• 제목/요약/키워드: Media AI

검색결과 343건 처리시간 0.023초

마코프 지연을 갖는 네트워크 제어 시스템을 위한 상태 궤환 제어기 설계 (A State Feedback Controller Design for a Networked Control System with a Markov Delay)

  • 양장훈
    • 한국항행학회논문지
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    • 제24권6호
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    • pp.549-556
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    • 2020
  • 이 논문에서는 마코프 프로세스로 모델링되는 전송 오류나 전송 지연이 있는 네트워크 제어 시스템을 위한 제어기 설계 방법들을 제안한다. 마코프 지연을 갖는 제어 시스템을 위한 안정화 조건을 지연 의존적인 리아프노프-크라소프스키 범함수가 증가된 제어 시스템의 리아프노프 함수와 동일한 형태를 갖는다는 점을 이용하여 찾는다. 유도된 안정화 조건으로부터 복잡도를 줄이기 위한 수 개의 제어 설계기 방법을 제안한다. 모의 실험을 통하여 제안된 방법 중 행렬 변수의 탐색 공간을 블록 대각 행렬로 제한하는 제한 부분 공간 방법이 성능과 복잡도 사이에서 가장 좋은 트레이드오프를 제공함을 확인되었다.

Framework for Reconstructing 2D Data Imported from Mobile Devices into 3D Models

  • Shin, WooSung;Min, JaeEun;Han, WooRi;Kim, YoungSeop
    • 반도체디스플레이기술학회지
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    • 제20권4호
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    • pp.6-9
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    • 2021
  • The 3D industry is drawing attention for its applications in various markets, including architecture, media, VR/AR, metaverse, imperial broadcast, and etc.. The current feature of the architecture we are introducing is to make 3D models more easily created and modified than conventional ones. Existing methods for generating 3D models mainly obtain values using specialized equipment such as RGB-D cameras and Lidar cameras, through which 3D models are constructed and used. This requires the purchase of equipment and allows the generated 3D model to be verified by the computer. However, our framework allows users to collect data in an easier and cheaper manner using cell phone cameras instead of specialized equipment, and uses 2D data to proceed with 3D modeling on the server and output it to cell phone application screens. This gives users a more accessible environment. In addition, in the 3D modeling process, object classification is attempted through deep learning without user intervention, and mesh and texture suitable for the object can be applied to obtain a lively 3D model. It also allows users to modify mesh and texture through requests, allowing them to obtain sophisticated 3D models.

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

  • 방준성;박판근
    • 방송공학회논문지
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    • 제27권5호
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    • pp.703-717
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    • 2022
  • 메타버스는 가상과 현실이 연결된 디지털 사회에서 사회·문화·경제 활동을 하며 다양한 가치를 생산할 수 있는 시뮬레이션 환경을 제공한다. 본 논문에서는 메타버스 서비스와 산업 현황을 분석하고 서비스 플랫폼 구현 기술들을 살펴봄으로써 그 발전 방향을 예측해 본다. 그리고, 지속가능한 메타버스를 구성하기 위한 메타버스 윤리(Metaverse Ethics)와 사용자들의 서비스 참여를 높이기 위한 메타버스 사용자경험(UX)에 대해서도 논의한다. 마지막으로, 기술 경쟁력 확보를 위해 디지털 윤리와 UX가 반영된 메타버스 R&D 추진전략을 제시한다.

On the Analysis of Natural Language Processing Morphology for the Specialized Corpus in the Railway Domain

  • Won, Jong Un;Jeon, Hong Kyu;Kim, Min Joong;Kim, Beak Hyun;Kim, Young Min
    • International Journal of Internet, Broadcasting and Communication
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    • 제14권4호
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    • pp.189-197
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    • 2022
  • Today, we are exposed to various text-based media such as newspapers, Internet articles, and SNS, and the amount of text data we encounter has increased exponentially due to the recent availability of Internet access using mobile devices such as smartphones. Collecting useful information from a lot of text information is called text analysis, and in order to extract information, it is performed using technologies such as Natural Language Processing (NLP) for processing natural language with the recent development of artificial intelligence. For this purpose, a morpheme analyzer based on everyday language has been disclosed and is being used. Pre-learning language models, which can acquire natural language knowledge through unsupervised learning based on large numbers of corpus, are a very common factor in natural language processing recently, but conventional morpheme analysts are limited in their use in specialized fields. In this paper, as a preliminary work to develop a natural language analysis language model specialized in the railway field, the procedure for construction a corpus specialized in the railway field is presented.

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

  • Soomin, HAN
    • 유통과학연구
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    • 제21권3호
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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 Study on NaverZ's Metaverse Platform Scaling Strategy

  • Song, Minzheong
    • International journal of advanced smart convergence
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    • 제11권3호
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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.

