• Title/Summary/Keyword: intelligent content

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ETRI AI Strategy #3: Leading Future Technologies of Network, Media, and Content (ETRI AI 실행전략 3: 네트워크 및 미디어·콘텐츠 미래기술 선도)

  • Kim, S.M.;Yeon, S.J.
    • Electronics and Telecommunications Trends
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    • v.35 no.7
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    • pp.23-35
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    • 2020
  • In this paper, we introduce ETRI AI Strategy #3, "Leading Future Technologies of Network, Media, and Content." Its first goal is "to innovate AI service technology to overcome the current limitations of AI technologies." Artificial intelligence (AI) services, such as self-driving cars and robots, are combinations of computing, network, AI algorithms, and other technologies. To develop AI services, we need to develop different types of network, media coding, and content creation technologies. Moreover, AI technologies are adopted in ICT technologies. Self-planning and self-managing networks and automatic content creation technologies using AI are being developed. This paper introduces the two directions of ETRI's ICT technology development plan for AI: ICT for AI and ICT by AI. The area of ICT for AI has only recently begun to develop. ETRI, the ICT leader, hopes to have opportunities for leadership in the second wave of AI services.

The Architecture of Tool server in MPEG-21

  • Kim, Kwang-Yong;Hong, Jin-Woo;Kim, Jin-Woong
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.272-275
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    • 2003
  • This paper presents the role and its function of Tool server. MPEG-21 means multimedia framework for delivery and consumption of multimedia which is being discussed in ISO/IEC 21000. A view of MPEC-21 aims to define multimedia framework to enable transparent use of multimedia resource across a wide range of networks and devices used by different communities. MPEG-21 will enable all-electronic creation delivery and trade of digital multimedia content and transparent usage of various content types on network device. Therefore, we can provide access to information and services from almost anywhere at anytime with various terminals and networks. In order to support multimedia delivery chain that contains content creation, production, delivery and consumption, we need many standards(elements) for identify, describe, manage and protect the content. Thus, we define Digital Item Player(DIP), Digital Item Adaptation(DIA) server and Tool server as primary objects of MPEG-21 multimedia framework. DIP provides a function which creates and consumes Digital Item(DI) as a kind of a digital object by user. A DI contains both media resources and metadata including rights information. DIA server deals with the usage environment description schema of the user characteristics, terminal and network characteristics and natural environments. DIA server adapts the original DI to the usage environment description sent from the terminal and transmits the adapted DI to the terminal. Tool server searches for a tool requested from DIP or DIA and downloads the best tool to DIP or DIA server. In this paper, we present how Tool sewer is organized and is used among 2 primary objects. The paper is structured as followings: Section 1 briefly describes why MPEG-21 is needed and what MPEG-21 wants. We see requirement that tool server must equip functionally in section 2. The proposed tool server,its structure and its functionality are presented in section 3. Section 4 explains a scenario that tool server transmits tool to DIP and shows the experimental result. The paper concludes in section 5.

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Designing Augmented Spatial Experiences of Architectural Heritage - Information Modeling for Intelligent Content Service Platform - (건축문화유산의 공간경험 디자인 - 지능형 콘텐츠 서비스 플랫폼과 정보표현체계 -)

  • Jang, Sun-Young;Kim, Seongjun;Kim, Sung-Ah
    • Journal of the Architectural Institute of Korea Planning & Design
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    • v.35 no.4
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    • pp.15-24
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    • 2019
  • Currently, museums and architectural heritage provide augmented user experiences by incorporating various media technologies. They still, however, suffer from the limitation of entertainment-based and the provision of location-based simple and repetitive contents. In addition, while acting as a key medium of experience for architectural heritage, the concept of space is not properly reflected in current services. The purpose of this study is to design user space experience considering such characteristics of architectural heritage. The spatial experience content and content production platform are defined. This software platform creates content that enhances the experience of the place by giving a context-based digital data associated with space and objects. The spatial experience content is designed as a series of experience sequences. The composition of the sequence borrows the method of film and narrative which segment and connect consecutive experiences on a scene basis considering user's detailed spatial experience. Therefore, content components can be combined and reproduced in various types. Augmented contents were extracted by using rule-based reasoning function of ontology at the moment. As a practical example of architectural heritage, the Seokjojeon Hall is used to reveal a spatial experience scenario.

