• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.695-713
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• 2023

In coastal waters, phytoplankton,suspended particulate matter, and dissolved organic matter intricately and nonlinearly alter the reflectivity of seawater. Neural network technology, which has been rapidly advancing recently, offers the advantage of effectively representing complex nonlinear relationships. In previous studies, a three-stage neural network was constructed to extract the inherent optical properties of each component. However, this study proposes an algorithm that directly employs a deep neural network. The dataset used in this study consists of synthetic data provided by the International Ocean Color Coordination Group, with the input data comprising above-surface remote-sensing reflectance at nine different wavelengths. We derived inherent optical properties using this dataset based on a deep neural network. To evaluate performance, we compared it with a quasi-analytical algorithm and analyzed the impact of log transformation on the performance of the deep neural network algorithm in relation to data distribution. As a result, we found that the deep neural network algorithm accurately estimated the inherent optical properties except for the absorption coefficient of suspended particulate matter (R² greater than or equal to 0.9) and successfully separated the sum of the absorption coefficient of suspended particulate matter and dissolved organic matter into the absorption coefficient of suspended particulate matter and dissolved organic matter, respectively. We also observed that the algorithm, when directly applied without log transformation of the data, showed little difference in performance. To effectively apply the findings of this study to ocean color data processing, further research is needed to perform learning using field data and additional datasets from various marine regions, compare and analyze empirical and semi-analytical methods, and appropriately assess the strengths and weaknesses of each algorithm.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.1 no.1
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• pp.53-68
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• 1981

Most clays under sustained load exhibit time-dependent deformation because of creep movement of soil particles and many investigators have attempted to relate their findings to the creep behavior of natural ground and to the long-term stability of slopes. Since the creep behavior of clays may assume a variety of forms depending on such factors as soil plasticity, activity and water content, it is difficult and complicated to analyse the creep behavior of clays. Rheological models composed of linear springs in combination with linear or nonlinear dashpots and sliders, are generally used for the mathematical description of the time-dependent behavior of soils. Most rheological models, however, have been proposed to simulate the behavior of secondary compression for saturated clays and few definitive data exist that can evaluate the behavior of non-saturated clays under the action of sustained stress. The clays change gradually from a solid state through plastic state to a liquid state with increasing water content, therefore, the rheological models also change. On the other hand, creep is time-dependent, and also the effect of thixotropy is time-function. Consequently, there may be certain correlations between creep behavior and the effects of thixotropy in compacted clays. In addition, the states of clay depend on water content and hence the height of the specimen under drained conditions. Futhermore, based on present and past studies, because immediate elastic deformation occurs instantly after the pressure increment without time-delayed behavior, the factor representing immediate elastic deformations in the rheological model is necessary. The investigation described in this paper, based on rheological model, is designed to identify the immediate elastic deformations and the effects of thixotropy and height of clay specimens with varing water content and stress level on creep deformations. For these purposes, the uniaxial drain-type creep tests were performed. Test results and data for three compacted clays have shown that a linear top spring is needed to account for immediate elastic deformations in the rheological model, and at lower water content below the visco-plastic limit, the effects of thixotropy and height of clay specimens can be represented by the proposed rheological model not considering the effects. Therefore, the rheological model does not necessitate the other factors representing these effects. On the other hand, at water content higher than the visco-plastic limit, although the state behavior of clays is visco-plastic or viscous flow at the beginning of the test, the state behavior, in the case of the lower height sample, does not represent the same behavior during the process of the test, because of rapid drainage. In these cases, the rheological model does not coincide with the model in the case of the higher specimens.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• The Korean Journal of Petroleum Geology
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• v.5 no.1_2 s.6
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• pp.9-15
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• 1997

The study area is located in the Central Bransfield Basin, Antarctica. To analyze the morphology of seafloor, structure of basement, and seismic stratigraphy of the sedimentary layers, we have acquired, processed, and interpreted the multi-channel seismic data. The northwest-southeastern back-arc extension dramatically changes seafloor morphology, volcanic and fault distribution, and basin structure along the spreading ridges. The northern continental shelf shows a narrow, steep topography. In contrast, the continental shelf or slope in the south, which is connected to the Antarctic Peninsula, has a gentle gradient. Volcanic activities resulted in the formation of large volcanos and basement highs near the spreading center, and small-scale volcanic diapirs on the shelf. A very long, continuous normal fault characterizes the northern shelf, whereas several basinward synthetic faults probably detach into the master fault in the south. Four transfer faults, the northwest-southeastern deep-parallel structures, controlled the complex distributions of the volcanos, normal faults, depocenters, and possibly hydrocarbon provinces in the study area. They have also deformed the basement structure and depositional pattern. Even though the Bransfield Basin was believed to be formed in the Late Cenozoic (about 4 Ma), the hydrocarbon potential may be very high due to thick sediment accumulation, high organic contents, high heat flow resulted from the active tectonics, and adequate traps.

