• Title/Summary/Keyword: Artificial Intelligence (AI)

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Metaverse R&D Promotion Strategy Reflecting Digital Ethics and UX (디지털 윤리와 UX를 반영한 메타버스 R&D 추진전략)

  • Bang, Junseong;Park, Pangun
    • Journal of Broadcast Engineering
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    • v.27 no.5
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    • pp.703-717
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    • 2022
  • Metaverse provides a simulated environment that can produce various values while conducting economic, social, and cultural activities in a digital society where the virtual and real worlds are connected. In this paper, the direction of technological progress is predicted by analyzing the characteristics of Metaverse services and their businesses. Technologies and latest researches for the realization of the Metaverse service platform are also explored. In addition, Metaverse Ethics to construct a sustainable Metaverse and Metaverse UX to increase users' service participation are also discussed. Moreover, the R&D promotion strategy for Metaverse services are presented.

IoT-Based Health Big-Data Process Technologies: A Survey

  • Yoo, Hyun;Park, Roy C.;Chung, Kyungyong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.3
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    • pp.974-992
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    • 2021
  • Recently, the healthcare field has undergone rapid changes owing to the accumulation of health big data and the development of machine learning. Data mining research in the field of healthcare has different characteristics from those of other data analyses, such as the structural complexity of the medical data, requirement for medical expertise, and security of personal medical information. Various methods have been implemented to address these issues, including the machine learning model and cloud platform. However, the machine learning model presents the problem of opaque result interpretation, and the cloud platform requires more in-depth research on security and efficiency. To address these issues, this paper presents a recent technology for Internet-of-Things-based (IoT-based) health big data processing. We present a cloud-based IoT health platform and health big data processing technology that reduces the medical data management costs and enhances safety. We also present a data mining technology for health-risk prediction, which is the core of healthcare. Finally, we propose a study using explainable artificial intelligence that enhances the reliability and transparency of the decision-making system, which is called the black box model owing to its lack of transparency.

Optimal Design of Semi-Active Mid-Story Isolation System using Supervised Learning and Reinforcement Learning (지도학습과 강화학습을 이용한 준능동 중간층면진시스템의 최적설계)

  • Kang, Joo-Won;Kim, Hyun-Su
    • Journal of Korean Association for Spatial Structures
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    • v.21 no.4
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    • pp.73-80
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    • 2021
  • A mid-story isolation system was proposed for seismic response reduction of high-rise buildings and presented good control performance. Control performance of a mid-story isolation system was enhanced by introducing semi-active control devices into isolation systems. Seismic response reduction capacity of a semi-active mid-story isolation system mainly depends on effect of control algorithm. AI(Artificial Intelligence)-based control algorithm was developed for control of a semi-active mid-story isolation system in this study. For this research, an practical structure of Shiodome Sumitomo building in Japan which has a mid-story isolation system was used as an example structure. An MR (magnetorheological) damper was used to make a semi-active mid-story isolation system in example model. In numerical simulation, seismic response prediction model was generated by one of supervised learning model, i.e. an RNN (Recurrent Neural Network). Deep Q-network (DQN) out of reinforcement learning algorithms was employed to develop control algorithm The numerical simulation results presented that the DQN algorithm can effectively control a semi-active mid-story isolation system resulting in successful reduction of seismic responses.

A Retail Strategy for the Prosperity of the Art Market within Online Distribution Channel

  • Soomin, HAN
    • Journal of Distribution Science
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    • v.21 no.3
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    • pp.113-121
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    • 2023
  • Purpose: Online distribution channel alludes to the many different digital channels utilized in marketing and distributing goods and services to end users. The present research aims to explore and provide various retail strategy for the success of the art market within online distribution channel. Research design, data and methodology: The current author has conducted and investigate the qualitative textual methodology to take a look at carefully the current and prior literature dataset to achieve the purpose of the present research so that the present author could obtain total 27 relevant prior studies. Results: According to the comprehensive literature investigation, this research has found that there are six kinds of retail strategy for the prosperity of the art market within online distribution channel as follows: (1) Blockchain Technology, (2) Artificial Intelligence (AI), (3) Virtual Reality (VR), (4) Online Market Places, (5) Social Media, and (6) Regulations. Conclusions: The results of this analysis of the relevant literature show that the art market industry needs to adjust to keep up with the quickly shifting landscape of the digital world. In addition, although these technologies can be helpful in addressing difficulties linked to authenticity and transparency, they cannot eliminate the hazards of fraud and misrepresentation.

