• Journal of Korean Society of Forest Science
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• v.89 no.3
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• pp.405-413
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• 2000

This study was conducted to develop an on-line monitoring system for a forest hydrological environment and its meteorological condition, such as temperature, wind direction and speed, rainfall and water level on V-notch, electrical conductivity(EC), potential of hydrogen(PH) by the motor drive sensor unit and measurement with a single-chip microprocessor as controller. These results are summarized as follows ; 1. The monitoring system consists of a signal process unit, motor drive sensor unit, radio modem unit and power supply. 2. The motor drive sensor unit protects the sensor from swift current or freezing and can constantly maintain fixed water level during measurements. 3. This monitoring system can transfer the data by radio modem. Additionally, this system can monitor hydrological conditions in real time. 4. The hardware was made of several modules with an independent CPU. They can be mounted, removed, repaired and added to. Their function can be changed and expanded. 5. These are the result of an accuracy test, the values of temperature, EC and pH measured within an error range of ${\pm}0.2^{\circ}C$, ${\pm}1{\mu}S$ and ${\pm}0.1pH$ respectively. 6. This monitoring system proved to be able to measure various factors for a forest hydrological environment in various experimental stations.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.4
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• pp.635-650
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• 2017

Acoustic emission (AE) sensors have broadly used to monitor the damage of underground structures and tunnels. The reliability of measured signal is determined by the coupling condition of the AE sensors which are embedded in the target underground structure. To secure the reliability of health monitoring results, it is important to understand the characteristics of the coupling materials. In this study, laboratory tests were performed using portland cement, micro cement, and gypsum as coupling materials in order to verify the bleeding characteristics. The effective parameters for bleeding were determined to be water-cement ratio, material type, curing time, and injected volume of coupling materials. As a results of the experimental study, the bleeding rate increases with an increase in a water-cement ratio and an injected volume; for portland cement, water-cement ratio and injected volume effects are larger than the micro cement. However, curing time is not much effective for occurrence of the bleeding phenomenon. It is anticipated that this study may be useful for the selection of suitable coupling materials for installation of acoustic emission sensors.

• Journal of Wetlands Research
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• v.20 no.1
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• pp.54-62
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• 2018

Nutrients generated from various land uses lead to eutrophication during the influx of water, and it is necessary to apply the LID techniques to reduce nutrients from nonpoint sources in order to mitigate the occurrence of the algal bloom. This study was carried out to derive the design factors of hybrid artificial wetland (HCW) to increase the removal efficiency of nutrients. HCW system was constructed in the year 2010 for the treatment of rainfall runoffs from parking lots and roads composed of 100% impervious floors in the Cheonan campus of Kongju University. The average nutrients removal efficiency of TN and TP was 74% and 72%, respectively. Both TN and TP removal efficiencies were higher than those of free surface wetlands and subsurface flow wetlands due to activated physical and ecological mechanisms. The critical design parameters for the efficient nutrients removal in the artificial wetlands were the ratio of the surface area to the catchment area (SA/CA), land use, the rainfall runoff, and the rainfall intensity. The optimal carbon to nitrogen (C/N) ratio was estimated at 5: 1 to 10.3: 1. The results of this study can be applied to the efficient design of hybrid artificial wetlands to treat nutrients in urban runoff with high efficiency.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.311-311
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• 2020

가뭄·홍수 등 수재해 대응대책 수립 측면에서 유역의 자연유출량 산정은 가장 핵심적인 사항이라 할 수 있다. 우리나라는 전국적으로 수위-유량관측소를 설치하여 실시간 유출량 모니터링을 통해 수문정보를 수집하며, 주요지점을 제외한 유역에서는 주기적으로 강우-유출모형의 매개변수 최적화를 통해 산정된 장기유출량 결과를 자연유출으로 가정하여 수자원 계획 수립시 활용하고 있다. 그러나 강우-유출모형의 최적 매개변수 추정을 위해 활용되는 관측 수문자료는 상대적으로 자료의 연한이 짧고, 계절·공간적인 특성으로 인해 매우 제한적이며, 유역의 특성을 충분히 고려하지 못해 미계측유역의 매개변수 추정시 모형의 자료에서 기인한 불확실성이 크게 발생한다는 단점이 있다. 이에 본 연구에서는 관측자료에 대한 신뢰성이 유의하며, 공간적으로 고르게 분포된 12개 댐 유역을 대상으로 매개변수 지역화 연구를 수행하였다. SCEM-UA기법을 통해 GR4J 강우-유출모형의 매개변수를 최적화 하였으며, 매개변수와의 상관관계 및 선형회귀분석을 통해 유역특성인자를 선별하여 Copula 함수를 통해 지역화된 매개변수를 추정하였다. 최종적으로 본 연구에서 제시된 방법론에 대한 적합성을 평가하기 위하여 매개변수 최적화가 수행된 유역을 미계측 유역으로 가정하여 교차검증 관점에서 적합성을 검토하였으며, 통계적으로 유의한 결과가 도출되는 것을 확인하였다.

