• Korean Journal of Digital Imaging in Medicine
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• v.16 no.1
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• pp.13-19
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• 2014

Purpose: FLAIR image is beneficial for the diagnosis of various bran diseases including ischemic CVS, brain tumors and infections. However the border between the legion of brain metastasis and surrounding edema may not be clear. Therefore, this study aims to investigate the practical benefits of delayed imaging by comparing the image from a patient with brain metastasis before a contrast enhancement and the image 10 minutes after a contrast enhancement. Materials and methods: Of the 92 people who underwent MRI brain metastases in suspected patients 13 people in three patients there is no video to target the 37 people confirmed cases, and motion artifacts brain metastases in our hospital June-December 2013, 18 people measurement position except for the three incorrect patient (male: 11 people, female: 7 people, average age: 60 years) in the target, test equipment, 3.0T MR System (ACHIEVA Release, Philips, I was 8ChannelSENSE Head Coil use Best, and the Netherlands). TR 11000 ms, TE 125 ms, TI2800 ms, Slice Thickness 5 mm, gap 5 mm, is a Slice number 21, the parameters of the 3D FFE, T2 FLAIR variable that was used to test, TR 8.1 ms, TE 3.7 ms, Slice number 240 I set to. The experiment was conducted by acquiring the FLAIR prior to contrast enhancement (heretofore referred to as Pre FLAIR), and acquiring the 3D FFE CE five minutes after the contrast enhancement, and recomposing the images in an axial plane of S/T 3mm, G 0mm (heretofore referred to as MPR TRA CE). Using the FLAIR 10 minutes after the contrast enhancement (heretofore referred to as Post FLAIR) and Pi-View, a retrospective study was conducted. Using MRIcro on the image of a patient confirmed for his diagnosis, the images before and after the contrast media, as well as the CNR and SNR of the MPR TRA CE images of the lesion and the site absent of lesion were compared and analyzed using a one-way analysis of variance. Results: CNR for Pre FLAIR and Post FLAIR were 34.35 and 60.13, respectively, with MPR TRA CE at 23.77 showing no significant difference (p<0.050). Post-experiment analysis shows a difference between Pre FLAIR and Post FLAIR in terms of CNR (p<0.050), but no difference in CNR between Post FLAIR and MPR TRA CE (p>0.050), indicating that the contrast media had an effect only on Pre FLAIR and Post FLAIR. The SNR for the normal site Pre FLAIR was 106.43, and for the lesion site 140.79. Post FLAIR for the normal site was 107.79, and for the lesion site 167.91. MPR TRA CE for the normal site was 140.23 and for the lesion site 183.19, showing significant difference (p<0.050), and post-experiment analysis shows that there was a difference in SNR only on the lesion sites for Pre FLAIR and Post FLAIR (p<0.050). There was no difference in SNR between the normal site and lesion site for Post FLAIR and MPR TRA CE, indicating no effect from the contrast media (p>0.050). Conclusions: This experiment shows that Post FLAIR has a higher contrast than Pre FLAIR, and a higher SNR for lesions, It was not not statistically significant and MPR TRA CE but CNR came out high. Inspection of post-contrast which is used in a high magnetic field is frequently used images of 3D T1 but, since the signal of the contrast medium and the blood flow is included, this method can be diagnostic accuracy is reduced, it is believed that when used in combination with Post FLAIR, and that can provide video information added to the diagnosis of brain metastases.

• Magazine of the Korean Society of Agricultural Engineers
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• v.30 no.4
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• pp.23-44
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• 1988

