• Title/Summary/Keyword: Conditional media

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Quality Enhancement for Hybrid 3DTV with Mixed Resolution Using Conditional Replenishment Algorithm

  • Jung, Kyeong-Hoon;Bang, Min-Suk;Kim, Sung-Hoon;Choo, Hyon-Gon;Kang, Dong-Wook
    • ETRI Journal
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    • v.36 no.5
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    • pp.752-760
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    • 2014
  • This paper proposes a conditional replenishment algorithm (CRA) to improve the visual quality (where spatial resolutions of the left and right views are mismatched) of a hybrid stereoscopic 3DTV that is based on the ATSC-M/H standard. So as to generate an enhanced view, the CRA is to choose the better substitute among a disparity-compensated view with high quality and a simply interpolated view. The CRA generates a disparity map that includes modes and disparity vectors as additional information. It also employs a quad-tree structure with variable block size by considering the spatial correlation of disparity vectors. In addition, it takes advantage of the disparity map used in a previous frame to keep the amount of additional information as small as possible. The simulation results show that the proposed CRA can successfully improve the peak signal-to-noise ratio of a poor-quality view and consequently have a positive effect on the subjective quality of the resulting 3D view.

Conditional Variational Autoencoder-based Generative Model for Gene Expression Data Augmentation (유전자 발현량 데이터 증대를 위한 Conditional VAE 기반 생성 모델)

  • Hyunsu Bong;Minsik Oh
    • Journal of Broadcast Engineering
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    • v.28 no.3
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    • pp.275-284
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    • 2023
  • Gene expression data can be utilized in various studies, including the prediction of disease prognosis. However, there are challenges associated with collecting enough data due to cost constraints. In this paper, we propose a gene expression data generation model based on Conditional Variational Autoencoder. Our results demonstrate that the proposed model generates synthetic data with superior quality compared to two other state-of-the-art models for gene expression data generation, namely the Wasserstein Generative Adversarial Network with Gradient Penalty based model and the structured data generation models CTGAN and TVAE.

Uncertainty Improvement of Incomplete Decision System using Bayesian Conditional Information Entropy (베이지언 정보엔트로피에 의한 불완전 의사결정 시스템의 불확실성 향상)

  • Choi, Gyoo-Seok;Park, In-Kyu
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.14 no.6
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    • pp.47-54
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    • 2014
  • Based on the indiscernible relation of rough set, the inevitability of superposition and inconsistency of data makes the reduction of attributes very important in information system. Rough set has difficulty in the difference of attribute reduction between consistent and inconsistent information system. In this paper, we propose the new uncertainty measure and attribute reduction algorithm by Bayesian posterior probability for correlation analysis between condition and decision attributes. We compare the proposed method and the conditional information entropy to address the uncertainty of inconsistent information system. As the result, our method has more accuracy than conditional information entropy in dealing with uncertainty via mutual information of condition and decision attributes of information system.

Recognition of the impact of success of task in human sleep with conditional random fields (CRF를 이용한 일의 성공이 수면에 미치는 영향 분석)

  • Yang, Hee Deok
    • Smart Media Journal
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    • v.10 no.2
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    • pp.55-60
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    • 2021
  • In this research, we design and perform experiment to investigate whether neuronal activity patterns elicited while solving game tasks are spontaneously reactivated in during sleep. In order to recognize human activity EEG-fMRI signals are used at the same time. Experimental results shows that reward for the success of tasks performed before sleeping have an effect on sleep brain activity. The study uncovers a neural mechanism whereby rewarded life experiences are preferentially replayed and consolidated while we sleep.

Few-Shot Image Synthesis using Noise-Based Deep Conditional Generative Adversarial Nets

  • Msiska, Finlyson Mwadambo;Hassan, Ammar Ul;Choi, Jaeyoung;Yoo, Jaewon
    • Smart Media Journal
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    • v.10 no.1
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    • pp.79-87
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    • 2021
  • In recent years research on automatic font generation with machine learning mainly focus on using transformation-based methods, in comparison, generative model-based methods of font generation have received less attention. Transformation-based methods learn a mapping of the transformations from an existing input to a target. This makes them ambiguous because in some cases a single input reference may correspond to multiple possible outputs. In this work, we focus on font generation using the generative model-based methods which learn the buildup of the characters from noise-to-image. We propose a novel way to train a conditional generative deep neural model so that we can achieve font style control on the generated font images. Our research demonstrates how to generate new font images conditioned on both character class labels and character style labels when using the generative model-based methods. We achieve this by introducing a modified generator network which is given inputs noise, character class, and style, which help us to calculate losses separately for the character class labels and character style labels. We show that adding the character style vector on top of the character class vector separately gives the model rich information about the font and enables us to explicitly specify not only the character class but also the character style that we want the model to generate.

