• 한국정보교육학회:학술대회논문집
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• 2007.08a
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• pp.300-305
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• 2007

발견학습이란 학습자에게 가르쳐야 할 내용을 최종적인 형태로 제공하는 것이 아니라 그 최종 형태를 학습자 스스로 조직하도록 요구되는 상황에서 일어나는 학습이라 한다. 지식과 정보가 끊임없이 창출되고 있는 현실에서 그 많은 지식과 정보를 모두 학습한다는 것은 불가능하며 무모한 일에 지나지 않는다. 그러므로 발견학습이 그 무엇보다도 중요하다고 할 수 있겠다. 그러나 교육 현장에서는 단위 시간의 부족과 발견학습에 적용시킬 자료의 부족함으로 인해 학습자에게 가르쳐야 할 내용을 최종적인 형태(개념 및 원리)를 교사가 전통적인 방법으로 가르치고 있다. 본 연구는 위의 문제점을 해결하고자 플래시를 활용한 자료 제시와 웹을 통해 교사와 상호작용할 수 있는 발견학습모형을 적용한 웹코스웨어를 설계하고자 한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.296-301
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• 1998

The Rough Set theory suggested by Pawlak in 1982 has been useful in AI, machine learning, knowledge acquisition, knowledge discovery from databases, expert system, inductive reasoning. etc. The main advantages of rough set are that it does not need any preliminary or additional information about data and reduce the superfluous informations. but it is a significant disadvantage in the real application that the inference result form is not the real control value but the divided disjoint interval attribute. In order to overcome this difficulty, we will propose approach in which Rough set theory and Neuro-fuzzy fusion are combined to obtain the optimal rule base from lots of input/output datum. These results are applied to the rule construction for infering the temperatures of refrigerator's specified points.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.119-124
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• 2004

Real data as web log file tend to be incomplete. But we have to find useful knowledge from these for optimal decision. In web log data, many useful things which are hyperlink information and web usages of connected users may be found. The size of web data is too huge to use for effective knowledge discovery. To make matters worse, they are very sparse. We overcome this sparse problem using Markov Chain Monte Carlo method as multiple imputations. This missing value imputation changes spare web data to complete. Our study may be a useful tool for discovering knowledge from data set with sparseness. The more sparseness of data in increased, the better performance of MCMC imputation is good. We verified our work by experiments using UCI machine learning repository data.

• Journal of Astronomy and Space Sciences
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• v.34 no.2
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• pp.153-159
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• 2017

The Standard Model of particle physics was established after discovery of the Higgs boson. However, little is known about dark matter, which has mass and constitutes approximately five times the number of standard model particles in space. The cross-section of dark matter is much smaller than that of the existing Standard Model, and the range of the predicted mass is wide, from a few eV to several PeV. Therefore, massive amounts of astronomical, accelerator, and simulation data are required to study dark matter, and efficient processing of these data is vital. Computational science, which can combine experiments, theory, and simulation, is thus necessary for dark matter research. A computational science and deep learning-based dark matter research platform is suggested for enhanced coverage and sharing of data. Such an approach can efficiently add to our existing knowledge on the mystery of dark matter.

• Research in Mathematical Education
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• v.13 no.1
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• pp.1-4
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• 2009

We are considering the discovery and the promotion of the talent from the viewpoint of education of talented children. The education that develops the talent is from "Individual needs for all children." Computer Algebra System (CAS) can be used as a new possibility in the education that develops the talent. We will need to take advantage of the research results from cognitive science. In order to fully utilize CASs in education, teaching methods that are based on cognitive science will be needed, and these are clearly different from those used in paper and pencil teaching.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.3
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• pp.11-23
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• 2011

Recently, Open APIs are getting attention with the advent of Web 2.0. Open APIs are used to combine services and generate new services by Mashup. However, the growing number of available Open APIs raises a challenging issue how to locate the desired APIs. We automatically build ontologies from WSDL, WADL, HTML, and their underlying semantics. The key ingredient of our method is a technique that clusters input/output parameters in the collection of API methods into semantically meaningful concepts, and captures the hierarchical relationships between the terms contained in a parameter. These semantic ontologies allow search engines to support a similarity search for Open APIs based on various protocols such as SOAP, REST, JavaScript, and XML-RPC, and significantly improve the quality of APIs matching by the clustering and hierarchical relationships mechanism.