Understanding Watching Patterns of Live TV Programs on Mobile Devices: A Content Centric Perspective

  • Li, Yuheng;Zhao, Qianchuan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.9
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    • pp.3635-3654
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    • 2015
  • With the rapid development of smart devices and mobile Internet, the video application plays an increasingly important role on mobile devices. Understanding user behavior patterns is critical for optimized operation of mobile live streaming systems. On the other hand, volume based billing models on cloud services make it easier for video service providers to scale their services as well as to reduce the waste from oversized service capacities. In this paper, the watching behaviors of a commercial mobile live streaming system are studied in a content-centric manner. Our analysis captures the intrinsic correlation existing between popularity and watching intensity of programs due to the synchronized watching behaviors with program schedule. The watching pattern is further used to estimate traffic volume generated by the program, which is useful on data volume capacity reservation and billing strategy selection in cloud services. The traffic range of programs is estimated based on a naive popularity prediction. In cross validation, the traffic ranges of around 94% of programs are successfully estimated. In high popularity programs (>20000 viewers), the overestimated traffic is less than 15% of real happened traffic when using upper bound to estimate program traffic.

An AI Technology-based Intelligent Senior Assistant Voice Recognition System (AI 기술 기반 지능형 시니어 도우미 음성인식 시스템)

  • Hong, Phil-Doo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2019.05a
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    • pp.355-357
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    • 2019
  • Now that we are entering an aging society, the user interface for new devices and IoT technology is very inconvenient for senior generation. To improve this, we propose an AI technology-based intelligent senior assistant voice recognition system. This system implements Cloud platform based API to accumulate data for machine learning processing, provides content for diagnosis and prevention of dementia, and provide chat-bot content for senior generation. We hope that senior generations will increase the accessibility and convenience of IoT devices and new technology devices with our system.

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Intelligent Piracy Site Detection Technique with High Accuracy

  • Kim, Eui-Jin;Kwak, Jin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.1
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    • pp.285-301
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    • 2021
  • Recently, with the diversification of media services and the development of smart devices, users have more opportunities to use digital content, such as movies, dramas, and music; consequently, the size of the copyright market expands simultaneously. However, there are piracy sites that generate revenue by illegal use of copyrighted works. This has led to losses for copyright holders, and the scale of copyrighted works infringed due to the ever-increasing number of piracy sites has increased. To prevent this, government agencies respond to copyright infringement by monitoring piracy sites using online monitoring and countermeasure strategies for infringement. However, the detection and blocking process consumes a significant amount of time when compared to the rate of generating new piracy sites. Hence, online monitoring is less effective. Additionally, given that piracy sites are sophisticated and refined in the same way as legitimate sites, it is necessary to accurately distinguish and block a site that is involved in copyright infringement. Therefore, in this study, we analyze features of piracy sites and based on this analysis, we propose an intelligent detection technique for piracy sites that automatically classifies and detects whether a site is involved in infringement.

The Intelligent Intrusion Detection Systems using Automatic Rule-Based Method (자동적인 규칙 기반 방법을 이용한 지능형 침입탐지시스템)

  • Yang, Ji-Hong;Han, Myung-Mook
    • Journal of the Korean Institute of Intelligent Systems
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    • v.12 no.6
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    • pp.531-536
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    • 2002
  • In this paper, we have applied Genetic Algorithms(GAs) to Intrusion Detection System(TDS), and then proposed and simulated the misuse detection model firstly. We have implemented with the KBD contest data, and tried to simulated in the same environment. In the experiment, the set of record is regarded as a chromosome, and GAs are used to produce the intrusion patterns. That is, the intrusion rules are generated. We have concentrated on the simulation and analysis of classification among the Data Mining techniques and then the intrusion patterns are produced. The generated rules are represented by intrusion data and classified between abnormal and normal users. The different rules are generated separately from three models "Time Based Traffic Model", "Host Based Traffic Model", and "Content Model". The proposed system has generated the update and adaptive rules automatically and continuously on the misuse detection method which is difficult to update the rule generation. The generated rules are experimented on 430M test data and almost 94.3% of detection rate is shown.3% of detection rate is shown.