Insights for Improving Road Safety : Focusing on Vehicle Accidents in Daegu Metropolitan City

  • Mee Qi Siow;Yang Sok Kim;Mi Jin Noh;Choong Kwon Lee;Sang Ill Moon;Jae Ho Shin
    • Smart Media Journal
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    • v.12 no.11
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    • pp.95-102
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    • 2023
  • Road accidents not only caused loss of human lives but also costed 3% of gross domestic product in most of the countries. The road accidents pose significant challenges to public safety and urban transportation management. There is a need to identify the high-risk area of accidents along with the critical day of week and vulnerable time period in order to implement effective preventive measures and optimizing the resource allocation. We collected 5,012 accident data from 대구교통종합정보. This study identified the high-risk locations, days of week, and time periods for accidents in Daegu and estimated the conditional probabilities of accidents occurring based on combinations of location, day of the week, and time period. The result is visualized in the form of dashboard in Tableau. This study holds substantial practical significance for urban planners, transportation authorities, and policymakers in Daegu to strategically allocate resources for traffic management, law enforcement, and targeted safety campaigns.

Mode Selection Method to Reduce the Flickering Effects of Conditional Replenishment Algorithm for Hybrid 3DTV (융합형 3DTV 시스템의 조건부대체 알고리즘에서 플리커링 현상 감소를 위한 모드 선택 방법)

  • Kwon, Tae-Ho;Kim, Ji-Won;Kim, Sung-Hoon;Kim, Hui-Yong;Kim, Ki-Doo;Jung, Kyeong-Hoon
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2016.06a
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    • pp.50-53
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    • 2016
  • 조건부 대체 알고리즘 (CRA: Conditional Replenishment Algorithm)은 융합형 3DTV 서비스에서 부가정보를 전송함으로써 수신기에서의 화질을 개선하는 방법이다. 이 알고리즘은 비용함수를 도입함으로써 가변크기의 처리단위 (PU: Processing Unit) 마다 최적의 모드를 결정하는데, 이 과정에서 시공간적 인접 PU 사이에 모드의 불연속이 발생하는 경우에 블록화 또는 플리커링 현상 등 주관적 화질을 저하시키는 문제가 생길 수 있다. 본 논문에서는 모드를 결정하는 과정에서 시간적으로 연속적인 PU 사이의 상관성을 고려함으로써 플리커링 현상을 방지하는 기법을 제안하고 모의실험을 통해 주관적 화질이 향상됨을 보였다.

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An Efficient Monitoring Method of a Network Protocol for Downloadable CAS

  • Jeong, Young-Ho;Kwon, Oh-Yung;Ahn, Chung-Hyun;Hong, Jin-Woo
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2010.07a
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    • pp.32-35
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    • 2010
  • This paper presents an efficient monitoring method of a network protocol for a downloadable conditional access system (DCAS) that can securely transmit conditional access software via a bi-directional communication channel. In order to guarantee a secure channel based on mutual authentication between a DCAS head end server and set-top boxes, DCAS messages are encrypted and digitally signed. Owing to applied cryptographic algorithms, it is impossible to get information from messages directly without additional processing. Through categorizing DCAS messages into several groups, the proposed monitoring method can efficiently parse and trace DCAS messages in real-time. In order to verify the stability and effectiveness of the proposed monitoring method, we implement a DCAS monitoring system capable of capturing and parsing all DCAS messages. The experimental results show that the proposed monitoring method is well designed.

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Performance Evaluation of Downloadable Conditional Access System (다운로드형 제한수신 시스템의 성능 검증)

  • Cho, Yong Seong;Kwon, O-Hyeong;Choi, Dong-Joon;Her, Namho
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2011.07a
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    • pp.116-118
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    • 2011
  • 최근 유료 방송 서비스를 위한 제한수신 시스템의 적용에 있어 지적되었던 여러 문제들을 해결할 수 있는 DCAS(Downloadable Conditional Access System) 기술이 소개되었다. 또한, OpenCable과 DCAS를 기반으로 국내 디지털 케이블 방송 시스템을 위한 교환가능형 제한수신 시스템(eXchangeable CAS: XCAS) 표준이 재정되었다. 본 논문에서는 DCAS와 국내 XCAS 표준 규격을 기반으로 개발된 다운로드형 제한수신 시스템을 소개하고, 개발된 시스템의 성능 검증 결과를 제시하여 상용 유료방송 시스템에 적용하는 방안에 대해 논하고자 한다.

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