The evaportranspiration of upland crops was measured by four types of lysimeter and water consumption characteristics together with the optimum irrigation point by the crops was defind. Among the evapotranspiration estimation formulas, the constant of wind function in the modified Penman equation was corrected to agree with the meteorological conditions of Korea. The evapotranspiration of the crops in the project standard year was estimated according to the cropping system of the project area in Chungju, and from the estimated evapotras - spiration, net duty of water per one time and irrigation in tervals were investigated. The results obtained are summarized as follows: 1. The evapotranspiration of the same crop measured at the same plot was slightly different by the lysimetric methods, and among the four types of lysimeter, the accuracy of the floating lysimeter was the highest. 2. The yields among the watering treatments showed the significance of 5% in the expe- riment with red cabbage and Chinese cabbage, and significance of 1% in the crisphead lettuce, and the optimum irrigation point for the tested crops was defined ad pF 2.0 by the least squre difference test. 3. The evapotranspiration of the crops in the mid-season stage showed maximum among the growing stages, and the average daily evapotranspiration by the crops over the growing seasons of cabbage, crisphead lettuce, Chinese cabbage, summer cucumber, tornato, salary and autumn cucumber was 4.18mm, 4.77mm, 3.9qrnm, 5.68mnn, joonim, 4.26mm and 3.3qrnn, respectively. 4. From the investigated soil moisture extration pattern(SMEP) of the crisphead lettuce, cucumber and tomato, the proportion of the first layer in the initial stage showed over so%, and the SMEP of the lowest fourth layer during the late-season stage in the experiment cabbage and Chinese cabbage was 15.8% and 16.9, respectively, with showed that the root elongated th the lowest soil layer. 5. The total available moisture(TAM) of clay loam was 21.2-23.3mm and that of sandy loam was 16.1 - 19.0mm under the optimum irrigation point of pF. 2.0, and the total readily available moisture( TRAM) of the crops cultivated in the clay loam soil was larger than that cultivated in the sandy loam soil, and the TRAM during the mid-and late-season were larger than that of the inital and crop development stage. 6. The estimated evapotranspration by the corrected Pennam equation, whkh corrected the constant of the wind function in the modified Penman equation, was nearly agreed with the actually measured evaporanspiration of grass. 7. Among the several evaportranspiration estimation methods, the evapotranspiration es- timated by the corrected Pennam equation was closed to the actual evapotranspiration of reference crop (grass) evapotranspiration, therefore it is suggested to use the corrected Penman equation to determine the duty of water of corps. 8. The average crop coefficient (Kc) of cabbage by the corrected Penman equation was 0.94 and that of crisphead lettuce, summer cucumber, tomato, salary, Chinese cabbage and autumn cucumber was 1.07, 1.22, 1.02, 1.01, 1.35, 1.09, respectively 9. The estimated total evapotranspiration of cabbage in the project area( Chungju) by the corrected Penman equation was 223.9mm and that of crisphead lettuce, Chinese cabbage, summer cucumber, tomato, salary and auturun cucumber was 215.7mm, 205.9mm, 359.Omrn, 300.9mm, 332.lmm and 202.7mm, respectively. 10. The net duty of water per one time of the crops cultivated in the sandy loam soil, and the net duty of water per one time in the mid-season & late-season showed larger than that of the initial stage. 11. The shortest irrigation interval of cabbage in the project area was 4.2 days, and that of crisphead lettuce, Chinese cabbage, cucumber, tomato and salary was 1.2days, 2.3days, 1.8days, 2.2days and 2.7days, respectively.

• The Journal of Korean Society for Radiation Therapy
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• v.26 no.1
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• pp.59-67
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• 2014

Purpose : This study aims to evaluate 3D dosimetric impact for MIP image and each phase image in stereotactic body radiotherapy (SBRT) for lung cancer using volumetric modulated arc therapy (VMAT). Materials and Methods : For each of 5 patients with non-small-cell pulmonary tumors, a respiration-correlated four-dimensional computed tomography (4DCT) study was performed. We obtain ten 3D CT images corresponding to phases of a breathing cycle. Treatment plans were generated using MIP CT image and each phases 3D CT. We performed the dose verification of the TPS with use of the Ion chamber and COMPASS. The dose distribution that were 3D reconstructed using MIP CT image compared with dose distribution on the corresponding phase of the 4D CT data. Results : Gamma evaluation was performed to evaluate the accuracy of dose delivery for MIP CT data and 4D CT data of 5 patients. The average percentage of points passing the gamma criteria of 2 mm/2% about 99%. The average Homogeneity Index difference between MIP and each 3D data of patient dose was 0.03~0.04. The average difference between PTV maximum dose was 3.30 cGy, The average different Spinal Coad dose was 3.30 cGy, The average of difference with $V_{20}$, $V_{10}$, $V_5$ of Lung was -0.04%~2.32%. The average Homogeneity Index difference between MIP and each phase 3d data of all patient was -0.03~0.03. The average PTV maximum dose difference was minimum for 10% phase and maximum for 70% phase. The average Spain cord maximum dose difference was minimum for 0% phase and maximum for 50% phase. The average difference of $V_{20}$, $V_{10}$, $V_5$ of Lung show bo certain trend. Conclusion : There is no tendency of dose difference between MIP with 3D CT data of each phase. But there are appreciable difference for specific phase. It is need to study about patient group which has similar tumor location and breathing motion. Then we compare with dose distribution for each phase 3D image data or MIP image data. we will determine appropriate image data for treatment plan.

