• Korean Journal of Remote Sensing
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• v.16 no.3
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• pp.211-220
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• 2000

Even though recurring eddies at the terminal end of the East Korean Warm Current have been identified in the thermal infrared imagery from the NOAA/AVHRR sensor and ocean color data from Orbview-2/SeaWiFS sensor, it is difficult to make observation in the field regarding recurring eddies located around the Wonsan coastal area in North Korea. But we could get in situ data related to an eddy from an ARGOS satellite tracking drifter trapped in the eddy on January 4th, 1999. An ARGOS drifter, a NOAA satellite tracked buoy was trapped by the eddy during January 4th.March 18, 1999. The ARGOS drifter rotated 10 times per 72 days on the edge of the eddy located at $39^{\circ}N$, $129^{\circ}E$. The diameter of the eddy was about 100 km. The horizontal rotation velocity of the recurring cold-core anti-cyclonic eddy was 1.53 km/h(42 cm/sec). The sea surface temperatures of the eddy varied from $14.7^{\circ}C$ on January 5, 1999 to $9.6^{\circ}C$ on March 18,1999. To study the mechanism of the recurring eddy. we tried to find out the relationship between the vector of the drifter moving in the eddy and the wind vector in Sokcho and Ulleung Island located near the eddy in southern Korea, and the difference in sea level between Ulleung Island and Mukho. We hope the results of this study would be useful for calibration and validation data of simulation and numerical modeling studies of the recurring eddy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.310-316
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• 2019

In automotive application, customers are demanding high efficiency and various functions for convenience. The demand for these automotive applications is steadily increasing. In this study, it has been studied the analysis of heat flow to improve the PCB(printed circuit board) heating performance of WPC (wireless power charger) recently developed for convenience. The charging performance of the wireless charger has been reduced due to power dissipation and thermal resistance of PCB. Therefore, it has been proposed optimal PCB design, layout and position of electronic parts through the simulation of heat flow analysis and PCB design was analyzed and decided at each design stage. Then, the experimental test is performed to verify the consistency of the analysis results under actual environmental conditions. In this paper, The PCB modeling and heat flow simulation in transient response were performed using HyperLynx Thermal and FloTHERM. In addition, the measurement was performed using infrared thermal imaging camera and used to verify the analysis results. In the final comparison, the error between analysis and experiment was found to be less than 10 % and the heating performance of PCB was also improved.

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.581-589
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• 2021

Using visible-near infrared(Vis-NIR) spectra combined with machine learning methods, the feasibility of quick and non-destructive classification of Convolvulaceae species was studied. The main aim of this study is to classify six Convolvulaceae species in the field in different geographical regions of South Korea using a handheld spectrometer. Spectra were taken at 1.5 nm intervals from the adaxial side of the leaves in the Vis-NIR spectral region between 400 and 1,075 nm. The obtained spectra were preprocessed with three different preprocessing methods to find the best preprocessing approach with the highest classification accuracy. Preprocessed spectra of the six Convolvulaceae sp. were provided as input for the machine learning analysis. After cross-validation, the classification accuracy of various combinations of preprocessing and modeling ranged between 43.4% and 98.6%. The combination of Savitzky-Golay and Support vector machine methods showed the highest classification accuracy of 98.6% for the discrimination of Convolvulaceae sp. The growth stage of the plants, different measuring locations, and the scanning position of leaves on the plant were some of the crucial factors that affected the outcomes in this investigation. We conclude that Vis-NIR spectroscopy, coupled with suitable preprocessing and machine learning approaches, can be used in the field to effectively discriminate Convolvulaceae sp. for effective weed monitoring and management.

• Horticultural Science & Technology
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• v.32 no.1
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• pp.105-114
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• 2014

We established a high throughput screening system of African yam tuber lines which contain high contents of total carotenoids, flavonoids, and phenolic compounds using ultraviolet-visible (UV-VIS) spectroscopy and Fourier transform infrared (FT-IR) spectroscopy in combination with multivariate analysis. The total carotenoids contents from 62 African yam tubers varied from 0.01 to $0.91{\mu}g{\cdot}g^{-1}$ dry weight (wt). The total flavonoids and phenolic compounds also varied from 12.9 to $229{\mu}g{\cdot}g^{-1}$ and from 0.29 to $5.2mg{\cdot}g^{-1}$dry wt. FT-IR spectra confirmed typical spectral differences between the frequency regions of 1,700-1,500, 1,500-1,300 and $1,100-950cm^{-1}$, respectively. These spectral regions were reflecting the quantitative and qualitative variations of amide I, II from amino acids and proteins ($1,700-1,500cm^{-1}$), phosphodiester groups from nucleic acid and phospholipid ($1,500-1,300cm^{-1}$) and carbohydrate compounds ($1,100-950cm^{-1}$). Principal component analysis (PCA) and subsequent partial least square-discriminant analysis (PLS-DA) were able to discriminate the 62 African yam tuber lines into three separate clusters corresponding to their taxonomic relationship. The quantitative prediction modeling of total carotenoids, flavonoids, and phenolic compounds from African yam tuber lines were established using partial least square regression algorithm from FT-IR spectra. The regression coefficients ($R^2$) between predicted values and estimated values of total carotenoids, flavonoids and phenolic compounds were 0.83, 0.86, and 0.72, respectively. These results showed that quantitative predictions of total carotenoids, flavonoids, and phenolic compounds were possible from FT-IR spectra of African yam tuber lines with higher accuracy. Therefore we suggested that quantitative prediction system established in this study could be applied as a rapid selection tool for high yielding African yam lines.

