• (The)Study of the Eastern Classic
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• no.50
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• pp.89-120
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• 2013

The concept of virtue seems to be one of the rare cases where the European and the Chinese traditions coincide. The meaning of the Latin word virtus and of Greek $aret{\acute{e}}$ seems to be similar to the Chinese $d{\acute{e}}$德. Most striking in virtue is that it is a capacity for self-realisation through action which is unique to man. On the other hand, there is something physical about it. It is the strength to do something. This strength overcomes the resistance of what is naturally given, it transforms the world, turns the natural world into a human one. In the Chinese tradition, $d{\acute{e}}$ 德, i.e. virtue, is therefore always connected with $da{\grave{o}}$ 道, the totality of natural forces. In the Chinese tradition, as opposed to the European one, virtue is itself considered to be a natural force that is present in man. This force sustains man's connectedness, unity and harmony with the surrounding world. Things exist through the unity of principle理 and ether氣. But the knowledge of this unity is due to principle. Moral and legal norms are shifted totally to the sphere of principle. Therefore their have found the final dissolution from a heroic models. Above all the classical Confucians, but also the other schools, would reply to this that there is nothing more precise than a concrete successful action. Its result fits the world perfectly. The difference is due to the differing interest of ethical thought. In the case of the Confucians the path is more direct. The actor establishes a precise pattern for other actions. Education therefore lies in detailed knowledge about forms of behaviour, not so much in conceptual differentiation. It is quite possible that generalisation may be a methodical prerequisite for success in this endeavour. That problem, too, is discussed. But the success of conceptualisation lies in the successful performance of individual actions, not in shaping actions in accordance with normative concepts.

• Journal of Practical Agriculture & Fisheries Research
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• v.22 no.1
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• pp.113-129
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• 2020

In this study we examined the topic analysis and correlation analysis by text mining to extract meaningful information or rules from the self introduction letter of freshman at Korea National College of Agriculture and Fisheries in 2020. The analysis items are described in items related to 'academic' and 'in-school activities' during high school. In the text mining results, the keywords of 'academic' items were 'study', 'thought', 'effort', 'problem', 'friend', and the key words of 'in-school activities' were 'activity', 'thought', 'friend', 'club', 'school' in order. As a result of the correlation analysis, the key words of 'thinking', 'studying', 'effort', and 'time' played a central role in the 'academic' item. And the key words of 'in-school activities' were 'thought', 'activity', 'school', 'time', and 'friend'. The results of frequency analysis and association analysis were visualized with word cloud and correlation graphs to make it easier to understand all the results. In the next study, TF-IDF(Term Frequency-Inverse Document Frequency) analysis using 'frequency of keywords' and 'reverse of document frequency' will be performed as a method of extracting key words from a large amount of documents.

• Journal of Ginseng Culture
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• v.4
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• pp.103-127
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• 2022

The influx of modern culture in the early 20th century in Korea led to numerous changes in the country's ginseng industry. With the development of ginseng cultivation technology and commerce, the production and consumption of ginseng increased, and various ginseng products were developed using modern manufacturing technology. Consequently, competition for the sales of these products became fierce. At that time, newspaper advertisements showed detailed trends in the development and sales competition of ginseng products. Before 1920, however, there were few advertisements of ginseng in newspapers. This is thought to be because newspapers had not yet been generalized, and the ginseng industry had not developed that much. Ginseng advertisements started to revitalize in the early 1920s after the launch of the Korean daily newspapers Dong-A Ilbo and Chosun Ilbo. Such advertisements in this period focused on emphasizing the traditional efficacy of Oriental medicine and the mysterious effects of ginseng. There were many advertisements for products that prescribed the combination of ginseng and deer antler, indicating the great popularity of this prescription at the time. Furthermore, advertisements showed many personal experience stories about taking such products. Mail order and telemarketing sales were already widely used in the 1920s . In 1925, there were advertisements that ginseng products were delivered every day. The advertisements revealed that ginseng roots were classified more elaborately than they are now according to size and quality. Ginseng products in the 1920s did not deviate significantly from the scope of traditional Oriental medicine formulations such as liquid medicine, pill, and concentrated extract. In the 1930s, ginseng advertisements became more active. At this time, experts such as university professors and doctors in medicine or in pharmacy appeared in the advertisements. They recommended ginseng products or explained the ingredients and medicinal effects of the products. Even their experimental notes based on scientific research results appeared in the advertisements to enhance the reliability of the ginseng products. In 1931, modern tablet advertisements appeared. Ginseng products supplemented with vitamins and other specific ingredients as well as ginseng thin rice gruel for the sick appeared at this time. In 1938, ginseng advertisements became more popular, and advertisements using talents as models, such as dancer Choi Seunghee or famous movie stars, models appeared. Ginseng advertisements in the 1920s and 1930s clearly show a side of our rapidly changing society at the time.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.110-123
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• 2022

