• Nuclear Medicine and Molecular Imaging
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• v.42 no.4
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• pp.301-306
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• 2008

Purpose: Recently, a number of patients needed total thyroidectomy and high dose radioiodine therapy (HD-RAI) get increased more. The aim of this study is to evaluate whether pathological staging (PS) and serum thyroglobulin (sTG) level could replace the diagnostic I-123 scan for the determination of therapeutic dose of HD-RAI in patients with differentiated thyroid cancer. Materials and Methods: Fifty eight patients (M:F=13;45, age $44.5{\pm}11.5\;yrs$) who underwent total thyroidectomy and central or regional lymph node dissection due to differentiated thyroid cancer were enrolled. Diagnostic scan of I-123 and sTG assay were also performed on off state of thyroid hormone. The therapeutic doses of I-131 (TD) were determined by the extent of uptakes on diagnostic I-123 scan as a gold standard. PS was graded by the criteria recommended in 6th edition of AJCC cancer staging manual except consideration of age. For comparison of the determination of therapeutic doses, PS and sTG were compared with the results of I-123 scan. Results: All patients were underwent HD-RAI. Among them, five patients (8.6%) were treated with 100 mCi of I-131, fourty three (74.1%) with 150 mCi, six (10.3%) with 180 mCi, three (5.2%) with 200 mCi, and one (1.7%) with 250 mCi, respectively. On the assessment of PS, average TDs were $154{\pm}25\;mCi$ in stage I (n=9), $175{\pm}50\;mCi$ in stage II (n=4), $149{\pm}21\;mCi$ in stage III (n=38), and $161{\pm}20\;mCi$ in stage IV (n=7). The statistical significance was not shown between PS and TD (p=0.169). Among fifty two patients who had available sTG, 25 patients (48.1%) having below 2 ng/mL of sTG were treated with $149{\pm}26\;mCi$ of I-131, 9 patients (17.3%) having $2{\leq}\;sTG\;<5\;ng/mL$ with $156{\pm}17\;mCi$, 5 patients (9.6%) having $5{\leq}\;sTG\;<10\;ng/mL$ with $156{\pm}13\;mCi$, 7 patients (13.5%) having $10{\leq}sTG\;<50\;ng/mL$ with $147{\pm}24\;mCi$, and 6 patients (11.5%) having above 50 ng/mL with $175{\pm}42\;mCi$. The statistical significance between sTG level and TD (p=0.252) was not shown. Conclusion: In conclusion, PS and sTG could not replace the determination of TD using I-123 scan for first HD-RAI in patients with differentiated thyroid cancer.

• The Journal of Korean Society for Radiation Therapy
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• v.30 no.1_2
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• pp.191-199
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• 2018

Purpose : In this study, we evaluated the usefulness of colloid gel(slime) as a compensator for irregular patient surfaces in radiation therapy. Materials and Methods : For this study, colloid gel suitable for treatment was made and four experiments were conducted to evaluate the applicability of radiation therapy. Trilogy(Varian) and CT(SOMATOM, Siemens) were used as treatment equipment and CT equipment. First, the homogeneity according to the composition of colloid gel was measured using EBT3 Film(RIT). Second, the Hounsfield Unit(HU) value of colloid gel was measured and confirmed by CRIS phantom, Eclipse RTP(Eclipse 13.1, Varian) and CT. Third, to measure the deformation and degeneration of colloid gel during the treatment period, it was measured 3 times daily for 2 weeks using an ion chamber(PTW-30013, PTW). The fourth experiment was compared the treatment plan and measured dose distributions using bolus, rice, colloid gel and additional, dose profiles in an environment similar to actual treatment using our own acrylic phantom. Result : First experiment, density of the colloid gel cases 1, 2 and 3 was $1.02g/cm^3$, $0.99g/cm^3$ and $0.96g/cm^3$. When the homogeneity was measured at 6 MV and 9 MeV, case 1 was more homogeneous than the other cases, as 1.55 and 1.98. In the second experiment, the HU values of case 1, 2, 3 were 15 and when the treatment plan was compared with the measured doses, the difference was within 1 % at all 9, 12 MeV and a difference of -1.53 % and -1.56 % within the whole 2 % at 6 MV. In the third experiment, the dose change of colloid gel was measured to be about 1 % for 2 weeks. In the fourth experiment, the dose difference between the treatment plan and EBT3 film was similar for both colloid gel and bolus, rice at 6 MV. But colloid gel showed less dose difference than bolus and rice at 9 MeV. Also, dose profile of colloid gel showed a more uniform dose distribution than the bolus and rice. Conclusion : In this study, the density of colloid gel prepared for radiation therapy was $1.02g/cm^3$ similar to the density of water, and alteration or deformation was not observed during the radiotherapy process. Although we pay attention to the density when manufacturing colloid gel, it is sufficient in that it can deliver the dose uniformly through the compensation of the patient's body surface more than the bolus and rice, and can be manufactured at low cost. Further studies and studies for clinical applications are expected to be applicable to radiation therapy.