• Korean journal of applied entomology
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• v.51 no.3
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• pp.235-243
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• 2012

Population dynamics of the American serpentine leafminer, Liriomyza trifolii (Burgess), were observed and modeled in order to compare the effects of air and tomato leaf temperatures inside a greenhouse using DYMEX model builder and simulator (pre-programed module based simulation programs developed by CSIRO, Australia). The DYMEX model simulator consisted of a series of modules with the parameters of temperature dependent development and oviposition models of L. trifolii were incorporated from pre-published data. Leaf surface temperatures of cherry tomato leaves (cv. 'Koko') were monitored according to three tomato plant positions (top, > 1.8 m above the ground level; middle, 0.9 - 1.2 m; bottom, 0.3 - 0.5 m) using an infrared temperature gun. Air temperature was monitored at the same three positions using a self-contained temperature logger. Data sets for the observed air temperature and average leaf surface temperatures were collected (top and bottom surfaces), and incorporated into the DYMEX simulator in order to compare the effects of air and leaf surface temperature on the population dynamics of L. trifolii. The initial population consisted of 50 eggs, which were laid by five female L. trifolii in early June. The number of L. trifolii larvae was counted by visual inspection of the tomato plants in order to verify the performance of DYMEX simulation. The egg, pupa, and adult stage of L. trifolii could not be counted due to its infeasible of visual inspection. A significant positive correlation between the observed and the predicted numbers of larvae was found when the leaf surface temperatures were incorporated into the DYMEX simulation (r = 0.97, p < 0.01), but no significant positive correlation was observed with air temperatures(r = 0.40, p = 0.18). This study demonstrated that the population dynamics of L. trifolii was affected greatly by the leaf temperatures, though to little discernible degree by the air temperatures, and thus the leaf surface temperature should be for a consideration in the management of L. trifolii within cherry tomato greenhouses.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.363-373
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• 2020

During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.

• Journal of Soil and Groundwater Environment
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• v.14 no.3
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• pp.1-13
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• 2009

Alkalinity and total carbon contents were measured by acid neutralizing titration (ANT), back titration (BT), gravitational weighing (GW), non-dispersive infrared-total carbon (NDIR-TC) methods for assessing precision and accuracy of alkalinity and total carbon concentration in $CO_2$-rich water. Artificial $CO_2$-rich water(ACW: pH 6.3, alkalinity 68.8 meq/L, $HCO_3^-$ 2,235 mg/L) was used for comparing the measurements. When alkalinity measured in 0 hr, percent errors of all measurement were 0~12% and coefficient of variation were less than 4%. As the result of post-hoc analysis after repeated measure analysis of variance (RM-AMOVA), the differences between the pair of methods were not significant (within confidence level of 95%), which indicates that the alkalinity measured by any method could be accurate and precise when it measured just in time of sampling. In addition, alkalinity measured by ANT and NDIR-TC were not change after 24 and 48 hours open to atmosphere, which can be explained by conservative nature of alkalinity although $CO_2$ degas from ACW. On the other hand, alkalinity measured by BT and GW increased after 24 and 48 hours open to atmosphere, which was caused by relatively high concentration of measured total carbon and increasing pH. The comparison between geochemical modeling of $CO_2$ degassing and observed data showed that pH of observed ACW was higher than calculated pH. This can be happen when degassed $CO_2$ does not come out from the solution and/or exist in solution as $CO_{2(g)}$ bubble. In that case, $CO_{2(g)}$ bubble doesn't affect the pH and alkalinity. Thus alkalinity measured by ANT and NDIR-TC could not detect the $CO_2$ bubble although measured alkalinity was similar to the calculated alkalinity. Moreover, total carbon measured by ANT and NDIR-TC could be underestimated. Consequently, it is necessary to compare the alkalinity and total carbon data from various kind of methods and interpret very carefully. This study provide technical information of measurement of dissolve $CO_2$ from $CO_2$-rich water which could be natural analogue of geologic sequestration of $CO_2$.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.401-409
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• 2021

This study aimed to estimate the photosynthetic capacity of tomato plants grown in a semi-closed greenhouse using temperature response models of plant photosynthesis by calculating the ribulose 1,5-bisphosphate carboxylase/oxygenase maximum carboxylation rate (V_cmax), maximum electron transport rate (J_max), thermal breakdown (high-temperature inhibition), and leaf respiration to predict the optimal conditions of the CO₂-controlled greenhouse, for maximizing the photosynthetic rate. Gas exchange measurements for the A-C_i curve response to CO₂ level with different light intensities {PAR (Photosynthetically Active Radiation) 200µmol·m^-2·s^-1 to 1500µmol·m^-2·s^-1} and leaf temperatures (20℃ to 35℃) were conducted with a portable infrared gas analyzer system. Arrhenius function, net CO₂ assimilation (A_n), thermal breakdown, and daylight leaf respiration (R_d) were also calculated using the modeling equation. Estimated J_max, A_n, Arrhenius function value, and thermal breakdown decreased in response to increased leaf temperature (> 30℃), and the optimum leaf temperature for the estimated J_max was 30℃. The CO₂ saturation point of the fifth leaf from the apical region was reached at 600ppm for 200 and 400µmol·m^-2·s^-1 of PAR, at 800ppm for 600 and 800µmol·m^-2·s^-1 of PAR, at 1000ppm for 1000µmol of PAR, and at 1500ppm for 1200 and 1500µmol·m^-2·s^-1 of PAR levels. The results suggest that the optimal conditions of CO₂ concentration can be determined, using the photosynthetic model equation, to improve the photosynthetic rates of fruit vegetables grown in greenhouses.