• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1207-1214
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• 2021

In thisletter, we developed technology which can exclude effect of cloudsto perform remote waterbody detection based on Sentinel-2 optical satellite imagery to calculate the area of ungauged reservoirs and applied to the Hwanggang dam reservoir, a representative ungauged reservoir, to verify usability. The remote waterbody detection technology calculates the cloud blocking ratio by comparing the cloud boundary in the Sentinel-2 imagery and the reservoir boundary first. Next, itselects data whose cloud blocking ratio does not exceed a specific value and calculates NDWI (Normalized Difference Water Index) with selected imagery. In last, it calculatesthe area of the reservoir by counting the number of grids which have NDWI value considered as waterbody within the boundary of the target reservoir and correcting with cloud blocking ratio. To determine cloud blocking ratio threshold forselecting image, we performed the area calculation of Hwanggang dam reservoir from July 2018 to October 2021. As a result, when the cloud blocking ratio threshold wasset 10%, we confirmed that the result with large error due to clouds were filtered well and obtained 114 results that can show changes in Hwanggang dam reservoir area among 220 images.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1235-1243
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• 2021

Geostationary Ocean Color Imager 2 (GOCI-II) on Geo-KOMPSAT-2 (GK2B)satellite was developed as a mission successor of GOCI on COMS which had been operated for around 10 years since launch in 2010 to observe and monitor ocean color around Korean peninsula. GOCI-II on GK2B was successfully launched in February of 2020 to continue for detection, monitoring, quantification, and prediction of short/long term changes of coastal ocean environment for marine science research and application purpose. GOCI-II had already finished IAC and IOT including early in-orbit calibration and had been handed over to NOSC (National Ocean Satellite Center) in KHOA (Korea Hydrographic and Oceanographic Agency). Radiometric calibration was periodically conducted using on-board solar calibration system in GOCI-II. The final calibrated gain and offset were applied and validated during IOT. And three video parameter sets for one day and 12 video parameter sets for a year was selected and transferred to NOSC for normal operation. Star measurement-based INR (Image Navigation and Registration) navigation filtering and landmark measurement-based image geometric correction were applied to meet the all INR requirements. The GOCI2 INR software was validated through INR IOT. In this paper, status and results of IOT, radiometric calibration and INR of GOCI-II are analysed and described.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.233-243
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• 2021

Photovoltaic panels are hazardous electronic waste that has heavy metal as one of the hazardous components. Each year, hazardous electronic waste is increasing worldwide and every heavy rainfall exposes the photovoltaic panel to become the source of heavy metal soil contamination. the development needs a monitoring technology for this hazardous exposure. this research use relationships between SAR temporal baseline and coherence of Sentinel-1 satellite to detected photovoltaic panel. Also, the photovoltaic plant detection tested using the difference between that photovoltaic panel and the other difference surface of coherence. The author tested the photovoltaic panel and its environment to calculate differences in coherence relationships. As a result of the experiment, the coherence of the photovoltaic panel, which is assumed to be a permanent scatterer, shows a bias that is biased toward a median value of 0.53 with a distribution of 0.50 to 0.65. Therefore, further research is needed to improve errors that may occur during processing. Additionally, the author found that the change detection using a temporal baseline is possible as the rate of reduction of coherence of photovoltaic panels differs from those of artificial objects such as buildings. This result could be an efficient way to continuously monitor regardless of weather conditions, which was a limitation of the existing optical satellite image-based photovoltaic panel detection research and to understand the spatial distribution in situations such as photovoltaic panel loss.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.469-476
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• 2021

The purpose of this study is to explore the predictors of academic probation in college. Especially, this study focused on student engagement variables among the predictors of academic probation in college. Student engagement variables include hours of absence from class and numbers of log to LMS(Learning Management System) and in extracurricular program system during four weeks after the opening of a course and the numbers of faculty counseling. GPA(grade Point Average) is a dependent variable and GPA of prior semester is a control variable in this study. 17,261 student data were collected for the study. Linear regression model and logistic regression model analyses were conducted in the study. The finding showed that the hours of absence from class and numbers of log in extracurricular program system during four weeks after the opening of a course predicted academic achievement of college students. The result also indicated that hours of absence from class and numbers of log-ins to LMS(Learning Management System) and in extracurricular program system during four weeks after the opening of a course were the predictors of academic probation in college. This study will contribute to investigate indicators of students with low academic performance and to provide proper support for underachievers.

• The Journal of Society for e-Business Studies
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• v.23 no.4
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• pp.109-126
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• 2018

With massive and dense production, the livestock industry is rapidly moving into a large-scale, capital-intensive industry especially in swine, poultry, and ducks. However, livestock epidemics can pose a serious threat to the livestock industry and the lives of the people. The government has established and operates the National Animal Protection and Prevention System (KAHIS) since 2013 in order to control the threat, in accordance with the five stages. The digitalized data and information are excellent in ease of management, but it is also pointed out that it is difficult to take countermeasures through linkage with the data in an emergency situation. Recently, the technology of the fourth industrial revolution such as Internet of Things (IoT), Big Data, Artificial intelligence (AI) has been rapidly implemented to the livestock industry, which makes smart livestock disease control system possible. Therefore, this study investigated the domestic and overseas cases which apply 4th Industrial Revolution technology in the industry, and derived 13 possible candidate tasks in the near future. In order to ascertain the priority of policy formulation, we surveyed the expert groups and examined the priority of each of the five stages of the prevention and the priority of each stage. The results of this study are expected to contribute to the establishment of policies for the advancement of smart livestock disease control research and livestock protection.