A Case Analysis for Learning Management Systems that support Individual Students' Mathematics Learning (개별 학습 지원을 위한 수학 플랫폼 LMS 사례 분석)

  • Han, Sang Ji;Kim, Hyung Won;Ko, Ho Kyoung
    • East Asian mathematical journal
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    • v.38 no.2
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    • pp.187-214
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    • 2022
  • This study compares the functions of the Learning Management Systems (LMS) in three widely used Edu-Tech platforms, that support students' individualized learning by using the learning characteristics of the students. The rapid advances in artificial intelligence (AI) are broadening their impacts in the education industry, and play a broad role in supporting student learning. In many countries, online classes have become a norm due to the COVID-19 crisis, and the demand for Edu-Tech in classes has increased rapidly. As a result, many countries, including South Korea, are now preparing and implementing various policy measures to adopt Edu-Tech in the class setting. Therefore, in this study, we analyze and compare the structures and characteristics of the three widely used Edu-Tech platforms that support individualized mathematics learning. In particular, we compare the LMSs of the three platforms by considering the elements such as learning design, learning management, learner analysis, learning result analysis, and student management functions. The results of this study give implications in the future directions to take on how to build Edu-Tech platform models that promote students' individualized mathematics learning in public education.

A Study on NaverZ's Metaverse Platform Scaling Strategy

  • Song, Minzheong
    • International journal of advanced smart convergence
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    • v.11 no.3
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    • pp.132-141
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    • 2022
  • We look at the rocket life stages of NaverZ's metaverse platform scaling and investigate the ignition and scale-up stage of its metaverse platform brand, Zepeto based on the Rocket Model (RM). The results are derived as follows: Firstly, NaverZ shows the event strategy by collaborating with K-pops, the piggybacking strategy by utilizing other SNSs, and the VIP strategy by investing in game and entertainment content genres in the 'attract' function. In the second 'match' function, based on the matching rule of Zepeto, the users can generate their own characters and "World" with Zepeto Studio. However, for strengthening the matching quality, NaverZ is investing in the artificial intelligence (AI) based companies consistently. In the 'connect' function, NaverZ's maximization of the positive interaction is possible by inducing feed activities in Zepeto & other SNSs and by uploading attractive content for viral effects in the ignition. For facilitating this, NaverZ expands the scale to other continents like Southeast Asia and Middle East with the localization strategy inclusive investment. Lastly, in the 'transact' function, based on three monetization experiments like Coin & ZEM, user generated content (UGC) fee, and advertising revenue in the ignition, NaverZ starts to invest in NFT platforms and abroad blockchain companies.

Effects of selfie semantic network analysis and AR camera app use on appearance satisfaction and self-esteem (셀피의 의미연결망 분석과 AR 카메라 앱 사용이 외모만족도와 자아존중감에 미치는 영향)

  • Lee, Hyun-Jung
    • The Research Journal of the Costume Culture
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    • v.30 no.5
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    • pp.766-778
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    • 2022
  • Image-oriented information is becoming increasingly important on social networking services (SNS); the background of this trend is the popularity of selfies. Currently, camera applications using augmented reality (AR) and artificial intelligence (AI) technologies are gaining traction. An AR camera app is a smartphone application that converts selfies into various interesting forms using filters. In this study, we investigated the change of keywords according to the time flow of selfies in Goolgle News articles through semantic network analysis. Additionally, we examined the effects of using an AR camera app on appearance satisfaction and self-esteem when taking a selfie. Semantic network analysis revealed that in 2013, postings of specific people were the most prominent selfie-related keywords. In 2019, keywords appeared regarding the launch of a new smartphone with a rear-facing camera for selfies; in 2020, keywords related to communication through selfies appeared. As a result of examining the effect of the degree of use of the AR camera app on appearance satisfaction, it was found that the higher the degree of use, the higher the user's interest in appearance. As a result of examining the effect of the degree of use of the AR camera app on self-esteem, it was found that the higher the degree of use, the higher the user's negative self-esteem.

