• (The) Research of the performance art and culture
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• no.34
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• pp.383-421
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• 2017

Because the Jitsori and the Hotsori of the Beompae(the Korean Budhhist chant) has no meter and no Jangdan(a Rhythmic cycle of the Korean Music), so it is hard to analyze the melody of the Beompae. Also the melody of the Beompae is different from that of the other Korean traditional music, so studying of the Beompae has been out of the limelight of many scholars, studying the Korean music. But the melody of Beompae had been handed down for thousands of years in Korea, it and other Korean trditional music, had exchanged the impacts each other for a longtime. So I thinks that the Korean Beomapae have shared the similarity of the musical features with the other Korean traditional music. Because the Beompae of the Bulmosan Yeongsanjae on the Geongsangnamdo province has also no meters and no Jangdan, it is difficult to understand, too. But because the Onghoge of Bulmosan Yeongsanjae have a well-regulated melodic structure in comparison with the Beompae of the Seoul province, so called Geongjae Beompae, it seem to be easy to analyze its melody. So I will analyze the melody of Bulmosan Yeongsanjae Onghoge. This analyze should be contribute to investigate the rule of the melodic progress method on the convoluted Beompae melody. Onghoge has been sung on the procedure for Siryeon, Samsiniun(Goebuliun), Jojeonjeoman, Sinjungjakbeop. And the monk for the ritual has sung the chant first to purify the ritual place and to protect the soul. They has called the song, Onghoge a Jitsori at the Bulmosan Yeongsanjae preservation society of the Gyeongnam province. Commonly, there were Jitsori and Hotsori in the Beompae melody, and the melody of Jitsori is longer than that of the Hotsori. So, the melody of Onghoge is lengthened. In other word, the melody of the Onghoge show the lengthened and curved melodic feture of the Beompae very well. Hahn Manyeong, who had studied on the Beompae, Budhhist chant, said that the Hotsori has five letters in a phrase, and there were 4 phrases in a song. And he had insisted that the form of the song, Hotsori, is ABAB. I analyze the melody of the Onghoge by the Hahn's method. I will extract the Wonjeom(a primary tone of a skeletal melodic structure) from the melody of Onghoge, and in the progress of the Wonjeom of Onghoge melodies, I will arrange the repeat of the Wonjeom melody. It is a structural melody of Onghoge. The first phrase of Bulmosan Yeongsanjae Onghoge, 'Pal bu geum gang ho do ryang(八部金剛護道場)' have 4 structural melodies, the second phrase 'Gong sin sog bu bo cheon wang(空神速赴報天王)', the third phrase 'Sam gye je cheon ham le jip(三界諸天咸來集)', the firth phrase 'Yeo geum bul chal bo jeong sang(如今佛刹補禎祥)' have 2 structural melodies each. The structural melodies of Onghoge are 10 in total. And the structural melody of the Onghoge is formed the shape of 'Mi - La - do - La - Mi'. All of the Onghoge melodies is repeated 10 times by the melodic shape. The form of the Onghoge is not ABAB by Hahn, but is 10 times repeat of the shape.

• (The)Study of the Eastern Classic
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• no.62
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• pp.145-176
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• 2016

