• Atmosphere
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• v.29 no.3
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• pp.269-282
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• 2019

While it is important to obtain the accurate information on snowfall data due to the increase in damage caused by the heavy snowfall in the winter season, it is not easy to observe the snowfall quantitatively. Recently, snow measurements using a weighing precipitation gauge have been carried out, but there is a problem that high snowfall intensity results in low accuracy. Also, the observed snowfall data are sensitive depending on wind speed, temperature, and humidity. In this study, a new process of quality control for snow water equivalent (SWE) data of the weighing precipitation gauge were proposed to cover the low accuracy of snow data and maximize the data utilization. Snowfall data (SWE) observed by Pluvio, Parsivel, snow-depth meter using laser or ultrasonic, and rainfall gauge in Cloud Physics Observation Site (CPOS) were compared and analyzed. Applying the QC algorithm including the use of number of hydrometeor particles as reference, the increased SWE per the unit time was determined and the data noise was removed and marked by flag. The SWE data converted by the number concentration of hydrometeor particles are tested as a method to restore the QC-removed data, and show good agreement with those of the weighing precipitation gauge, though requiring more case studies. The three events data for heavy snowfall disaster in Pyeongchang area was analyzed. The SWE data with improved quality was showed a good correlation with the eye-measured data ($R^2$ > 0.73).

• Korean Journal of Construction Engineering and Management
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• v.20 no.3
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• pp.105-112
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• 2019

Due to abnormal high temperature, electric power demand has exceeded the backup power reserved for emergency case, hence, resulting in a major power outage. In today's overcrowded cities, the unexpected disruption in energy supply and demand is a major threat to the enormous economic damage and urban malfunctions. Existing methods for estimating the demand of the emergency power source do not lend themselves to predict the actual demand in the spatial dimension of the city. In addition, the reserve power is arbitrarily distributed in the case of emergency. This paper presents a method that predicts the emergency power demand using the spatial distribution of emergency power demand by applying the daily energy consumption intensity and emergency power demand according to urban spatial information and building use.

• Corrosion Science and Technology
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• v.18 no.2
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• pp.61-71
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• 2019

Flow-Accelerated Corrosion (FAC) is a phenomenon in which a protective coating on a metal surface is dissolved by a flow of fluid in a metal pipe, leading to continuous wall-thinning. Recently, many countries have developed computer codes to manage FAC in power plants, and the FAC prediction model in these computer codes plays an important role in predictive performance. Herein, the FAC prediction model was developed by applying a machine learning method and the conventional nonlinear regression method. The random forest, a widely used machine learning technique in predictive modeling led to easy calculation of FAC tendency for five input variables: flow rate, temperature, pH, Cr content, and dissolved oxygen concentration. However, the model showed significant errors in some input conditions, and it was difficult to obtain proper regression results without using additional data points. In contrast, nonlinear regression analysis predicted robust estimation even with relatively insufficient data by assuming an empirical equation and the model showed better predictive power when the interaction between DO and pH was considered. The comparative analysis of this study is believed to provide important insights for developing a more sophisticated FAC prediction model.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.5
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• pp.787-797
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• 2021

Yellowtail Seriola quinqueradiata tagged with a Pop-up Satellite Archival Tag (PSAT) was released off the coast of near the Moseulpo, Jeju Island and the ecological data during about 40 days was obtained. However, it is difficult to determine the spatial location of underwater ecological data. To improve the accuracy of estimating the Yellowtail migration route using temperature, suitable background field of the oceanic environment data was evaluated and used for input data. After developing of the tracking algorithm for migration route estimation, three experiment cases were estimated with ecological data among the surface layer, the mixed layer, and the whole water column. All tracking experiments move from western to eastern Jeju Island. Additionally, tracking experiment using 3D ocean numerical model reveal that it is possible to estimate the migration route using the fish ecological data of the entire water column. Therefore, using a large number of ecological data and a high-accuracy ocean numerical model to estimate the migration route seems to be a way to increase the accuracy of the tracking experiment. Moreover, the tracking algorithm of this study can be applied to small pelagic fishery using small archival electronic tags to track the migration route.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.233-238
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• 2020

Process-based model (PBM), based on the interactions between endogenous physiological processes and many environmental factors, can be a powerful tool for estimating crop growth and productivity. Carbon acquisition and biomass accumulation are the main components in PBM, so it has become important to understand and integrate gas exchange process in crop model. This study aimed to assess the applicability of FvCB model (a leaf model of C3 photosynthesis proposed by Farquhar, von C aemmerer, and Berry (1980)) in onion (Allium cepa L.). For parameterization, two early-maturing onion cultivars, 'Singsingball' and 'Thunderball', grown in a temperature gradient plastic film house, were used in measuring leaf net CO2 assimilation rate (A), and then, parameter estimation was carried out for four parameters including Vcmax (maximum rate of carboxylation), Jmax (maximum rate of electron transport), TPU (rate of triose phosphate utilization), and Rd (Dark respiration rate). The gas-exchange model calibrated in this research is expected to be able to explain the photosynthetic responses of onion under various environmental conditions (R2=0.95***).

