• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.165-168
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• 2005

최근 온라인 게임 시장이 커지면서 게임을 위한 필수요소로 동시 접속자를 지속적으로 확보/유지해야 하는 문제가 이슈화 되고 있다. 온라인 게임을 즐기는 유저 수는 정해져 있는 반면, 게임 컨텐츠 수는 지속적으로 증가되고 있는 상황에서 온라인 게임 시장은 전형적인 레드오션[1]의 시장형태로 변모되어 가고 있다 이러한 문제를 보완하기 위한 대안으로서 본 논문에서는 에이전트 시스템을 이용한 동시 접속자를 생성, 유지할 수 있는 솔루션에 대해서 제시한다. 이를 통해 경쟁력 있는 게임 컨텐츠가 시장 진입을 보다 원활하게 할 수 있을 것으로 기대하며, 아울러 게임 초반의 스트레스 테스트를 위한 툴로써의 활용, 게임의 라이프 사이클의 증대, 경쟁력 강화로 이어질 수 있을 것으로 기대된다

• Journal of The Korean Association For Science Education
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• v.30 no.4
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• pp.487-497
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• 2010

The purpose of this study was to investigate how a teaching approach influences student's ability of classification at the brain level. Twenty four healthy and right-handed college students participated in this study, which investigated a brain plasticity associated with category-generation and -understanding in classification learning. The participants were divided into one of two groups, one each for category-generation and -understanding learning programs, which were composed of twelve topics taught over a twelve-week period. To measure the change in student competence and brain activations, a paper and pencil test and an fMRI scanning session were administered before and after the training programs. Unlike the understanding group, the generation group showed significant changes in classification ability quotients and learning-related brain activations (cerebral cortex and basal ganglia were increased and prefrontal cortex and parahippocampal gyrus were decreased). Nevertheless, the understanding group showed an increased activation in the cerebral cortex and parahippocampal gyrus and a decreased activation in the right prefrontal cortex and cerebellum. Therefore, it can be concluded that teaching styles could influence students' brain activation patterns and classification ability. The results might also be used to develop a brain-compatible science education curriculum.

• The Journal of Society for e-Business Studies
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• v.25 no.2
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• pp.15-27
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• 2020

This study starts with the idea that the process of creating a Gantt Chart for schedule planning is similar to Tetris game with only a straight line. In Tetris games, the X axis is M machines and the Y axis is time. It is assumed that all types of orders can be worked without separation in all machines, but if the types of orders are different, setup cost will be incurred without delay. In this study, the game described above was named Gantris and the game environment was implemented. The AI-scheduling table through in-depth reinforcement learning compares the real-time scheduling table with the human-made game schedule. In the comparative study, the learning environment was studied in single order list learning environment and random order list learning environment. The two systems to be compared in this study are four machines (Machine)-two types of system (4M2T) and ten machines-six types of system (10M6T). As a performance indicator of the generated schedule, a weighted sum of setup cost, makespan and idle time in processing 100 orders were scheduled. As a result of the comparative study, in 4M2T system, regardless of the learning environment, the learned system generated schedule plan with better performance index than the experimenter. In the case of 10M6T system, the AI system generated a schedule of better performance indicators than the experimenter in a single learning environment, but showed a bad performance index than the experimenter in random learning environment. However, in comparing the number of job changes, the learning system showed better results than those of the 4M2T and 10M6T, showing excellent scheduling performance.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.967-971
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• 2023

Recently, a variety of AI-based platform services are available, and one of them is ChatGPT that processes a large quantity of data in the natural language and generates an answer after self-learning. ChatGPT can perform various tasks including software programming in the IT sector. Particularly, it may help generate a simple program and correct errors using C Language, which is a major programming language. Accordingly, it is expected that ChatGPT is capable of effectively using Verilog HDL, which is a hardware language created in C Language. Verilog HDL synthesis, however, is to generate imperative sentences in a logical circuit form and thus it needs to be verified whether the products are executed properly. In this paper, we aim to select small-scale logical circuits for ease of experimentation and to verify the results of circuits generated by ChatGPT and human-designed circuits. As to experimental environments, Xilinx ISE 14.7 was used for module modeling, and the xc3s1000 FPGA chip was used for module embodiment. Comparative analysis was performed on the use area and processing time of FPGA to compare the performance of ChatGPT products and Verilog HDL products.

