• 제목/요약/키워드: AI Solutions

검색결과 163건 처리시간 0.025초

Using No-Code/Low-Code Solutions to Promote Artificial Intelligence Adoption in Vietnamese Businesses

  • Quoc Cuong Nguyen;Hoang Tuan Nguyen;Jaesang Cha
    • International Journal of Internet, Broadcasting and Communication
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    • 제16권3호
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    • pp.370-378
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    • 2024
  • Recently, Artificial Intelligence (AI) has been emerging as a technology that has transformed and revolutionized various industries around the world. In recent years, businesses in Vietnam have also started to embrace AI applications to enhance their operations and gain a competitive edge in the market. As AI technologies continue to evolve rapidly, their impact on Vietnamese businesses is becoming increasingly profound. As artificial intelligence continues to progress across various fields, the need to democratize AI technology becomes increasingly clear. In a rapidly growing market like Vietnam, leveraging AI offers significant opportunities for businesses to improve operational efficiency, customer engagement, and overall competitiveness. However, significant barriers to AI adoption in Vietnam are the scarcity of skilled developers and the high cost of implementing traditional AI. No-code/low-code platforms offer an innovative solution that can accelerate AI adoption by making these technologies accessible to a wider audience. This article analyzes and understands the benefits of no-code/low-code solutions and proposes a roadmap for implementing no-code/low-code solutions in promoting AI applications in Vietnamese businesses.

Trends in the AI-based Banking Conversational Agents Literature: A Bibliometric Review

  • Eden Samuel Parthiban;Mohd. Adil
    • Asia pacific journal of information systems
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    • 제33권3호
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    • pp.702-736
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    • 2023
  • Artificial Intelligence (AI) and the technologies powered by AI fuel the fourth industrial revolution. Being the primary adopter of such innovations, banking has recently started using the most common AI-based technology, i.e., conversational agents. Although research extensively focuses on this niche area and provides bibliometric understanding for such agents in other industries, a similar review with scientometric insights of the banking literature concerning AI conversational agents is absent till date. Furthermore, in the era following the pandemic, banks are faced with the imperative to provide solutions that align with the changing landscape of remote consumer behavior. As a result, banks are proactively integrating technology-driven solutions, such as automated agents, to effectively address the growing demand for remote customer support. Hence more research is needed to perfect such agents. In order to bridge these existing gaps, the present study undertook a comprehensive examination of two decades' worth of banking literature. A meticulous review was conducted, analyzing approximately 116 papers published from 2003 to 2023. The aim was to provide a scientometric overview of the topic, catering to the research needs of both academic and industrial professionals. Holistically, the study seeks to present a macro-view about the existing trends in AI based banking conversational agents' literature while focusing on quantity, qualitative and structural indicators that are effectively necessary to offer new directions for the AI-based banking solutions. Our study, therefore, presents insights surrounding the literature, using selected techniques related to performance analysis and science mapping.

Challenges of diet planning for children using artificial intelligence

  • Changhun, Lee;Soohyeok, Kim;Jayun, Kim;Chiehyeon, Lim;Minyoung, Jung
    • Nutrition Research and Practice
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    • 제16권6호
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    • pp.801-812
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    • 2022
  • BACKGROUND/OBJECTIVES: Diet planning in childcare centers is difficult because of the required knowledge of nutrition and development as well as the high design complexity associated with large numbers of food items. Artificial intelligence (AI) is expected to provide diet-planning solutions via automatic and effective application of professional knowledge, addressing the complexity of optimal diet design. This study presents the results of the evaluation of the utility of AI-generated diets for children and provides related implications. MATERIALS/METHODS: We developed 2 AI solutions for children aged 3-5 yrs using a generative adversarial network (GAN) model and a reinforcement learning (RL) framework. After training these solutions to produce daily diet plans, experts evaluated the human- and AI-generated diets in 2 steps. RESULTS: In the evaluation of adequacy of nutrition, where experts were provided only with nutrient information and no food names, the proportion of strong positive responses to RL-generated diets was higher than that of the human- and GAN-generated diets (P < 0.001). In contrast, in terms of diet composition, the experts' responses to human-designed diets were more positive when experts were provided with food name information (i.e., composition information). CONCLUSIONS: To the best of our knowledge, this is the first study to demonstrate the development and evaluation of AI to support dietary planning for children. This study demonstrates the possibility of developing AI-assisted diet planning methods for children and highlights the importance of composition compliance in diet planning. Further integrative cooperation in the fields of nutrition, engineering, and medicine is needed to improve the suitability of our proposed AI solutions and benefit children's well-being by providing high-quality diet planning in terms of both compositional and nutritional criteria.