• Tuberculosis and Respiratory Diseases
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• v.56 no.4
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• pp.393-404
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• 2004

Background : Nucleic acid hybridization has become an essential technique in the development of our understanding of gene structure and function. The quantitative analysis of hybridization has been used in the measurement of genome complexity and gene copy number. The filter hybridization assay is rapid, sensitive and can be used to measure RNAs complementary to any cloned DNA sequence. Methods : The authors assessed the accuracy, linearity, correlation coefficient and specificity of the hybridization depending on the added dose(0, 1, 5, and $10{\mu}g$) of non-specific rat spleen RNA to hybridization of surfactant protein A mRNA. Filter hybridization assays were used to obtain the equation of standard curve and thereby to quantitate the mRNA quantitation. Results : 1. Standard curve equation of filter hybridization assay between counts per minute (X) and spleen RNA input (Y) was Y=0.13X-19.35. Correlation coefficient was 0.98. 2. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) was Y=0.00066X-0.046. Correlation coefficient was 0.99. 3. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) after the addition of $1{\mu}g$ spleen RNA was Y=0.00056X-0.051. Correlation coefficient was 0.99. 4. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) after the addition of $5{\mu}g$ spleen RNA was Y=0.00065X-0.088. Correlation coefficient was 0.99. 5. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) after the addition of $10{\mu}g$ spleen RNA was Y=0.00051X-0.10. Correlation coefficient was 0.99. Conclusions : Comparison of cpm/filter in a linear range allowed accurate and reproducible estimation of surfactant protein A mRNA copy number irrespective of the addition dosage of non-specific rat spleen RNA over the range $0-10{\mu}g$.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.2
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• pp.135-145
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• 2020

Wave observation is widely used to direct observation method for observing the water surface elevation using wave buoy or pressure gauge and remote-sensing wave observation method. The wave buoy and pressure gauge can produce high-quality wave data but have disadvantages of the high risk of damage and loss of the instrument, and high maintenance cost in the offshore area. On the other hand, remote observation method such as radar is easy to maintain by installing the equipment on the land, but the accuracy is somewhat lower than the direct observation method. This study investigates the data quality of MIROS Wave and Current Radar (MWR) installed at Dokdo and improve the data quality of remote wave observation data using the wave buoy (CWB) observation data operated by the Korea Meteorological Administration. We applied and developed the three types of wave data quality control; 1) the combined use (Optimal Filter) of the filter designed by MIROS (Reduce Noise Frequency, Phillips Check, Energy Level Check), 2) Spike Test Algorithm (Spike Test) developed by OOI (Ocean Observatories Initiative) and 3) a new filter (H-Ts QC) using the significant wave height-period relationship. As a result, the wave observation data of MWR using three quality control have some reliability about the significant wave height. On the other hand, there are still some errors in the significant wave period, so improvements are required. Also, since the wave observation data of MWR is different somewhat from the CWB data in high waves of over 3 m, further research such as collection and analysis of long-term remote wave observation data and filter development is necessary.

• Journal of Genetic Medicine
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• v.4 no.1
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• pp.45-52
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• 2007

Purpose : A simple, rapid, and highly sensitive analytical method for Gb3 in plasma was developed without labor-ex tensive pre-treatment by electrospray ionization MS/ MS (ESI-MS/MS). Measurement of globotriaosy lceramide (Gb3, ceramide trihex oside) in plasma has clinical importance for monitoring after enzyme replacement therapy in Fabry disease patients. The disease is an X-linked lipid storage disorder that results from a deficiency of the enzyme ${\alpha}$-galactosidase A (${\alpha}$-Gal A). The lack of ${\alpha}$-Gal A causes an intracellular accumulation of glycosphingolipids, mainly Gb3. Methods : Only simple 50-fold dilution of plasma is necessary for the extraction and isolation of Gb3 in plasma. Gb3 in diluted plasma was dissolved in dioxane containing C17:0 Gb3 as an internal standard. After centrifugation it was directly injected and analyzed through guard column by in combination with multiple reaction monitoring mode of ESI-MS/MS. Results : Eight isoforms of Gb3 were completely resolved from plasma matrix. C16:0 Gb3 occupied 50% of total Gb3 as a major component in plasma. Linear relationship for Gb3 isoforms w as found in the range of 0.001-1.0 ${\mu}g$/mL. The limit of detection (S/N=3) was 0.001 ${\mu}g$/mL and limit of quantification was 0.01 ${\mu}g$/mL for C16:0 Gb3 with acceptable precision and accuracy. Correlation coefficient of calibration curves for 8 Gb3 isoforms ranged from 0.9678 to 0.9982. Conclusion : This quantitative method developed could be useful for rapid and sensitive 1st line Fabry disease screening, monitoring and/or diagnostic tool for Fabry disease.

