• Korean Institute of Interior Design Journal
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• v.19 no.6
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• pp.20-29
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• 2010

Art historians and critics have defined the style as common features appeared in a class of objects. Abstract common features from a set of objects have been used as a bench mark for date and location of original works. Commonalities in shapes are identified by relationships as well as physical properties from shape descriptions. This paper will focus on how the computer and human can recognize common shape properties from a class of shape objects to learn design knowledge. Shape representation using schema theory has been explored and possible inductive generalization from shape descriptions has been investigated. Also learned shape knowledge can be used. for new design process as design concept. Several design process such as parametric design, replacement design, analogy design etc. are used for these design processes. Works of Mario Botta and Louis Kahn are analyzed for explicitly clarifying the process from conceptual ideas to final designs. In this paper, theories of computer science, artificial intelligence, cognitive science and linguistics are employed as important bases.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.99-102
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• 2021

The article considers one of the areas of development of artificial intelligence where there is the development of computer intelligent systems capable of performing functions traditionally considered intelligent - language comprehension, inference, use of accumulated knowledge, learning, pattern recognition, as well as learn and explain their decisions. It is found that informational intellectual systems are promising in their development. The article is devoted to intelligent information systems and technologies in educational activities, ie issues of organization, design, development and application of systems designed for information processing, which are based on the use of artificial intelligence methods.

• Korean Journal of Artificial Intelligence
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• v.8 no.2
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• pp.23-28
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• 2020

Purpose: Today, we often hear complaints from customers: poor quality, poor service, expensive prices, etc. Customer complaints are an indication that the company's products and services do not meet customer requirements, which in turn causes customer complaints. An important content of corporate marketing practice is how to use the opportunity of handling customer complaints to win the trust of customers and gain a competitive advantage. According to the concept of marketing, the way for an enterprise to obtain profits is to continuously meet the needs of customers. However, with increasingly fierce market competition and the overall formation of a buyer's market, providing high-quality products and high-efficiency and high-level services have become the eternal theme of enterprises. Therefore, meeting the actual needs of customers and effectively handling customer complaints are issues that we must take seriously. Research design, data, and methodology: This article mainly analyzes the causes of customer complaints, proposes relevant solutions for different types of complaints, builds a customer complaint management system, improves the efficiency and ability of handling complaints, and provides more references and basis for enterprises to solve customer complaints. Conclusions: To further improve the quality of enterprise products and service standards, to help enterprises increase customer loyalty and satisfaction, and to enable enterprises to gain advantages in the increasingly competitive global market.

• Journal of Korea Multimedia Society
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• v.25 no.3
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• pp.510-518
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• 2022

This paper confirmed the technical reliability of mobile-based sarcopenia prediction and monitoring system. In implementing the developed system, we designed using only sensors built into a smartphone without a separate external device. The prediction system predicts the possibility of sarcopenia without visiting a hospital by performing the SARC-F survey, the 5-time chair stand test, and the rapid tapping test. The Monitoring system tracks and analyzes the average walking speed in daily life to quickly detect the risk of sarcopenia. Through this, it is possible to rapid detection of undiagnosed risk of undiagnosed sarcopenia and initiate appropriate medical treatment. Through prediction and monitoring system, the user may predict and manage sarcopenia, and the developed system can have a positive effect on reducing medical demand and reducing medical costs. In addition, collected data is useful for the patient-doctor communication. Furthermore, the collected data can be used for learning data of artificial intelligence, contributing to medical artificial intelligence and e-health industry.

• 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.

• Journal of Christian Education in Korea
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• v.66
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• pp.309-341
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• 2021

The purpose of this study is to develop an intelligent learning platform model for faith education in preparation for the post-corona era. This study reviewed artificial intelligence algorithms, research on learning platform development, and prior research related to faith education. The draft of the intelligent learning platform design model was developed by synthesizing previous studies. The developed draft model was validated by a Delphi survey targeting 5 experts. The content validity of the developed draft model was all 1. This is the validation of the draft model. Three revised opinions of experts were presented on the model. And the model was revised to reflect the opinions of experts. The modified final model consisted of three areas: learning materials, learning activities, learning data, and artificial intelligence. Each area is composed of 9 elements of curriculum, learning content additional learning resources, learner type, learning behavior, evaluation behavior, learner characteristic data, learning activity data, artificial intelligence data, and learning analysis. Each component has 29 sub-elements. In addition, 14 learning floors were formed. The biggest implication of this study is the first development of a basic model of an intelligent learning platform for faith education.

• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.1-14
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• 2022

This study tried to suggest crisis management compliance to prevent personal information infringement accidents that may occur in the process because the data including personal information is being processed in the artificial intelligence (AI) service process. To this end, first, the AI service provision process is divided into 3 processes such as service planning/data design and collection process, data pre-processing and purification process, and algorithm development and utilization process. And 3 processes are subdivided into 9 stages following to personal information processing stages to infringe personal information. All processes were investigated with literature and experts' Delphi. Second, the investigated personal information infringement factors were selected through FGI, Delphi, etc. for experts. Third, a survey was conducted with experts on the severity and possibility of each personal information infringement factor, and the validity and adequacy of the 94 responses were verified. Fourth, to present appropriate risk management compliance for personal information infringement factors in AI services, a method for calculating the risk level of personal information infringement is prepared by utilizing the asset value of personal information, personal information infringement factors, and the possibility of infringement accidents. Through this, the countermeasures for personal information infringement incidents were suggested according to the scored risk level.

• 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 Korea Game Society
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• v.8 no.3
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• pp.77-85
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• 2008

In the current online game field, many studies on the realization of AI have been carried out. It is, however, very hard to apply smart AI to the online games due to the limited use of resources. The Fuzzy extension method this thesis presents is suitable to online games because it causes less loads in the system and makes it possible to realize more human-like AI. To realize this kind of AI, this paper suggests AI system design methods suitable to fuzzy-based online game and presents practical plans to apply them through the produced demos.

• Archives of Metallurgy and Materials
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• v.67 no.4
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• pp.1459-1463
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• 2022

The soft magnetic properties of Fe-based amorphous alloys can be controlled by their compositions through alloy design. Experimental data on these alloys show some discrepancy, however, with predicted values. For further improvement of the soft magnetic properties, machine learning processes such as random forest regression, k-nearest neighbors regression and support vector regression can be helpful to optimize the composition. In this study, the random forest regression method was used to find the optimum compositions of Fe-Si-B-C alloys. As a result, the lowest coercivity was observed in Fe_80.5Si_3.63B_13.54C_2.33 at.% and the highest saturation magnetization was obtained Fe_81.83Si_3.63B_12.63C_1.91 at.% with R² values of 0.74 and 0.878, respectively.