• Korean Journal of Optics and Photonics
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• v.2 no.3
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• pp.139-148
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• 1991

A fiber-optic magnetic sensor system for the detection of small ac magnetic field(200Hz-2 kHz) was constructed. Magnetic field sensing part was fabricated by bonding a section of optical fiber to amorphous metallic glass(2605SC) having large magnetostriction effect. And with the directional coupler, all fiber type Mach-Zehnder interferometer was constructed to measure the variation of the external magnetic field by translating it into the optical phase shift in the interferometer. The signal fading problem of the interferometer, which is due to random phase drifts originated from the environment, i.e., temperature fluctuation, vibrations, etc., was elliminated by feedback phase compensation. This allows the sensitivity to be maintained at the maximum by keeping the interferometer in quadrature phase condition. The frequency response of metallic glass was found to be nearly flat in the range of 90 Hz-2 kHz and dc bias field for the maximum ac response was 3.5 Oe. The interferometer output showed good linearity over the range $\pm$0.5 Oe. For 1 kHz ac magnetic field the scale factor S and the minimum detectable magnetic field were measured to be 8.0 rad/Oe and $3X10^{-6} Oe/\sqrt{Hz}$at 1 Hz detection bandwidth respectively.

• Smart Structures and Systems
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• v.24 no.6
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• pp.769-781
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• 2019

Dynamic displacement response of civil structures is an important index for in-construction and in-service structural condition assessment. However, accurately measuring the displacement of large-scale civil structures such as high-rise buildings still remains as a challenging task. In order to cope with this problem, a vision-based system with the use of industrial digital camera and image processing has been developed for long-distance, remote, and real-time monitoring of dynamic displacement of supertall structures. Instead of acquiring image signals, the proposed system traces only the coordinates of the target points, therefore enabling real-time monitoring and display of displacement responses in a relatively high sampling rate. This study addresses the in-situ experimental verification of the developed vision-based system on the Canton Tower of 600 m high. To facilitate the verification, a GPS system is used to calibrate/verify the structural displacement responses measured by the vision-based system. Meanwhile, an accelerometer deployed in the vicinity of the target point also provides frequency-domain information for comparison. Special attention has been given on understanding the influence of the surrounding light on the monitoring results. For this purpose, the experimental tests are conducted in daytime and nighttime through placing the vision-based system outside the tower (in a brilliant environment) and inside the tower (in a dark environment), respectively. The results indicate that the displacement response time histories monitored by the vision-based system not only match well with those acquired by the GPS receiver, but also have higher fidelity and are less noise-corrupted. In addition, the low-order modal frequencies of the building identified with use of the data obtained from the vision-based system are all in good agreement with those obtained from the accelerometer, the GPS receiver and an elaborate finite element model. Especially, the vision-based system placed at the bottom of the enclosed elevator shaft offers better monitoring data compared with the system placed outside the tower. Based on a wavelet filtering technique, the displacement response time histories obtained by the vision-based system are easily decomposed into two parts: a quasi-static ingredient primarily resulting from temperature variation and a dynamic component mainly caused by fluctuating wind load.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.478-488
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• 2023

This paper investigates the naval application of laser communication as a potential replacement for traditional acoustic wave communication in underwater environments. We developed a laser transceiver using Arduino and MATLAB, conducting a water tank experiment to validate communication feasibility across diverse underwater conditions. In the first experiment, when transmitting data through a laser, the desired message was converted into data and transmitted, received, and confirmed to be converted into the correct message. In the second experiment, the operation of communication in underwater situations was confirmed, and in the third experiment, the intensity of light was measured using the CDS illuminance sensor module and the limits of laser communication were measured and confirmed in various underwater situations. Additionally, MATLAB code was employed to gather data on salinity, water temperature, and water depth for calculating turbidity. Optimal wavelength values (532nm, 633nm, 785nm, 1064nm) corresponding to calculated turbidity levels (5, 20, 55, 180) were determined and presented. The study then focuses on analyzing potential applications in naval tactical communication, remote sensing, and underwater drone control. Finally, we propose measures for overcoming current technological limitations and enhancing performance.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.4
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• pp.229-241
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• 2006

