• Journal of Korean Library and Information Science Society
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• v.52 no.1
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• pp.155-178
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• 2021

In the era of the 4th industrial revolution, public libraries need a strategy for promoting intelligent library services in order to actively respond to changes in the external environment such as artificial intelligence. Therefore, in this study, based on the concept of artificial intelligence and analysis of domestic and foreign artificial intelligence related trends, policies, and cases, we proposed the future direction of introduction and development of artificial intelligence services in the library. Currently, the library operates a reference information service that automatically provides answers through the introduction of artificial intelligence technologies such as deep learning and natural language processing, and develops a big data-based AI book recommendation and automatic book inspection system to increase business utilization and provide customized services for users. Has been provided. In the field of companies and industries, regardless of domestic and overseas, we are developing and servicing technologies based on autonomous driving using artificial intelligence, personal customization, etc., and providing optimal results by self-learning information using deep learning. It is developed in the form of an equation. Accordingly, in the future, libraries will utilize artificial intelligence to recommend personalized books based on the user's usage records, recommend reading and culture programs, and introduce real-time delivery services through transport methods such as autonomous drones and cars in the case of book delivery service. Service development should be promoted.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.891-898
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• 2022

Along with global interest, drones are expanding the base of utilization such as transportation of goods, forest protection, and safety management, and cluster flights are being applied in various fields such as military operations and environmental monitoring. Currently, specialized networks such as e-UM 5G for services in specific industries are being established in Korea. In this regard, drone systems are also moving to establish specialized networks to provide services that are fused with AI and autonomous flight. As drones converge with various services, various security threats in various environments are also subordinated, and in response, requirements and guidelines for drone security are being prepared in Korea. In this paper, we propose a technology method for peer identification and safe information provision between cluster flight drones by utilizing a cryptographic module equipped with wireless LAN and quantum entropy-based random number generator in a cluster flight system and a mobile communication network such as e-UM 5G.

• Journal of Korean Library and Information Science Society
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• v.29
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• pp.443-464
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• 1998

21세기를 맞이하여 대학도서관은 정보기술의 도입, 업무내용의 변화, 이용자의 요구변화등 급격하게 변화하는 새로운 환경에 직면해 있다. 본 연구는 한국의 대학도서관 조직구조의 현황에 대한 분석과 함께 다양한 조직이론들과 정보환경의 변화에 기초해서 도서관조직을 활성화시키기위한 개념적인 조직모델을 제시하고자 한다. 한국의 대학도서관은 거의 10년동안 법적인 제약과 조직내외의 환경적인 한계 등으로 인해 전산화시스템의 도입, 도서관부관장의 임명, 그리고 도서관과 컴퓨터 센터와의 통합시도와 같은 약간의 변화외에는 거의 변화가 없었다. 전형적인 한국의 대학도서관은 수서, 기술서비스, 열람과 참고봉사 부문으로 조직되었다. 여기서 수서 기능을 기술서비스의 부문으로 간주한다면, 본 연구의 대상인 대학도서관 114개관 중 95개관(82.5%)이 전통적인 도서관조직의 형태인 기술서비스와 공공서비스 부문으로 조직된 것으로 나타났다. 본 연구에서는 전통적인 도서관조직의 문제점들을 급복할 수 있는 21세기의 개념적인 대학도서관 조직모델로서, 네가지 부문 - 서비스 부문, 서비스지원 부문, 기술지원 부문, 그리고 통합·조정부문-을 대학도서관의 개념적인 기본 구성요소로써 제안하였다. 그러나 모든 도서관의 서비스나 업무과정에 대해 적합한 잉상적인 조직구조는 없으며, 조직의 재조직과정은 도서관의 형태와 목적, 업무과정에 따라 매우 다양하다. 따라서 도서관의 재조직화는 환경의 변화에 따라 끊임없는 과정이 될 것이며, 도서관조직의 성공은 이러한 변화에 적응할 수 있는 개인과 조직의 역량에 달려있다고 하겠다.대한 순서에 있어서 차이가 있다. 4) 도서관에 대한 태도에 있어서 두 집단은 상이한 입장을 보이고 있다. 학자들의 과반수는 중요 정보원으로서 자신의 개인장서를 활용하며, 도서관의 장서 및 그 조직방법에 대해서도 별로 만족하지를 못하고 있다. 반면에, 실무가들은 도서관에 대하여 비교적 만족하며 따라서 도서관에 대한 이용도도 높다. 5) 두 집단 모두 보조인을 적극적으로 활용하지 않으며 사서의 도움을 받는 경우도 극소수에 불과하다. 이러한 조사결과를 기초로 하여 볼 때 법률전문직을 둘러싼 정보환경을 개선하기 위하여는, 인쇄된 일차적 정보자료의 검색방법등을 개선하고, 나아가서는 법령과 판례정보를 위한 효율적인 시스템을 구축하며, 뿐만 아니라 이용자의 요구에 충분히 대처할 수 잇는 도서관으로 변화되는 것이다. 이와 함께 가장 중요한 것은 법과대학과 사법연수원에서 법학 연구방법에 관한 강좌를 개설하여 각종 법률정보원의 활용 내지 도서관 이용방법에 관하여 교육하는 것이다.글을 연구하고, 그 결과에 의존하여서 우리의 실제의 생활에 사용하는 $\boxDr$한국어사전$\boxUl$등을 만드는 과정에서, 어떤 의미에서 실험되었다고 말할 수가 있는 언어과학의 연구의 결과에 의존하여서 수행되는 철학적인 작업이다. 여기에서는 하나의 철학적인 연구의 시작으로 받아들여지는 이 의미분석의 문제를 반성하여 본다. 것이 필요하다고 사료된다.크기에 의존하며, 또한 이러한 영향은 $(Ti_{1-x}AI_{x})N$ 피막에 존재하는 AI의 함량이 높고, 초기에