• Journal of The Korean Association For Science Education
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• v.38 no.3
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• pp.393-405
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• 2018

In this study, we classified the group model construction types in the actual classroom situation implementing the instructional strategy mixed with individual model construction and group model construction types. The purpose of this study is to analyze the information flow and the individual construction types of each group model construction type to obtain implications for model co-construction in a real classroom environment. A two-session class on sound propagation was carried out for thirty-three 8th grade students in Seoul. A total of 65 individual model construction and 16 group model construction processes were collected and analyzed. The group model construction types were classified as unchanged, enumerated, and elaborated. The unchanged type was found in 8 groups, the enumerated type in 3 groups, and the elaborated type in 5 groups. The isolated individual and independent construction (i.I) were found mostly in the unchanged group construction type (50.0%) and enumerated group construction type (54.5%). In the unchanged type, the radial shape of flow in which one student's information is transmitted to all the members of the group appeared. In the enumerated type, the starting point of the information flow was observed from two individuals. In the elaborated type, linear information flow appeared and both the second dissemination and reflective construction (2d.R) contributed to the group model construction (58.3%). This study suggests a viewpoint that enables to understand the process of complex model construction in an actual classroom context rather than in an ideal situation. The result of this study suggests the necessity of a modeling strategy considering the characteristics of Korean small group culture. It is expected that the discussion will progress through further studies.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.301-306
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• 2018

Urbanization causes urban floods and urban heat island in the summer, so it is necessary to understanding the changes of the thermal environment through urban climate and energy balance. This can be explained by the energy balance, but in urban areas, unlike the typical energy balance, the storage heat flux saved in the building or artificial land cover should be considered. Since the environment of each city is different, there is a difficulty in applying the method of retrieving the storage heat flux of the previous research. Especially, most of the previous studies are focused on the overseas cities, so it is necessary to study the storage heat retrieval suitable for various land cover and building characteristics of the urban areas in Korea. Therefore, the object of this study, it is to derive the regression formula which can quantitatively retrieve the storage heat using the data of the area where various surface types exist. To this end, nonlinear regression analysis was performed using net radiation and surface temperature data as independent variables and flux tower based storage heat estimates as dependent variables. The retrieved regression coefficients were applied to each independent variable to derive the storage heat retrieval regression formula. As a result of time series analysis with flux tower based storage heat estimates, it was well simulated high peak at day time and the value at night. Moreover storage heat retrieved in this study was possible continuous retrieval than flux tower based storage heat estimates. As a result of scatter plot analysis, accuracy of retrieved storage heat was found to be significant at $50.14Wm^{-2}$ and bias $-0.94Wm^{-2}$.

• The Journal of Korean Society for Radiation Therapy
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• v.21 no.2
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• pp.83-88
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• 2009

Purpose: Cone beam computed tomography (CBCT) using an on board imager (OBI) can check the movement and setup error in patient position and target volume by comparing with the image of computer simulation treatment in real.time during patient treatment. Thus, this study purposed to check the change and movement of patient position and target volume using CBCT in IMRT and calculate difference from the treatment plan, and then to correct the position using an automated match system and to test the accuracy of position correction using an electronic portal imaging device (EPID) and examine the usefulness of CBCT in IMRT and the accuracy of the automatic match system. Materials and Methods: The subjects of this study were 3 head and neck patients and 1 pelvis patient sampled from IMRT patients treated in our hospital. In order to investigate the movement of treatment position and resultant displacement of irradiated volume, we took CBCT using OBI mounted on the linear accelerator. Before each IMRT treatment, we took CBCT and checked difference from the treatment plan by coordinate by comparing it with the image of CT simulation. Then, we made correction through the automatic match system of 3D/3D match to match the treatment plan, and verified and evaluated using electronic portal imaging device. Results: When CBCT was compared with the image of CT simulation before treatment, the average difference by coordinate in the head and neck was 0.99 mm vertically, 1.14 mm longitudinally, 4.91 mm laterally, and 1.07o in the rotational direction, showing somewhat insignificant differences by part. In testing after correction, when the image from the electronic portal imaging device was compared with DRR image, it was found that correction had been made accurately with error less than 0.5 mm. Conclusion: By comparing a CBCT image before treatment with a 3D image reconstructed into a volume instead of a 2D image for the patient's setup error and change in the position of the organs and the target, we could measure and correct the change of position and target volume and treat more accurately, and could calculate and compare the errors. The results of this study show that CBCT was useful to deliver accurate treatment according to the treatment plan and to increase the reproducibility of repeated treatment, and satisfactory results were obtained. Accuracy enhanced through CBCT is highly required in IMRT, in which the shape of the target volume is complex and the change of dose distribution is radical. In addition, further research is required on the criteria for match focus by treatment site and treatment purpose.