This paper aims to define the leadership of Gunja (君子, translated into prince, gentleman, or ideal man) based on Confucian Classics which offer the general values and norms of individuals' virtue and social virtuous acts. Thus, humanitarianism is regarded as true value, and the values of a virtuous person who properly practices social human relationships are discussed. The real worth of Gunja image is discussed as a true human image of "self-completion and completion of all things" (成己成物) which involves the convergence of truth, good and beauty where there is a sense of harmony and balance, where there is stern self discipline and self cultivation and where win-win values of human relationships are created. Confucian saint (聖人), wise man (賢人), great man (大人), and gentleman (君子) mean social leaders. They practice human morals, enlighten and beautify society with teachings, and are indicated as equipped with mental and material harmony, good character and competence, and economic power and morality. People today pursue their own personal growth according to their material preferences rather than pure intellectual cultural values, and are engrossed in visually beautiful external unlimited competition. In this digital age, we are supposed to demonstrate our individuality, but many people are obsessed with appearance, go on severe diet, and lose their health beauty, and consequently suffer mental stress. This trend fuels obsession with appearance and the sick practice of valuing appearance. As an alternative method to overcome this phenomenon, we need a leader image with the convergence of truth, good and beauty, which is characterized by internal self cultivation, external professionalism, and handsome and solid character. Confucian thoughts consist in practicing the Way of disciplining oneself for governing others (修己治人). Self discipline involves developing personal virtuous ability for cultivating a virtuous character, and governing others involves interacting to work together in society and to have right human relationships. Thus, leaders should impress not only themselves but also others. Self discipline for governing others means cultivating virtue for oneself and leading others. A true leader has self introspection and establishes himself through self discipline so that he can govern others or reach the realm of settling others where people live together. As all things have a value and a virtue, humans endeavor to cultivate character and virtue by learning and studying for securing their professionalism, reliability, character and ability, so as to create their own brand value. Personal character does not come from a high position, wealth and power. Character is a personal virtue, and is cultivated as immaculate and fresh through self discipline. As such, it well matches with a clean and clear spirit. This offers the ideal leader as the Guja image who has an extremely humane character, as well as being equipped with inherent virtues of intellect, benevolence and courage. Self development can foster virtue and self management through self leadership and self discipline. The leader in the relationship area can practice his virtue through virtuous acts, in other words, even think from another person's perspective. Such leader is mentioned as the principle of measuring square in the Great Learning. In our viewpoint, the beauty of character can breed the seed of virtue through intellect, benevolence and courage, the beauty of win-win can realize the right virtue by showing exemplary acts to others through considerateness, and the beauty of harmony can love and care for others like me through the principle of measuring square, thereby realizing the universal principle of virtue and harmony, which is like my mind. As such, the ideal leader, when his virtue and mind of being considerate of others all blending well, can exercise his ability to the full, can live together and coexist with many people, and can grow again into a triumphant relationship.

• The Journal of Korean Philosophical History
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• no.35
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• pp.309-334
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• 2012

This study attempts to study in what form Folk Taoism in the late of $Chos{\breve{o}}n$ Dynasty has existed and discuss the contents and characteristics of ideological aspects forming the foundation of private Taoism. While Guan Yu Belief(關帝信仰) in the late of $Chos{\breve{o}}n$ Dynasty is a folk belief focusing on Guan Yu, Seoneumjeulgyo(善陰?敎) and Musangdan(無相壇) are religious groups with organization. In case of Seoneumjeulgyo(善陰?敎), 'Seoneumjeul' contains perspective of Tian(天觀) of Confucianism but the ascetic practice method is to practice by reciting the name of the Buddha and the targets of a belief are Gwanje, Munchang, Buwoo. This shows the unified phenomenon of Confucianism, Buddhism, Taoism of Folk Taoism in the late of $Chos{\breve{o}}n$ Dynasty. Guan Yu Belief started at the national level led by the royal family of $Chos{\breve{o}}n$ after Japanese Invasion of Korea in 1592 was firmly settled in non-official circles. Guan Yu in the late of $Chos{\breve{o}}n$ Dynasty is expressed as the incarnation of loyalty and filial piety as well as God controlling life, death and fate. As this divine power and empowerment were spreading as scriptures among people, Guan Yu Belief was settled as a target to defeat the evil and invoke a blessing. Seoneumjeulgyo is the religious group that imitated 'Paekryunsa(白蓮社)' of Ming Qing time of China. Seoneumjeulgyo emphasized 'sympathy' with God through chanting. And it expressed writing written in the state of religious ecstasy as 'Binan(飛鸞).' Binan is also called as revelation and means to be revealed from heaven in the state united with God. Seoneumjeulgyo pursued the state united with God through a recitation of a spell and made scriptures written in the state united with God as its central doctrine. Musangdan published and spread Nanseo(鸞書,Book written by the revelation from God) and Seonso(善書) while worshipping Sam Sung Je Kun(三聖帝君). The scriptures of Folk Taoismin the late of $Chos{\breve{o}}n$ Dynasty can be roughly divided into Nanseo(鸞書) and Seonso(善書). Nanseo is a book written by the revelation from God and Seonso is a book to the standards of good deeds and encourage a person to do them such as Taishangganyingbian(太上感應篇) and Gonghwagyuk(功過格). The characteristics of Folk Taoism in the late of $Chos{\breve{o}}n$ Dynasty are as follows. First, a shrine of Guan Yu built for political reasons played a central role of Folk Taoism in the late of $Chos{\breve{o}}n$ Dynasty. Second, specific private Taoist groups such as Temple $Myory{\breve{o}}nsa$ and Musangdan appeared in the late of $Chos{\breve{o}}n$ Dynasty. These are Nandan Taoism(鸞壇道敎) that pursued the unity of God through 'sympathy' with God. Third, private Taoism of $Chos{\breve{o}}n$ was influenced by the unity of Confucianism, Buddhism, Taoism with private Taoism in the Qing Dynasty of China and religious organization form etc. Fourth, the Folk Taoism scriptures of $Chos{\breve{o}}n$ are divided into Nanseo and Seonso and Nanseo directly made in $Chos{\breve{o}}n$ is expected to be the key to reveal the characteristics of Folk Taoism.

