• Korean Journal of Agricultural Science
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• v.38 no.4
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• pp.747-752
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• 2011

Wireless technology has enabled farmers monitor and control protected production environment more efficiently. Utilization of USN (Ubiquitous Sensor Network) devices also brought benefits due to reduced wiring and central data handling requirements. However, wireless communication loses signal under unfavorable conditions (e.g., blocked signal path, low signal intensity). In this paper, performance of commercial wireless communication devices were evaluated for application to protected crop production. Two different models of wireless communication devices were tested. Sensors used in the study were weather units installed outside and top of a greenhouse (wind velocity and direction, precipitation, temperature and humidity), inside ambient condition units (temperature, humidity, $CO_2$, and light intensity), and irrigation status units (irrigation flow and pressure, and soil water content). Performance of wireless communication was evaluated with and without crop. For a 2.4 GHz device, communication distance was decreased by about 10% when crops were present between the transmitting and receiving antennas installed on the ground, and the best performance was obtained when the antennas were installed 2 m above the crop canopy. When tested in a greenhouse, center of a greenhouse was chosen as the location of receiving antenna. The results would provide information useful for implementation of wireless environment monitoring system for protected crop production using USN devices.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.69-74
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• 2005

In order to evaluate the safety of navigation at sea and the safety of mooring on berthing, it is necessary that the wave and wind induced ship dynamic motion should be measured in real time domain for the validity of theoretical evaluation method sum as sea-keeping performance and safety of mooring. In this paper, the basic design of sensors is discussed and some system configurations were shown. The developed system mainly consists of 4 kind of sensors sum as three dimensional accelerator, two dimensional tilt sensor, two displacement sensors and azimuth sensor. Using this measuring system(MMS), it can be obtained the 6 degrees of freedom of ship dynamic motions at sea and on berthing sum as rolling, pitching, yawing, swaying, heaving, surging under the certain external forces.

• Journal of Environmental Science International
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• v.28 no.8
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• pp.701-707
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• 2019

Highland farming is agriculture that takes place 400 m above sea level and typically involves both low temperatures and long sunshine hours. Most highland Chinese cabbages are harvested in the Gangwon province. The Ubiquitous Sensor Network (USN) has been deployed to observe Chinese cabbages growth because of the lack of installed weather stations in the highlands. Five representative Chinese cabbage cultivation spots were selected for USN and meteorological data collection between 2015 and 2017. The purpose of this study is to develop a weight prediction model for Chinese cabbages using the meteorological and growth data that were collected one week prior. Both a regression and random forest model were considered for this study, with the regression assumptions being satisfied. The Root Mean Square Error (RMSE) was used to evaluate the predictive performance of the models. The variables influencing the weight of cabbage were the number of cabbage leaves, wind speed, precipitation and soil electrical conductivity in the regression model. In the random forest model, cabbage width, the number of cabbage leaves, soil temperature, precipitation, temperature, soil moisture at a depth of 30 cm, cabbage leaf width, soil electrical conductivity, humidity, and cabbage leaf length were screened. The RMSE of the random forest model was 265.478, a value that was relatively lower than that of the regression model (404.493); this is because the random forest model could explain nonlinearity.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.11
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• pp.944-951
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• 2018

Artificial icing test and wind tunnel test can be performed to reduce the development period when a rotorcraft is required operation under icing situations. Artificial icing test of the KUH(Korean Utility Helicopter) was performed in advance to verify anti-icing and de-icing performance before natural icing test. Although high-precision sensor, the CCP(Cloud Combination Probe) is used to measure icing test condition parameters such as LWC(Liquid Water Content) and MVD(Median Volume Diameter), the measured values need to be verified in various methods due to the possibility of uncertainties which are the test atmosphere environment, sensor errors, and etc. The calculated LWC from the ice thickness cumulated on the fuselage of the KUH is compared to the measured value by CCP, and the results show the effective indirect method to check the test conditions.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1653-1667
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• 2020

In this study, we coupled a computation fluid dynamics (CFD) model to the local data assimilation and prediction system (LDAPS), a current operational numerical weather prediction model of the Korea Meteorological Administration. We investigated the characteristics of fine particulate matter (PM2.5) distributions in a building-congested district. To analyze the effects of road emission on the PM2.5 concentrations, we calculated road emissions based on the monthly, daily, and hourly emission factors and the total amount of PM2.5 emissions established from the Clean Air Policy Support System (CAPSS) of the Ministry of Environment. We validated the simulated PM2.5 concentrations against those measured at the PKNU-AQ Sensor stations. In the cases of no road emission, the LDAPS-CFD model underestimated the PM2.5 concentrations measured at the PKNU-AQ Sensor stations. The LDAPS-CFD model improved the PM2.5 concentration predictions by considering road emission. At 07 and 19 LST on 22 June 2020, the southerly wind was dominant at the target area. The PM2.5 distribution at 07 LST were similar to that at 19 LST. The simulated PM2.5 concentrations were significantly affected by the road emissions at the roadside but not significantly at the building roof. In the road-emission case, the PM2.5 concentration was high at the north (wind speeds were weak) and west roads (a long street canyon). The PM2.5 concentration was low in the east road where the building density was relatively low.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.347-350
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• 2018

