• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.6
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• pp.27-42
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• 2020

Startup accelerators have emerged as new investment entities that help early startups, which are not easy to survive continuously due to lack of funds, commercialization capabilities, and experiences. As their positive performance on early startups and the ecosystem has been proven, the number of early startups which want to receive their investment is also increasing. However, they are vaguely preparing to attract accelerators' investment because they do not have any information on what factors the accelerators consider important. In addition, researches on startup accelerators are also at an early level, so there are no remarkable prior studies on factors that decide on investment. Therefore, this study aims to help startups prepare for investment attraction by looking at what factors are important for accelerators to invest, and to provide meaningful implications to academia. In the preceding study, we derived five upper level categories, 26 lower level accelerators' investment determinants through the qualitative meta-synthesis method, secondary data analysis, observation on US accelerators and in-depth interviews. In this study, we want to derive important implications by deriving priorities of the accelerators' investment determinants. Therefore, we used AHP that are evaluated as the suitable methodology for deriving importance and priority. The analysis results show that accelerators value market-related factors most. This means that startups that are subject to investment by accelerators are early-stage startups, and many companies have not fully developed their products or services. Therefore, market-related factors that can be evaluated objectively seem to be more important than products (or services) that are still ambiguous. Next, it was found that the factors related to the internal workforce of startups are more important. Since accelerators want to develop their businesses together with start-ups and team members through mentoring, ease of collaboration with them is very important, which seems to be important. The overall priority analysis results of the 26 investment determinants show that 'customer needs' and 'founders and team members' understanding of customers and markets' (0.62) are important and high priority factors. The results also show that startup accelerators consider the customer-centered perspective very important. And among the factors related to startups, the most prominent factor was the founder's openness and execution ability. Therefore, it can be confirmed that accelerators consider the ease of collaboration with these startups very important.

• (The) Research of the performance art and culture
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• no.38
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• pp.193-224
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• 2019

Shaman's play is significant in that it provided public theater for a long time in the theatrical and dramatic history. Unlike upper class who could call entertainer or Korean geisha in the traditional society, the majority of ordinary people could see professional performances through gut. Therefore, the shaman of the traditional society pulled the play which developed in the gut and the outside play into the gut and prepared the performance street for the ordinary people. shaman's play, apart from the religious context, has also functioned as a theatrical performance. Through shaman's play, you can see the process of ritual development into play. Shaman's play is a ritual ritual of expel calamity in an agriculture based society. In Korean consciousness, evil spirits are thought to bring disease or disaster to humans, so they should be good for evil spirits. This is a ritual that goes hand in hand with the Confucian Yeoje and the Buddhist Suryukjae. Most traditional plays, including masque performance, tend to weaken and become stifling after the designation of intangible cultural properties. However, shaman's play is transformed every time it is executed and is given a new meaning. Depending on the ability of the shaman to respond to and accommodate social change, adaptability is excellent depending on the situation in the field. Shaman's play has richness, prevent calamity and playful elements such as imitation of god and sexual connection based on the element of shamanism. In addition, it is necessary to pay attention to the meaning and the direction of Shaman's play because it is differentiated into play including social subject beyond mere magic imitation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.1-16
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• 2022

Although start-up is a key national strategy to increase national competitiveness and create employment, the survival rate of start-ups has not improved significantly. This is an important reason for the inability to provide timely and appropriate support to startups, which are in the early stages of start-up, due to the unique limitations of existing start-up support institutions and investors. The relatively recent accelerator is attracting attention as a subject of solving the above problems through professional incubation and investment. However, there are only a few empirical studies on investment determinants that affect the survival and success of accelerators, and there is a lack of theoretical evidence. Accordingly, in previous studies, 12 investment determinants were derived from a static, strategic, and dynamic perspective as accelerator investment determinants based on a business model innovation framework. This study subdivided the accelerator investment determinants derived through previous studies into 21 and analyzed the importance and priority of each factor using AHP (Analytic Hierarchy Process) analysis technique for domestic accelerator investment experts. As a result of the analysis, the top factors of importance of accelerator investment determinants were in the order of 'human resources', 'customer and market', 'intellectual resources', and 'entrepreneur's ability to realize opportunities'. It can be seen that the accelerator considers the core competencies of startups to implement solutions as the most important factor when making startup investment decisions. It was also confirmed that accelerators are strategic to create a clear value proposition and differentiated market position based on the core competitiveness of startups, and that the core value delivery method prefers a market-oriented business model and recognizes entrepreneurs's innovation capability is an important factor to realize a business model with limited resources in a rapidly changing market. This study is of academic significance in that it analyzes the importance and priority of accelerator investment determinants through demonstration as a follow-up study on accelerator investment determinants derived based on business model innovation theory that reflects the nature, goals, and major activities of accelerator investment. In addition, it is of practical value as it contributes to revitalizing the domestic startup investment ecosystem by providing accelerators with theoretical grounds for investment decisions and specific information on detailed investment determinants.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.167-181
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• 2018

