• Title/Summary/Keyword: Media AI

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Meta's Metaverse Platform Design in the Pre-launch and Ignition Life Stage

  • Song, Minzheong
    • International Journal of Internet, Broadcasting and Communication
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    • v.14 no.4
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    • pp.121-131
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    • 2022
  • We look at the initial stage of Meta (previous Facebook)'s new metaverse platform and investigate its platform design in pre-launch and ignition life stage. From the Rocket Model (RM)'s theoretical logic, the results reveal that Meta firstly focuses on investing in key content developers by acquiring virtual reality (VR), video, music content firms and offering production support platform of the augmented reality (AR) content, 'Spark AR' last three years (2019~2021) for attracting high-potential developers and users. In terms of three matching criteria, Meta develops an Artificial Intelligence (AI) powered translation software, partners with Microsoft (MS) for cloud computing and AI, and develops an AI platform for realistic avatar, MyoSuite. In 'connect' function, Meta curates the game concept submitted by game developers, welcomes other game and SNS based metaverse apps, and expands Horizon Worlds (HW) on VR devices to PCs and mobile devices. In 'transact' function, Meta offers 'HW Creator Funding' program for metaverse, launches the first commercialized Meta Avatar Store on Meta's conventional SNS and Messaging apps by inviting all fashion creators to design and sell clothing in this store. Mata also launches an initial test of non-fungible token (NFT) display on Instagram and expands it to Facebook in the US. Lastly, regarding optimization, especially in the face of recent data privacy issues that have adversely affected corporate key performance indicators (KPIs), Meta assures not to collect any new data and to make its privacy policy easier to understand and update its terms of service more user friendly.

The History and Future of String Quartet Performances: Examining the Possibility of Convergent Performances Employing Media and Artificial Intelligence (현악사중주 공연의 역사와 미래: 미디어와 인공지능을 활용한 융합 공연의 가능성에 대하여)

  • Eun-Ji Park
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.5
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    • pp.697-706
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    • 2023
  • This study examines the history of string quartet performances and analyzes contemporary integrated performances to propose a new performance paradigm for future audiences. It examines past developments and audience interactions, and how modern classical performance can gain a competitive edge internationally through tech integration. Building on this foundation, a future vision is proposed for Korean string quartet performances, drawing from novel performances that are interconnected with their historical context. The study concludes that modern string quartets necessitate innovative and original performance directions that can be achieved through various technological integrations.

Development of a Smart Supply-Chain Management Solution Based on Logistics Standards Utilizing Artificial Intelligence and the Internet of Things

  • Oh, Am-Suk
    • Journal of information and communication convergence engineering
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    • v.17 no.3
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    • pp.198-204
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    • 2019
  • In this study, the author introduces a supply-chain management (SCM) solution that connects suppliers, manufacturers, customers, and other companies within a transactional relationship to enable efficient inventory management and timely product supply, which ultimately maximizes corporate profits. This proposed solution exploits Fourth Industrial Revolution technologies, such as artificial intelligence (AI) and the Internet of Things (IoT), which provide solutions to complex management issues generated by the broader market. The goal of the current study was to develop an advanced and intelligent smart SCM solution that complies with logistics standards, to enhance the visibility, safety, and efficiency of a supply chain made up of manufacturers and suppliers. This smart SCM solution aims at maximizing corporate profits through efficient inventory management and timely supply of products, and solves the complex management problems caused by operating within a wide range of markets.

The Metaverse and Video Games: Merging Media to Improve Soft Skills Training

  • Shin, Edward;Kim, Jang Hyun
    • Journal of Internet Computing and Services
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    • v.23 no.1
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    • pp.69-76
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    • 2022
  • Education systems have made efforts to prepare students by providing technical and nontechnical courses. With video games, however, there is the potential to develop dedicated metaverses that can help teach soft skills even during casual pastimes. The research conducted will propose a set of design practices for metaverse and game development to promote soft skills. While there are many soft skills people can acquire, this paper will focus on certain aspects based on specific games and studies. There will be some information collected from the information to support the design model and arguments. This paper will provide developers with a starting point for imaginative game creation and impart users with soft skills to assist in their professions and social life.

Korean CSAT Problem Solving with KoBigBird (KoBigBird를 활용한 수능 국어 문제풀이 모델)

  • Park, Nam-Jun;Kim, Jaekwang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2022.11a
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    • pp.207-210
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    • 2022
  • 최근 자연어 처리 분야에서 기계학습 독해 관련 연구가 활발하게 이루어지고 있다. 그러나 그 중에서 한국어 기계독해 학습을 통해 문제풀이에 적용한 사례를 찾아보기 힘들었다. 기존 연구에서도 수능 영어와 수능 수학 문제를 인공지능(AI) 모델을 활용하여 문제풀이에 적용했던 사례는 있었지만, 수능 국어에 이를 적용하였던 사례는 존재하지 않았다. 또한, 수능 영어와 수능 수학 문제를 AI 문제풀이를 통해 도출한 결괏값이 각각 12점, 16점으로 객관식이라는 수능의 특수성을 고려했을 때 기대에 못 미치는 결과를 나타냈다. 이에 본 논문은 한국어 기계독해 데이터셋을 트랜스포머(Transformer) 기반 모델에 학습하여 수능 국어 문제 풀이에 적용하였다. 이를 위해 객관식으로 이루어진 수능 문항의 각각의 선택지들을 질문 형태로 변형하여 모델이 답을 도출해낼 수 있도록 데이터셋을 변형하였다. 또한 BERT(Bidirectional Encoder Representations from Transformer)가 가진 입력값 개수의 한계를 극복하기 위해 더 큰 입력값을 처리할 수 있는 트랜스포머 기반 모델 중에서 한국어 기계독해 학습에 적합한 KoBigBird를 사전학습모델로 설정하여 성능을 높였다.

