological parameters of strawberry plant and it is surrounding environment may allow to give an idea on production of strawberry. Therefore, this study intends to build a machine learning model to predict strawberry's yield, cultivated in greenhouse. The environmental parameter like as temperature, humidity and CO₂ and physiological parameters such as length of leaves, number of flowers and fruits and chlorophyll content of 'Seolhyang' (widely growing strawberry cultivar in Korea) were collected from three strawberry greenhouses located in Sacheon of Gyeongsangnam-do during the period of 2019-2020. A predictive model, Lasso regression was designed and validated through 5-fold cross-validation. The current study found that performance of the Lasso regression model is good to predict the number of flowers and fruits, when the MAPE value are 0.511 and 0.488, respectively during the model validation. Overall, the present study demonstrates that using AI based regression model may be convenient for farms and agricultural companies to predict yield of crops with fewer input attributes.

• Journal of Korea Water Resources Association
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• v.55 no.6
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• pp.405-419
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• 2022

Flood frequency analysis commonly used to design the hydraulic structures to minimize flood damage includes uncertainty. Therefore, the most appropriate design flood within a uncertainty should be selected in the final stage of a hydraulic structure, but related studies were rarely carried out. The total expected cost function introduced into the flood frequency analysis is a new approach for determining the optimal design flood. This procedure has been used as UNCODE (UNcertainty COmpliant DEsign), but the application has not yet been introduced in South Korea. This study introduced the mathematical procedure of UNCODE and calculated the optimal design flood using the annual maximum inflow of hydroelectric dams located in the Bukhan River system and results were compared with that of the existing flood frequency. The parameter uncertainty was considered in the total expected cost function using the Gumbel and the GEV distribution, and the Metropolis-Hastings algorithm was used to sample the parameters. In this study, cost function and damage function were assumed to be a first-order linear function. It was found that the medians of the optimal design flood for 4 Hydroelectric dams, 2 probability distributions, and 2 return periods were calculated to be somewhat larger than the design flood by the existing flood frequency analysis. In the future, it is needed to develop the practical approximated procedure to UNCODE.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.3
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• pp.9-24
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• 2022

Currently, a vast amount of hydrologic data is accumulated in real-time through automatic water level measuring instruments in agricultural reservoirs. At the same time, false and missing data points are also increasing. The applicability and reliability of quality control of hydrological data must be secured for efficient agricultural water management through calculation of water supply and disaster management. Considering the characteristics of irregularities in hydrological data caused by irrigation water usage and rainfall pattern, the Korea Rural Community Corporation is currently applying the Hampel filter as a water level data quality management method. This method uses window size as a key parameter, and if window size is large, distortion of data may occur and if window size is small, many outliers are not removed which reduces the reliability of the corrected data. Thus, selection of the optimal window size for individual reservoir is required. To ensure reliability, we compared and analyzed the RMSE (Root Mean Square Error) and NSE (Nash-Sutcliffe model efficiency coefficient) of the corrected data and the daily water level of the RIMS (Rural Infrastructure Management System) data, and the automatic outlier detection standards used by the Ministry of Environment. To select the optimal window size, we used the classification performance evaluation index of the error matrix and the rainfall data of the irrigation period, showing the optimal values at 3 h. The efficient reservoir automatic calibration technique can reduce manpower and time required for manual calibration, and is expected to improve the reliability of water level data and the value of water resources.

• CELLMED
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• v.11 no.4
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• pp.21.1-21.9
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• 2021