Over the past decade, deep learning has been in spotlight among various machine learning algorithms. In particular, CNN(Convolutional Neural Network), which is known as the effective solution for recognizing and classifying images or voices, has been popularly applied to classification and prediction problems. In this study, we investigate the way to apply CNN in business problem solving. Specifically, this study propose to apply CNN to stock market prediction, one of the most challenging tasks in the machine learning research. As mentioned, CNN has strength in interpreting images. Thus, the model proposed in this study adopts CNN as the binary classifier that predicts stock market direction (upward or downward) by using time series graphs as its inputs. That is, our proposal is to build a machine learning algorithm that mimics an experts called 'technical analysts' who examine the graph of past price movement, and predict future financial price movements. Our proposed model named 'CNN-FG(Convolutional Neural Network using Fluctuation Graph)' consists of five steps. In the first step, it divides the dataset into the intervals of 5 days. And then, it creates time series graphs for the divided dataset in step 2. The size of the image in which the graph is drawn is $40(pixels){\times}40(pixels)$, and the graph of each independent variable was drawn using different colors. In step 3, the model converts the images into the matrices. Each image is converted into the combination of three matrices in order to express the value of the color using R(red), G(green), and B(blue) scale. In the next step, it splits the dataset of the graph images into training and validation datasets. We used 80% of the total dataset as the training dataset, and the remaining 20% as the validation dataset. And then, CNN classifiers are trained using the images of training dataset in the final step. Regarding the parameters of CNN-FG, we adopted two convolution filters ($5{\times}5{\times}6$ and $5{\times}5{\times}9$) in the convolution layer. In the pooling layer, $2{\times}2$ max pooling filter was used. The numbers of the nodes in two hidden layers were set to, respectively, 900 and 32, and the number of the nodes in the output layer was set to 2(one is for the prediction of upward trend, and the other one is for downward trend). Activation functions for the convolution layer and the hidden layer were set to ReLU(Rectified Linear Unit), and one for the output layer set to Softmax function. To validate our model - CNN-FG, we applied it to the prediction of KOSPI200 for 2,026 days in eight years (from 2009 to 2016). To match the proportions of the two groups in the independent variable (i.e. tomorrow's stock market movement), we selected 1,950 samples by applying random sampling. Finally, we built the training dataset using 80% of the total dataset (1,560 samples), and the validation dataset using 20% (390 samples). The dependent variables of the experimental dataset included twelve technical indicators popularly been used in the previous studies. They include Stochastic %K, Stochastic %D, Momentum, ROC(rate of change), LW %R(Larry William's %R), A/D oscillator(accumulation/distribution oscillator), OSCP(price oscillator), CCI(commodity channel index), and so on. To confirm the superiority of CNN-FG, we compared its prediction accuracy with the ones of other classification models. Experimental results showed that CNN-FG outperforms LOGIT(logistic regression), ANN(artificial neural network), and SVM(support vector machine) with the statistical significance. These empirical results imply that converting time series business data into graphs and building CNN-based classification models using these graphs can be effective from the perspective of prediction accuracy. Thus, this paper sheds a light on how to apply deep learning techniques to the domain of business problem solving.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.127-148
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• 2020

The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.