Global air temperature has risen by $0.6^{\circ}C$ over the last one hundred years due to increased atmospheric greenhouse gases. Moreover, this global warming trend is projected to continue in the future. This study was carried out to evaluate spatial variations in rice production areas by simulating rice-growth and development with projected high resolution climate data in Korea far 2011-2100, which was geospatially interpolated from the 25 km gridded data based on the IPCC SRES A2 emission scenario. Satellite remote sensing data were used to pinpoint the rice-growing areas, and corresponding climate data were aggregated to represent the official 'crop reporting county'. For the simulation experiment, we used a CERES-Rice model modified by introducing two equations to calculate the leaf appearance rate based on the effective temperature and existing leaf number and the final number of leaves based on day-length in the photoperiod sensitive phase of rice. We tested the performance of this model using data-sets obtained from transplanting dates and nitrogen fertilization rates experiments over three years (2002 to 2004). The simulation results showed a good performance of this model in heading date prediction [$R^2$=0.9586 for early (Odaebyeo), $R^2$=0.9681 for medium (Hwasungbyeo), and $R^2$=0.9477 for late (Dongjinbyeo) maturity cultivars]. A modified version of CERES-Rice was used to simulate the growth and development of three Japonica varieties, representing early, medium, and late maturity classes, to project crop status for climatological normal years between 2011 and 2100. In order to compare the temporal changes, three sets of data representing 3 climatological years (2011-2040, 2041-2070, and 2071-2100) were successively used to run the model. Simulated growth and yield data of the three Japonica cultivars under the observed climate for 1971-2000 was set as a reference. Compared with the current normal, heading date was accelerated by 7 days for 2011-2040 and 20 days for 2071-2100. Physiological maturity was accelerated by 15 days for 2011-2040 and 30 days for 2071-2100. Rice yield was in general reduced by 6-25%, 3-26%, and 3-25% per 10a in early, medium, and late maturity classes, respectively. However, mid to late maturing varieties showed an increased yield in northern Gyeonggi Province and in most of Kwangwon Province in 2071-2100.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.107-120
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• 2017

There are many wildfire risk indices worldwide, but objective comparisons between such various wildfire risk indices and surface dryness indices have not been conducted for the wildfire cases in Korea. This paper describes a sensitivity analysis on the wildfire risk indices and surface dryness indices for Korea using LDAPS(Local Analysis and Prediction System) meteorological dataset on a 1.5-km grid and MODIS(Moderate-resolution Imaging Spectroradiometer) satellite images on a 1-km grid. We analyzed the meteorology-based wildfire risk indices such as the Australian FFDI(forest fire danger index), the Canadian FFMC(fine fuel moisture code), the American HI(Haines index), and the academically presented MNI(modified Nesterov index). Also we examined the satellite-based surface dryness indices such as NDDI(normalized difference drought index) and TVDI(temperature vegetation dryness index). As a result of the comparisons between the six indices regarding 120 wildfire cases with the area damaged over 1ha during the period between January 2013 and May 2017, we found that the FFDI and FFMC showed a good predictability for most wildfire cases but the MNI and TVDI were not suitable for Korea. The NDDI can be used as a proxy parameter for wildfire risk because its average CDF(cumulative distribution function) scores were stably high irrespective of fire size. The indices tested in this paper should be carefully chosen and used in an integrated way so that they can contribute to wildfire forecasting in Korea.

• Journal of Bio-Environment Control
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• v.29 no.2
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• pp.161-170
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• 2020

There is systematic spatial variations in environmental properties due to sensitive reaction to external conditions at plastic greenhouse occupied 99.2% of domestic agricultural facilities. In order to construct 3 dimensional distribution of temperature, relative humidity, CO₂ and illuminance, measurement matrix as 3 by 3 by 5 in direction of width, height and length, respectively, dividing indoor space of greenhouse was designed and tested at experimental site. Linear regression analysis was conducted to evaluate optimal estimation method in terms with horizontal and vertical variations. Even though sole measurement point for temperature and relative humidity could be feasible to assess indoor condition, multiple measurement matrix is inevitably required to improve spatial precision at certain time domain such as period of sunrise and sunset. In case with CO₂, multiple measurement matrix could not successfully improve the spatial predictability during a whole experimental period. In case with illuminance, prediction performance was getting smaller after a time period of sunrise due to systematic interference such as indoor structure. Thus, multiple sensing methodology was proposed in direction of length at higher height than growing bed, which could compensate estimation error in spatial domain. Appropriate measurement matrix could be constructed considering the transition of stability in indoor environmental properties due to external variations. As a result, optimal measurement matrix should be carefully designed considering flexibility of construction relevant with the type of property, indoor structure, the purpose of crop and the period of growth. For an instance, partial cooling and heating system to save a consumption of energy supplement could be successfully accomplished by the deployment of multiple measurement matrix.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.374-390
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• 2021