OSCILLATORY BEHAVIOUR OF SOLUTIONS OF y"+P(x)y=f(x)

  • Zaghrout, A.A.S.;Ragab, A.A.
    • Kyungpook Mathematical Journal
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    • 제27권1호
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    • pp.7-13
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    • 1987
  • This paper is a study of the oscillatory and asymptotic behaviour of solutions of the second order nonhomogeneous linear differential equation y"+P(x)y=f(x), and the associated homogeneous equation. Conditions are determined, under which the nonhomogeneous equation is oscillatory if and only if the homogeneous equation is oscillatory.

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이미지 인식 기반의 지도학습을 활용한 생산관리 효율화 방법에 관한 연구 (A study on Production Management Efficiency Method using Supervised Learning based Image Cognition)

  • 장우식;이건우;이상덕;김영곤
    • 한국인터넷방송통신학회논문지
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    • 제21권5호
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    • pp.47-52
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    • 2021
  • 최근 제조 산업에서 생산공정 관리에 대한 인공지능 솔루션 수요가 증가하고 있다. 그러나, 제조산업의 AI 솔루션 적용을 통하여 POP, MES와 같은 레거시 스마트공장 솔루션의 한계가 존재한다. 따라서, 본 논문에서는 이를 극복하기 위하여 이미지 인식 시스템에 인공지능 개념인 지도학습을 적용하여, 생산관리 효율을 향상시키고자 하였다. 시스템 흐름에서는 As_is To be를 구분하여 실제 업무 흐름을 적용하였으며, 전체 생산성 효율을 위하여 프로세스 개선을 하였다. AI 지도학습을 위한 사전 전처리 계획을 수립하고 관련 AI 모델 설계, 개발, 시뮬레이션을 수행하여, 그 결과로는 97%의 인식률을 확인하였다.

ETRI AI 실행전략 6: 산업·공공 AI 활용기술 연구개발 및 적용 (ETRI AI Strategy #6: Developing and Utilizing of AI Technology for Industries and Public Sector)

  • 김태완;연승준
    • 전자통신동향분석
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    • 제35권7호
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    • pp.56-66
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    • 2020
  • As the development of artificial intelligence (AI) technology spreads to various industrial sectors, diversity in AI utilization rapidly increases, creating rich user experience. In addition, AI is required to solve various social problems through the use of public data. The spread of AI utilization across all sectors will continue, covering such industrial and public demands. This article examines the domestic and international trends in AI utilization technologies and establishes the direction of research and development (R&D), which is highly consistent with Korea's AI policy. ETRI, which leads AI's national R&D, has used its experience to establish AI R&D implementation strategies as well as technology roadmaps for the utilization of AI to improve individual quality of life, continuous growth in society, industrial innovation, and the solutions to public societal problems. In addition, it has derived tasks and implementation strategies for developing AI utilization technologies in 10 major areas including medical services.

A Conceptual Architecture for Ethic-Friendly AI

  • Oktian, Yustus-Eko;Brian, Stanley;Lee, Sang-Gon
    • 한국컴퓨터정보학회논문지
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    • 제27권4호
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    • pp.9-17
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    • 2022
  • 최첨단 AI 시스템은 방대한 데이터 수집에서 알고리즘 편향에 이르기까지 많은 윤리적 문제를 드러내고 있다. 이에 본 논문에서는 연합학습과 블록체인을 결합하여, 더 윤리적인 AI 아키텍처를 제안하였다. AI의 윤리성에 관한 중요한 문제들을 논의하고, 문헌조사를 통하여 윤리적 AI 시스템에 대한 요구사항을 연구하고 도출한다. 제안한 아키텍처의 요구사항 만족을 분석하였다. 제안한 AI 구조를 디자인에 채택함으로써 AI 서비스를 보다 윤리적으로 수행할 수 있다.

Future Trends of AI-Based Smart Systems and Services: Challenges, Opportunities, and Solutions

  • Lee, Daewon;Park, Jong Hyuk
    • 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.

Future Trends of IoT, 5G Mobile Networks, and AI: Challenges, Opportunities, and Solutions

  • Park, Ji Su;Park, Jong Hyuk
    • Journal of Information Processing Systems
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    • 제16권4호
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    • pp.743-749
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    • 2020
  • Internet of Things (IoT) is a growing technology along with artificial intelligence (AI) technology. Recently, increasing cases of developing knowledge services using information collected from sensor data have been reported. Communication is required to connect the IoT and AI, and 5G mobile networks have been widely spread recently. IoT, AI services, and 5G mobile networks can be configured and used as sensor-mobile edge-server. The sensor does not send data directly to the server. Instead, the sensor sends data to the mobile edge for quick processing. Subsequently, mobile edge enables the immediate processing of data based on AI technology or by sending data to the server for processing. 5G mobile network technology is used for this data transmission. Therefore, this study examines the challenges, opportunities, and solutions used in each type of technology. To this end, this study addresses clustering, Hyperledger Fabric, data, security, machine vision, convolutional neural network, IoT technology, and resource management of 5G mobile networks.