• Korean Journal of Heritage: History & Science
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• v.52 no.3
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• pp.172-187
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• 2019

Knowledge of intangible cultural heritage is usually disseminated through word-of-mouth and actions rather than written records. Thus, people assemble to teach others about it and form communities. Accordingly, to understand and spread information about intangible cultural heritage properly, it is necessary to understand not only their attributes but also a community's relational characteristics. Community members include specialized transmitters who work under the auspices of institutions, and general transmitters who enjoy intangible cultural heritage in their daily lives. They converse about intangible cultural heritage in close relationships. However, to date, research has focused only on professionals. Thus, this study focused on the roles of general transmitters of intangible cultural heritage information by investigating intangible cultural heritage communities centering around Jeongseon Arirang; a social network analysis was performed. Regarding the research objectives presented in the introduction, the main findings of the study are summarized as follows. First, there were 197 links between 74 members of the Jeongseon Arirang Transmission Community. One individual had connections with 2.7 persons on average, and all were connected through two steps in the community. However, the density and the clustering coefficient were low, 0.036 and 0.32, respectively; therefore, the cohesiveness of this community was low, and the relationships between the members were not strong. Second, 'Young-ran Yu', 'Nam-gi Kim' and 'Gil-ja Kim' were found to be the prominent figures of the Jeongseon Arirang Transmission Community, and the central structure of the network was concentrated around these three individuals. Being located in the central structure of the network indicates that a person is popular and ranked high. Also, it means that a person has an advantage in terms of the speed and quantity of the acquisition of information and resources, and is in a relatively superior position in terms of bargaining power. Third, to understand the replaceability of the roles of Young-ran Yu, Nam-gi Kim, and Gil-ja Kim, who were found to be the major figures through an analysis of the central structure, structural equivalence was profiled. The results of the analysis showed that the positions and roles of Young-ran Yu, Nam-gi Kim, and Gil-ja Kim were unrivaled and irreplaceable in the Jeongseon Arirang Transmission Community. However, considering that these three members were in their 60s and 70s, it seemed that it would be necessary to prepare measures for the smooth maintenance and operation of the community. Fourth, to examine the subgroup hidden in the network of the Jeongseon Arirang Transmission Community, an analysis of communities was conducted. A community refers to a subgroup clearly differentiated based on modularity. The results of the analysis identified the existence of four communities. Furthermore, the results of an analysis of the central structure showed that the communities were formed and centered around Young-ran Yu, Hyung-jo Kim, Nam-gi Kim, and Gil-ja Kim. Most of the transmission TAs recommended by those members, students who completed a course, transmission scholarship holders, and the general members taught in the transmission classes of the Jeongseon Arirang Preservation Society were included as members of the communities. Through these findings, it was discovered that it is possible to maintain the transmission genealogy, making an exchange with the general members by employing the present method for the transmission of Jeongseon Arirang, the joint transmission method. It is worth paying attention to the joint transmission method as it overcomes the demerits of the existing closed one-on-one apprentice method and provides members with an opportunity to learn their masters' various singing styles. This study is significant for the following reasons: First, by collecting and examining data using a social network analysis method, this study analyzed phenomena that had been difficult to investigate using existing statistical analyses. Second, by adopting a different approach to the previous method in which the genealogy was understood, looking at oral data, this study analyzed the structures of the transmitters' relationships with objective and quantitative data. Third, this study visualized and presented the abstract structures of the relationships among the transmitters of intangible cultural heritage information on a 2D spring map. The results of this study can be utilized as a baseline for the development of community-centered policies for the protection of intangible cultural heritage specified in the UNESCO Convention for the Safeguarding of Intangible Cultural Heritage. To achieve this, it would be necessary to supplement this study through case studies and follow-up studies on more aspects in the future.