Namsan Park in Seoul was designated as a "grand park" in 1954 and is currently operated as an 'Urban Nature Park Area' and four 'neighborhood parks.' However, despite the park's historical and cultural value as an urban park, it has been discussed mainly from a perspective revolving around notions of a mountain or a city wall. To ensure a comprehensive exploration of Namsan Park's history, this study examined public records at the Seoul Metropolitan Archives (SMA), which houses the city's permanent records for preservation and organization. To this end, documents in the SMA Database (DB) were analyzed, yielding 1,359 records concerning Namsan Park. Based on the contents, general characteristics of the urban park were identified through production periods, record types, and disclosure types. Then, essential keywords concerning organizations, people, geographical areas, subjects, and business functions were examined. Finally, the contents and characteristics of Namsan Park in public records were scrutinized, focusing on specific spaces. This research also uncovered important information, such as park drawings, photos, planting lists, plant parcel lists, and significant discussions and decisions regarding the operation and management of the park. Although the public records do not contain a comprehensive history of Namsan Park, it was possible to check the primary historical changes and deliberation processes pertaining to the park's history. Therefore, continuous research intended to interpret and describe public records is expected to identify many implications. In addition, because the public records showed heterogeneous characteristics that center on specific periods and events, an essential task is to advance collaboration and networking with various related institutions, designers, researchers, and citizens.

• Korean Journal of Environment and Ecology
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• v.36 no.6
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• pp.651-661
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• 2022

Plants social network analysis, which combines plants society and social network analyses, is a new research method for understanding plants society. This study was conducted to investigate the relationship between species, using plant social network analysis targeting Taejongdae in Busan, and build basic data for management. Taejongdae, located in the warm temperate forest in Korea, is a representative coastal forest of Busan Metropolitan City, and the Pinus thunbergii-Eurya japonicacommunity is widely distributed. This study set up 100 quadrats (size of 100m²each) in Taejongdae to investigate the species that emerged and analyzed the interspecies association focusing on major species. Based on the results, a sociogram was created using the Gephi 0.9.2, and the network centrality and structure were analyzed. The results showed that the frequency of appearance was high in the order of P. thunbergii, E. japonica, Quercus serrata, Sorbus alnifolia, Ligustrum japonicum, and Styrax japonicusand that many evergreen broad-leaved trees appeared due to the environmental characteristics of the site. The plants social network of Taejongdae was composed of a small-scale network with 50 nodes and 172 links and was divided into 4 groups through modularization. The succession sere identified through a sociogram confirmed that the group that include P. thunbergiiand E. japonicawould progress to a deciduous broadleaf community dominated by Q. serrataand Carpinus tschonoskii, using hub nodes such as Prunus serrulataf. spontaneaand Toxicodendron trichocarpum. Another succession sere was highly likely to progress to an evergreen broad-leaved community dominated by Machilus thunbergiiand Neolitsea sericea, using M. thunbergiias a medium. In some areas, a transition to a deciduous broad-leaved community dominated by Celtis sinensis, Q. variabilisand Zelkova serratausing Lindera obtusilobaand C. sinensisas hub nodes was expected.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.73.4-74
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• 2021