Background: Unani System of Medicine (USM) has its origin to Greece. To ensure and develop the quality, authenticity of Unani drugs, standardization on modern analytical parameter is essential requirement for drugs. Objectives: The aimed of the present study was to develop a standard profile of "Qurṣ-e-Mafasil" by systematic study through authenticated ingredients, pharmacognostic identification followed by physicochemical, TLC, HPTLC fingerprinting analysis as per standard protocol. Material and Methods: In this study three batches of "Qurṣ-e-Mafasil" QM were prepared by standard method as per UPI had been followed by organoleptic properties of formulation such as appearance, color, odor, taste. Powder Microscopy and physicochemical studies were carried out such as Uniformity of weight, Friability, Disintegration time, hardness, LOD, ash vales and extractive values in like aqueous, alcohol & hexane. Further qualitative tests such as Thin-Layer Chromatography (TLC), and High-Performance Thin Layer Chromatography (HPTLC) studies were also carried out to develop fingerprint pattern of the alcoholic solvent extract of QM. Phytochemical screening was carried out in different solvent extracts such as alcoholic, aqueous and chloroform extracts to detect the presence phytoconstituents in the formulation QM. Heavy metals, Microbial Load Contamination and pesticidal residues were also determined. Results: Qurṣ-e-Mafasil showed tablet-like appearance, light brown colour, mild pungent odour and acrid taste. Uniformity of weight (mg), friability (rpm), and hardness (kg/cm) and disintegration time was ranged between (500 to 503), (0.0340 to 0.038), (8.40 to 8.67) and (4-5 minutes) respectively for the three batches. Loss in weight on drying at 105℃ was ranged between (8.3425 to 8.7346). Extracted values were calculated in distilled water ranged between (30.9091 to 31.4358), hexane (1.1419 to 1.4281), and alcohol (3.3352 to 3.3962). The ash values recorded were ranged between (3.7336 to 3.8378), and acid insoluble ash (0.5859 to 0.6112).

• Journal of Korean Society of Forest Science
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• v.111 no.3
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• pp.435-449
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• 2022

Forest canopy height is an indispensable vertical structure parameter that can be used for understanding forest biomass and carbon storage as well as for managing a sustainable forest ecosystem. Plot-based field surveys, such as the national forest inventory, have been conducted to provide estimates of the forest canopy height. However, the comprehensive nationwide field monitoring of forest canopy height has been limited by its cost, lack of spatial coverage, and the inaccessibility of some forested areas. These issues can be addressed by remote sensing technology, which has gained popularity as a means to obtain detailed 2- and 3-dimensional measurements of the structure of the canopy at multiple scales. Here, we reviewed both international and domestic studies that have used remote sensing technology approaches to estimate the forest canopy height. We categorized and examined previous approaches as: 1) LiDAR approach, 2) Stereo or SAR image-based point clouds approach, and 3) combination approach of remote sensing data. We also reviewed upscaling approaches of utilizing remote sensing data to generate a continuous map of canopy height across large areas. Finally, we provided suggestions for further advancement of the Korean forest canopy height estimation system through the use of various remote sensing technologies.

• The Korean Journal of Physiology and Pharmacology
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• v.27 no.3
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• pp.267-275
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• 2023

Cardiotoxicity, particularly drug-induced Torsades de Pointes (TdP), is a concern in drug safety assessment. The recent establishment of human induced pluripotent stem cell-derived cardiomyocytes (human iPSC-CMs) has become an attractive human-based platform for predicting cardiotoxicity. Moreover, electrophysiological assessment of multiple cardiac ion channel blocks is emerging as an important parameter to recapitulate proarrhythmic cardiotoxicity. Therefore, we aimed to establish a novel in vitro multiple cardiac ion channel screening-based method using human iPSC-CMs to predict the drug-induced arrhythmogenic risk. To explain the cellular mechanisms underlying the cardiotoxicity of three representative TdP high- (sotalol), intermediate- (chlorpromazine), and low-risk (mexiletine) drugs, and their effects on the cardiac action potential (AP) waveform and voltage-gated ion channels were explored using human iPSC-CMs. In a proof-of-principle experiment, we investigated the effects of cardioactive channel inhibitors on the electrophysiological profile of human iPSC-CMs before evaluating the cardiotoxicity of these drugs. In human iPSC-CMs, sotalol prolonged the AP duration and reduced the total amplitude (TA) via selective inhibition of I_Kr and I_Na currents, which are associated with an increased risk of ventricular tachycardia TdP. In contrast, chlorpromazine did not affect the TA; however, it slightly increased AP duration via balanced inhibition of I_Kr and I_Ca currents. Moreover, mexiletine did not affect the TA, yet slightly reduced the AP duration via dominant inhibition of I_Ca currents, which are associated with a decreased risk of ventricular tachycardia TdP. Based on these results, we suggest that human iPSC-CMs can be extended to other preclinical protocols and can supplement drug safety assessments.