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머신러닝 기반 사진인식 기술을 활용한 다이어트 AI

  • Noh, Gahyeon;Yun, Ingyeong
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2020.11a
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    • pp.384-387
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    • 2020
  • AI가 각광받고 있는 시대에 발 맞추어 머신러닝, 딥러닝을 활용한 이미지 인식 기술을 구현하였다. 사용자가 원하는 음식 사진을 업로드하면 인공 신경망 알고리즘이 convolution을 수행해 데이터베이스에 학습시켜 두었던 이미지들 가운데 유사도가 가장 높은 수치로 나오는 이미지를 결과로 보여주어, 사용자는 사진만으로도 음식의 칼로리 정보, 칼로리를 소모하기 위한 운동량 등의 정보를 간편하게 알 수 있는 시스템을 구축하였다. 또한 MYSQL과 PHP를 활용하여 자신의 칼로리 정보를 저장하고, 사용자가 매일 입력하는 몸무게의 변화량 등을 실시간으로 확인할 수 있는 등의 데이터베이스 서버를 구축하였다. 스마트폰을 통해 정보를 얻을 수 있도록 어플리케이션을 구성했다.

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Music Composition with Collaboratory AI Composers

  • Kim, Haekwang;You, Younghwan
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2021.06a
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    • pp.23-25
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    • 2021
  • This paper describes an approach of composing music with multiple AI composers. This approach enriches more the creativity space of artificial intelligence music composition than using only one composer. This paper presents a simple example with 2 different deep learning composers working together for composing one music. For the experiment, the two composers adopt the same deep learning architecture of an LSTM model trained with different data. The output of a composer is a sequence of notes. Each composer alternatively appends its output to the resulting music which is input to both the composers. Experiments compare different music generated by the proposed multiple composer approach with the traditional one composer approach.

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A Study on the Comparison of the Commercial API for Recognizing Speech with Emotion (상용 API 의 감정에 따른 음성 인식 성능 비교 연구)

  • Janghoon Yang
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.05a
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    • pp.52-54
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    • 2023
  • 최근 인공지능 기술의 발전에 따라서 다양한 서비스에서 음성 인식을 활용한 서비스를 제공하면서 음성 인식에 대한 중요성이 증가하고 있다. 이 논문에서는 국내에서 많이 사용되고 있는 대표적인 인공지능 서비스 API 를 제공하는 구글, ETRI, 네이버에 대해서 감정 음성 관점에서 그 차이를 평가하였다. AI Hub 에서 제공하는 감성 대화 말뭉치 데이터 셋의 일부인 음성 테스트 데이터를 사용하여 평가한 결과 ETRI API 가 문자 오류율 (1.29%)과 단어 오류율(10.1%)의 성능 지표에 대해서 가장 우수한 음성 인식 성능을 보임을 확인하였다.

U-Net-based Recommender Systems for Political Election System using Collaborative Filtering Algorithms

  • Nidhi Asthana;Haewon Byeon
    • Journal of information and communication convergence engineering
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    • v.22 no.1
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    • pp.7-13
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    • 2024
  • User preferences and ratings may be anticipated by recommendation systems, which are widely used in social networking, online shopping, healthcare, and even energy efficiency. Constructing trustworthy recommender systems for various applications, requires the analysis and mining of vast quantities of user data, including demographics. This study focuses on holding elections with vague voter and candidate preferences. Collaborative user ratings are used by filtering algorithms to provide suggestions. To avoid information overload, consumers are directed towards items that they are more likely to prefer based on the profile data used by recommender systems. Better interactions between governments, residents, and businesses may result from studies on recommender systems that facilitate the use of e-government services. To broaden people's access to the democratic process, the concept of "e-democracy" applies new media technologies. This study provides a framework for an electronic voting advisory system that uses machine learning.

Determination of Free Acid in U(VI)-Al(III) Solutions by Gran Plot Titration (Gran Plot 적정법을 이용한 U(VI)-AI(III) 용액의 자유산 농도 측정)

  • Suh, Moo-Yul;Lee, Chang-Heon;Sohn, Se-Chul;Kim, Jung-Suk;Kim, Won-Ho;Eom, Tae-Yoon
    • Analytical Science and Technology
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    • v.12 no.3
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    • pp.177-183
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    • 1999
  • The determination method of free acid in spent U-Al nuclear fuel solutions by Gran plot titration was described. Effect of U(VI) and Al(III) on the alkalimetric titration of nitric acid was investigated in oxalate complexing media as well as in noncomplexing media. Positive biases were observed in both titration media when the end-point was estimated by the Gran plot method. It was found that the cause of the bias was U(VI) in the oxalate complexing media, but Al(III) in the noncomplexing media. The relative error was less than 1% in the titration of 0.1 M $HNO_3$ at a U(VI) : Al(III) : $H^+$ mole ratio of up to 2:12:1 as long as the pH of the oxalate titration media was sustained to be below 5.0 at the beginning of titration. The method was successfully applied to the determination of nitric acid in a solution of HANARO reactor fuel with U:Al mole ratio of 1:6.

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