• Journal of Christian Education in Korea
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• v.78
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• pp.57-85
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• 2024

Purpose of the study: In order to utilize artificial intelligence-generated AI in educational ministry, this study analyzes the concept of artificial intelligence and generative AI and the educational theological aspects of educational ministry to find ways to efficiently utilize artificial intelligence ChatGPT in educational ministry. Contents and methods of the study: The contents of this study are. First, the contents of this study were analyzed by dividing the concepts of artificial intelligence and generative AI into the concept of artificial intelligence, types of artificial intelligence, and generative language model AI ChatGPT. Second, the educational theological analysis of educational ministry was divided into the concept of educational ministry, the goals of educational ministry, the content of educational ministry, and the direction of educational ministry in the era of artificial intelligence. Third, the plan to use artificial intelligence ChatGPT in educational ministry is to provide tools for writing sermon manuscripts, preparation tools for worship and prayer, and church education, focusing on the five functions of the early church community. It was analyzed by dividing it into tools for teaching, tools for teaching materials for believers, and tools for serving and volunteering. Conclusion and Recommendation: The conclusion of this study is that, first, when writing sermon manuscripts through artificial intelligence ChatGPT, high-quality sermon manuscripts can be written through the preacher's spirituality, faith, and insight. Second, through artificial intelligence ChatGPT, you can efficiently design and plan worship services and prepare services that serve the congregation objectively through various scenarios. Third, by using artificial intelligence ChatGPT in church education, it can be used while maintaining a complementary relationship with teachers through collaboration with human and artificial intelligence teachers. Fourth, through artificial intelligence ChatGPT, we provide a program that allows members of the church community to share spiritual fellowship, a plan to meet the needs of church members and strengthen interdependence, and an attitude of actively welcoming new people and respecting diversity. It provides useful materials that can play an important role in giving, loving, serving, and growing together in the love of Christ. Lastly, through artificial intelligence ChatGPT, we are seeking ways to provide various information about volunteer activities, learning support for children and youth in the community, mentoring-related programs, and playing a leading role in forming a village community in the local community.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.33-38
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• 2019

In this paper, we propose a new blockchain technology that could comply with GDPR. The proposed model can prevent illegal access by controlling access to the personal information according to a access policy. For example, it can control access to the information on a role-basis and information validation period. The core mechanism of the proposed model is to encrypt the personal information with public key which is associated with users attributes policy, and then decrypt it with a private key and users attributes based on a Attribute-based Encryption scheme. It can reduce a trusted third-part risk by replacing it with a number of nodes selected from the blockchain. And also the private key is generated in the form of one-time token to improve key management efficiency. We proved the feasibility by simulating the proposed model using the chaincode of the Hyperledger Fabric and evaluate the security.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.487-492
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• 2022

Universities are looking for various methods to enhance educational competence level suitable for the rapidly changing social environment. This study suggests a method to promote academic and educational achievements by reducing drop-out rate from their majors through implementation of pre-survey of satisfaction that revised and complemented survey items. To supplement the CQI method implemented after a general satisfaction survey, a pre-survey of satisfaction was carried out. To consolidate students' competences, this study made prediction and analysis of data with more importance possible using the Random Forest of the machine learning technique that can be applied to AI Medici platform, whose design is underway. By pre-processing the pre-survey of satisfaction, the students information enrolled in classes were defined as an explanatory variable, and they were classified, and a model was created and learning was conducted. For the experimental environment, the algorithms and sklearn library related in Jupyter notebook 3.7.7, Python 3.7 were used together. This study carried out a comparative analysis of change in educational satisfaction survey, carried out after classes, and trends in the drop-out students by reflecting the results of the suggested method in the classes.

• Industry Promotion Research
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• v.8 no.2
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• pp.21-27
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• 2023

This study studies the policies and use cases of the government and the financial sector for artificial intelligence, and the future policy tasks of the financial sector. want to derive According to Gartner, noteworthy technologies leading the financial industry in 2022 include 'generative AI', 'autonomous system', 'Privacy Enhanced Computation (PEC) was selected. The financial sector is developing new technologies such as artificial intelligence, big data, and blockchain. Developments are spurring innovation in the financial sector. Data loss due to the spread of telecommuting after the corona pandemic As interests in sharing and personal information protection increase, companies are expected to change in new digital technologies. Global financial companies also utilize new digital technology to develop products or manage and operate existing businesses. I n order to promote process innovation, I T expenses are being expanded. The financial sector utilizes new digital technology to prevent money laundering, improve work efficiency, and strengthen personal information protection. are applying In the era of Big Blur, where the boundaries between industries are disappearing, the competitive edge in the challenge of new entrants In order to preoccupy the market, financial institutions must actively utilize new technologies in their work.

