• Korean journal of communication and information
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• v.53
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• pp.53-72
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• 2011

has become the representative program of EBS after first airing in 2004. After seeing as a media text, this study was fulfilled on the basis of Bill Nichols' "Rhetoric" discussion, in order to analyze the structural method and social meaning of the program. As a result of the study, we were first able to see that was taking form as a documentary to make a constructive statement on current affairs related to Korean society, by mobilizing 'knowledge' related to these issues. Second, the "rhetoric" plays an important role in the program's process to generate meaning, and despite the text being relatively short, the rhetorical process undergone for the generation of meaning has been fully reflected. Moreover, the program was successfully structuring a new method of generating meaning by enthusiastically raising questions and choosing a unique method of vision mix. Third, by looking at the study's results in-depth, we can see that was creating a ideological place for open discussion, which was providing viewers with the satisfaction of overcoming our society's dominating ideology and forming new ones. In that sense, the easily accessible 'knowledge'that surrounds us holds somewhat of a political meaning. On top of that, it can be seen that the program especially, is a media text that holds a cultural political meaning, which is an important factor to consider in the Korean broadcasting industry. In conclusion, we found out that this program uses 'knowledge' to see the possibility of 'knowledge'journalism by making constructive statements through a 'rhetorical' process.

• Journal of Korea Spatial Information System Society
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• v.1 no.1 s.1
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• pp.5-18
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• 1999

Recently, the necessity of automatic knowledge extraction from spatial data stored in spatial databases has been increased. Spatial data mining can be defined as the extraction of implicit knowledge, spatial relationships, or other knowledge not explicitly stored in spatial databases. In order to extract useful knowledge from spatial data, an object management system that can store spatial data efficiently, provide very fast indexing & searching mechanisms, and support a distributed computing environment is needed. In this paper, we designed and implemented an open object management system for spatial data mining, that supports efficient management of spatial, aspatial, and knowledge data. In order to develop this system, we used Open OODB that is a widely used object management system. However, the lark of facilities for spatial data mining in Open OODB, we extended it to support spatial data type, dynamic class generation, object-oriented inheritance, spatial index, spatial operations, etc. In addition, for further increasement of interoperability with other spatial database management systems or data mining systems, we adopted international standards such as ODMG 2.0 for data modeling, SDTS(Spatial Data Transfer Standard) for modeling and exchanging spatial data, and OpenGIS Simple Features Specification for CORBA for connecting clients and servers efficiently.

• Journal of Science Education
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• v.42 no.2
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• pp.148-164
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• 2018

This study developed the sex education program based on the 'reproduction and development' unit of the middle school science, and examined its effectiveness on middle school boys' sex-related knowledge and attitude towards sex. The sex education program consisted of six topics of the structures and functions of generative organs, the importance of life, abortion, the human generation process, venereal diseases and AIDS, and responsibility of self-determination on sexual behavior. The results indicated that the experimental group demonstrated the statistically higher scores of the knowledge on sex than the control groups' scores, especially in the subcategories of 'pregnancy and delivery' and 'sex-related health'. However, both groups did not display any statistical difference on the attitude toward sex. In the subcategory of the attitude towards sex, the experimental group showed the statistically higher scores on 'self-determination and selection' and 'a health relationship'. In addition, the Pearson correlation results indicated the strongest relationship between the attitude toward sex and 'the self-determination and selection'. These results implicated that the sex education program related to the unit of reproduction and development in the middle school science helps the middle school boys develop the better knowledge and attitude towards sex.

• Journal of Internet Computing and Services
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• v.13 no.4
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• pp.45-52
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• 2012

T cells induce immune responses and thereby eliminate infected micro-organisms when peptides from the microbial proteins are bound to HLAs in the host cell surfaces, It is known that the more stable the binding of peptide to HLA is, the stronger the T cell response gets to remove more effectively the source of infection. Accordingly, if peptides (HLA binder) which can be bound stably to a certain HLA are found, those peptieds are utilized to the development of peptide vaccine to prevent infectious diseases or even to cancer. However, HLA is highly polymorphic so that HLA has a large number of alleles with some frequencies even in one population. Therefore, it is very inefficient to find the peptides stably bound to a number of HLAs by testing random possible peptides for all the various alleles frequent in the population. In order to solve this problem, computational methods have recently been developed to predict peptides which are stably bound to a certain HLA. These methods could markedly decrease the number of candidate peptides to be examined by biological experiments. Accordingly, this paper not only introduces a method of machine learning to predict peptides binding to an HLA, but also suggests a new prediction model so called 'knowledge-based genetic algorithm' that has never been tried for HLA binding peptide prediction. Although based on genetic algorithm (GA). it showed more enhanced performance than GA by incorporating expert knowledge in the process of the algorithm. Furthermore, it could extract rules predicting the binding peptide of the HLA alleles common in Koreans.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.3
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• pp.13-29
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• 2021