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.1
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• pp.1-13
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• 2022

In Korea, attention is being paid to the use of renewable energy in the livestock industry, and Ground Source Heat Pump (GSHP), which is advantageous for temperature control, is considered as one of the ways to reduce the use of fossil fuels. But GSHP is expensive to install, which proper capacity calculation is required. GSHP capacity is related to its maximum energy load. Energy loads are affected by climate characteristics and time, so dynamic analysis is required. In this study, the optimal capacity of GSHP was calculated by calculating the heating and cooling load of pig farms using BES (Building Energy Simulation) and economic analysis was performed. After designing the inside of the pig house using TRNSYS, one of the commercial programs of the BES technique, the energy load was calculated based on meteorological data. Through the calculated energy load, three heating devices and GSHP used in pig farms were analyzed for economic feasibility. As a result, GSHP's total cost of ownership was the cheapest, but the installation cost was the highest. In order to reduce the initial cost of GSHP, the capacity of GSHP was divided, and a scenario was created in which some of it was used as an auxiliary heating device, and economic analysis was conducted. In this study, a method to calculate the proper capacity of GSHP through dynamic energy analysis was proposed, and it can be used as data necessary to expand the spread of GSHP.

• Journal of Korean Society on Water Environment
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• v.37 no.6
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• pp.531-538
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• 2021

In this study, the TOC in six estuarine reservoirs in the West Sea (Ganwol, Namyang, Daeho, Bunam, Sapkyo, and Asan) was estimated using optically-active water quality factors by the water environment monitoring network. First, specification data and land use maps of each estuarine reservoir were collected. Subsequently, water quality data from 2013 to 2020 were collected. The data comprised of 11 parameters: pH, dissolved oxygen, BOD, COD, suspended solids (SS), total nitrogen, total phosphorus, water temperature, electrical conductivity, total coliforms, and chlorophyll-a (Chl-a). The TOC in the estuarine reservoirs was 4.9~7.0 mg/L, with the highest TOC of 7.0 mg/L observed at the Namyang reservoir, which has a low shape coefficient and high drainage density. The correlation of TOC with water quality factors was also analyzed, and the correlation coefficients of Chl-a and SS were 0.28 and 0.19, respectively, while the correlation coefficients of these factors in the Namyang reservoir were 0.42 and 0.27, respectively. To improve the estimation of TOC using Chl-a and SS, the TOC was averaged in 5 mg/L units, and Chl-a and SS were averaged. Correlation analysis was then performed and the R² of Chl-a-TOC was 0.73. The R² of SS-TOC was 0.73 with a non-linear relationship. TOC had a significant non-linear relationship with Chl-a and SS. However, the relationship should be assessed in terms of the spatial and temporal variations to construct a reliable remote sensing system.

• Journal of IKEEE
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• v.26 no.2
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• pp.249-256
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• 2022

The prosthetic leg is a device that performs walking instead of a amputated lower limb, and require a change in locomotion mode by providing the user's intention to respond to a discontinuous locomotion environment. Research has been conducted to detect the users' intentions through biomechanical features inside the socket that directly contacts the cut site in demand for natural locomotion mode changes without external control equipment. However, there is still a need for a sensor system that is suitable for the internal environment of the main body and socket of the cut site. Accordingly, this paper proposed a film-type sensor system that is suitable for the main body characteristics of the cut site, is not affected by the temperature and humidity conditions inside the socket, and is easy to manufacture in various sizes. The proposed sensor is manufactured base on Velostat film and takes into account the pressure measurement characteristics that vary with size. Through the experiment, the change in the internal pressure of the socket due to the intentional posture performance of the wearer was measured, and the possibility of detecting the intention to change the locomotion mode was confirmed.

• Journal of Astronomy and Space Sciences
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• v.39 no.3
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• pp.117-126
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• 2022

The Ionospheric Anomaly Monitoring by Magnetometer And Plasma-probe (IAMMAP) is one of the scientific instruments for the Compact Advanced Satellite 500-3 (CAS 500-3) which is planned to be launched by Korean Space Launch Vehicle in 2024. The main scientific objective of IAMMAP is to understand the complicated correlation between the equatorial electro-jet (EEJ) and the equatorial ionization anomaly (EIA) which play important roles in the dynamics of the ionospheric plasma in the dayside equator region. IAMMAP consists of an impedance probe (IP) for precise plasma measurement and magnetometers for EEJ current estimation. The designated sun-synchronous orbit along the quasi-meridional plane makes the instrument suitable for studying the EIA and EEJ. The newly-devised IP is expected to obtain the electron density of the ionosphere with unprecedented precision by measuring the upper-hybrid frequency (f_UHR) of the ionospheric plasma, which is not affected by the satellite geometry, the spacecraft potential, or contamination unlike conventional Langmuir probes. A set of temperature-tolerant precision fluxgate magnetometers, called Adaptive In-phase MAGnetometer, is employed also for studying the complicated current system in the ionosphere and magnetosphere, which is particularly related with the EEJ caused by the potential difference along the zonal direction.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.50-61
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• 2022

Snow, rain, fog, and particulate matter interfere with the vehicle driver's vision, which causes a non-secure safety distance and an increase in speed deviation, causing repetitive large-scale traffic accidents. This study developed a road environment sensor capable of measuring 11 types of fog, snow, rain, temperature, humidity, direction of wind, speed of wind, Insolation, atmospheric pressure, fine particles, rainfall, etc. and compared the visibility measured by the infrared signal value of the development sensor. The relationship between the existing fog visibility sensor and the development sensor measurement was derived from data measured at a visibility of 500m or less that directly affects road safety.