• The Korean Journal of Malacology
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• v.29 no.1
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• pp.15-21
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• 2013

Nitric oxide (NO) is an important intra-intercellular signaling molecule that regulates many physiological processes and participates in the development some pathological conditions in animals. In this study, we compared different methods for determining NO concentration in the hemocytes of Manila clam Ruditapes philippinarum. For measuring the intracellular NO levels, we used the specific fluorescent probe 4,5-diaminofluorescein diacetate (DAF-2 DA), and the quantification methods that were compared were based on image analysis, spectrophotometry, and flow cytometry. NO concentration could be determined using all the 3 methods, and the concentration varied significantly depending upon the presence of NO regulators in the hemocytes; NO concentration increased in the presence of L-arginine, while it decreased in the presence of N-nitro-L-arginine methyl ester. In particular, it is found that estimation of NO using a flowcytometry is more economical, reliable and accurate compared to image analysis and spectrophotometry. Accordingly we believe that determining NO concentration by using flowcytometry will be useful in evaluating physiological and pathological conditions in marine bivalves.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.34 no.6
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• pp.624-631
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• 2001

The relationship between the catch of squid, Todarodes pacificus, according to the jigging depth and underwater illumination by fishing lamps was investigated during nighttime operations off-Tusima Islands in November 1994 and off-Oki Islands in November 1995. We used echo sounder to observe the distribution of squid. Echo images on the echo sounder showed the distribution of squid at the water layer of 50 meter depth at the beginning of jigging operation. After the time elapsed, a continuous dense image had moved to the layer of 60-80 meters jigging depth. A larger number of squid were caught by jigging machines set at a lowest depth of 90 meters, when it compared with machines set at a 60 meters. However, Catch increased around 60 meters jigging depth, when fishing lamps output were switched to 24 kW halogen lights:.The underwater illumination, under the each light power of fishing lamps of squid jigging boat was continuously measured with an underwater illuminometer. Values of the underwater illumination, when schools were distributed from 60 to 80 meters, ranged from $3.0\times10^{-2}lx\;to\;3.4\times10^{-3}lx$ in average at $80\~360$ kW fishing lamps output of squid jigging boat.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.4
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• pp.287-293
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• 2018

It is prerequisite to generate epipolar resampled images by reducing the y-parallax for accurate and efficient processing of satellite stereo images. Minimizing y-parallax requires the accurate sensor modeling that is carried out with ground control points. However, the approach is not feasible over inaccessible areas where control points cannot be easily acquired. For the case, a relative orientation can be utilized only with conjugate points, but its accuracy for satellite sensor should be studied because the sensor has different geometry compared to well-known frame type cameras. Therefore, we carried out the bias-compensation of RPCs (Rational Polynomial Coefficients) without any ground control points to study its precision and effects on the y-parallax in epipolar resampled images. The conjugate points were generated with stereo image matching with outlier removals. RPCs compensation was performed based on the affine and polynomial models. We analyzed the reprojection error of the compensated RPCs and the y-parallax in the resampled images. Experimental result showed one-pixel level of y-parallax for Kompsat-3 stereo data.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1089-1098
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• 2020

In this study, we propose a method to detect red tide Cochlodinium Polykrikoide using by machine learning and geostationary marine satellite images. To learn the machine learning model, GOCI Level 2 data were used, and the red tide location data of the National Fisheries Research and Development Institute was used. The machine learning model used logistic regression model, decision tree model, and random forest model. As a result of the performance evaluation, compared to the traditional GOCI image-based red tide detection algorithm without machine learning (Son et al., 2012) (75%), it was confirmed that the accuracy was improved by about 13~22%p (88~98%). In addition, as a result of comparing and analyzing the detection performance between machine learning models, the random forest model (98%) showed the highest detection accuracy.It is believed that this machine learning-based red tide detection algorithm can be used to detect red tide early in the future and track and monitor its movement and spread.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.63-80
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• 2022

As a technology to analyze and predict an issue has been developed by constructing real space into virtual space, it is becoming more important to acquire precise spatial information in complex cities. In this study, images were acquired using an unmanned aerial vehicle for urban area with complex landscapes, and land cover classification was performed object-based image analysis and semantic segmentation techniques, which were image classification technique suitable for high-resolution imagery. In addition, based on the imagery collected at the same time, the replicability of land cover classification of each artificial intelligence (AI) model was examined for areas that AI model did not learn. When the AI models are trained on the training site, the land cover classification accuracy is analyzed to be 89.3% for OBIA-RF, 85.0% for OBIA-DNN, and 95.3% for U-Net. When the AI models are applied to the replicability assessment site to evaluate replicability, the accuracy of OBIA-RF decreased by 7%, OBIA-DNN by 2.1% and U-Net by 2.3%. It is found that U-Net, which considers both morphological and spectroscopic characteristics, performs well in land cover classification accuracy and replicability evaluation. As precise spatial information becomes important, the results of this study are expected to contribute to urban environment research as a basic data generation method.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.536-542
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• 2023

