• Journal of the Korean Society of Hazard Mitigation
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• v.1 no.1 s.1
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• pp.139-155
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• 2001

We investigate the vertical velocity models beneath the newly installed broadband seismic network of KMA (Korea Meteorological Administration) by using receiver function inversion technique. The seismic phases are primarily P-to-S conversions and reverberations generated at the two highest impedance interfaces like the Moho (crust-mantle boundary) and the sediment-basement contact. We obtained the teleseismic P-wave receiver functions, which were derived from teleseismic records of Seoul (SEO), Inchon (INCN), Tejeon (TEJ) , Sosan (SOS/SES), Kangnung (KAN), Ulchin (ULC/ULJ), Taegu (TAG), Pusan (PUS), and Ullung-do (ULL) stations. For Kwangju (KWA/KWJ) and Chunchon (CHU) stations, the Moho conversion Ps arrivals and waveforms of radial receiver functions are azimuthally inconsistent and unclear. From the receiver function inversion result, we found that crustal thickness is 29 km at INCN, SEO, and SOS (SES) stations, 28 km at KAN station in the Kyonggi Massif, 32 km at TEJ station in Okchon Folded Belt, 34 km at TAG, 33 km at PUS station in the Kyongsang Basin, 32 km at KWJ station (readjusted station by prior KWA station) included in the Youngdong-Kwangju Depression Zone, 28 km at ULC station in the eastern margin of the Ryongnam Massif, and 17 km at ULL station in the Ullung Island of the East Sea, respectively. The Moho configuration of INCN, SOS, KWJ, and KAN stations show a laminated smooth transition zone with a 3-5 km thick. The upper crusts(${\sim}5km$) of KAN, ULC, and PUS stations show complex structures with a high velocity. The unusually thick crusts are found at the TAG and PUS stations in the Kyongsang Basin compared to the thin (29-32 km) crust of the western part (INCN, SEO, SOS, TEJ, and KWA stations) The crustal thickness beneath Ullung Island (ULL station) shows the suboceanic crust with about 17 km thickness and complex with a high velocity layer of the upper crust, and the amplitudes of Incoming Ps waves from the western direction are relatively large compared to those from othor directions.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.551-558
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• 2008

It is well known that the protein content of rice grain is an indicator of taste of cooked rice in the countries where people as the staple food. Ground-based optical sensing over the crop canopy would provide information not only on the mass of plant body which reflects the light, but also on the crop nitrogen content which is closely related to the greenness of plant leaves. The vegetation index has been related to crop variables such as biomass, leaf nitrogen, plant cover, and chlorophyll in cereals. The objective of this study was to investigate the correlation between GNDVI and NDVI values, and grain protein content at different dates and to estimate the grain protein content using G(NDVI) values. We measured Green normalized difference vegetation index [$GNDVI=({\rho}0.80{\mu}m-{\rho}0.55{\mu}m)/({\rho}0.80{\mu}m+{\rho}0.55{\mu}m)$] and [$GNDVI=({\rho}0.80{\mu}m-{\rho}0.68{\mu}m)/({\rho}0.80{\mu}m+{\rho}0.68{\mu}m)$] by using two different active sensors. The study was conducted during the rice growing season for three years from 2005 through 2007 at the experimental plots of National Institute of Agricultural Science and Technology. The experiments were carried out by randomized complete block design with the application of four levels of nitrogen fertilizers(0, 70, 100, 130kg N/ha) and the same amount of phosphorous and potassium content of the fertilizers. After heading stage, relationships between GNDVI of rice canopy and grain protein content showed the highly positive correlation at different dates for three years. GNDVI values showed higher correlation coefficients than that of NDVI during growing season in 2005-07. The correlation between GNDVI values at different dates and grain protein contents was highly correlated at early July. We attempted to estimate the grain protein content at harvesting stage using GNDVI values from early July for three years. The determination coefficients of the linear model by GNDVI values were 0.9l and the measured and estimated grain protein content at harvesting stage using GNDVI values highly correlated($R^2=0.96^{***}$). Results from this study show that GNDVI appeared very effective to estimate leaf nitrogen and grain protein content of rice canopy.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.968-974
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• 2010

We assessed the feasibility of discrete wavelet transform (DWT) applied for the spectral processing to enhance the estimation performance quality of soil organic matters using visible-near infrared spectra and mapped their distribution via block Kriging model. Continuum-removal and $1^{st}$ derivative transform as well as Haar and Daubechies DWT were used to enhance spectral variation in terms of soil organic matter contents and those spectra were put into the PLSR (Partial Least Squares Regression) model. Estimation results using raw reflectance and transformed spectra showed similar quality with $R^2$ > 0.6 and RPD> 1.5. These values mean the approximation prediction on soil organic matter contents. The poor performance of estimation using DWT spectra might be caused by coarser approximation of DWT which not enough to express spectral variation based on soil organic matter contents. The distribution maps of soil organic matter were drawn via a spatial information model, Kriging. Organic contents of soil samples made Gaussian distribution centered at around 20 g $kg^{-1}$ and the values in the map were distributed with similar patterns. The estimated organic matter contents had similar distribution to the measured values even though some parts of estimated value map showed slightly higher. If the estimation quality is improved more, estimation model and mapping using spectroscopy may be applied in global soil mapping, soil classification, and remote sensing data analysis as a rapid and cost-effective method.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.603-614
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• 2021

