• 한국인터넷방송통신학회논문지
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• 제23권1호
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• pp.7-13
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• 2023

본 연구의 목적은 인공지능 서비스 영향성 평가를 위한 분석 기준에 대해 조사하는 것이다. 본 연구 결과는 다음과 같이 조사 되었다. 인공지능 평가 대상은 인공지능 서비스와 인공지능 기술인 2가지 영역으로 분류하였다. 인공지능 서비스 평가는 영향력, 지속가능성, 효율성, 효과성, 적절성 등을 도입하여 평가할 수 있다. 인공지능 서비스의 시간적 측면평가는 사전평가와 사후 평가로 나누어 정리 할 수 있다. 사전평가는 사전 서비스를 위해 개발하고 설계할 때 검토해야 하는 사항에 대해 제시하고 있다. 인공지능 서비스 영역 평가는 공공서비스와 민간서비스 및 혼합형태로 분류 될 수 있다. 인공지능 서비스 영향성 평가 분류 기준으로 수직적 또는 수평적 구조 형태로 분류가 가능하다. 인공지능 서비스 적용(활용) 기준은 규범적 측면과 규제적 측면으로 나누어 볼 수 있다. 인공지능 서비스 목적 측면에서 영향평가 또는 과정 평가로 분류될 수 있다. 인공지능 서비스 목적 측면에서 바라보면, 주제별 평가와 분야별 평가를 들 수 있다. 본 연구는 인공지능 서비스 영향성 정책 및 대응 방안 마련하는데 도움이 되며. 향후 연구는 인공지능 서비스 영향성 분석 기준을 바탕으로 구체적인 지표를 발굴하는게 필요하다.

• 한국IT서비스학회지
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• 제18권2호
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• pp.123-141
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• 2019

The goal of this study is to review the major research trend on the convergence studies of AI and healthcare technologies. For the study, 15,260 English articles on AI and healthcare related topics were collected from Scopus for 55 years from 1963, and text mining techniques were conducted. As a result, seven key research topics were defined : "AI for Clinical Decision Support System (CDSS)", "AI for Medical Image", "Internet of Healthcare Things (IoHT)", "Big Data Analytics in Healthcare", "Medical Robotics", "Blockchain in Healthcare", and "Evidence Based Medicine (EBM)". The result of this study can be utilized to set up and develop the appropriate healthcare R&D strategies for the researchers and government. In this study, text mining techniques such as Text Analysis, Frequency Analysis, Topic Modeling on LDA (Latent Dirichlet Allocation), Word Cloud, and Ego Network Analysis were conducted.

• International Journal of Advanced Culture Technology
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• 제10권2호
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• pp.246-251
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• 2022

As the number of data and devices explodes, centralized data processing and AI analysis have limitations due to the load on the network and cloud. On-device AI technology can provide intelligent services without overloading the network and cloud because the device itself performs AI models. Accordingly, the need for on-device AI technology is emerging. Many smartphones are equipped with On-Device AI technology to support the use of related functions. In this paper, we compare software tools that implement On-Device AI.

• 스마트미디어저널
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• 제10권1호
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• pp.99-107
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• 2021

4차 산업혁명, Industry 4.0 과 더불어 최근 ICT 분야의 메가트렌드는 빅데이터, IoT, 클라우드 컴퓨팅, 그리고 인공지능이라고 할 수 있다. 따라서, 4차 산업혁명 시대에 알맞은 AI 서비스들의 기술 개발과 다양한 산업 영역에서 ICT 분야의 융합에 따른 BI (Business Intelligence), IA (Intelligent Analytics, BI + AI), AIoT (Artificial Intelligence of Things), AIOPS (Artificial Intelligence for IT Operations), RPA 2.0 (Robotic Process Automation + AI) 등의 세분화된 기술 발전으로 급속한 디지털 전환 (Digital Transformation)이 진행되고 있는 추세이다. 본 연구에서는 이러한 기술적 상황에 따른 대용량 분산 Abyss 스토리지 기반으로 인프라 측면의 GPU, CDA (Connected Data Architecture) 프레임워크, 그리고 AI의 다양한 머신러닝 서비스들을 통합 및 고도화를 목표로 하며, AI 비즈니스의 수익 모델을 다양한 산업 영역에 활용하고자 한다.

• 전자통신동향분석
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• 제35권3호
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• pp.1-8
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• 2020

Artificial-intelligence (AI) technology is used in a variety of fields, from robot cleaner motion control to call center counselors, AI speakers, and Mars exploration. Because the technology levels of all applications and services that utilize AI vary widely, it is not possible to view all applications using AI technology at the same level. Nevertheless, there have been no cases in which the level of AI technology was defined. Therefore, the Electronics and Telecommunications Research Institute (ETRI) Artificial Intelligence Research Laboratory has defined the levels of the main technical elements of AI from steps 1 to 6. In this report, the Artificial Intelligence Technology Level 1.0 (ATL 1.0) is presented. It was established by comprehensively referring to the AI technology prospects and technology roadmaps of major countries. It is hoped that it can be used as a measure for determining the levels of AI applications or services or as an indicator for establishing a technology roadmap.

