• Korea Science and Art Forum
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• v.30
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• pp.151-161
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• 2017

In the fields of science and engineering, multidisciplinary research is common, and researchers with a diverse range of expertise collaborate to achieve common goals. As the 4th industrial revolution gains currency in society, there is growing demand on talented personnel both with technical knowledge and skills and with communicative skills. That is, future engineers are expected to possess competence in social and artistic skills in addition to specialized knowledge and skills in engineering. In this paper we introduce an emerging field of 3D bioprinting as an exemplary case of interdisciplinary research. We have chosen the case to demonstrate the possibility of cultivating engineers with π-shaped expertise. Building on the concept of T-shaped talent, we define π-shaped expertise as having both technical skills in more than one specialized field and interpersonal/communicative skills. Wtih references to such concepts as trading zones and interactional expertise, we suggest that π-shaped expertise can be cultivated via the creation of multi-level trading zones. Trading zones are referred to as the physical, conceptual, or metaphorical spaces in which experts with different world views trade ideas, objects, and the like. Interactional expertise is cultivated, as interactions between researches are under way, with growing understanding of each other's expertise. Under the support of the university and the government, two researchers with expertise in printing technology and life sciences cooperate to develop a 3D bioprinting system. And the primary investigator of the research laboratory under study has aimed to create multiple dimensions of trading zones where researchers with different educational and cultural backgrounds can exchange ideas and interact with each other. As 3D bioprinting has taken shape, we have found that a new form of expertise, namely π-shaped expertise is formed.

• Journal of Intelligence and Information Systems
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• v.15 no.4
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• pp.183-200
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• 2009

Collaborative Filtering is one of the most used recommender systems. However, basically it cannot be used to recommend new products to customers because it finds products only based on the purchasing history of each customer. In order to cope with this shortcoming, many researchers have proposed the hybrid recommender system, which is a combination of collaborative filtering and content-based filtering. Content-based filtering recommends the products whose attributes are similar to those of the products that the target customers prefer. However, the hybrid method is used only for the limited categories of products such as music and movie, which are the products whose attributes are easily extracted. Therefore it is essential to find a more effective approach to recommend to customers new products in any category. In this study, we propose a new recommendation method which applies centrality concept widely used to analyze the relational and structural characteristics in social network analysis. The new products are recommended to the customers who are highly likely to buy the products, based on the analysis of the relationships among products by using centrality. The recommendation process consists of following four steps; purchase similarity analysis, product network construction, centrality analysis, and new product recommendation. In order to evaluate the performance of this proposed method, sales data from H department store, one of the well.known department stores in Korea, is used.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.809-814
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• 2023

Currently, there is a lack of research that directly applies and integrates science and technology in the field of dance and translates it into creative work. In this study, the researcher applied motion capture to creative dance performance 'Youth' and described the process of incorporating motion capture into scenes for the performance. The research method involved utilizing practice-based research, which derives new knowledge and meaning from creative outcomes through the analysis of phenomena and experiences generated on-site. The creative ballet performance "<Youth>" consists of a total of 4 scenes, and the motion-captured video in these scenes serves as the highlight moments. It visually represents the image of a past ballerina while embodying the meaning of a scene that is both the 'past me' and the 'dream of the present.' The use of motion capture enhances the visual representation of the scenes and plays a role in increasing the audience's immersion. The dance field needs to become familiar with collaborating with scientific and technological advancements like motion capture to digitize intangible assets. It is essential to engage in experimental endeavors and continue training for such collaborations. Furthermore, through collaboration, the ongoing research should extend the scope of movement through digitized processes, performances, and performance records. This will continually confer value and meaning to the field of dance

• Journal of Korean Library and Information Science Society
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• v.48 no.3
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• pp.259-279
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• 2017

The academic library has the ideal environment as a facilitator of knowledge creation, as a space where researchers can collaborate and as a creation hub center on campus. Recently, based on the 4th Industrial Revolution and creative theories, the maker space is gradually being introduced into academic libraries in foreign countries. Maker Space of the academic library is the best place to discover new knowledge and interests, practice, and interdisciplinary education. In this study, we propose a plan to introduce the maker space of domestic university libraries through case studies of domestic and overseas university and university libraries.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.550-552
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• 2007

Bioworks is designed to make, visualize, automate and execute a model of biological analysis processes as a workflow in biotechnology field. It provides for constructing a workflow model of complex biological analysis processes more easily and reporting the analysis results of each step. Users can perform their analysis process by using a visuality and validation module provided as a plug-in program. It supports sharing their workflow in XML format, to which conversion is supplied by Bioworks, with Web Services to improve the efficiency of their study.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.200-204
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• 2006

본 논문은 지식 기반 정보유통 플랫폼 OntoFrame-K$^{(R)}$ 상에서 추론을 이용하여 연구자 간 협업 서비스를 제공할 수 있도록 하는 DBMS 기반 추론 서비스 OntoThink-K$^{(R)}$에 대해 기술한다. 본 추론 서비스는 URI 서버를 이용하여 RDF 트리플을 생성하고 추론 규칙에 의해 해당 트리플을 확장하며 SPARQL을 통해 질의 결과를 생성해낸다. 특히 이 모든 과정은 DBMS 기반으로 설계 구현되었는데 URI 서버와 성과 비성과 등록 인터페이스를 통해 별도의 추론 엔진을 사용하지 않고도 정합성이 보장되는 지식을 생성 관리할 수 있도록 하며, 불안정한 성능을 보이는 추론 엔진을 이용하지 않기 때문에 안정적인 성능을 보장할 수 있다는 데 그 특징이 있다. OntoThink-K$^{(R)}$는 온톨로지 스키마 트리플, 인스턴스 트리플, 그리고 전방 추론을 통해 획득한 추가 트리플을 포함하는 확장 트리플을 기반 지식으로 하는데, 최종 사용되는 RDF 트리플의 크기는 지식 확장 이전 631,158개, 지식 확장 이후 1,112,100개이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1632-1635
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• 2012