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.313-315
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• 2019

Although Korea's fashion market has negative growth, it has been growing again since 2018. This phenomenon means that people are becoming more interested in fashion. As interest in fashion grows, people visit various community sites for reference to find a suitable coordination for themselves. Most community sites, however, are manually categorizing each garment. Not only do these tasks take a lot of time, but they also make it difficult to search for multiple clothing at the same time. In other words, I can't choose what I want at the same time, and if I choose what I want, I have to look at what the model is wearing and refer to it. The problem with this may not help because the coordination in which the model provided is worn is more likely to be the one that the user does not want. In this paper, when the image is uploaded to improve the problem, the clothing is analyzed with AI analysis model and automatically classified and stored. Therefore, not only can you search for one clothes in the existing way, but you can also search for multiple clothes at the same time. The service is expected to allow more people to easily find and refer to the code for themselves.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.94-104
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• 2022

As the audio content market grows due to the spread of the AI speaker market and the influence of connected cars, the demand for podcast service is increasing. Therefore, in this study, the behaviors of podcast users were identified and the user types were classified. In the background study, podcast usage motives and user types were studied, and they were referred to when making the questionnaire. In the survey, preferred audio content was identified according to the situation, and in the in-depth interview, the user type and insights were derived by identifying the audio service usage behavior. As a result of the survey, there was little difference between preferred content for single listening and multitasking, but the difference in preferred content according to time period was statistically significant. The three user types derived from the in-depth interview were divided into users who listen alone for the purpose of study, find and listen to useful information quickly while on the go, and multitask and listen to the light and comfortable contents. It is expected that the results of this study will be an important reference for designing an audio content platform to improve user experience.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.99-105
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• 2023

In the 4th industrial revolution, the field of criminal justice is paying attention to Legaltech using artificial intelligence to provide efficient legal services. This paper attempted to create a crime prediction model that can apply Recurrent Neural Network(RNN) to increase the potential for using legal technology in the domestic criminal justice field. To this end, the crime process was divided into pre, during, and post stages based on the criminal facts described in the judgment, utilizing crime script analysis techniques. In addition, at each time point, the method and evidence of crime were classified into objects, actions, and environments based on the sentence composition elements and the 8 principles of investigation. The case summary analysis framework derived from this study can contribute to establishing situational crime prevention strategies because it is easy to identify typical patterns of specific crime methods. Furthermore, the results of this study can be used as a useful reference for research on generating crime situation prediction data based on RNN models in future follow-up studies.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.41-48
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• 2023

In this paper, we propose an analysis of recent trends in the NFT (Non-Fungible Token) industry using topic modeling techniques, focusing on their universal application across various industrial fields. For this study, patent data was utilized to understand industry trends. We collected data on 371 domestic and 454 international NFT-related patents registered in the patent information search service KIPRIS from 2017, when the first NFT standard was introduced, to October 2023. In the preprocessing stage, stopwords and lemmas were removed, and only noun words were extracted. For the analysis, the top 50 words by frequency were listed, and their corresponding TF-IDF values were examined to derive key keywords of the industry trends. Next, Using the LDA algorithm, we identified four major latent topics within the patent data, both domestically and internationally. We analyzed these topics and presented our findings on NFT industry trends, underpinned by real-world industry cases. While previous review presented trends from an academic perspective using paper data, this study is significant as it provides practical trend information based on data rooted in field practice. It is expected to be a useful reference for professionals in the NFT industry for understanding market conditions and generating new items.