• (The)Study of the Eastern Classic
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• no.56
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• pp.35-73
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• 2014

This paper examined the poem world of Simjae(深齋) Cho Geung-seop(曺兢燮: 1873-1933) in the turning point of the modern era, focused on his Hwaunsi (和韻詩: Poems written by using the rhymes of other poets' poems). In his poems, there are lots of Hwaunsi on the poems of Tu Fu(杜甫) and Su Shi(蘇軾), especially. This makes him regarded as a medieval poet, engaged in Chinese poem creation in the most traditional method in the turbulent period. Looking at the Hawunsi(和韻詩) alone, Simjae's creative life became the starting point of turnaround at around 40 years old. Before the age of 40, the poets in the Tang Dynasty and Song Dynasty and Ming Dynasty and Qing Dynasty and Korean figures like Lee Hwang(李滉), as well as Tu Fu and Su Shi were the subjects of his Hwanunsi. After the age of 40, some examples of writing poems using the rhymes of other poets' poems, especially Korean figures related to regions, are often found, reducing Hwaunsi on Tu Fu and Su Shi. Simjae called Tu Fu the integration of poets, talking about the integrity of poetic talent and his being highly proficient in mood and view. As reflecting such an awareness, the themes and moods and views are demonstrated diversely in Simjae's Hwaunsi. Although, he did not reveal his thinking about the poems of Su Shi, he seemed to love Su Shi's poems to some degree. The closeness to the original poems, the poems of Tu Fu are relatively higher than those of Su Shi. Roughly speaking, Simjae tried to find his own individuality, intending to follow Tu Fu, but, he seemed to attempt to reveal his intention using Su Shi's poems, rather than trying to imitate. To carefully examine, Simjae wrote Hwaunsi, but he did not just imitate, but revealed the aesthetics of comparison and difference. In many cases, he made new meanings by implanting his intentions in the poems, while sharing the opportunity of creation, rather than bringing the theme and mood and view as they are. The Hwaunsi on Su Shi's poems reveal the closeness to the original poems relatively less. This can be the trace of an effort to make his own theme and individuality, not being dominated by the Hwaun(和韻: using the rhymes of other poets' poems) entirely, as he used the creative method having many restrictions. However, it is noted that the Hwaunsi on Tu Fu's poems was not written much, after the age of 40. Is this the reason why he realized literary reality that he could not cope with anymore with only his effort within the Hwaunsi? For example, he wrote four poems by borrowing Su Shi's Okjungsi(獄中詩: poem written in jail) rhymes and also wrote Gujung Japje(拘中雜題), in 1919, while he was detained. In these poems, his complex contemplation and emotion, not restricted by any poet's rhymes, are revealed diversely. Simjae's Hwaunsi testifies the reality, in which Chinese poetry's habitus existed and the impressive existence mode at the turning point of the modern era. Although, the creation of Hwaunsi reflects his disposition of liking the old things, it is judged that his psychology, resisting modern characters' change, affected to some degree in the hidden side. In this regard, Simaje's Hwaunsi encounters limitation on its own, however, it has significance in that some hidden facts were revealed in the modern Chinese poetry history, which was captured with attention under the name of novelty, eccentricity and modernity.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.