Artificial Intelligence in Personalized ICT Learning

  • Volodymyrivna, Krasheninnik Iryna;Vitaliiivna, Chorna Alona;Leonidovych, Koniukhov Serhii;Ibrahimova, Liudmyla;Iryna, Serdiuk
    • International Journal of Computer Science & Network Security
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    • v.22 no.2
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    • pp.159-166
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    • 2022
  • Artificial Intelligence has stimulated every aspect of today's life. Human thinking quality is trying to be involved through digital tools in all research areas of the modern era. The education industry is also leveraging artificial intelligence magical power. Uses of digital technologies in pedagogical paradigms are being observed from the last century. The widespread involvement of artificial intelligence starts reshaping the educational landscape. Adaptive learning is an emerging pedagogical technique that uses computer-based algorithms, tools, and technologies for the learning process. These intelligent practices help at each learning curve stage, from content development to student's exam evaluation. The quality of information technology students and professionals training has also improved drastically with the involvement of artificial intelligence systems. In this paper, we will investigate adopted digital methods in the education sector so far. We will focus on intelligent techniques adopted for information technology students and professionals. Our literature review works on our proposed framework that entails four categories. These categories are communication between teacher and student, improved content design for computing course, evaluation of student's performance and intelligent agent. Our research will present the role of artificial intelligence in reshaping the educational process.

Analysis on Lightweight Methods of On-Device AI Vision Model for Intelligent Edge Computing Devices (지능형 엣지 컴퓨팅 기기를 위한 온디바이스 AI 비전 모델의 경량화 방식 분석)

  • Hye-Hyeon Ju;Namhi Kang
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.24 no.1
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    • pp.1-8
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    • 2024
  • On-device AI technology, which can operate AI models at the edge devices to support real-time processing and privacy enhancement, is attracting attention. As intelligent IoT is applied to various industries, services utilizing the on-device AI technology are increasing significantly. However, general deep learning models require a lot of computational resources for inference and learning. Therefore, various lightweighting methods such as quantization and pruning have been suggested to operate deep learning models in embedded edge devices. Among the lightweighting methods, we analyze how to lightweight and apply deep learning models to edge computing devices, focusing on pruning technology in this paper. In particular, we utilize dynamic and static pruning techniques to evaluate the inference speed, accuracy, and memory usage of a lightweight AI vision model. The content analyzed in this paper can be used for intelligent video control systems or video security systems in autonomous vehicles, where real-time processing are highly required. In addition, it is expected that the content can be used more effectively in various IoT services and industries.

A Hybrid Knowledge Representation Method for Pedagogical Content Knowledge (교수내용지식을 위한 하이브리드 지식 표현 기법)

  • Kim, Yong-Beom;Oh, Pill-Wo;Kim, Yung-Sik
    • Korean Journal of Cognitive Science
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    • v.16 no.4
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    • pp.369-386
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    • 2005
  • Although Intelligent Tutoring System(ITS) offers individualized learning environment that overcome limited function of existent CAI, and consider many learners' variable, there is little development to be using at the sites of schools because of inefficiency of investment and absence of pedagogical content knowledge representation techniques. To solve these problem, we should study a method, which represents knowledge for ITS, and which reuses knowledge base. On the pedagogical content knowledge, the knowledge in education differs from knowledge in a general sense. In this paper, we shall primarily address the multi-complex structure of knowledge and explanation of learning vein using multi-complex structure. Multi-Complex, which is organized into nodes, clusters and uses by knowledge base. In addition, it grows a adaptive knowledge base by self-learning. Therefore, in this paper, we propose the 'Extended Neural Logic Network(X-Neuronet)', which is based on Neural Logic Network with logical inference and topological inflexibility in cognition structure, and includes pedagogical content knowledge and object-oriented conception, verify validity. X-Neuronet defines that a knowledge is directive combination with inertia and weights, and offers basic conceptions for expression, logic operator for operation and processing, node value and connection weight, propagation rule, learning algorithm.

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