• Sleep Medicine and Psychophysiology
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• v.19 no.1
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• pp.27-34
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• 2012

Objectives: The analysis of heart rate variability (HRV) is a useful non-invasive tool to investigate the autonomic nerve function. Previous studies on the relationship between HRV and depression have been reported controversial results. Similarly, the correlation between the serum lipids and depression is debatable. The purpose of this study is to examine the relationship between heart rate variability, lipid profile and depression. Methods: A total of 42 patients with major depressive disorder (MDD) and 32 age and sex-matched normal subjects who had no previous history of major medical and mental illnesses were recruited for this study. A structured-interview was used to assess the general characteristics and psychiatric illness. HRV measures were assessed by time-domain and frequency-domain analyses. Psychological symptoms were measured using the Hamilton rating scale for anxiety (HAM-A), Hamilton rating scale for depression (HAM-D). In addition, the evaluation for lipid profile was performed by blood test. Results: In serum lipid profile test, MDD group showed higher cholesterol ($197.68{\pm}42.94$ mg/dL vs. $176.85{\pm}34.68$ mg/dL, p=0.044), TG ($139.45{\pm}92.54$ mg/dL vs. $91.4{\pm}65.68$ mg/dL, p=0.018), LDL ($130.03{\pm}33.18$ vs. $106.62{\pm}27.08$, p=0.004) level than normal control group. In HRV time domain analyses, the standard deviation of the NN interval (SDNN) was decreased in MDD group than normal control group, but was not significant ($32.82{\pm}14.33$ ms vs. $40.36{\pm}21.40$ms, p=0.078). ApEn (Approximate Entrophy) was significantly increased in MDD group than normal control group ($1.13{\pm}0.11$ vs. $0.91{\pm}0.18$, p<0.001). ApEn was correlated with LDL level (r=0.277, p=0.028), HAM-D scores (r=0.534, p<0.001) and HAM-A scores (r=0.470, p<0.001). Conclusions: MDD patients showed increased ApEn, one of the HRV measurement. And this ApEn was correlated with LDL, HAM-D and HAM-A scores. In this study, the analysis of ApEn would be a useful test of MDD.

• Journal of Korean Association for Spatial Structures
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• v.4 no.2 s.12
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• pp.89-97
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• 2004

The objective of this study is the development of a scheme and discrete optimum design algorithm, which is based on the genetic algorithm. The algorithm can perform both scheme and size optimum designs of plane trusses. The developed Scheme genetic algorithm was implemented in a computer program. For the optimum design, the objective function is the weight of structures and the constraints are limits on loads and serviceability. The basic search method for the optimum design is the genetic algorithm. The algorithm is known to be very efficient for the discrete optimization. However, its application to the complicated structures has been limited because of the extreme time need for a number of structural analyses. This study solves the problem by introducing the size & scheme genetic algorithm operators into the genetic algorithm. The genetic process virtually takes no time. However, the evolutionary process requires a tremendous amount of time for a number of structural analyses. Therefore, the application of the genetic algorithm to the complicated structures is extremely difficult, if not impossible. The scheme genetic algorithm operators was introduced to overcome the problem and to complement the evolutionary process. It is very efficient in the approximate analyses and scheme and size optimization of plane trusses structures and considerably reduces structural analysis time. Scheme and size discrete optimum combined into the genetic algorithm is what makes the practical discrete optimum design of plane fusses structures possible. The efficiency and validity of the developed discrete optimum design algorithm was verified by applying the algorithm to various optimum design examples: plane pratt, howe and warren truss.

• Progress in Medical Physics
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• v.14 no.4
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• pp.211-217
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• 2003

The Principal component analysis (PCA) is a well-known data analysis method that is useful in linear feature extraction and data compression. The PCA is a linear transformation that applies an orthogonal rotation to the original data, so as to maximize the retained variance. PCA is a classical technique for obtaining an optimal overall mapping of linearly dependent patterns of correlation between variables (e.g. neurons). PCA provides, in the mean-squared error sense, an optimal linear mapping of the signals which are spread across a group of variables. These signals are concentrated into the first few components, while the noise, i.e. variance which is uncorrelated across variables, is sequestered in the remaining components. PCA has been used extensively to resolve temporal patterns in neurophysiological recordings. Because the retinal signal is stochastic process, PCA can be used to identify the retinal spikes. With excised rabbit eye, retina was isolated. A piece of retina was attached with the ganglion cell side to the surface of the microelectrode array (MEA). The MEA consisted of glass plate with 60 substrate integrated and insulated golden connection lanes terminating in an 8${\times}$8 array (spacing 200 $\mu$m, electrode diameter 30 $\mu$m) in the center of the plate. The MEA 60 system was used for the recording of retinal ganglion cell activity. The action potentials of each channel were sorted by off­line analysis tool. Spikes were detected with a threshold criterion and sorted according to their principal component composition. The first (PC1) and second principal component values (PC2) were calculated using all the waveforms of the each channel and all n time points in the waveform, where several clusters could be separated clearly in two dimension. We verified that PCA-based waveform detection was effective as an initial approach for spike sorting method.