• The Journal of Korean Society for Radiation Therapy
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• v.32
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• pp.93-109
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• 2020

Purpose: The radiochromic film (Gafchromic EBT3, Ashland Advanced Materials, USA) and 3-dimensional analysis system dosimetry checkTM (DC, MathResolutions, USA) were evaluated for patient-specific quality assurance (QA) of helical tomotherapy. Materials and Methods: Depending on the tumors' positions, three types of targets, which are the abdominal tumor (130.6㎤), retroperitoneal tumor (849.0㎤), and the whole abdominal metastasis tumor (3131.0㎤) applied to the humanoid phantom (Anderson Rando Phantom, USA). We established a total of 12 comparative treatment plans by the four geometric conditions of the beam irradiation, which are the different field widths (FW) of 2.5-cm, 5.0-cm, and pitches of 0.287, 0.43. Ionization measurements (1D) with EBT3 by inserting the cheese phantom (2D) were compared to DC measurements of the 3D dose reconstruction on CT images from beam fluence log information. For the clinical feasibility evaluation of the DC, dose reconstruction has been performed using the same cheese phantom with the EBT3 method. Recalculated dose distributions revealed the dose error information during the actual irradiation on the same CT images quantitatively compared to the treatment plan. The Thread effect, which might appear in the Helical Tomotherapy, was analyzed by ripple amplitude (%). We also performed gamma index analysis (DD: 3mm/ DTA: 3%, pass threshold limit: 95%) for pattern check of the dose distribution. Results: Ripple amplitude measurement resulted in the highest average of 23.1% in the peritoneum tumor. In the radiochromic film analysis, the absolute dose was on average 0.9±0.4%, and gamma index analysis was on average 96.4±2.2% (Passing rate: >95%), which could be limited to the large target sizes such as the whole abdominal metastasis tumor. In the DC analysis with the humanoid phantom for FW of 5.0-cm, the three regions' average was 91.8±6.4% in the 2D and 3D plan. The three planes (axial, coronal, and sagittal) and dose profile could be analyzed with the entire peritoneum tumor and the whole abdominal metastasis target, with planned dose distributions. The dose errors based on the dose-volume histogram in the DC evaluations increased depending on FW and pitch. Conclusion: The DC method could implement a dose error analysis on the 3D patient image data by the measured beam fluence log information only without any dosimetry tools for patient-specific quality assurance. Also, there may be no limit to apply for the tumor location and size; therefore, the DC could be useful in patient-specific QAl during the treatment of Helical Tomotherapy of large and irregular tumors.

• The Journal of Korean Society for Radiation Therapy
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• v.32
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• pp.17-29
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• 2020