The purpose of this study was to analyze the spatial distribution and location factors of startups by generation (young and middle-aged) in Seoul. To this end, a research model was established that included factors of industry, population, and startup institutions by generation in 424 administrative districts using the Seoul Business Enterprise Survey(2018), which includes data on the age group of entrepreneurs. As an analysis method, descriptive statistics were conducted to confirm the frequency, average and standard deviation of startups by generation and major variables in the administrative districts of Seoul, and spatial distribution and characteristics of startups by generation were analyzed through global and local spatial autocorrelation analysis. In particular, the spatial distribution of startups in Seoul was confirmed in-depth by categorizing and analyzing startups by major industries. Afterwards, an appropriate spatial regression analysis model was selected through the Lagrange test, and based on this, the location factors affecting startups by generation were analyzed. The main results derived from the research results are as follows. First, there was a significant difference in the spatial distribution of young and middle-aged startups. The young people started to startups in the belt-shaped area that connects Seocho·Gangnam-Yongsan-Mapo-Gangseo, while middle-aged people were relatively active in the southeastern region represented by Seocho, Gangnam, Songpa, and Gangdong. Second, startups by generation in Seoul showed various spatial distributions according to the type of business. In the knowledge high-tech industries(ICT, professional services) in common, Seocho, Gangnam, Mapo, Guro, and Geumcheon were the centers, and the manufacturing industry was focused on existing clusters. On the other hand, in the case of the life service industry, young people were active in startups near universities and cultural centers, while middle-aged people were concentrated on new towns. Third, there was a difference in factors that influenced the startup location of each generation in Seoul. For young people, high-tech industries, universities, cultural capital, and densely populated areas were significant factors for startup, and for middle-aged people, professional service areas, low average age, and the level of concentration of start-up support institutions had a significant influence on startup. Also, these location factors had different influences for each industry. The implications suggested through the study are as follows. First, it is necessary to support systematic startups considering the characteristics of each region, industry, and generation in Seoul. As there are significant differences in startup regions and industries by generation, it is necessary to strengthen a customized startup support system that takes into account these regional and industrial characteristics. Second, in terms of research methods, a follow-up study is needed that comprehensively considers culture and finance at the large districts(Gu) level through data accumulation.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.131-137
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• 1999

전문가시스템 개발에 있어서 지식획득 병목현상(knowledge acquisition bottleneck)은 해결해야 할 큰 걸림돌중 하나이다. 지식획득을 위한 여러 과정을 단순화하고 자동화함으로 지식공학자의 작업을 최소화하면서 전문지식을 쉽고 빠르게 획득할 수 있도록 지식획득시스템을 설계·구현한다면 전문가시스템의 대중화는 지금보다 쉽게 이루어질 것이다. 본 연구는 지식 획득시스템 설계와 구현을 위한 연구의 일환으로 기계학습의 한 방법인 PIPPER(Repeated Incremental Pruning to Produce Error Reduction)를 이용하여 규칙을 생성하고 생성된 규칙을 JESS(Justification based Expert System Shell)에서 처리하도록 하였다. 규칙을 생성하기 위한 데이터는 Bohanec이 1997년도에 만든 자동차 평가 데이터베이스(Car Evaluation Database)를 사용하여 실험하였으며, 1700여 개의 레코드에서 약 40개의 규칙이 생성되었고, 생성된 규칙은 지식베이스의 정당성을 위반하지 않으면서 실행되었다.

• Journal of the Korean Society of Systems Engineering
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• v.8 no.1
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• pp.77-82
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• 2012

In Weapons acquisition process, if the requirements are not clear, it leads to confusion and conflict in business. In the development of next-generation weapons, to define and derive requirements has to start from decision of operational concept. It is difficult task and has many uncertainties. This paper has goal about development of knowledge acquisition process that derive military operational scenario-based requirements acquisition process and framework that classify and save the derived requirements for next project. That framework can generate new class and category, also suggest that verification of requirements. It help to derive and manage the requirements, and make it easy to grasp the requirements. Accordingly, it can help make military requirement plan and weapon acquisition process.

• Journal of Environmental Health Sciences
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• v.38 no.2
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• pp.83-94
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• 2012

The research on microbial fuel cells (MFCs) needs various knowledge of different fields such as electrochemistry, microbiology, environmental engineering, and material engineering. Although electrochemically active bacteria are very diverse, the performance of MFCs is affected primarily by the structure of the reactor system. Thus, the development in the system architecture is critical to lower internal resistance and increase power generation for commercialization. This paper summarizes the principles of MFCs and demonstrates the infinite potential of MFCs in various applications including wastewater treatment, biosensors, biohydrogen production, remote power sources, implantable medical devices, etc.

• Computational Structural Engineering
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• v.1 no.1
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• pp.95-102
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• 1988

I-BUILDS is the building design expert system conceptually modeled for synthesizing the conventional CAD programs (BUILDS; an integrated BUILding Desing System) and the knowledge base into an unified system. As a part of the efforts to build this system, this paper presents the conceptual model by which the data items generated by inference are transformed into a formatted input file to be used for several BUILDS subsystems, each of which is assigned to have various computational capabilities and to perform specialized task.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.2
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• pp.60-68
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• 1992

Fuzzy logic rule based controller has many desirable advantages, whih are simple to implement on the real time and need not the information of structure and dynamic characteristics of the system. Thus, nowadays, the scope of the application of the fuzzy logic controller becomes enlarged. But, if the controlled plant is a time-varying/nonlinear system, it is not easy to construct the fuzzy logic rules which need the knowledge of and expert. In this paper, an approach by which the logic control rules can be auto-generated using the genetic algorithm that is known to be very effective in the optimization problem will be proposed and the effectiveness of the proposed approach will be verified by computer simulation of the 2 d.o.f. planner robot.