In order for an IoT system to automatically make the house temperature pleasant for the user, the system needs to predict the optimal start-up time of air-conditioner or heater to get to the temperature that the user has set. Predicting the optimal start-up time is important because it prevents extra fee from the unnecessary operation of the air-conditioner and heater. This paper introduces an ANN(Artificial Neural Network) and an IoT system that predicts the cooling and heating time in households using air-conditioner and heater. Many variables such as house structure, house size, and external weather condition affect the cooling and heating. Out of the many variables, measurable variables such as house temperature, house humidity, outdoor temperature, outdoor humidity, wind speed, wind direction, and wind chill was used to create training data for constructing the model. After constructing the ANN model, an IoT system that uses the model was developed. The IoT system comprises of a main system powered by Raspberry Pi 3 and a mobile application powered by Android. The mobile's GPS sensor and an developed feature used to predict user's return.

• Journal of Environmental Science International
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• v.9 no.5
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• pp.385-388
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• 2000

Visibility reduction is a barometer of air pollution which people can notice easily. First of all we need to measure quantified visibility continuously in order to examine visibility reduction. Prevailing visibility is not practical to measure visibility depending on observer's expertness. Scattering visibility using Forward Scattering Meter(Belfort Visibility Sensor 6230) has been measured at Kwangan-Dong in Pusan and analysed since July 1998. According to the analysis the correlation coefficient(R) between prevailing visibility and scattering visibility was 0.7235. The visibility appeared that each frequency of poor visibility(under 6km) and good visibility(over 25km) was 10.6%, 9.7% on summertime in Pusan and the visibility range from 10km to 20km ranked high frequency as a half of whole ranges. The order of correlation coefficients between visibility an air pollutants are ranking CO. PM10 and NO2 that values are 0.5878, 0.5369,l 0.5284 respectively. In meteorolgical factor the case of poor visibility presented more weakly wind speed and higher relative humidity than the case of good visibility. The correlation coefficient between calculated visibility of multiple linear regression model and observed visibility was 0.7215. But the trend of calculated and observed visibility variation was similar with the exception of several good visibility cases.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.5
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• pp.498-509
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• 2015

The existing mobile antenna networks in the military use have been operated by the manual pointing between two antennas. The work presented here describes the study of ATPC(Automatic Tracking and Pointing Control) system between facing antennas and the related tracking and pointing performances. This system is able to automatically track the maximum RSSI(Received Signal Strength Indication) value from the source's RF(Radio Frequency) signal and then control for maintaining the LOS(Line of Sight) between two antennas. The system has three major units; the driving unit consisting of motors, harmonic drives and encoders, the sensor unit with a GPS(Global Positioning System) and AHRS(Attitude and Heading Reference System) and the control unit regulating all the tracking and pointing events. By using PI(Proportional and Integral) controller, this system is able to properly track and point the other antenna under the external disturbance like the wind load. Both the simulation and the experimental works have been successively carried out to prove the performances of the system.

• Wind and Structures
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• v.21 no.6
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• pp.677-691
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• 2015

In this study, the geometrical setup of a turbine blade is tracked. A research-scale rotating turbine blade system is setup with a single 3-axes accelerometer mounted on one of the blades. The turbine system is rotated by a controlled motor. The tilt and rolling angles of the rotating blade under operating conditions are determined from the response measurement of the single accelerometer. Data acquisition is achieved using a prototype wireless sensing system. First, the Rodrigues' rotation formula and an optimization algorithm are used to track the blade rolling angle and pitching angles of the turbine blade system. In addition, the blade flapwise natural frequency is identified by removing the rotation-related response induced by gravity and centrifuge force. To verify the result of calculations, a covariance-driven stochastic subspace identification method (SSI-COV) is applied to the vibration measurements of the blades to determine the system natural frequencies. It is thus proven that by using a single sensor and through a series of coordinate transformations and the Rodrigues' rotation formula, the geometrical setup of the blade can be tracked and the blade flapwise vibration frequency can be determined successfully.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.6
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• pp.7-16
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• 2011

This study discussed the applicability of satellite SAR (Synthetic Aperture Radar) imagery with regard to reservoir monitoring, and tried the extraction of reservoir storage from multi-temporal C-band RADARSAT-1 SAR backscattering images of Yedang and Goongpyeong agricultural reservoirs, acquired from May to October 2005. SAR technology has been advanced as a complementary and alternative approach to optical remote sensing and in-situ measurement. Water bodies in SAR imagery represent low brightness induced by low backscattering, and reservoir storage can be derived from the backscatter contrast with the level-area-volume relationship of each reservoir. The threshold segmentation over the routine preprocessing of SAR images such as speckle reduction and low-pass filtering concluded a significant correlation between the SAR-derived reservoir storage and the observation record in spite of the considerable disagreement. The result showed up critical limitations for adopting SAR data to reservoir monitoring as follows: the inappropriate specifications of SAR data, the unreliable rating curve of reservoir, the lack of climatic information such as wind and precipitation, the interruption of inside and neighboring land cover, and so on. Furthermore, better accuracy of SAR-based reservoir monitoring could be expected through different alternatives such as multi-sensor image fusion, water level measurement with altimeters or interferometry, etc.