Purpose: The purpose of this work was to investigate the dosimetric impact of mixed energy partial arc technique on prostate cancer VMAT. Materials and Methods: This study involved prostate only patients planned with 70Gy in 30 fractions to the planning target volume (PTV). Femoral heads, Bladder and Rectum were considered as oragan at risk (OARs). For this study, mixed energy partial arcs (MEPA) were generated with gantry angle set to 180°~230°, 310°~50° for 6MV arc and 130°~50°, 310°~230° for 15MV arc. Each arc set the avoidance sector which is gantry angle 230°~310°, 50°~130° at first arc and 50°~310° at second arc. After that, two plans were summed and were analyzed the dosimetry parameter of each structure such as Maximum dose, Mean dose, D2%, Homogeneity index (HI) and Conformity Index (CI) for PTV and Maximum dose, Mean dose, V70Gy, V50Gy, V30Gy, and V20Gy for OARs and Monitor Unit (MU) with 6MV 1 ARC, 6MV, 10MV, 15MV 2 ARC plan. Results: In MEPA, the maximum dose, mean dose and D2% were lower than 6MV 1 ARC plan(p<0.0005). However, the average difference of maximum dose was 0.24%, 0.39%, 0.60% (p<0.450, 0.321, 0.139) higher than 6MV, 10MV, 15MV 2 ARC plan, respectively and D2% was 0.42%, 0.49%, 0.59% (p<0.073, 0.087, 0.033) higher than compared plans. The average difference of mean dose was 0.09% lower than 10MV 2 ARC plan, but it is 0.27%, 0.12% (p<0.184, 0.521) higher than 6MV 2 ARC, 15MV 2 ARC plan, respectively. HI was 0.064±0.006 which is the lowest value (p<0.005, 0.357, 0.273, 0.801) among the all plans. For CI, there was no significant differences which were 1.12±0.038 in MEPA, 1.12±0.036, 1.11±0.024, 1.11±0.030, 1.12±0.027 in 6MV 1 ARC, 6MV, 10MV, 15MV 2 ARC, respectively. MEPA produced significantly lower rectum dose. Especially, V70Gy, V50Gy, V30Gy, V20Gy were 3.40, 16.79, 37.86, 48.09 that were lower than other plans. For bladder dose, V30Gy, V20Gy were lower than other plans. However, the mean dose of both femoral head were 9.69±2.93, 9.88±2.5 which were 2.8Gy~3.28Gy higher than other plans. The mean MU of MEPA were 19.53% lower than 6MV 1 ARC, 5.7% lower than 10MV 2 ARC respectively. Conclusion: This study for prostate radiotherapy demonstrated that a choice of MEPA VMAT has the potential to minimize doses to OARs and improve homogeneity to PTV at the expense of a moderate increase in maximum and mean dose to the femoral heads.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.2
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• pp.155-170
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• 2021

Oats (Avena sativa L.) represent a good forage crop for cultivation in regions with short growing periods and/or cool weather, such as the mountainous areas of southern Korea. In this study, using the Korean elite summer oat varieties 'High speed' and 'Dark horse', we aimed to determine the optimal time to plant and harvest forage oats seeded in spring and summer in a mountainous area. Seeds were planted three times from late February and early August at 9- or 10-days intervals, respectively, and plants were harvested three times from late May to October at 10-day intervals. The experiment was carried out in an upland field (Jangsu-gun Jeonbuk) in 2015 and 2016. We investigated the changes in forage yield (FY) and quality [crude protein (CP) and total digestible nutrient (TDN) contents] based on the time of planting and harvest. Neither the forage quality nor yield of either spring and summer oats was significantly influenced by the time of planting. The CP of spring oats harvested three times at 10-day intervals from late May was 12.0%, 8.2%, and 6.5%, thereby indicating a reduction with a delay in the time of harvest. In summer oats, CP ranged from 8.4% to 8.7%, although unlike CP in spring oats, was not significantly influenced by the time of harvest. For both forage types, harvest time had no significant effect on TDN. The FY of spring oats harvested in late May and early and mid-June was 10.2, 18.7, and 19.5 ton ha^-1, respectively, with that of oats harvested on the latter two dates being significantly increased by 83% and 91%, respectively, compared with that in late May. Similarly, the FY of spring oats harvested in late October and early and mid-November was 7.1, 12.5, and 12.1 ton ha^-1, respectively, with that of oats harvested on the latter two dates being significantly increased by 75% and 71%, respectively, compared with that in late October. Taking into consideration forage yield and quality (not less than 8% CP), it would be profitable to plant spring oats in the mountainous areas of southern Korea until March 15 and harvest around June 10, whereas summer oats could be beneficially planted until August 25 and harvested from early November.

• 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.