• Smart Media Journal
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• v.10 no.2
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• pp.70-75
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• 2021

Grouping and classifying similar designs in design increase efficiency in terms of management and provide convenience in terms of use. Using artificial intelligence algorithms, this study attempted to classify textile designs into four categories: dots, flower patterns, stripes, and geometry. In particular, we explored whether it is possible to find and explain the regions of interest underlying classification from the perspective of artificial intelligence. We randomly extracted a total of 4,536 designs at a ratio of 8:2, comprising 3,629 for training and 907 for testing. The models used in the classification were VGG-16 and ResNet-34, both of which showed excellent classification performance with precision on flower pattern designs of 0.79%, 0.89% and recall of 0.95% and 0.38%. Analysis using the Local Interpretable Model-agnostic Explanation (LIME) technique has shown that geometry and flower-patterned designs derived shapes and petals from the region of interest on which classification was based.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.182-184
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• 2022

As artificial intelligence (AI) is emphasized in elementary and secondary school education, interest in AI-applied class activities is increasing. Since AI is taught across various subjects in schools, teachers must plan lessons based on the principles of convergence education. In this paper, the concept of convergence education and matters to be considered for productive class activities were reviewed. Then, considerations for designing AI classes in schools are presented in the following aspects: characteristics of AI education in schools; educational goals for each school level in the general guidelines of the national curriculum; resources to be referenced when composing class content; perspectives on AI-applied software; and anticipated instructional procedures. As a suggestion, the following is presented. First, it is necessary to derive competencies that can be cultivated by AI education in school. Second, it is necessary to specify the design elements and procedures of AI classes based on the subject characteristics.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.329-332
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• 2022

This study aims to identify problems with existing e-learning content and non-face-to-face class methods, improve students' concentration, improve class achievement and educational effectiveness, and propose an artificial intelligence class system design using a web server. By using the function of face and eye tracking using OpenCV to identify attendance and concentration, and by inducing feedback through voice or message to questions asked by the instructor in the middle of class, learners relieve boredom caused by online classes and test by runner If the score is not reached, we propose an artificial intelligence education program system design that can bridge the academic gap and improve academic achievement by providing educational materials and videos for the wrong problem.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.280-283
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• 2022

This study aims to identify problems with existing e-learning content and non-face-to-face class methods, improve students' concentration, improve class achievement and educational effectiveness, and propose an artificial intelligence class system design using a web server. By using the function of face and eye tracking using OpenCV to identify attendance and concentration, and by inducing feedback through voice or message to questions asked by the instructor in the middle of class, learners relieve boredom caused by online classes and test by runner If the score is not reached, we propose an artificial intelligence education program system design that can bridge the academic gap and improve academic achievement by providing educational materials and videos for the wrong problem.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.6
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• pp.187-196
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• 2001

In this study, by using the natural language processing of the field of artificial intelligence, automated index was performed. And then, the Natural Language Processing Interface for knowledge representation(NALPI) has been developed. Furthermore, the DEsign KnOwledge DataBase(DEKODB) has been also developed, which is designed to interlock the knowledge base. The DEKODB processes both the documented design-data, like a concrete standard specification, and the design knowledge from an expert. The DEKODB is also simulates the design space of structures accordance with the production rule, and thus it is determined that DEKODB can be used as a engine to retrieve new knowledge and to implement knowledge base that is necessary to the development of automatic design system. The application field of the system, which has been developed in this study, can be expanded by supplement of the design knowledge at DEKODB and developing dictionaries for foreign languages. Furthermore, the perfect automation at the data accumulation and development of the automatic rule generator should benefit the unified design automation.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.237-238
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• 2023

Urbanization and the increase in building scale have amplified the complexity of M.E.P design. Traditional design methods face limitations when considering intricate pathways and variables, leading to an emergent need for research in automated design. Initial algorithmic approaches encountered challenges in addressing complex architectural structures and the diversity of M.E.P types. However, with the launch of OpenAI's ChatGPT-3.5 beta version in 2022, new opportunities in the automated design sector were unlocked. ChatGPT, based on the Large Language Model (LLM), has the capability to deeply comprehend the logical structures and meanings within training data. This study analyzed the potential application and latent value of LLMs in M.E.P design. Ultimately, the implementation of LLM in M.E.P design will make genuine automated design feasible, which is anticipated to drive advancements across designs in the construction sector.

• Journal of the Korean Geotechnical Society
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• v.21 no.9
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• pp.25-34
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• 2005

This paper proposes a selection methodology composed of neural network (NN) and genetic algorithm (GA) to design optimal NN structure. We combine the characteristics of GA and NN to reduce the computational complexity of artificial intelligence applications and increase the precision of NN' prediction in the design of NN structure. Genetic selection approach of design parameters of NN is introduced to obtain optimal NN structure. Analyzed results for geotechnical problems are given to evaluate the performance of the proposed hybrid methodology.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 1995.10a
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• pp.85-93
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• 1995

Recently, the development of Artificial Intelligence(AI) and Expert System has caused some interest in the possibility of developing an intelligent CAD system. However, these development and possibility are in an extremenly early stage for Architectural design. In this study, the design process of Residence being recognized as a Constraints-satisfied model, a part of these constraints used in the Architectural design of Residence are being systematized and sorted by the design process. Those regulations and planning items to be considered in the basic planning stage are being systematized as a knowledge base system. The possibility of this knowledge-based system as an effective design tool is studied and an integrated form of Architectural design system is proposed.

• The Journal of Information Systems
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• v.2
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• pp.194-206
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• 1993

Intelligent remote learning system is a system that incorporate communication technology and others : a database engine, an intelligent tutorial system. Learners can study by themselves through the intelligent tutorial system. The existence of a communication, database and artificial intelligence enhance the capability of IRLS. According to Parsaye, an intelligent databases should have the following features : 1) Knowledge discovery. 2) Data integrity and quality control. 3) Hypermedia management. 4) Data presentation and display. 5) Decision support and scenario analysis. 6) Data format management. 7) Intelligent system design tools. I hope that this research of framework for IRLS paves for the future research. As mentioned in the above, the future work will include an intelligent database, self-learning mechanism using neural network.

• Journal of Information Technology Applications and Management
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• v.10 no.4
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• pp.119-133
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• 2003

맞춤형 금융상품 설계시스템(Financial Product Factory System)이란 온라인으로 접근하는 고객의 요구사항을 고려하여 고객에게 가장 적합한 금융상품을 실시간으로 설계하여 제공하는 시스템이다. 최근 들어 인터넷 뱅킹 고객의 수가 급증함에 따라 맞춤형 금융상품 설계시스템의 필요성이 대두되고 있으나, 이러한 시스템의 정의나 성격, 필요 기능, 구축 방안에 대한 연구가 되어 있지 않은 실정이다. 본 연구에서는 맞춤형 금융상품 설계시스템의 정의를 내리고, 이 시스템이 갖추어야 할 요구사항을 시스템과 서비스 측면에서 분석한 후, 이 요구사항을 반영하는 시스템의 아키텍처를 제안ㆍ구현한다