• Journal of Information Processing Systems
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• 제15권4호
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• pp.717-723
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• 2019

Smart systems and services aim to facilitate growing urban populations and their prospects of virtual-real social behaviors, gig economies, factory automation, knowledge-based workforce, integrated societies, modern living, among many more. To satisfy these objectives, smart systems and services must comprises of a complex set of features such as security, ease of use and user friendliness, manageability, scalability, adaptivity, intelligent behavior, and personalization. Recently, artificial intelligence (AI) is realized as a data-driven technology to provide an efficient knowledge representation, semantic modeling, and can support a cognitive behavior aspect of the system. In this paper, an integration of AI with the smart systems and services is presented to mitigate the existing challenges. Several novel researches work in terms of frameworks, architectures, paradigms, and algorithms are discussed to provide possible solutions against the existing challenges in the AI-based smart systems and services. Such novel research works involve efficient shape image retrieval, speech signal processing, dynamic thermal rating, advanced persistent threat tactics, user authentication, and so on.

• 벤처혁신연구
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• 제7권2호
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• pp.41-56
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• 2024

최근들어 ChaGPT를 비롯한 생성형AI서비스가 화두가 되고 있다. 디지털 네이티브인 Z세대 뿐만 아니라 디지털 이민자인 시니어들도 관심을 가지고 있는 서비스이다. 이러한 시점에서 시니어를 대상으로 생성형AI 서비스 이용의도에 영향을 미치는 요인에 대해 실증분석을 하였다. 이를 위해 시니어를 대상으로 설문조사를 실시하였으며 유효한 250부를 분석에 활용하였다. 본 연구에서는 시니어의 기술수용에 관한 연구모형인 MATOA(Model for the Adoption of Technology by Older Adults)를 토대로 성과기대, 노력기대, 사회적영향, 사전지식, 시니어의 생리적노화현상 및 생성형AI서비스의 환각을 독립변수로 설정했다. 분석은 다중회귀분석방법을 사용하였다. 실증분석결과는 다음과 같다. 성과기대와 사회적영향은 시니어의 생성형AI서비스 이용의도에 유의한 정(+)의 영향을 미쳤다. 또한 사전지식은 시니어의 생성형AI 서비스 이용의도에 유의한 정(+)의 영향을 미쳤고 생리적노화현상은 유의한 부(-)의 영향을 미쳤다. 한편, 노력기대 및 AI 환각(hallucinations)이 시니어의 생성형AI 서비스 이용의도에 미치는 유의한 영향 관계는 검정되지 않았다. 영향을 미치는 변인의 영향력 순서는 성과기대, 사회적영향, 사전지식, 생리적노화현상 순이었다. 이러한 연구결과를 토대로 학술적 및 실무적 시사점을 제시하였다.

• Imaging Science in Dentistry
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• 제50권3호
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• pp.193-198
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• 2020

Purpose: This study investigated knowledge, attitudes, and perceptions regarding the future of artificial intelligence (AI) for radiological diagnosis among dental specialists in central India. Materials and Methods: An online survey was conducted consisting of 15 closed-ended questions using Google Forms and circulated among dental professionals in central India. The survey consisted of questions regarding participants' recognition of and attitudes toward AI, their opinions on directions of AI development, and their perceptions regarding the future of AI in oral radiology. Results: Of the 250 participating dentists, 68% were already familiar with the concept of AI, 69% agreed that they expect to use AI for making dental diagnoses, 51% agreed that the major function of AI would be the interpretation of complicated radiographic scans, and 63% agreed that AI would have a future in India. Conclusion: This study concluded that dental specialists were well aware of the concept of AI, that AI programs could be used as an adjunctive tool by dentists to increasing their diagnostic precision when interpreting radiographs, and that AI has a promising role in radiological diagnosis.