• 디지털산업정보학회논문지
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• 제19권1호
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• pp.57-76
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• 2023

This study analyzes the factors and effects on the users' intention to switch from contact center-oriented to AI chatbot-oriented customer services by combining Push-Pull-Mooring Model and provides insights for companies considering the adoption of AI chatbots. To test the model, we surveyed users with experience using chatbots at least once across different age groups. Finally, we analyzed 176 cases for the analysis using IBM SPSS Statistics and SmartPLS 4.0. The results of hypotheses testing rejected the hypotheses for variables of inconsistent quality and low availability of push factors and low switching cost of mooring factor while accepting the hypotheses for the tardy response of push factors and all pull factors. Therefore, these findings provide important implications for researchers and practitioners who wish to conduct research or adopt AI chatbots. In conclusion, users do not feel inconvenienced by the contact center-oriented service but also perceive high trust and convenience with AI chatbot-oriented service. However, despite low switching costs, users consider chatbots a complementary tool rather than an alternative. So, companies adopting AI chatbots should consider what features the users expect from AI chatbots and facilitate these features when implementing AI chatbots.

• 한국빅데이터학회지
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• 제7권2호
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• pp.91-102
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• 2022

인공지능이 발전하면서 AI 챗봇 시스템의 활용이 활발히 이루어지고 있다. 그 예로 공공기관에서는 민원, 행정 분야에서 업무 보조, 전문지식 서비스 등으로 챗봇 활용 분야가 확대되고 있으며 민간기업은 대화형 고객 응대 서비스 등으로 챗봇을 활용하고 있다. 본 연구에서는 시나리오 기반의 AI 음성 챗봇 시스템을 제안하여 박물관의 운영 비용을 절감하고 관람객에게 양방향성 안내 서비스를 제공하고자 한다. 구현한 음성 챗봇 시스템은 실시간으로 특정 디렉터리를 감시하여 사용자의 음성을 감지하는 감시자 객체와 음성 파일이 생성되면 순차적으로 모델별 추론을 수행하여 AI의 응대 음성을 출력하는 이벤트 핸들러 객체로 구성되며, 스레드와 데크를 활용한 중복 방지 기능을 포함하여 단일 GPU 환경에서 추론 중에 GPU의 연산이 중복되지 않도록 한다.

• 한국IT서비스학회지
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• 제19권2호
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• pp.93-107
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• 2020

Recently, artificial intelligence (AI) technologies has been widely used in various fields such as finance, and distribution. Accordingly, Korea has also announced its AI R&D strategy for the realization of i-Korea 4.0 in May 2018. However, Korea's AI technology is inferior to major competitors such as the US, Canada, and Japan Therefore, in order to cope with the 4th industrial revolution, it is necessary to allocate AI R&D budgets efficiently through selection and concentration so as to gain competitive advantage under a limited budget. In this study, the importance of each AI technology was evaluated in multi-dimensional way through the questionnaire of expert group using the evaluation index derived from the literature review From the results of this study, we draw the following implication. In order to successfully establish the AI technology development strategies, it is necessary to prioritize the cognitive computing technology that has great market growth potential, ripple effect of technology development, and the urgency of technology development according to the principle of selection and concentration. To this end, it is necessary to find creative ideas, manage assessments, converge multidisciplinary systems and strengthen core competencies. In addition, since AI technology has a large impact on socioeconomic development, it is necessary to comprehensively grasp and manage scientific and technological regulations in order to systematically promote AI technology development.

• 한국IT서비스학회지
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• 제20권1호
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• pp.93-115
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• 2021

Various policy declarations and institutional experiments involving artificial intelligence are being made in most countries. Depending on how the artificial intelligence policy changes, the role of the government, the scope of the policy, and the policy means used may vary, which can lead to the success or failure of the policy. This study proposed a perspective on AI(Artificial Intelligence) in policy research, investigated the theory of path change, and derived the characteristics of path change in AI policy. Since AI policy is related to a wide range of policy areas and the policy making is at the start points, this study is based on the neo-institutional path theory about the types of institutional changes. As a result of this study, AI policy showed the characteristics of path creation, and in detail presented the conflict relationship between institutional design elements, the scalability of policy areas, policy stratification and policy mix, the top policy characteristics transcending the law, and the experiment for regulatory innovation. Since AI can also be used as a key tool for policy innovation in the future, research on the path and characteristics of AI policy will provide a new direction and approach to government policy or institutional innovation seeking digital transformation.

• Asian-Australasian Journal of Animal Sciences
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• 제10권3호
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• pp.329-332
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• 1997

A study on the conception rate of 885 cows and heifers bred under artificial insemination (AI) and natural service was carried out at AI sub-centers. A high conception rate was observed at first service in all breeding methods. It was revealed that the conception rates in AI with liquid semen (LS) were found to be 25.08, 18.58, 12.69, and 2.48% after 1, 2, 3 and 4 services, respectively. Inseminations of cattle with frozen semen (FS) were found to achieve 42.15, 14.46, 5.85, and 2.46% conception rates after 1, 2, 3, and 4 services, respectively. In natural service, conception rates were found to be 62.45, 6.75, 5.91, and 4.64%, respectively, after 1, 2, 3, and 4 services. Insemination of cows and heifers at mid-cycle had significantly (p < 0.05) higher conception rate as compared to early and late cycles. The existing AI machineries and breeding management need to be improved to achieve higher conception rate of dairy cattle under AI.