A study on estimating the main dimensions of a small fishing boat using deep learning (딥러닝을 이용한 연안 소형 어선 주요 치수 추정 연구)

  • JANG, Min Sung;KIM, Dong-Joon;ZHAO, Yang
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.58 no.3
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    • pp.272-280
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    • 2022
  • The first step is to determine the principal dimensions of the design ship, such as length between perpendiculars, beam, draft and depth when accomplishing the design of a new vessel. To make this process easier, a database with a large amount of existing ship data and a regression analysis technique are needed. Recently, deep learning, a branch of artificial intelligence (AI) has been used in regression analysis. In this paper, deep learning neural networks are used for regression analysis to find the regression function between the input and output data. To find the neural network structure with the highest accuracy, the errors of neural network structures with varying the number of the layers and the nodes are compared. In this paper, Python TensorFlow Keras API and MATLAB Deep Learning Toolbox are used to build deep learning neural networks. Constructed DNN (deep neural networks) makes helpful in determining the principal dimension of the ship and saves much time in the ship design process.

Synthetic Infra-Red Image Dataset Generation by CycleGAN based on SSIM Loss Function (SSIM 목적 함수와 CycleGAN을 이용한 적외선 이미지 데이터셋 생성 기법 연구)

  • Lee, Sky;Leeghim, Henzeh
    • Journal of the Korea Institute of Military Science and Technology
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    • v.25 no.5
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    • pp.476-486
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    • 2022
  • Synthetic dynamic infrared image generation from the given virtual environment is being the primary goal to simulate the output of the infra-red(IR) camera installed on a vehicle to evaluate the control algorithm for various search & reconnaissance missions. Due to the difficulty to obtain actual IR data in complex environments, Artificial intelligence(AI) has been used recently in the field of image data generation. In this paper, CycleGAN technique is applied to obtain a more realistic synthetic IR image. We added the Structural Similarity Index Measure(SSIM) loss function to the L1 loss function to generate a more realistic synthetic IR image when the CycleGAN image is generated. From the simulation, it is applicable to the guided-missile flight simulation tests by using the synthetic infrared image generated by the proposed technique.

Economic impact of digitalization on agriculture: a Korean perspective

  • Jung-Won Youm;Su-Hwan Myeong;Jeong-Ho Yoo
    • Korean Journal of Agricultural Science
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    • v.49 no.1
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    • pp.31-43
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    • 2022
  • The global trade environment is rapidly changing. The spread of COVID-19 promotes digitalization, and online transactions are becoming the new normal. Currently, Korea is actively introducing information and communication technology (ICT) that uses the internet of things (IoT) in relation to agriculture. However, few studies have analyzed the impact of digitalization on trade in the agricultural sector. Thus, the purpose of this study is to examine how the introduction of digital technology can affect the economy and trade of Korea. In this study, we estimate the impact of introducing digital technologies using the computable general equilibrium (CGE) model. The results of this analysis indicate that the GDP could increase by 3.82% to 10.53%. Also, agricultural production and trade according to the model will significantly increase to 8.67% and 5.72%, respectively, through a productivity increase from Blockchain, IoT, and artificial intelligence (AI) technologies, despite logistics inefficiencies. Although the effects of digitalization could be significant, farmers are still struggling to introduce digital technologies, stemming from the fact that government support systems are concentrated in only a few sub-sectors. In this regard, support in this area must be expanded and diversified according to the current environment of agriculture in Korea.