• 국제초고층학회논문집
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• 제12권3호
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• pp.203-208
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• 2023

The implementation of artificial intelligence (AI) design for tall building structures is an essential solution for addressing critical challenges in the current structural design industry. Generative AI technology is a crucial technical aid because it can acquire knowledge of design principles from multiple sources, such as architectural and structural design data, empirical knowledge, and mechanical principles. This paper presents a set of AI design techniques for building structures based on two types of generative AI: generative adversarial networks and graph neural networks. Specifically, these techniques effectively master the design of vertical and horizontal component layouts as well as the cross-sectional size of components in reinforced concrete shear walls and frame structures of tall buildings. Consequently, these approaches enable the development of high-quality and high-efficiency AI designs for building structures.

• Asia Marketing Journal
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• 제26권2호
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• pp.129-144
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• 2024

This research is on how people's trust in human-like AI-based service will influence customer engagement (CE). This study will discuss the relationship between trust and CE and explore how people's trust in AI affects CE when they lack knowledge of the company/brand. Items from the philosophical study of trust were extracted to build a scale suitable for trust in AI. The scale's reliability was ensured, and six components of trust in AI were merged into three dimensions: trust based on Quality Assurance, Risk-taking, and Corporate Social Responsibility. Trust based on quality assurance and risk-taking is verified to positively impact customer engagement, and the feelings about AI-based service fully mediate between all three dimensions of trust in AI and CE. The new trust scale for human-like AI-based services on social media sheds light on further research. The relationship between trust in AI and CE provides a theoretical basis for subsequent research.

• 사물인터넷융복합논문지
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• 제8권6호
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• pp.49-54
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• 2022

코로나 이후 급격한 현대사회의 변화는 인공지능 인재가 국가 경쟁력을 좌우하는 주요한 영향요인으로 부각시겼다. 이에 따라 교육부에서는 인공지능 교육 공백기에 있는 초등학교 4-6학년과 중고등학생의 디지털 역량을 개발시키기 위해 대단위 SW·AI 캠프 교육 사업을 기획하였다. 이에 본 연구에서는 초등학교 4-6학년 학생들을 대상으로 하는 캠프 형 SW·AI교육프로그램을 개발하여 초등학교 4-6학년 학생들로 하여금 인공지능 기초소양을 갖추도록 하고자 한다. 이를 위해 초등학교에서의 SW·AI 교육의 의미를 정의하고 초등학교과정에서 다루어야 할 SW·AI 내용으로 'SW·AI의 이해', 'SW·AI의 원리와 활용' 및 'SW·AI의 사회적 영향'을 설정하였다. 또한 설정된 초등학교 SW·AI 교육학습 요소와 현재 초등학교에서 사용하고 있는 교과서의 관련 교과 및 단원과의 연계를 시도하였다. 교육에 사용되는 프로그램으로는 블록코딩 기반의 소프트웨어 코딩 학습 도구인 엔트리를 통하여 소프트웨어 프로그래밍 기초 역량을 강화하도록 하였으며, 모든 프로그램은 초등학생의 발달적 특징을 고려하여 경험과 체험 위주의 참여자 중심으로 운영되도록 설계하였다. 본 연구에서 이루어진 SW·AI 캠프 교육 프로그램은 방과 후 과정이나 방학 등을 이용하여 단기간에 운영되는 프로그램이다. 따라서 이를 토대로 초등학교 과정에서 SW·AI 교육이 정규교육과정의 일원으로 편성되어 운영되기 위해서는 정규교과 내용분석과 SW·AI 교육내용의 심층적인 분석을 기초로 한 연구가 필요함을 제언하는 바이다.

• 지식경영연구
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• 제21권1호
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• pp.175-195
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• 2020

The development of platform service based on the information and communication technology has revolutionized patterns of commercial transactions, driving the growth of global economy. Furthermore, the radical advancement of artificial intelligence(AI) presents the huge potential to innovate almost all the industrial and economic activities. Given these technological developments, the goal of this paper is to investigate AI's impact on the platform service innovation as well as its influence on the business performance. For the goal, this paper presents the review of the types of service innovation, the nature of platform services, and technological characteristics of leading AI technologies, such as chatbot and recommendation system. As an empirical study, this paper performs a multiple case study of Kakao Group which is the leading mobile platform service with the most advanced AI in Korea. To understand the role and effect of AI on Kakao platform service, this study investigated three cases, including chatbot agent of Kakao Bank, Smart Call service of Kakao Taxi, and music recommendation system of Kakao Mellon. The analysis results of the case study show that AI initiated innovations in platform service concepts, service delivery, and customer interface, all of which lead to a significant decrease in the transaction costs and the personalization of services. Finally, for the successful development of AI, this research emphasizes the significance of the accumulation of customer and operational data, the AI human capital, and the design of R&D organization.