• MISULJARYO - National Museum of Korea Art Journal
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• v.96
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• pp.123-154
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• 2019

Ancestral Burial Ground on the Inwangsan Mountain is a ten-panel folding screen with images and postscripts. Commissioned by Bak Gyeong-bin (dates unknown), this screen was painted by Jo Jung-muk (1820-after 1894) in 1868. The postscripts were written by Hong Seon-ju (dates unknown). The National Museum of Korea restored this painting, which had been housed in the museum on separate sheets, to its original folding screen format. The museum also opened the screen to the public for the first time at the special exhibition Through the Eyes of Joseon Painters: Real Scenery Landscapes of Korea held from July 23 to September 22, 2019. Ancestral Burial Ground on the Inwangsan Mountain depicts real scenery on the western slopes of Inwangsan Mountain spanning present-day Hongje-dong and Hongeun-dong in Seodaemun-gu, Seoul. In the distance, the Bukhansan Mountain ridges are illustrated. The painting also bears place names, including Inwangsan Mountain, Chumohyeon Hill, Hongjewon Inn, Samgaksan Mountain, Daenammun Gate, and Mireukdang Hall. The names and depictions of these places show similarities to those found on late Joseon maps. Jo Jung-muk is thought to have studied the geographical information marked on maps so as to illustrate a broad landscape in this painting. Field trips to the real scenery depicted in the painting have revealed that Jo exaggerated or omitted natural features and blended and arranged them into a row for the purposes of the horizontal picture plane. Jo Jung-muk was a painter proficient at drawing conventional landscapes in the style of the Southern School of Chinese painting. Details in Ancestral Burial Ground on the Inwangsan Mountain reflect the painting style of the School of Four Wangs. Jo also applied a more decorative style to some areas. The nineteenth-century court painters of the Dohwaseo(Royal Bureau of Painting), including Jo, employed such decorative painting styles by drawing houses based on painting manuals, applying dots formed like sprinkled black pepper to depict mounds of earth and illustrating flowers by dotted thick pigment. Moreover, Ancestral Burial Ground on the Inwangsan Mountain shows the individualistic style of Jeong Seon(1676~1759) in the rocks drawn with sweeping brushstrokes in dark ink, the massiveness of the mountain terrain, and the pine trees simply depicted using horizontal brushstrokes. Jo Jung-muk is presumed to have borrowed the authority and styles of Jeong Seon, who was well-known for his real scenery landscapes of Inwangsan Mountain. Nonetheless, the painting lacks an spontaneous sense of space and fails in conveying an impression of actual sites. Additionally, the excessively grand screen does not allow Jo Jung-muk to fully express his own style. In Ancestral Burial Ground on the Inwangsan Mountain, the texts of the postscripts nicely correspond to the images depicted. Their contents can be divided into six parts: (1) the occupant of the tomb and the reason for its relocation; (2) the location and geomancy of the tomb; (3) memorial services held at the tomb and mysterious responses received during the memorial services; (4) cooperation among villagers to manage the tomb; (5) the filial piety of Bak Gyeong-bin, who commissioned the painting and guarded the tomb; and (6) significance of the postscripts. The second part in particular is faithfully depicted in the painting since it can easily be visualized. According to the fifth part revealing the motive for the production of the painting, the commissioner Bak Gyeongbin was satisfied with the painting, stating that "it appears impeccable and is just as if the tomb were newly built." The composition of the natural features in a row as if explaining each one lacks painterly beauty, but it does succeed in providing information on the geomantic topography of the gravesite. A fair number of the existing depictions of gravesites are woodblock prints of family gravesites produced after the eighteenth century. Most of these are included in genealogical records and anthologies. According to sixteenth- and seventeenth-century historical records, hanging scrolls of family gravesites served as objects of worship. Bowing in front of these paintings was considered a substitute ritual when descendants could not physically be present to maintain their parents' or other ancestors' tombs. Han Hyo-won (1468-1534) and Jo Sil-gul (1591-1658) commissioned the production of family burial ground paintings and asked distinguished figures of the time to write a preface for the paintings, thus showing off their filial piety. Such examples are considered precedents for Ancestral Burial Ground on the Inwangsan Mountain. Hermitage of the Recluse Seokjeong in a private collection and Old Villa in Hwagae County at the National Museum of Korea are not paintings of family gravesites. However, they serve as