한국천문연구원은 2017년 제1차 구술채록사업에 이어 2020년 제2차 사업을 진행하면서 최초로 원외 원로에 대한 구술채록을 시도하였다. 국가 대표 천문연구의 산실로서 연구원 존재 의의를 확립하기 위하여 원내 원로에 국한되었던 구술자 대상을 확장한 것이다. 그 첫 외부 구술 대상자로 방득룡 전임 노스웨스턴 천문학과 교수를 선정하여 2020년 7월부터 준비단계에 들어갔다. 방득룡 전(前)교수가 첫 번째 한국천문연구원 원외 인사 구술자로 선정된 이유는, 그가 우리나라 천문대1호 망원경 구매 선정에 개입한 서신(1972년)이 자료로 남아있었기 때문이다. 한국천문연구원에서 2017년에 수행한 제1차 구술채록사업에서 구술자로 참여한 오병렬 한국천문연구원 원로가 기증한 사료들은 대부분 연구원 태동기 국립천문대 구축과 망원경 구매 관련 자료였으며 이 가운데 1972년 당시 과학기술처 김선길 진흥국장에게 Boller and Chivesns(사(社))의 반사경을 추천한 방득룡 전(前)교수의 서신은 한국 천문학 발전사에서 중요한 사료였다. 연구진은 이 자료를 시작으로, 방득룡 전(前)교수의 생존 여부와 문서고의 공기록물들에서 그의 흔적을 찾아가기 시작했다. 놀랍게도 그는 실제 세계와 한국천문연구원 문서고 깊숙이 기록물들 모두에서 상존하고 있었다. 1927년생인 방득룡 전(前)교수, Dr. John D. R.은 미국 플로리다 한 실버타운에서 건강한 정신으로 생존하여 있었고 연구진의 인터뷰에 흔쾌히 응했다. 2020년 9월 16일에 한국천문연구원 본원 세종홀 2층 회의실에서 영상통신회의로 그와의 구술인터뷰가 진행되었다. 이 구술인터뷰는 원외 인사가 대상이란 점 외에도 방법적으로는 전형적인 대면 방식이 아닌 영상 인터뷰였다는 점에서 코로나 시대의 대안이 되는 실험적 시도였다. 현대 한국천문학 발전사의 재조명 측면에서도 의미가 있었다. 1960년대 초반부터 1992년 정년퇴임까지 30년을 미국 유수 대학교 천문학과 교수로 재직하며 활발한 활동을 해 온 한국계 천문학자가 우리나라 최초 반사망원경 구매 선정에 적극 개입하였던 역사는, 공문서 자료들과 서신 사료들에 이어 그의 육성으로 나머지 의구심의 간극이 채워졌다. 또 구술자 개인이 주관적으로 중요하다고 여기는 '기억'이 중요한 아카이빙 콘텐츠 확장의 단초가 될 수 있다는 것을 보여줌으로써 구술사 연구에 있어서도 중요한 관점을 주었다. 애초 연구진이 방득룡 전(前)교수의 공식 기록에서 아카이빙의 큰 줄기로 잡았던 것은 1948년 도미, 1957년 위스콘신 대학교 천문학 박사학위 취득, 1962년부터 노스웨스턴 대학(일리노이주 에반스턴)의 천문학 교수진, 1992년 은퇴로 이어진 생애였다. 그러나 그와의 구술 준비 서신 왕래와 구술을 통하여 알게 된 그가 인생에서 중요시 여겼던 지점은, 1948년 도미 무렵 한국의 전쟁 전 상황과 당시 비슷한 시기에 유학한 한국 천문학자들의 동태, 그리고 1957년부터 1962년까지 프린스턴 대학교에서 M. Schwarzschild 교수와 L. Spitzer 교수를 보조하며 Stratoscope Project를 연구하였던 경험이었다. 기록학적 의미에서도, 전자를 통해서 그와 함께 동시대 한국 천문학을 이끌었던 인재들의 맥락정보를 얻을 수 있었으며, 후자를 통해서는 세계 천문학사에 큰 영향을 미친 석학에 대한 아카이브 정보와의 연계 지점과 방득룡 전(前)교수의 연구 근원을 찾을 수 있었다. 이들은 추후 방득룡 콘텐츠 서비스 시에 AIP, NASM, Lyman Spitzer 콘텐츠, 평양천문대, 화천조경천문대, 서울대와 연세대, 그리고 한국천문연구원까지 연계되어 전 세계 폭넓은 이용자들의 유입을 유도할 수 있는 검색 도구가 될 수 있다. 이번 방득룡 구술사 연구에서 구술자 개인의 주관적인 소회가 공식 기록이 다가갈 수 없는 역사적 실체에 일정 부분 가까울 수 있다는 것, 그리고 이를 통하여 개인의 역사는 공동체의 역사로 확장될 수 있다는 사실을 발견할 수 있었다. 또 연구진은 방득룡 전(前)교수의 회상을 통하여 구술자 개인의 시각으로 한국과 미국 천문학계의 공동체 역사를 재조명할 수 있었고, 이것을 아카이브 콘텐츠 확장 서비스에 반영할 수 있다는 기대를 가지게 되었다. 무엇보다 이 연구를 통하여 다양한 주제의 아카이브로 연동될 수 있는 주제어와 검색도구를 구술자 개인의 회상으로부터 유효하게 도출할 수 있다는 것을 확인하였다. 그리고 향후 한국천문 구술아카이브의 확장을 통하여 보다 다양한 활용과 연구 재활용의 선순환이 가능하다는 것도 알 수 있었다. 이는 최근 기록학계에서 대두되고 있는 LOD(Linked Open Data)의 방향성과도 흡사하여 한국천문학 구술사연구의 차세대 통합형 기록관리의 미래모형을 기대케 하는 대목이다.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.63-79
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• 2024