연구기관의 연구 활동에 대한 평가는 연구기관에 소속된 연구자들의 논문으로 연구 활동을 분석함으로써 이루어질 수 있다. 논문으로 연구 활동을 분석하여 연구기관에 대한 평가를 하기 위해서는 논문을 작성한 저자의 소속기관이 가장 먼저 식별되어야 한다. 본 논문에서는 국내 과학학술지 논문에 대한 저자의 소속 연구기관을 식별하는 시스템을 구축하여 각 연구기관의 연구 활동에 대하여 분석해 보았다. 이러한 시스템을 기반으로 연구기관별 논문 수, 피인용 횟수, 1회 이상 피인용 된 논문 수 등의 기본 연구 활동을 분석하여 얻은 결과는 연구 기관 평가의 근거로 사용할 있으며, 나아가 특정 분야에서 강세를 보이는 연구기관과 연구기관끼리의 협업 관계를 분석하여 정책에 활용할 수도 있다.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.145-150
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• 2021

This thesis attempted to examine the mechanization of humans, humanization of machines, and coexistence through dance works. The dance works were reviewed by partial excerpts from Oscar Schlemer's <3 Chord Ballet>, Felindrome Dance Company's , and . Also, I looked at the dance work , which has an inherent form of coexistence. Through the above work, robot-like science and technology and fusion. It was found that various dance performances that coexist in complex forms provide continuous creativity to humans, and various forms of sensibility and creative movements based on data make it possible to produce rich performances for humans. This researcher expects numerous works that accept and reflect the changes of the times through the embodied interaction of dance performances with science and technology.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.59-69
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• 2010

The research on protein for the diseases analysis and the new medicines development is one of the most important themes in biotechnology. Since the analysis on diseases and protein needs to handle a large scale of data, we don't use the way to approach it by the experiments anymore. In recent, we have accelerated the research on diseases and protein analysis by sharing and connecting the various experimental data by combining the biotechnology with the IT technology. However, many biotechnology researchers have difficulty in handling the protein analysis tools based on the IT knowledge. In order to solve such problems, data analysis tools through the cooperation between IT researchers and biologists have been developed. However, the existing data analysis tools still have the problems that it is very hard for biologists to extend their functions and to use them. In this paper, we design and implement an effective analysis system for diseases and protein based on components that alleviates the problems of the existing data analysis systems.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.139-152
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• 2011

Recommender systems have become an important research field since the emergence of the first paper on collaborative filtering in the mid-1990s. In general, recommender systems are defined as the supporting systems which help users to find information, products, or services (such as books, movies, music, digital products, web sites, and TV programs) by aggregating and analyzing suggestions from other users, which mean reviews from various authorities, and user attributes. However, as academic researches on recommender systems have increased significantly over the last ten years, more researches are required to be applicable in the real world situation. Because research field on recommender systems is still wide and less mature than other research fields. Accordingly, the existing articles on recommender systems need to be reviewed toward the next generation of recommender systems. However, it would be not easy to confine the recommender system researches to specific disciplines, considering the nature of the recommender system researches. So, we reviewed all articles on recommender systems from 37 journals which were published from 2001 to 2010. The 37 journals are selected from top 125 journals of the MIS Journal Rankings. Also, the literature search was based on the descriptors "Recommender system", "Recommendation system", "Personalization system", "Collaborative filtering" and "Contents filtering". The full text of each article was reviewed to eliminate the article that was not actually related to recommender systems. Many of articles were excluded because the articles such as Conference papers, master's and doctoral dissertations, textbook, unpublished working papers, non-English publication papers and news were unfit for our research. We classified articles by year of publication, journals, recommendation fields, and data mining techniques. The recommendation fields and data mining techniques of 187 articles are reviewed and classified into eight recommendation fields (book, document, image, movie, music, shopping, TV program, and others) and eight data mining techniques (association rule, clustering, decision tree, k-nearest neighbor, link analysis, neural network, regression, and other heuristic methods). The results represented in this paper have several significant implications. First, based on previous publication rates, the interest in the recommender system related research will grow significantly in the future. Second, 49 articles are related to movie recommendation whereas image and TV program recommendation are identified in only 6 articles. This result has been caused by the easy use of MovieLens data set. So, it is necessary to prepare data set of other fields. Third, recently social network analysis has been used in the various applications. However studies on recommender systems using social network analysis are deficient. Henceforth, we expect that new recommendation approaches using social network analysis will be developed in the recommender systems. So, it will be an interesting and further research area to evaluate the recommendation system researches using social method analysis. This result provides trend of recommender system researches by examining the published literature, and provides practitioners and researchers with insight and future direction on recommender systems. We hope that this research helps anyone who is interested in recommender systems research to gain insight for future research.