• The Journal of Korean Society for Radiation Therapy
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• v.30 no.1_2
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• pp.161-167
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• 2018

Purpose : This study evaluates the usefulness of the Modified Hybrid-VMAT scheme with consideration of background radiation when establishing a treatment plan for multiple bone metastatic cancer including multiple tumors on the same axis. Materials and Methods : The subjects of this study consisted of five patients with multiple bone metastatic cancer on the same axis. The planning target volume(PTV) prescription dose was 30 Gy, and the treatment plan was established using Ray Station(Ray station, 5.0.2.35, Sweden). In the treatment plan for each patient, two or more tumors were set as one isocenter. A volumetric modulated arc therapy(VMAT) plan, a hybrid VMAT(h) plan with no consideration of background radiation, and a modified hybrid VMAT(mh) with consideration of background radiation were established. Then, using each dose volume histogram(DVH), the PTV maximum dose($D_{max}$), mean dose($D_{mean}$), conformity index(CI), and homogeneity index(HI) were compared among the plans. In addition, the organ at risk(OAR) of each treatment site was evaluated, and the total MU(Monitor Unit) and treatment time were also analyzed. Results : The PTV $D_{max}$ values of VMAT, VMAT(h) and VMAT(mh) were 3188.33 cGy, 3526 cGy, and 3285.67 cGy, the $D_{mean}$ values were 3081 cGy, 3252 cGy, and 3094 cGy; the CI values were $1.35{\pm}0.19$, $1.43{\pm}0.12$, and $1.30{\pm}0.06$; the HI values were $1.06{\pm}0.01$, $1.14{\pm}0.06$, and $1.09{\pm}0.02$; and the VMAT(h) OAR value was increased 3 %, and VMAT(mh) OAR value was decreased 18 %, respectively. Furthermore, the mean MU values were 904.90, 911.73, and 1202.13, and the mean beam on times were $128.67{\pm}10.97$, $167.33{\pm}7.57$, and $190.33{\pm}4.51$ respectively. Conclusions : Applying Modified Hybrid-VMAT when treating multiple targets can prevent overdose by correcting the overlapping of doses. Furthermore, it is possible to establish a treatment plan that can protect surrounding normal organs more effectively while satisfying the inclusion of PTV dose. Long-term follow-up of many patients is necessary to confirm the clinical efficacy of Modified Hybrid-VMAT.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.1-32
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• 2018

In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.

• The Journal of Korean Society for Radiation Therapy
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• v.31 no.1
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• pp.51-56
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• 2019

Purpose: The usefulness of using single-electron radiation for secondary radiotherapy of breast cancer patients after surgery is assessed and the use of a combine of different energy. Methods and materials : In this study, 40 patients (group A) using energy 6 MeV and 9 MeV, and 19 patients (group B) using a combine of 9 MeV and 12 MeV were studied among 59 patients who performed secondary care using combine electronic radiation. Each patient in each group, 6 MeV, 9 MeV, Combine(6 MeV / 9 MeV) and 9 MeV, 12 MeV, Combine (9 MeV / 12 MeV) were developed in different ways, and the maximum doses delivered to the original hospital, D95, D5, and $V_3$, $V_5$, $V_{10}$ were compared. Result: The D95 mean value of Group A treatment plan was $785.33{\pm}225.37cGy$, $1121.79{\pm}87.02cGy$ at 9 MeV, and $1010.98{\pm}111.17cGy$ at 6 MeV / 9 MeV, and the mean value at 6 MeV / 9 MeV was most appropriate for the dose. The mean values of the low dose area $V_3$ and $V_5$ in the lung of the breast direction being treated were $3.24{\pm}3.49%$ and $0.72{\pm}1.55%$ at 6 MeV, the highest 9 MeV at $7.25{\pm}4.59%$, $3.07{\pm}2.64%$, the lowest at 6 MeV. Maximum and average lung dose was $727.78{\pm}137.27cGy$ at 6 MeV / 9 MeV, $49.16{\pm}24.44cGy$, highest 9 MeV at $998.97{\pm}114.35cGy$, $85.33{\pm}41.18cGy$, and lowest 6 MeV at $387.78{\pm}208.88cGy$, $9.27{\pm}6.60cGy$. The value of $V_{10}$ was all close to zero. Group B appeared in the pattern of Group A. Conclusion: Relative differences in low-dose areas of the lungs $V_3$ and $V_5$ were seen and were most effective in the dose transfer of tumor bed in the application of combined energy. It is thought that the method of using electronic energy in further radiation treatments for breast cancer is a more effective way to use the energy effect of limiting energy resources, and that if you think about it again, it could be a little more beneficial radiation treatment for patients.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.109-125
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• 2019

As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.