• Journal of the Korean Institute of Gas
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• v.23 no.4
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• pp.40-45
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• 2019

This paper is a purpose to study the failure example for heavy-duty vehicle fire. The first example, the researcher found the engine over-heating phenomenon causing a coolant leakage by the sealing poor of head-gasket because of D-ring part deformation contacting with cylinder liner top-part and cylinder head. He certified a fire breakout by short transferred to surrounding wiring of air-cleaner. The second example, a brake lining by return fault of break operating S cam causing with much wear of a rear 4 wheel brake lining repeatably was worn by friction. In the long run, it became the cause of fire. The third example, the researcher knew the fire cause was came about the short of wire by overload of tilting motor when the driver tilted up the cap to inspect a engine. Therefore, a heavy-duty fire must minimize the fire occurrence by thorough controlling.

• Journal of Bio-Environment Control
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• v.28 no.1
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• pp.16-27
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• 2019

Using virtual reality technology, users can learn and experience many interactions in virtual space like the actual physical space. This study was conducted to develop air flow simulator that allows farmers and consultants to consult air flow through VR devices by creating a greenhouse or pigpen model. It can help educate farmers about the importance of ventilation effects for agricultural facilities. We proposed CFD visualization system by building a virtual reality environment and constructing database of CFD and structure of agricultural facilities. After consultants can set up situations according to environmental conditions, the users experience the visualized air flow of agricultural facility according to the ventilation effects. Also it can provide a quantified environmental distribution in the agricultural facility. Currently, the CFD data in agricultural facilities are established during winter and summer. In order to experience various environmental conditions in the developed system, The experts need to run CFD data under various environmental conditions and register them in the system requirements.

• Journal of Climate Change Research
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• v.3 no.1
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• pp.13-24
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• 2012

CCGIS (Climate Change Adaptation Toolkit based on GIS) was developed to use as a tool for the climate change assessment and any relevant tasks involving climate change adaptation policy over Korean peninsula. The main objective of CCGIS is to facilitate an efficient and relevant information for the estimation of climate change vulnerability index by providing key information in the climate change adaptation process. In particular, the atmospheric modeling system implemented in CCGIS, which is composed of climate and meteorological numerical model and the atmospheric environmental models, were used as a tool to generate the climate and environmental IPCC SRES (A2, B1, A1B, A1T, A1FI, and A1 scenarios) climate data for the year of 2000, 2020, 2050, and 2100. This article introduces the components of CCGIS and describes its application to the Korean peninsula. Some examples of the CCGIS and its use for both climate change adaptation and estimation of vulnerability index applied to Korean provinces are presented and discussed here.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.8
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• pp.582-589
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• 2019

The dynamic balancing test of helicopter main rotor blades is a blade rotation test conducted on the ground to make the track of each blade and the load on each pitch rod to a similar level before the flight tests. The purpose of the test is to reduce the vibration occurring on main rotor system as a result of dissimilarity of each blade. The RTB test has been performed for a long period at Whirl Tower Test Facility located in Goheung Flight Centre, accumulating its data. As the amount of the results has become increasingly enormous the needs for the development of database system has been raised to manage the data with effective method. This research aimed to describe the development of Dynamic-Balancing Database System for the RTB test results. For the design of the database system the informations of RTB test results have been categorized into properties, connecting each others according to its logical meaning, and comprised into a database system with relational elements. It has been shown in this paper that the Dynamic Balancing database system enables to effectively accumulate the RTB test data and to be utilized for the data analysis.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.187-195
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• 2019

The needs for precise diagnostics and farm management-decision aids have increased to reduce the risk of climate change and environmental stress. Crop simulation models have been widely used to search optimal solutions for effective cultural practices. However, limited knowledge on physiological responses to environmental variation would make it challenging to apply crop simulation models to a wide range of studies. Advanced research facilities would help investigation of plant response to the environment. In the present study, the sunlit controlled environment chambers, known as Korean SPAR (Soil-Plant-Atmosphere-Research) system, was developed by renovating existing SPAR system. The Korean SPAR system controls and monitors major environmental variables including atmospheric carbon dioxide concentration, temperature and soil moisture. Furthermore, plants are allowed to grow under natural sunlight. Key physiological and physical data such as canopy photosynthesis and respiration, canopy water and nutrient use over the whole growth period are also collected automatically. As a case study, it was shown that the Korean SPAR system would be useful for collection of data needed for understanding the growth and developmental processes of a crop, e.g., soybean. In addition, we have demonstrated that the canopy photosynthetic data of the Korean SPAR indicate the precise representation of physiological responses to environment variation. As a result, physical and physiological data obtained from the Korean SPAR are expected to be useful for development of an advanced crop simulation model minimizing errors and confounding factors that usually occur in field experiments.