references for seventeenth-century paintings depicting family gravesites in that they are hanging scrolls in the style of the paintings of literary gatherings and they illustrate geomancy. As an object of worship, Ancestral Burial Ground on the Inwangsan Mountain recalls a portrait. As indicated in the postscripts, the painting made Bak Gyeong-bin "feel like hearing his father's cough and seeing his attitudes and behaviors with my eyes." The fable of Xu Xiaosu, who gazed at the portrait of his father day and night, is reflected in this gravesite painting evoking a deceased parent. It is still unclear why Bak Gyeong-bin commissioned Ancestral Burial Ground on the Inwangsan Mountain to be produced as a real scenery landscape in the folding screen format rather than a hanging scroll or woodblock print, the conventional formats for a family gravesite paintings. In the nineteenth century, commoners came to produce numerous folding screens for use during the four rites of coming of age, marriage, burial, and ancestral rituals. However, they did not always use the screens in accordance with the nature of these rites. In the Ancestral Burial Ground on the Inwangsan Mountain, the real scenery landscape appears to have been emphasized more than the image of the gravesite in order to allow the screen to be applied during different rituals or for use to decorate space. The burial mound, which should be the essence of Ancestral Burial Ground on the Inwangsan Mountain, might have been obscured in order to hide its violation of the prohibition on the construction of tombs on the four mountains around the capital. At the western foot of Inwangsan Mountain, which was illustrated in this painting, the construction of tombs was forbidden. In 1832, a tomb discovered illegally built on the forbidden area was immediately dug up and the related people were severely punished. This indicates that the prohibition was effective until the mid-nineteenth century. The postscripts on the Ancestral Burial Ground on the Inwangsan Mountain document in detail Bak Gyeong-bin's efforts to obtain the land as a burial site. The help and connivance of villagers were necessary to use the burial site, probably because constructing tombs within the prohibited area was a burden on the family and villagers. Seokpajeong Pavilion by Yi Han-cheol (1808~1880), currently housed at the Los Angeles County Museum of Art, is another real scenery landscape in the format of a folding screen that is contemporaneous and comparable with Ancestral Burial Ground on the Inwangsan Mountain. In 1861 when Seokpajeong Pavilion was created, both Yi Han-cheol and Jo Jung-muk participated in the production of a portrait of King Cheoljong. Thus, it is highly probable that Jo Jung-muk may have observed the painting process of Yi's Seokpajeong Pavilion. A few years later, when Jo Jungmuk was commissioned to produce Ancestral Burial Ground on the Inwangsan Mountain, his experience with the impressive real scenery landscape of the Seokpajeong Pavilion screen could have been reflected in his work. The difference in the painting style between these two paintings is presumed to be a result of the tastes and purposes of the commissioners. Since Ancestral Burial Ground on the Inwangsan Mountain contains the multilayered structure of a real scenery landscape and family gravesite, it seems to have been perceived in myriad different ways depending on the viewer's level of knowledge, closeness to the commissioner, or viewing time. In the postscripts to the painting, the name and nickname of the tomb occupant as well as the place of his surname are not recorded. He is simply referred to as "Mister Bak." Biographical information about the commissioner Bak Gyeong-bin is also unavailable. However, given that his family did not enter government service, he is thought to have been a person of low standing who could not become a member of the ruling elite despite financial wherewithal. Moreover, it is hard to perceive Hong Seon-ju, who wrote the postscripts, as a member of the nobility. He might have been a low-level administrative official who belonged to the Gyeongajeon, as documented in the Seungjeongwon ilgi (Daily Records of Royal Secretariat of the Joseon Dynasty). Bak Gyeong-bin is presumed to have moved the tomb of his father to a propitious site and commissioned Ancestral Burial Ground on the Inwangsan Mountain to stress his filial piety, a conservative value, out of his desire to enter the upper class. However, Ancestral Burial Ground on the Inwangsan Mountain failed to live up to its original purpose and ended up as a contradictory image due to its multiple applications and the concern over the exposure of the violation of the prohibition on the construction of tombs on the prohibited area. Forty-seven years after its production, this screen became a part of the collection at the Royal Yi Household Museum with each panel being separated. This suggests that Bak Gyeong-bin's dream of bringing fortune and raising his family's social status by selecting a propitious gravesite did not come true.