• 한국정보교육학회:학술대회논문집
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• 2007.01a
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• pp.209-216
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• 2007

고도의 지식정보사회 속에서 논리적 사고력과 창의력, 문제해결력을 길러주는 프로그래밍 교육의 필요성은 더욱 강조되고 있다. 이에 본 연구에서는 초등학생들에게 적합한 교육용 프로그래밍 언어인 JavaMAL을 활용하여, 프로그래밍의 함수개념 형성을 위한 학습모형을 구안 적용하고 일반화 가능성을 탐색하고자 하였다. 먼저 기초적인 프로그래밍 요소 중 함수개념과 관련된 학습요소를 추출하여 차시별 지도계획을 수립하였다. 또한, 프로그래밍의 함수가 수학적 함수의 모방이라는 것에 착안하여 수학의 '규칙성과 함수'지도 단계를 LOGO의 문제해결력 수업모형인 안내된 발견식 교수법(guided discovery teaching method)에 강화한 후, 인터넷을 활용한 문제해결 수업모형을 구안하였다. 기본명령어와 변수개념을 이미 익힌 계발활동 부서 6학년 아동들을 지도 대상으로 한 달간 웹 기반 JavaMAL 환경에서 학습할 수 있도록 하였으며, 게시판 활동 및 활동지를 통해 함수개념 형성 여부를 측정하였다.

• Journal of Information Technology Applications and Management
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• v.27 no.5
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• pp.35-47
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• 2020

Global waste has become a global issue and we can see the new trend of discovery businesses established to focus on solving the waste problem using new renewable energy technology and the circular economy business model. This paper aims to study factors that impact green entrepreneurship in Thailand, such as environmental concern, organizational environment, founder demographics, education background, entrepreneurship awareness, as well as external factors of a business. The study analyzes the data from three qualitative in-depth interviews with green entrepreneur founders who started the businesses in polymer up-cycling, waste management, and renewable energy. The study finds overseas educational background to be one of the key main drivers for the entrepreneurial courage to decide to pursue a new business venture. By having the exposure toward the different culture, three entrepreneurs hands-on experiential learning through three key drivers who are composed of the can-do attitude, the willingness to be self-employed, and the way of seeking for the freedom to express their passions.

• Journal of the Korean Chemical Society
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• v.62 no.3
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• pp.187-190
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• 2018

A three-component coupling reaction of phenylacetylene, p-toluenesulfonyl azide, and water through copper catalysis is described to provide knowledge of spectroscopy and catalytic reactions and to introduce current research topics in organic chemistry for second-year undergraduate students. In the presence of stoichiometric amounts of phenylacetylene, p-toluenesulfonyl azide, and triethylamine, the reaction was performed with 4 mol% CuCl in water as the sole solvent and was completed in 1.5 h. A practical purification method and recrystallization of the crude reaction mixture resulted in the rapid isolation of the desired product with yields of 42~65%. Students characterized 4-methyl-N-(phenylacetyl)benzenesulfonamide by using melting-point determination, infrared spectroscopy, and nuclear magnetic resonance (NMR) spectroscopy. This experimental procedure and spectroscopic data analysis will serve as a platform for students to apply classroom knowledge in practical state-of-the-art research.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.894-897
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• 2014

The speed of processes and the extremely large amount of data to be used in Intelligence Transportations System (ITS) cannot be handling by humans without considerable automation. However, it is difficult to develop software with conventional fixed algorithms (hard-wired logic on decision making level) for effectively manipulate dynamically evolving real time transportation environment. This situation can be resolved by applying methods of artificial intelligence and data mining that provide flexibility and learning capability. This paper presents a brief introduction of data mining and artificial intelligence (AI) applications in Intelligence Transportation System (ITS), analyzing the prospects of enhancing the capabilities by means of knowledge discovery and accumulating intelligence to support in decision making.