Finger Gesture와 Voice Recognition을 활용한 IoT 통합 제어 웹 플랫폼 (IoT Multi Control Platform by Finger Gesture and Voice Recognition)

  • 강진형;김한주;김동호
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송∙미디어공학회 2022년도 추계학술대회
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    • pp.236-239
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    • 2022
  • 증강현실로 날씨, 뉴스 요약 등이 제공되거나 AI 비서 기능을 제공하는 스마트 미러(smart mirror)가 개발되고 있다. 본 작품에서는 IoT 통합제어, 뉴스 요약 및 날씨 정보 제공 등의 서비스를 하나의 웹 플랫폼으로 구축하고 이를 손가락 제스쳐 및 음성 명령으로 제어하는 것을 제안하고 구현하였다. 본 작품에서는 음성 인식을 통해 IoT 서비스를 직관적으로 이용할 수 있게끔 설계하여 사용자의 편의성을 높였으며, 디바이스를 직접 터치하는 방식이 아닌 finger gesture로 제어하는 방식을 채택해, 디바이스 유지 보수 및 위생 문제를 해결하였다. 단순 IoT 통합 제어 기능뿐만 아니라 다양한 컨텐츠 및 기능을 제공함으로써 통합 플랫폼의 기능을 수행할 수 있도록 하였다. 뉴스 홈페이지에서 Crawling한 뉴스를 text rank 알고리즘을 이용. 자동으로 요약하는 기능과, 사용자의 IP를 기반으로 위도와 경도를 추론, 해당 지역의 일기 예보 정보를 표현해 주는 등 단순 IoT 제어 플랫폼이 아닌, 통합 플랫폼의 기능을 다하도록 설계하였다. 이처럼 다양한 정보를 압축해서 사용자가 편하게 볼 수 있도록 제공하며, 직관적인 two track 제어 방식을 채택. 사용 대상의 편의성을 증대시켜 본 프로젝트는 기존 프로젝트보다 사용자에게 더 나은 사용 경험을 제공할 것이다.

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머신 러닝을 사용한 개인화된 뉴스 추천 시스템 (Personalized News Recommendation System using Machine Learning)

  • 펭소니;양예선;박두순;이혜정
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2022년도 춘계학술발표대회
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    • pp.385-387
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    • 2022
  • With the tremendous rise in popularity of the Internet and technological advancements, many news keeps generating every day from multiple sources. As a result, the information (News) on the network has been highly increasing. The critical problem is that the volume of articles or news content can be overloaded for the readers. Therefore, the people interested in reading news might find it difficult to decide which content they should choose. Recommendation systems have been known as filtering systems that assist people and give a list of suggestions based on their preferences. This paper studies a personalized news recommendation system to help users find the right, relevant content and suggest news that readers might be interested in. The proposed system aims to build a hybrid system that combines collaborative filtering with content-based filtering to make a system more effective and solve a cold-start problem. Twitter social media data will analyze and build a user's profile. Based on users' tweets, we can know users' interests and recommend personalized news articles that users would share on Twitter.

빅데이터를 활용한 복지정책 시각화분석 -충청도 중심으로- (Welfare Policy Visualization Analysis using Big Data -Chungcheong-)

  • 김대유;나원식
    • 산업과 과학
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    • 제2권1호
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    • pp.15-20
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    • 2023
  • 본 연구의 목적은 4차산업혁명 시대의 빅데이터 분석 기술을 활용한 충청도 복지정책 변화와 중요성을 분석하고 사회적 약자를 포함한 모든 세대의 안정적 복지정책을 제안하였다. 충청도 정책 관련 빅데이터를 파이선으로 코딩하여 시각화분석 결과를 토대로 안정적인 정부 정책을 제안한다. 연구 결과 충청도 정부 정책의 키워드는 지역, 사회, 정부 및 지원, 교육, 여성 등의 순으로 확인되었으며, 지역 건강정책과 사회 복지 향상을 중심으로 복지 정책을 강화해야 한다. 향후 연구 방향은 해외사례를 비교하고, 전국적인 복지정책의 안정적인 영향에 관한 정책 제안이 필요할 것이다.

영상정보를 활용한 소셜 미디어상에서의 가짜 뉴스 탐지: 유튜브를 중심으로 (Fake News Detection on Social Media using Video Information: Focused on YouTube)

  • 장윤호;최병구
    • 한국정보시스템학회지:정보시스템연구
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    • 제32권2호
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    • pp.87-108
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    • 2023
  • Purpose The main purpose of this study is to improve fake news detection performance by using video information to overcome the limitations of extant text- and image-oriented studies that do not reflect the latest news consumption trend. Design/methodology/approach This study collected video clips and related information including news scripts, speakers' facial expression, and video metadata from YouTube to develop fake news detection model. Based on the collected data, seven combinations of related information (i.e. scripts, video metadata, facial expression, scripts and video metadata, scripts and facial expression, and scripts, video metadata, and facial expression) were used as an input for taining and evaluation. The input data was analyzed using six models such as support vector machine and deep neural network. The area under the curve(AUC) was used to evaluate the performance of classification model. Findings The results showed that the ACU and accuracy values of three features combination (scripts, video metadata, and facial expression) were the highest in logistic regression, naïve bayes, and deep neural network models. This result implied that the fake news detection could be improved by using video information(video metadata and facial expression). Sample size of this study was relatively small. The generalizablity of the results would be enhanced with a larger sample size.