• Korean Journal of Remote Sensing
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• v.25 no.4
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• pp.383-389
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• 2009

The main objective of the research is a feasibility study on the intertidal zone using a X-band radar satellite, TerraSAR-X. The TerraSAR-X data have been acquired in the west coast of Korea where large tidal flats, Ganghwa and Yeongjong tidal flats, are developed. Investigations include: 1) waterline and backscattering characteristics of the high resolution X-band images in tidal flats; 2) polarimetric signature of halophytes (or salt marsh plants), specifically Suaeda japonica; and 3) phase and coherence of interferometric pairs. Waterlines from TerraSAR-X data satisfy the requirement of horizontal accuracy of 60 m that corresponds to 20 cm in average height difference while current other spaceborne SAR systems could not meet the requirement. HH-polarization was the best for extraction of waterline, and its geometric position is reliable due to the short wavelength and accurate orbit control of the TerraSAR-X. A halophyte or salt marsh plant, Suaeda japonica, is an indicator of local sea level change. From X-band ground radar measurements, a dual polarization of VV/VH-pol. is anticipated to be the best for detection of the plant with about 9 dB difference at 35 degree incidence angle. However, TerraSAR-X HH/TV dual polarization was turned to be more effective for salt marsh monitoring. The HH-HV value was the maximum of about 7.9 dB at 31.6 degree incidence angle, which is fairly consistent with the results of X-band ground radar measurement. The boundary of salt marsh is effectively traceable specifically by TerraSAR-X cross-polarization data. While interferometric phase is not coherent within normal tidal flat, areas of salt marsh where the landization is preceded show coherent interferometric phases regardless of seasons or tide conditions. Although TerraSAR-X interferometry may not be effective to directly measure height or changes in tidal flat surface, TanDEM-X or other future X-band SAR tandem missions within one-day interval would be useful for mapping tidal flat topography.

• Journal of the Korean Society of Radiology
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• v.15 no.6
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• pp.781-788
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• 2021

Due to the high sensitivity to radiation, excessive exposure needs to be prevented by accurately measuring the dose irradiated to the skin during radiation therapy. Although clinical trials use dosimeters such as film, OSLD, TLD, glass dosimeter, etc. to measure skin dose, these dosimeters have difficulty in accurate dosimetry on skin curves. In this study, to solve these problems, we developed a skin dosimeter that can be attached according to human flexion and evaluated its response characteristics. For the manufacture of the dosimeter, lead oxide (PbO) with high atomic number (Z_Pb: 82, Z_O: 8) and density (9.53 g/cm³) and silicon binders that can bend according to human flexion were used. In the case of a dosimeter made of PbO material, the performance degradation has been prevented by using parylene and others due to the presence of degradation due to oxidation, but the previously used parylene is affected by bending, so a new form of passive layer was produced and applied to the skin dosimeter. The characteristic evaluation of the skin dosimeter was evaluated by analyzing SEM, reproducibility, and linearity. Through SEM analysis, bending was evaluated, reproducibility and linearity at 6 MeV energy were evaluated, and applicability was assessed with a skin dosimeter. As a result of observing the dosimeter surface through SEM analysis, the parylene passive layer PbO dosimeter with the positive layer raised to the parylene produced cracks on the surface when bent. On the other hand, no crack was observed in the silicon passive layer PbO dosimeter, which was raised to silicon passive layer. In the reproducibility measurement results, the RSD of the silicon passive layer PbO dosimeter was 1.47% which satisfied the evaluation criteria RSD 1.5% and the linearity evaluation results showed the R² value of 0.9990, which satisfied the evaluation criteria R² 9990. The silicon passive layer PbO dosimeter was evaluated to be applicable to skin dosimeters by demonstrating high signal stability, precision, and accuracy in reproducibility and linearity, without cracking due to bending.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.321-335
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• 2021

Particulate matter (PM10 and PM2.5 with a diameter less than 10 and 2.5 ㎛, respectively) can be absorbed by the human body and adversely affect human health. Although most of the PM monitoring are based on ground-based observations, they are limited to point-based measurement sites, which leads to uncertainty in PM estimation for regions without observation sites. It is possible to overcome their spatial limitation by using satellite data. In this study, we developed machine learning-based retrieval algorithm for ground-level PM10 and PM2.5 concentrations using aerosol parameters from Geostationary Ocean Color Imager (GOCI) satellite and various meteorological parameters from a numerical weather prediction model during January to December of 2019. Gradient Boosted Regression Trees (GBRT) and Light Gradient Boosting Machine (LightGBM) were used to estimate PM concentrations. The model performances were examined for two types of feature sets-all input parameters (Feature set 1) and a subset of input parameters without meteorological and land-cover parameters (Feature set 2). Both models showed higher accuracy (about 10 % higher in R2) by using the Feature set 1 than the Feature set 2. The GBRT model using Feature set 1 was chosen as the final model for further analysis(PM10: R2 = 0.82, nRMSE = 34.9 %, PM2.5: R2 = 0.75, nRMSE = 35.6 %). The spatial distribution of the seasonal and annual-averaged PM concentrations was similar with in-situ observations, except for the northeastern part of China with bright surface reflectance. Their spatial distribution and seasonal changes were well matched with in-situ measurements.