• Journal of Life Science
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• v.33 no.5
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• pp.397-405
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• 2023

Although glutathione (GSH) has been shown to play an important role in the prevention of oxidative damage as an antioxidant, studies on immune regulation by it have not been properly conducted. In this study, we investigated whether luthione^®, a reduced GSH, has an immune enhancing effect in murine macrophage RAW 264.7 cells. The results of flow cytometry and immunofluorescence experiments indicated that luthione increased phagocytic activity, a representative function of macrophages, compared to the control cells. According to the results of the cytokine array, the expression of interleukin (IL)-5, IL-1β, and IL-27 was significantly increased in the luthione-treated cells. Luthione also enhanced the production of tumor necrosis factor-α and IL-1β through increased expression of their proteins, and increased release of the immune mediators such as nitric oxide (NO) and prostaglandin E₂ was associated with increased expression of inducible NO synthase and cyclooxygenase-2. In addition, the expression of cluster of differentiation 86, an M1 macrophage marker, was dramatically enhanced in RAW 264.7 cells treated with luthione. Furthermore, as a result of heat map analysis, we found that cytokine signaling 1/3-mediated signal transducer and activator of transcription/Janus tyrosine kinase signaling pathway was involved in the immunomodulatory effect by luthione. In conclusion, our data suggested that luthione could act as a molecular regulator in M1 macrophage polarization and enhance immune capacity by promoting macrophage phagocytic function.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2001.05a
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• pp.105-106
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• 2001

일반적인 정보 검색은 색인어를 통해 이루어지는데 이런 경우 사용자는 정보를 검색하기 위해 데이터베이스에 저장된 정보들이 가지고 있는 색인어를 정확하게 입력해야 한다. 그러나 일반 사용자가 색인어를 정확하게 입력하기는 어렵고, 특히 찾고자 하는 분야가 전문 분야에서 사용되는 용어일 때는 더욱 그러하다. 이럴 때 시소러스와 같은 지식구조를 이용해서 색인어를 탐색하여 검색의 효율을 높일 수 있다. 최근 들어 정보기술 분야의 연구가 활발함에 따라 정보자로의 생산이 급격히 증가하고 이를 관련 주제 분야의 연구정보로 활용하는 경우가 증가하고 있다. 따라서 IT 분야의 정보를 관리할 수 있는 시스템의 개발이 시급하다. 또한 IT 분야와 같은 전문분야일 때 검색 시스템에서 사용할 용어의 관리에 대한 연구의 필요성이 증가하고 있다. 본 논문에서는 IT분야의 정보를 검색할 수 있는 IT 업체정보검색시스템에서 정보 검색시에 생기는 용어간의 불일치 문제를 해결하고, 각 용어들간의 계층 관계를 나타내어 정보 검색시 검색어의 확장을 도울 수 있는 용어 관리 시스템의 구조를 제안하고 그에 대한 검색 알고리즘을 제시한다. 제안된 구조는 사용자의 검색어에 대한 동의어 관계나 상위어, 하위어 등의 계층 관계를 파악하여 검색의 범위에 추가함으로써 검색 효율을 높일 수 있다. 또한 새로운 용어의 생성이나 삭제와 같은 연산이 발생했을 때 시스템을 동적으로 확장할 수 있도록 구현하였다. 제안된 시스템은 단어간의 계층 구조를 효율적으로 검색하기 위하여 객체-관계형 데이터베이스를 사용하였다. 또한 메모리 상주 DBMS를 사용하여 많은 사용자들이 동시에 접근하는 환경에서도 빠른 검색 성능을 유지할 수 있도록 하였다. 제시된 방법은 정보기술 분야뿐만 아니라 다른 전문용어 분야의 연구로도 그 범위를 확장 할 수 있다.자기자본비용의 조합인 기회자본비용으로 할인함으로써 현재의 기업가치를 구할 수 있기 때문이다. 이처럼 기업이 영업활동이나 투자활동을 통해 현금을 창출하고 소비하는 경향은 해당 비즈니스 모델의 성격을 규정하는 자료도로 이용될 수 있다. 또한 최근 인터넷기업들의 부도가 발생하고 있는데, 기업의 부실원인이 어떤 것이든 사회전체의 생산력의 감소, 실업의 증가, 채권자 및 주주의 부의 감소, 심리적 불안으로 인한 경제활동의 위축, 기업 노하우의 소멸, 대외적 신용도의 하락 등과 같은 사회적·경제적 파급효과는 대단히 크다. 이상과 같은 기업부실의 효과를 고려할 때 부실기업을 미리 예측하는 일종의 조기경보장치를 갖는다는 것은 중요한 일이다. 현금흐름정보를 이용하여 기업의 부실을 예측하면 기업의 부실징후를 파악하는데 그치지 않고 부실의 원인을 파악하고 이에 대한 대응 전략을 수립하며 그 결과를 측정하는데 활용될 수도 있다. 따라서 본 연구에서는 기업의 부도예측 정보 중 현금흐름정보를 통하여 '인터넷기업의 미래 현금흐름측정, 부도예측신호효과, 부실원인파악, 비즈니스 모델의 성격규정 등을 할 수 있는가'를 검증하려고 한다. 협력체계 확립, ${\circled}3$ 전문인력 확보 및 인력구성 조정, 그리고 ${\circled}4$ 방문보건사업의 강화 등이다., 대사(代謝)와 관계(關係)있음을 시사(示唆)해 주고 있다.ble nutrient (TDN) was highest in booting stage (59.7%); however no significant difference was found among other stages. The concentrations of Ca and P were not different among mature stages. Accordi