• Clinical and Experimental Pediatrics
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• 제65권5호
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• pp.239-249
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• 2022

Cells survive and proliferate through complex interactions among diverse molecules across multiomics layers. Conventional experimental approaches for identifying these interactions have built a firm foundation for molecular biology, but their scalability is gradually becoming inadequate compared to the rapid accumulation of multiomics data measured by high-throughput technologies. Therefore, the need for data-driven computational modeling of interactions within cells has been highlighted in recent years. The complexity of multiomics interactions is primarily due to their nonlinearity. That is, their accurate modeling requires intricate conditional dependencies, synergies, or antagonisms between considered genes or proteins, which retard experimental validations. Artificial intelligence (AI) technologies, including deep learning models, are optimal choices for handling complex nonlinear relationships between features that are scalable and produce large amounts of data. Thus, they have great potential for modeling multiomics interactions. Although there exist many AI-driven models for computational biology applications, relatively few explicitly incorporate the prior knowledge within model architectures or training procedures. Such guidance of models by domain knowledge will greatly reduce the amount of data needed to train models and constrain their vast expressive powers to focus on the biologically relevant space. Therefore, it can enhance a model's interpretability, reduce spurious interactions, and prove its validity and utility. Thus, to facilitate further development of knowledge-guided AI technologies for the modeling of multiomics interactions, here we review representative bioinformatics applications of deep learning models for multiomics interactions developed to date by categorizing them by guidance mode.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2023년도 제35회 한글 및 한국어 정보처리 학술대회
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• pp.301-305
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• 2023

최근 등장한 Large Language Models (LLM)은 자연어 처리 분야에서 눈에 띄는 성과를 보여주었지만, 주로 영어 중심의 연구로 진행되어 그 한계를 가지고 있다. 본 연구는 사전 학습된 LLM의 언어별 지식 전이 가능성을 한국어를 중심으로 탐구하였다. 이를 위해 한국어와 영어로 구성된 코드 스위칭 코퍼스를 구축하였으며, 기본 모델인 LLAMA-2와 코드 스위칭 코퍼스를 추가 학습한 모델 간의 성능 비교를 수행하였다. 결과적으로, 제안하는 방법론으로 학습한 모델은 두 언어 간의 희미론적 정보가 효과적으로 전이됐으며, 두 언어 간의 지식 정보 연계가 가능했다. 이 연구는 다양한 언어와 문화를 반영하는 다국어 LLM 연구와, 소수 언어를 포함한 AI 기술의 확산 및 민주화에 기여할 수 있을 것으로 기대된다.

• 한국인공지능학회지
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• 제11권3호
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• pp.1-5
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• 2023

With recent advancements in artificial intelligence (AI) technology, more products based on AI are being launched and used. However, using AI safely requires an awareness of the potential risks it can pose. These concerns must be evaluated by experts and users must be informed of the results. In response to this need, many countries have implemented certification programs for products based on AI. In this study, we analyze several trends and differences in AI product certification programs across several countries and emphasize the importance of such programs in ensuring the safety and trustworthiness of products that include AI. To this end, we examine four international AI product certification programs and suggest methods for improving and promoting these programs. The certification programs target AI products produced for specific purposes such as autonomous intelligence systems and facial recognition technology, or extend a conventional software quality certification based on the ISO/IEC 25000 standard. The results of our analysis show that companies aim to strategically differentiate their products in the market by ensuring the quality and trustworthiness of AI technologies. Additionally, we propose methods to improve and promote the certification programs based on the results. These findings provide new knowledge and insights that contribute to the development of AI-based product certification programs.