Recently, the surface temperature in the seas around Korea has been continuously rising. This temperature rise causes changes in fishery resources and affects leisure activities such as fishing. In particular, high temperatures lead to the occurrence of red tides, causing severe damage to ocean industries such as aquaculture. Meanwhile, changes in sea temperature are closely related to military operation to detect submarines. This is because the degree of diffraction, refraction, or reflection of sound waves used to detect submarines varies depending on the ocean mixed layer. Currently, research on the prediction of changes in sea water temperature is being actively conducted. However, existing research is focused on predicting only the surface temperature of the ocean, so it is difficult to identify fishery resources according to depth and apply them to military operations such as submarine detection. Therefore, in this study, we predicted the temperature of the ocean mixed layer at a depth of 38m by using temperature data for each water depth in the upper mixed layer and meteorological data such as temperature, atmospheric pressure, and sunlight that are related to the surface temperature. The data used are meteorological data and sea temperature data by water depth observed from 2016 to 2020 at the IEODO Ocean Research Station. In order to increase the accuracy and efficiency of prediction, LSTM (Long Short-Term Memory), which is known to be suitable for time series data among deep learning techniques, was used. As a result of the experiment, in the daily prediction, the RMSE (Root Mean Square Error) of the model using temperature, atmospheric pressure, and sunlight data together was 0.473. On the other hand, the RMSE of the model using only the surface temperature was 0.631. These results confirm that the model using meteorological data together shows better performance in predicting the temperature of the upper ocean mixed layer.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.384-392
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• 2022

The objective of this study was to estimated nitrogen content and chlorophyll using RGB, Hyperspectral sensors to diagnose of nitrogen nutrition in apple tree leaves. Spectral data were acquired through image processing after shooting with high resolution RGB and hyperspectral sensor for two-year-old 'Hongro/M.9' apple. Growth data measured chlorophyll and leaf nitrogen content (LNC) immediately after shooting. The growth model was developed by using regression analysis (simple, multi, partial least squared) with growth data (chlorophyll, LNC) and spectral data (SPAD meter, color vegetation index, wavelength). As a result, chlorophyll and LNC showed a statistically significant difference according to nitrogen fertilizer level regardless of date. Leaf color became pale as the nutrients in the leaf were transferred to the fruit as over time. RGB sensor showed a statistically significant difference at the red wavelength regardless of the date. Also hyperspectral sensor showed a spectral difference depend on nitrogen fertilizer level for non-visible wavelength than visible wavelength at June 10th and July 14th. The estimation model performance of chlorophyll, LNC showed Partial least squared regression using hyperspectral data better than Simple and multiple linear regression using RGB data (Chlorophyll R²: 81%, LNC: 81%). The reason is that hyperspectral sensor has a narrow Full Half at Width Maximum (FWHM) and broad wavelength range (400-1,000 nm), so it is thought that the spectral analysis of crop was possible due to stress cause by nitrogen deficiency. In future study, it is thought that it will contribute to development of high quality and stable fruit production technology by diagnosis model of physiology and pest for all growth stage of tree using hyperspectral imagery.

• Journal of Korean Philosophical Society
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• no.125
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• pp.63-89
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• 2019

The aim of this paper is to examine the so-called theory of automatic action attributed to Plotinus, according to which the sage can act automatically without deliberation or reasoning. Concerns were raised that such a theory runs the risk of turning the agent into an automaton by reducing action to mechanical reflexes to external stimuli. I attempt to show that Plotinus does not hold a theory of automatic action by arguing that the Plotinian sage's non-deliberative action is not automatic at all. For this purpose, I first draw attention to the non-deliberative action of the World-Reason (i.e. the reason of the World-Soul), which is supposed to present an ideal model of action. Indeed, Plotinus mentions that the World-Reason rules the world "as if automatically". This is, however, meant to indicate the spontaneous and natural manner in which the World-Reason rules. In this respect, the way the World-Reason works is compared to the way nature (i.e. the productive power of the World-Soul) works. But Plotinus points out that the World-Reason knows what to do, whereas nature works without knowing. In this connection, Plotinus makes it clear that the World-Reason does not calculate or deliberate about what to do because it already knows it. To clarify this point, I turn to Plotinus' analogy of practical wisdom (phronêsis) and skill, according to which the World-Reason is compared to an accomplished craftsman or artist, who confidently works without any doubt, hesitation or difficulty, thereby expressing her intelligence, unmediated by deliberation. From this perspective, non-deliberative action according to practical wisdom turns out to be superior to deliberative action. Plotinus admits that there are difficult circumstances in which even the skilled craftsman, unlike the World-Reason who always controls the whole situation, needs to deliberate or calculate, but he is nevertheless confident that the craftsman easily finds the solution. This suggests that the sage, who possesses practical wisdom, can act normally like a great master or virtuoso without deliberation, but in an emergency situation he also employs deliberation, but resourcefully and creatively responds to challenge. The attempt is made to elucidate the Plotinian model of sage's action with the help of Csikzentmihalyi's concept of 'flow' and Annas' application of it to the analogy of virtue and skill. Finally, it is shown that the sage's virtuous action, in spite of being a habituated action, is not a passive, routinized, automatic action, but an active, flexible, intelligent action.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.9-18
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• 2024