• Journal of the Korean Institute of Gas
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• v.15 no.6
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• pp.1-7
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• 2011

The Measurement of risk parameter in city-gas equipments have been measured and confirmed by human, and evolved into remote monitoring system using wireless communication. Furthermore, domestic and international industry increase the efficiency of management, which can develop remote monitoring and control system using wireless communication. However, Those wireless system might be decrease the efficiency and ease because of connecting PDA and lap-top using wire-cable when data have checked immediately from outside. This paper is able to improve efficiency of safety management on city-gas equipments by developing mobile city-gas safety management system on AR.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.2
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• pp.107-120
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• 2019

In this study, the characteristics of watershed and pollution source were investigated in SoOakcheon located in the upper stream of Daecheong Lake. The Dimension Index method was applied to index various watershed and pollution source data. The influence factors of each pollutant source were derived through correlation analysis between selected index and water quality monitoring data. BOD and COD were significantly influenced by population density and land area ratio, T-N by CN and rice area ratio, and T-P by population density and land area ratio, respectively. The discharge load is often used to establish non-point source countermeasures, but there is a difference between the water load and the water load in the lake or river. Therefore, in order to manage non-point pollution efficiently, it is necessary to analyze influential factors with high correlation with water quality and to manage the relevant factors with priority.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.1
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• pp.49-54
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• 2020

Cardiovascular disease is the leading cause of death worldwide and is caused by a variety of causes. The highest risk factor for cardiovascular disease is high blood pressure, which has no obvious symptoms, but if left untreated, it causes several complications. In order to treat hypertension, medication and regular exercise are required. In people with high blood pressure, excessive physical activity can put a great strain on the heart and lead to cardiovascular disease. Therefore, there is a need for an exercise intensity monitoring system through PTT measurement that can perform exercise at an appropriate intensity. In this study, we implemented a PTT change monitoring system according to exercise intensity by calculating PTT through ECG and PPG measurement. The implemented system differentiates the R-peak of the ECG and P-peak of the PPG, and calculates the PTT using the time difference between R-peak and P-peak. A running experiment was conducted to monitoring PTT change according to exercise intensity. As a result of the experiment, low intensity PTT is 0.313s, moderate is 0.220s, high is 0.188s, it was confirmed that the PTT decreased as the exercise increase increased.

• 한국생물공학회:학술대회논문집
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• 2005.10a
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• pp.730-734
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• 2005

Flow injection analysis (FIA) system was developed to monitor glucose concentrations in biotechnological processes. A fiber optic oxygen sensor was used to determine consumption of oxygen concentration by reaction of immobilized glucose oxidase (GOD). The GOD was immobilized on VA-Epoxy carrier and integrated into FIA system. A calibration curve for glucose was obtained in the range of 0.5 $g/L{\sim}3.0$ g/L.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1651-1669
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• 2023

Sea ice currently covers approximately 7% of the world's ocean area, primarily concentrated in polar and high-altitude regions, subject to seasonal and annual variations. It is very important to analyze the area and type classification of sea ice through time series monitoring because sea ice is formed in various types on a large spatial scale, and oil and gas exploration and other marine activities are rapidly increasing. Currently, research on the type and area of sea ice is being conducted based on high-resolution satellite images and field measurement data, but there is a limit to sea ice monitoring by acquiring field measurement data. High-resolution optical satellite images can visually detect and identify types of sea ice in a wide range and can compensate for gaps in sea ice monitoring using Geostationary Ocean Color Imager-II (GOCI-II), an ocean satellite with short time resolution. This study tried to find out the possibility of utilizing sea ice monitoring by training a rule-based machine learning model based on learning data produced using high-resolution optical satellite images and performing detection on GOCI-II images. Learning materials were extracted from Liaodong Bay in the Bohai Sea from 2021 to 2022, and a Random Forest (RF) model using GOCI-II was constructed to compare qualitative and quantitative with sea ice areas obtained from existing normalized difference snow index (NDSI) based and high-resolution satellite images. Unlike NDSI index-based results, which underestimated the sea ice area, this study detected relatively detailed sea ice areas and confirmed that sea ice can be classified by type, enabling sea ice monitoring. If the accuracy of the detection model is improved through the construction of continuous learning materials and influencing factors on sea ice formation in the future, it is expected that it can be used in the field of sea ice monitoring in high-altitude ocean areas.

• Korean Journal of Environment and Ecology
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• v.34 no.1
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• pp.55-62
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• 2020

To estimate headwater stream temperature with seasonal variations, we analyzed precipitation, runoff and air temperature in experimental forest of Kangwon National University, Gangwon-do (2017~2018 years). The daily mean value of headwater stream temperature for spring was 6.9~17.7℃ and correlated with air temperature, that for summer and fall were 12.2~26.3℃ and 3.6~19.3℃, correlated with air temperature and runoff. Based on seasonal variations, we applied for stepwise multiple linear regression analyses to estimate headwater stream temperature with seasonal variations. The equations were headwater stream temperature(WT)_spring=(0.553×Air temperature)+(0.086×Runoff)+4.145 (R²=0.505; p<0.01), WT_summer=(0.756×Air temperature)+(-0.072×Runoff)+2.670 (R²=0.510; p<0.01), and WT_fall=(0.738×Air temperature)+(0.028×Precipitation)+2.660 (R²=0.844; p<0.01). The coefficient of determination (R²) was greater than when it was estimated by air temperature in all seasons and progressively increased from spring to winter. Therefore, we indicated difference on estimated magnitude of stepwise multiple linear regression, due to effects on headwater stream temperature of different environmental factors with seasonal variations. Furthermore, temporal factors with spatial characteristics (e.g., river versus headwater stream) could be recommended for estimating headwater stream temperature.