Growth and yield of field vegetable crops would be affected by climate conditions, which cause a relatively large fluctuation in crop production and consumer price over years. The yield prediction system for these crops would support decision-making on policies to manage supply and demands. The objectives of this study were to compile literatures related to onion and garlic and to perform data-mining analysis, which would shed lights on the development of crop models for these major field vegetable crops in Korea. The literatures on crop growth and yield were collected from the databases operated by Research Information Sharing Service, National Science & Technology Information Service and SCOPUS. The keywords were chosen to retrieve research outcomes related to crop growth and yield of onion and garlic. These literatures were analyzed using text mining approaches including word cloud and semantic networks. It was found that the number of publications was considerably less for the field vegetable crops compared with rice. Still, specific patterns between previous research outcomes were identified using the text mining methods. For example, climate change and remote sensing were major topics of interest for growth and yield of onion and garlic. The impact of temperature and irrigation on crop growth was also assessed in the previous studies. It was also found that yield of onion and garlic would be affected by both environment and crop management conditions including sowing time, variety, seed treatment method, irrigation interval, fertilization amount and fertilizer composition. For meteorological conditions, temperature, precipitation, solar radiation and humidity were found to be the major factors in the literatures. These indicate that crop models need to take into account both environmental and crop management practices for reliable prediction of crop yield.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.329-339
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• 2021

Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R²=0.74, RMSE=246 g/m², RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m² and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m² and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m²) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.4 no.4
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• pp.224-236
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• 2002

A long-term growth simulation was performed at 496 land units in the western coastal plains (WCP) of North Korea to test the potential adaptability of each land unit for growing South Korean rice cultivars. The land units for rice cultivation (CZU), each of them represented by a geographically referenced 5 by 5 km grid tell, were identified by analyzing satellite remote sensing data. Surfaces of monthly climatic normals for daily maximum and minimum temperature, precipitation number of rain days and solar radiation were generated at a 1 by 1 km interval by spatial statistical methods using observed data at 51 synoptic weather stations in North and South Korea during 1981-2000. Grid cells felling within a same CZU and, at the same time, corresponding to the satellite data- identified rice growing pixels were extracted and aggregated to make a spatially explicit climatic normals relevant to the rice growing area of the CZU. Daily weather dataset for 30 years was randomly generated from the monthly climatic normals of each CZU. Growth and development parameters of CERES-rice model suitable for 11 major South Korean cultivars were derived from long-term field observations. Eight treatments comprised of 2 transplanting dates $\times$ 2 cropping systems $\times$ 2 irrigation methods were assigned to each cultivar. Each treatment was simulated with the randomly generated 30 years' daily weather data (from planting to physiological maturity) for 496 land units in WCP to simulate the growth and yield responses to the interannual climate variation. The same model was run with the input data from the 3 major crop experiment stations in South Korea to obtain a 30 year normal performance of each cultivar, which was used as a "reference" for comparison. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to evaluate the suitability of each land unit for growing a specific South Korean cultivar. The results may be utilized as decision aids for agrotechnology transfer to North Korea, for example, germplasm evaluation, resource allocation and crop calendar preparation.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.101-104
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• 2006

In the Korean seas, Sea Surface Temperature (SST) and Thermal Fronts (TF) were analyzed temporally and spatially during 8 years from 1993 to 2000 using NOAA/AVHRR MCSST. As the result of EOF method applying SST, the variance of the 1st mode was 97.6%. It is suitable to explain SST conditions in the whole Korean seas. Time coefficients were shown annual variations and spatial distributions were shown the closer to the continent the higher SST variations like as annual amplitudes. The 2nd mode presented higher time coefficients of 1993, 94, and 95 than those of other years. Although the influence is a little, that can explain ElNINO effect to the Korean seas. TF were detected by Sobel Edge Detection Method using gradient of SST. Consequently, TF were divided into 4 fronts; the Subpola. Front (SPF) dividing into the north and south part of the East sea, the Kuroshio Front (KF) in the East China Sea (ESC), the South Sea Coastal Front (SSCF) in the South sea, and the Tidal Front in the West sea. TF located in steep slope of submarine topography. The distributions of 1st mode in SST were bounded in the same place, and these results should be considered to influence of seasonal variations. To discover temporal and spatial variations of TF,SST gradient values were analyzed by EOF. The time coefficients fo the 1st mode (variance : 64.55%) showed distinctive annual variations and SPF, KF, and SSCF was significantly appeared in March. the spatial distributions of the 2nd mode showed contrast distribution, as SPF and SSCF had strong '-' value, where KF had strong '+' value. The time of '+' and '-' value was May and October, respectively. Time coefficients of the 3rd mode had 2 peaks per year and showed definite seasonal variations. SPF represented striking '+' value which time was March and October That was result reflected time of the 1st and 2nd mode. We can suggest specific temporal and spatial variations of TF using EOF.