The importance of active sonar systems is emerging due to the quietness of underwater targets and the increase in ambient noise due to the increase in maritime traffic. However, the low signal-to-noise ratio of the echo signal due to multipath propagation of the signal, various clutter, ambient noise and reverberation makes it difficult to identify underwater targets using active sonar. Attempts have been made to apply data-based methods such as machine learning or deep learning to improve the performance of underwater target recognition systems, but it is difficult to collect enough data for training due to the nature of sonar datasets. Methods based on mathematical modeling have been mainly used to compensate for insufficient active sonar data. However, methodologies based on mathematical modeling have limitations in accurately simulating complex underwater phenomena. Therefore, in this paper, we propose a sonar signal synthesis method based on a deep neural network. In order to apply the neural network model to the field of sonar signal synthesis, the proposed method appropriately corrects the attention-based encoder and decoder to the sonar signal, which is the main module of the Tacotron model mainly used in the field of speech synthesis. It is possible to synthesize a signal more similar to the actual signal by training the proposed model using the dataset collected by arranging a simulated target in an actual marine environment. In order to verify the performance of the proposed method, Perceptual evaluation of audio quality test was conducted and within score difference -2.3 was shown compared to actual signal in a total of four different environments. These results prove that the active sonar signal generated by the proposed method approximates the actual signal.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.53-61
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• 2014

Landsat OLI satellite imagery can be applied to various remote sensing applications, such as generation of land cover map, urban area analysis, extraction of vegetation index and change detection, because it includes various multispectral bands. In addition, land cover map is an important information to monitor and analyze land cover using GIS. In this paper, land cover map is generated by using Landsat OLI and existing land cover map. First, training dataset is obtained using correlation between existing land cover map and unsupervised classification result by K-means, automatically. And then, spectral signatures corresponding to each class are determined based on training data. Finally, abundance map and land cover map are generated by using iterative spectral mixture model. The experiment is accomplished by Landsat OLI of Cheongju area. It shows that result by our method can produce land cover map without manual training dataset, compared to existing land cover map and result by supervised classification result by SVM, quantitatively and visually.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.5
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• pp.345-352
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• 2016

As aircrafts are being operated at high altitude, wing structures experience various fatigue loadings under cryogenic environments. As a result, fatigue damage such as a crack could be develop that could eventually lead to a catastrophic failure. For this reason, fatigue damage monitoring is an important process to ensure efficient maintenance and safety of structures. To implement damage detection in real-world flight environments, a special cooling chamber was built. Inside the chamber, the temperature was maintained at the cryogenic temperature, and harmonic fatigue loading was given to a wing structure. In this study, piezoelectric active-sensing based guided waves were used to detect the fatigue damage. In particular, a beamforming technique was applied to efficiently measure the scattering wave caused by the fatigue damage. The system was used for detection, growth monitoring, and localization of a fatigue crack. In addition, a sensor diagnostic process was also applied to ensure the proper operation of piezoelectric sensors. Several experiments were implemented and the results of the experiments demonstrated that this process could efficiently detect damage in such an extreme environment.

• Journal of Radiation Protection and Research
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• v.33 no.3
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• pp.113-120
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• 2008

In this study, The TRITGO code was introduced, which can predict the amount of tritium production, it's transport, removal, distribution and the level of contamination for the produced hydrogen by the tritium on the VHTR (very high temperature gas cooled reactor). The TRITGO code was improved so that the permeation to the IS Iodine Sulfide) loop for producing the hydrogen can be simulated. The contamination level of the produced hydrogen by the tritium was predicted by the improved code for the VHTR with 600MW thermal power. The contamination level for the produced hydrogen by tritium was predicted as 0.055 Bq/$H_2-g$. This level is three order of lower than the regulation value of 56 Bq/$H_2-g$ from Japan. From this study, the following results were obtained. it is important that the fuel coating (SiC layer) should be kept intact to prevent the tritium from releasing. Also it is necessary that the level of impurity such as 3He and Li in the helium coolant and the reflector consisting of the graphite should be kept as low as possible. It was found that the capacity of the purification system for filtering the impurities directly from the coolant will be the important design parameter.