The startup ecosystem is experiencing a paradigm shift in founding due to the acceleration of digital transformation, online platform companies have grown significantly into unicorns, but the lack of differentiated approaches and strategic support for deep tech startups has led to the inactivity of the startup ecosystem. is lacking. Therefore, in this study, we proposed ways to develop domestic startup development policies, focusing on the US system, which is an advanced example overseas. Focusing on the definition and characteristics of deep tech startups, current investment status, success stories, support policies, etc., we comprehensively analyzed domestic and international literature and derived suggestions. In particular, he proposed specific ways to improve support policies for domestic deep tech startups and presented milestones for their development. Currently, the United States is significantly strengthening the role of the government in supporting deep tech startups. The US government provides direct financial support to deep tech startups, including detergent support and infrastructure support. It has also established policies to foster deep tech startups, established related institutions, and systematized support. It is worth noting that US universities play a core role in nurturing deep tech startups. Leading universities in the United States operate deep tech startup discovery and development programs, providing research and development infrastructure and technology. It also works with companies to provide co-investment and commercialization support for deep tech startups. As a result, the growth of domestic deep tech startups requires the cooperation of diverse entities such as the government, universities, companies, and private investors. The government should strengthen policy support, and universities and businesses should work together to support R&D and commercialization capabilities. Furthermore, private investors must stimulate investment in deep tech startups. Through such efforts, deep tech startups are expected to grow and Korea's innovation ecosystem will be revitalized.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Korean Security Journal
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• no.18
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• pp.169-190
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• 2009

Today, the rapid advance of scientific technologies has brought about fundamental changes to the types and levels of terrorism while the war against the world more than one thousand small and big terrorists and crime organizations has already begun. A method highly likely to be employed by terrorist groups that are using 21st Century state of the art technology is cyber terrorism. In many instances, things that you could only imagine in reality could be made possible in the cyber space. An easy example would be to randomly alter a letter in the blood type of a terrorism subject in the health care data system, which could inflict harm to subjects and impact the overturning of the opponent's system or regime. The CIH Virus Crisis which occurred on April 26, 1999 had significant implications in various aspects. A virus program made of just a few lines by Taiwanese college students without any specific objective ended up spreading widely throughout the Internet, causing damage to 30,000 PCs in Korea and over 2 billion won in monetary damages in repairs and data recovery. Despite of such risks of cyber terrorism, a great number of Korean sites are employing loose security measures. In fact, there are many cases where a company with millions of subscribers has very slackened security systems. A nationwide preparation for cyber terrorism is called for. In this context, this research will analyze the current status of Korea's cyber security systems and its laws from a policy perspective, and move on to propose improvement strategies. This research suggests the following solutions. First, the National Cyber Security Management Act should be passed to have its effectiveness as the national cyber security management regulation. With the Act's establishment, a more efficient and proactive response to cyber security management will be made possible within a nationwide cyber security framework, and define its relationship with other related laws. The newly passed National Cyber Security Management Act will eliminate inefficiencies that are caused by functional redundancies dispersed across individual sectors in current legislation. Second, to ensure efficient nationwide cyber security management, national cyber security standards and models should be proposed; while at the same time a national cyber security management organizational structure should be established to implement national cyber security policies at each government-agencies and social-components. The National Cyber Security Center must serve as the comprehensive collection, analysis and processing point for national cyber crisis related information, oversee each government agency, and build collaborative relations with the private sector. Also, national and comprehensive response system in which both the private and public sectors participate should be set up, for advance detection and prevention of cyber crisis risks and for a consolidated and timely response using national resources in times of crisis.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.