Satellites represent cutting-edge technology, of ering significant advantages in spatial and temporal observations. National agencies worldwide harness satellite data to respond to marine accidents and analyze ocean fluctuations effectively. However, challenges arise with high-resolution satellite-based sea surface temperature data (Operational Sea Surface Temperature and Sea Ice Analysis, OSTIA), where gaps or empty areas may occur due to satellite instrumentation, geographical errors, and cloud cover. These issues can take several hours to rectify. This study addressed the issue of missing OSTIA data by employing LaMa, the latest deep learning-based algorithm. We evaluated its performance by comparing it to three existing image processing techniques. The results of this evaluation, using the coefficient of determination (R²) and mean absolute error (MAE) values, demonstrated the superior performance of the LaMa algorithm. It consistently achieved R² values of 0.9 or higher and kept MAE values under 0.5 ℃ or less. This outperformed the traditional methods, including bilinear interpolation, bicubic interpolation, and DeepFill v1 techniques. We plan to evaluate the feasibility of integrating the LaMa technique into an operational satellite data provision system.

• Journal of Astronomy and Space Sciences
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• v.28 no.4
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• pp.333-344
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• 2011

An optical tracking system has advantages for observing geostationary earth orbit (GEO) satellites relatively over other types of observation system. Regular surveying for unidentified space objects with the optical tracking system can be an early warning tool for the safety of five Korean active GEO satellites. Two strategies of positioning on the observed image of Communication, Ocean and Meteorological Satellite 1 are tested and compared. Photometric method has a half root mean square error against streak method. Also eccentricity method for initial orbit determination (IOD) is tested with simulation data and real observation data. Under 10 minutes observation time interval, eccentricity method shows relatively better IOD results than the other time interval. For follow-up observation of unidentified space objects, at least two consecutive observations are needed in 5 minutes to determine orbit for geosynchronous orbit space objects.

• Journal of the Korean Society of Marine Environment & Safety
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• v.17 no.4
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• pp.331-337
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• 2011

We described for the production of cloud-free satellite sea surface temperature(SST) data around Northeast Asian using NOAA AVHRR(Advanced Very High Resolution Radiometer) SST data during 1990-2005. As a result of Markov model, it was found that the value of Markov coefficient in the strong current region such as Kuroshio region showed smaller than that in the weak current. The variations of average SST and regional difference of seasonal day-to-day SST in spring and fall were larger than those in summer and winter. In particular, the distribution of the regional difference appeared large in the vicinity of continental in spring and fall. The difference of seasonal day-to-day SST was also small in Kuroshio region and southern part of East Sea due to the heat advection by warm currents.

• Journal of the Korean Recycled Construction Resources Institute
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• v.2 no.4
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• pp.314-320
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• 2014

Although the cement industry serves as the cornerstone of the construction industry by supplying one of its fundamental materials, it confronts new environmental challenges due to the problem of the $CO_2$ generated from raw materials and fuel used in the cement manufacturing process. Also, concrete structures can be decomposed and reused as construction materials. Simply in terms of the cyclic processing of $CO_2$, recycling waste concrete to manufacture recycled aggregate or recycling waste concrete powder, which is the material for cement can be considered optimally environment-friendly practices. This study contributes to the aim of manufacturing high value added materials that exploits the chemical properties of the waste concrete powder. From the research results, waste concrete powder is feasible to use to produce low carbon type recycled cement.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.1
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• pp.102-108
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• 2016

A flying drone generates vibrations in a great variety of frequencies, and it requires a gimbal system stabilization loop design in order to obtain clean and accurate image from the camera attached to the drone under this environment. The gimbal system for drone comprises the structure that supports the camera module and the stabilization loop which follows the precise angle while blocking the vibration from outside. This study developed a dynamic model for one axis for the stabilization loop design of a gimbal system for drones and applied classical PID controller and intelligent PID controller. The Stabilization loop design was developed by using MATLAB/Simulink and compared the performance of each controller through simulation. Especially, the intelligent PID controller can be designed almost without the dynamic model and it demonstrates that the angle can be followed without readjusting the parameters of the controller even when the characteristics of the model changes.