• The Journal of Korean Society for Radiation Therapy
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• v.30 no.1_2
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• pp.9-16
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• 2018

Purpose : Brain Stereotactic Radiosurgery can treat non-invasive diseases with high rates of complications due to surgical operations. However, brain stereotactic radiosurgery may be accompanied by radiation induced side effects such as fractionation radiation therapy because it uses radiation. The effects of Coplanar Volumetric Modulated Arc Therapy(C-VMAT) and Non-Coplanar Volumetric Modulated Arc Therapy(NC-VMAT) on surrounding normal tissues were analyzed in order to reduce the side effects caused fractionation radiation therapy such as head and neck. But, brain stereotactic radiosurgery these contents were not analyzed. In this study, we evaluated the usefulness of NC-VMAT by comparing and analyzing C-VMAT and NC-VMAT in patients who underwent brain stereotactic radiosurgery. Methods and materials : With C-VMAT and NC-VMAT, 13 treatment plans for brain stereotactic radiosurgery were established. The Planning Target Volume ranged from a minimum of 0.78 cc to a maximum of 12.26 cc, Prescription doses were prescribed between 15 and 24 Gy. Treatment machine was TrueBeam STx (Varian Medical Systems, USA). The energy used in the treatment plan was 6 MV Flattening Filter Free (6FFF) X-ray. The C-VMAT treatment plan used a half 2 arc or full 2 arc treatment plan, and the NC-VMAT treatment plan used 3 to 7 Arc 40 to 190 degrees. The angle of the couch was planned to be 3-7 angles. Results : The mean value of the maximum dose was $105.1{\pm}1.37%$ in C-VMAT and $105.8{\pm}1.71%$ in NC-VMAT. Conformity index of C-VMAT was $1.08{\pm}0.08$ and homogeneity index was $1.03{\pm}0.01$. Conformity index of NC-VMAT was $1.17{\pm}0.1$ and homogeneity index was $1.04{\pm}0.01$. $V_2$, $V_8$, $V_{12}$, $V_{18}$, $V_{24}$ of the brain were $176{\pm}149.36cc$, $31.50{\pm}25.03cc$, $16.53{\pm}12.63cc$, $8.60{\pm}6.87cc$ and $4.03{\pm}3.43cc$ in the C-VMAT and $135.55{\pm}115.93cc$, $24.34{\pm}17.68cc$, $14.74{\pm}10.97cc$, $8.55{\pm}6.79cc$, $4.23{\pm}3.48cc$. Conclusions : The maximum dose, conformity index, and homogeneity index showed no significant difference between C-VMAT and NC-VMAT. $V_2$ to $V_{18}$ of the brain showed a difference of at least 0.5 % to 48 %. $V_{19}$ to $V_{24}$ of the brain showed a difference of at least 0.4 % to 4.8 %. When we compare the mean value of $V_{12}$ that Radione-crosis begins to generate, NC-VMAT has about 12.2 % less amount than C-VMAT. These results suggest that if NC-VMAT is used, the volume of $V_2$ to $V_{18}$ can be reduced, which can reduce Radionecrosis.

• The Journal of Korean Society for Radiation Therapy
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• v.32
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• pp.41-52
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• 2020