• Information Systems Review
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• v.25 no.4
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• pp.131-159
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• 2023

Recently, amidst the backdrop of the COVID-19 pandemic shifting towards an endemic phase, there has been a rise in discussions and debates about the future of the metaverse. Simultaneously, major metaverse platforms like Roblox have been launching services integrated with generative AI, and Apple's mixed reality hardware, Vision Pro, has been announced, creating new expectations for the metaverse. In this situation where the outlook for the metaverse is divided, it is crucial to diagnose the metaverse from an ecosystem perspective, examine its key ecological features, driving forces for development, and future possibilities for advancement. This study utilized Wang's (2021) Information Ecology Theory (IET) framework, which is representative of ecosystem research in the field of Information Systems (IS), to derive the Metaverse Industrial Ecosystem (MIE). The analysis revealed that the MIE consists of four main domains: Tech Landscape, Category Ecosystem, Metaverse Platform, and Product/Service Ecosystem. It was found that the MIE exhibits characteristics such as digital connectivity, the integration of real and virtual worlds, value creation capabilities, and value sharing (Web 3.0). Furthermore, the interactions among the domains within the MIE and the four characteristics of the ecosystem were identified as driving forces for the development of the MIE at an ecosystem level. Additionally, the development of the MIE at an ecosystem level was categorized into three distinct stages: Narrow Ecosystem, Expanded Ecosystem, and Everywhere Ecosystem. It is anticipated that future advancements in related technologies and industries, such as robotics, AI, and 6G, will promote the transition from the current Expanded Ecosystem level of the MIE to an Everywhere Ecosystem level, where the connection between the real and virtual worlds is pervasive. This study provides several implications. Firstly, it offers a foundational theory and analytical framework for ecosystem research, addressing a gap in previous metaverse studies. It also presents various research topics within the metaverse domain. Additionally, it establishes an academic foundation that integrates concept definition research and impact studies, which are key areas in metaverse research. Lastly, referring to the developmental stages and conditions proposed in this study, businesses and governments can explore future metaverse markets and related technologies. They can also consider diverse metaverse business strategies. These implications are expected to guide the exploration of the emerging metaverse market and facilitate the evaluation of various metaverse business strategies.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.11-11
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• 2020

18년 물관리일원화 이후 인프라와 사람 중심으로부터 자연과 인간의 조화를 위한 환경·생태계의 자연성 회복으로의 물관리 패러다임 전환이 빠르게 이루어지고 있으며, 대규모 국책사업이후의 하천 관리에 있어서도 기존의 이수, 치수, 환경이라는 단순한 기능적 구분을 벗어나 보다 근본적이고 장기적인 대국민 서비스로의 전환을 도모하고 있다. 또한, ICBAM 등으로 정의되는 4차산업혁명 기반 기술의 접목이 거의 대부분의 분야에서 이루어지고 있는 것을 실질적으로 체감하는 시기가 도래하였다. 그러나, 하천 및 수자원 관리분야에서의 기술은 근대 엔지니어링의 기초가 되는 수로 건설 등으로부터 시발되어 사실상 가장 앞선 과학적 진보의 토대를 갖추었으나 최근의 기술적 트렌드를 잘 추종하지 못하는 것처럼 비추어 지는 것이 사실이다. 주된 이유로서 기후변화라는 광범위하고 장기적인 입력요소를 가진 하천관리 시스템의 특성상 불확실성의 추정 및 즉각적인 응답이 어려운 부분이 분명히 존재하지만, 실질적으로 여전히 해소되지 않는 부분은 하천의 기초자료 수집에 대한 효율성과 신뢰도가 낮은 것이라고 하겠다. 또한, 유역으로부터 댐-다기능보-하천으로 이어지는 의사결정을 위한 다양한 형태의 자료로부터 적절한 정보를 수집하는 체계(거버넌스의 문제이자 기술적/재정적 한계)가 확립되지 않은 점도 고려해야 할 것이다. 본 연구에서는 인공지능을 활용한 하천의 유량 예측 등을 위해 필요한 수자원 기초데이터의 근원적인 수집 및 관리상의 문제점에 대해서 검토하고자 하였으며, ARIMA, Kalman Filtering, MA 및 복합기법을 통한 자료처리 기법을 적용하여 상황에 맞게 오차 및 불확실성의 저감을 위한 방안을 찾고자 하였다. 또한, 이용자 중심의 하천 관리에 근접한다고 볼 수 있는 스마트워터시티 개념에서의 바람직한 하천관리 기법에 대해서 논의하고, 관련하여 근자에 개발한 하천의 물리적 해석 도구들에 대해서 적용 사례를 검토한다. 마지막으로, 지식기반의 하천관리 의사결정 플랫폼 개발을 위해서 기존의 기계학습을 통한 자동화된 의사결정에 부가하여 전문가와 시스템이 상호작용을 통해서 AI를 학습시켜 결정한 사항을 전문가의 의사결정에 참고하는 MCRDR기법의 적용의 적용 가능성과 도입 방향에 대해서 논의하였다.