Purpose: To find out the dosimetric usefulness, setup reproducibility and efficiency of applying 3D Bolus by comparing two treatment plans in which Commercial Bolus and 3D Bolus produced by 3D Printing Technology were applied to the neck during VMAT treatment of Hypopahrynx Cancer to evaluate the clinical applicability. Materials and Methods: Based on the CT image of the RANDO phantom to which CB was applied, 3D Bolus were fabricated in the same form. 3D Bolus was printed with a polyurethane acrylate resin with a density of 1.2g/㎤ through the SLA technique using OMG SLA 660 Printer and MaterializeMagics software. Based on two CT images using CB and 3D Bolus, a treatment plan was established assuming VMAT treatment of Hypopharynx Cancer. CBCT images were obtained for each of the two established treatment plans 18 times, and the treatment efficiency was evaluated by measuring the setup time each time. Based on the obtained CBCT image, the adaptive plan was performed through Pinnacle, a computerized treatment planning system, to evaluate target, normal organ dose evaluation, and changes in bolus volume. Results: The setup time for each treatment plan was reduced by an average of 28 sec in the 3D Bolus treatment plan compared to the CB treatment plan. The Bolus Volume change during the pretreatment period was 86.1±2.70㎤ in 83.9㎤ of CB Initial Plan and 99.8±0.46㎤ in 92.2㎤ of 3D Bolus Initial Plan. The change in CTV Min Value was 167.4±19.38cGy in CB Initial Plan 191.6cGy and 149.5±18.27cGy in 3D Bolus Initial Plan 167.3cGy. The change in CTV Mean Value was 228.3±0.38cGy in CB Initial Plan 227.1cGy and 227.7±0.30cGy in 3D Bolus Initial Plan 225.9cGy. The change in PTV Min Value was 74.9±19.47cGy in CB Initial Plan 128.5cGy and 83.2±12.92cGy in 3D Bolus Initial Plan 139.9cGy. The change in PTV Mean Value was 226.2±0.83cGy in CB Initial Plan 225.4cGy and 225.8±0.33cGy in 3D Bolus Initial Plan 224.1cGy. The maximum value for the normal organ spinal cord was the same as 135.6cGy on average each time. Conclusion: From the experimental results of this paper, it was found that the application of 3D Bolus to the irregular body surface is more dosimetrically useful than the application of Commercial Bolus, and the setup reproducibility and efficiency are excellent. If further case studies along with research on the diversity of 3D printing materials are conducted in the future, the application of 3D Bolus in the field of radiation therapy is expected to proceed more actively.

• The Journal of Korean Philosophical History
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• no.52
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• pp.393-424
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• 2017

This study investigates the relationship between South Korean youths' Confucian values and sense of citizen ethics while presenting outlook on the sense of citizen ethics based on the theory of human nature. The purpose of this study, by doing so, is to present educational measures. For this purpose, empirical research method was applied in this study. In the empirical study, youths were surveyed and the answers were statistically analyzed and discussed with a view to achieve the study purpose. In the empirical research part of the study, Korean youths' awareness on Confucian values was examined along with its relationship with the sense of citizen ethics. The effect of Confucian values on sense of citizen ethics and their relationship were analyzed to evaluate the receptivity of youths on Confucian ideas and usefulness of sense of citizen ethics. This study investigated a total of final 311 sets of data from male and female students at middle and high schools located in Seoul, Gyeonggi, South Korea. First, to identify the youths' Confucian values and level of sense of citizen ethics, descriptive statistical analysis was conducted. As a result, the survey subjects were found to have, concerning the Confucian values, world view M=3.54, human relations view M=3.66, morality cultivation M=3.76, and social order M=3.45, higher than 3.0 to represent positive levels. The morality cultivation, in particular, was recorded the highest among all whereas the social order was relatively lower, which represents the degree of relying on Confucian values to establish social order. Second, the sub-variables of Confucian values were verified according to the personal characteristics of the surveyed youths and differences in their entire perception was investigated. As a result, according to gender, morality cultivation was found higher in female students (M=3.85) than in male students (M=3.64). According to the subjective economic level of their household, world view was found higher in upper class (M=3.98) than middle-low class (M=3.25) and low class (M=3.22) while human relations view was found higher in middle-upper class (M=3.79) than low class (M=3.46). As for the family type, morality cultivation was found higher in extended family (M=3.83) than nuclear family (M=3.62); and social order was higher in extended family (M=3.54) than nuclear family (M=3.36). Third, to verify the study theme of identifying the effects of youths' Confucian values on sense of citizen morality, hierarchical regression analysis was employed in this study, which used the multi-level model of multiple regression analysis. As a result, the Confucian values was found to have significant positive (+) correlations with the entire sense of citizen ethics in order of human relations view(${\beta}=.499$), world view(${\beta}=.412$), social order(${\beta}=.341$), and morality cultivation(${\beta}=.241$). Confucian value showed significant positive (+) correlations with autonomy in order of morality cultivation(${\beta}=.458$), human relations view(${\beta}=.454$), social order(${\beta}=.362$), and world view(${\beta}=.158$). Confucian values was found to have significant positive (+) correlations with community spirit in order of human relations view(${\beta}=.295$), social order(${\beta}=.281$), and morality cultivation(${\beta}=.232$). As shown in the findings above, youths' Confucian values was found to have significant positive (+) effects on the sense of citizen ethics. It is noted that the higher the Confucian values, the more positive the sense of citizen ethics would be. Consequentially, the Confucian values was identified to play an important role in the sense of citizen ethics in the modern society. Based on this analysis, this study presented specific measures - the necessity and possibility of education on sense of citizen ethics under the theory of human nature. To this end, this study proposed to find an optimal interface between the contemporary sense of citizen ethics and Confucian ethics through the respect for human life and nature, man of virtue as the ideal human model, and united society as a desirable society model.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.